Not Cool Epilogue: A Climate Conversation

In this brief epilogue, Ariel reflects on what she’s learned during the making of Not Cool, and the actions she’ll be taking going forward. Read the full transcript below.

The way I would put it is: we produced this problem, and we can solve it. It’s produced by humans, it can be solved by humans.
~ Alan Robock
There’s a huge international push in the right direction, and it’s only going to take people to just put a bit of effort in, and I’m sure we can do it.
~ Joanna Haigh
I’m betting long on humanity because I don’t yet think we’ve had our finest hour. I’m hoping that our finest hour comes in the context of addressing climate change.
~ Cullen Hendrix
Part of what we need is a new normal. And I think the new normal is that we all think about these decisions every day.
~ Deborah Lawrence
Roll out whatever policies you can find that will help emissions go down.
~ Glen Peters
I think more and more people are getting educated, more and more people are voting, and if that trend continues, which I hope it will, then I’ll stay hopeful.
~ Lindsay Getschel
I truly do believe that we all have part of the solution in our own hands.
~ Stephanie Herring

Hi everyone. Ariel Conn here with some final thoughts for Not Cool, a climate podcast. 

Last spring I became pretty overwhelmed by climate-related news. The IPCC report was calling on countries to make massive changes by 2030 if we wanted any hope of keeping global warming under 1.5 degrees celsius, and every new study seemed to indicate that things were even more dire than we had previously thought. So I decided to reach out to a few climate scientists to learn more about what was really going on, and what we could realistically do. I thought that if I could talk to just five or six scientists, we could help paint a better picture of what the problem was and how we could fix it. I thought this could be a quick project in May that might overflow into June, and then we’d release a single episode a week for a few weeks during the summer. 

31 experts and 26 episodes later, well into winter, we’re finally concluding this series. And not because we’ve covered everything there is to cover. There are so many more topics I wanted to get into, like feedback loops, the impact of animal agriculture, how to shape climate policy — the list goes on and on. For each question that was answered, more kept cropping up. 

But I also learned a lot. And perhaps the most important lesson from all of these interviews was that, as bad things are — and they are bad — these problems are solvable. The technical alternatives for most fossil fuel technologies already exist. We just need the political will to start implementing them. 

That’s not to say that there aren’t some pesky problems, like the carbon emissions associated with construction and flying that we haven’t yet figured out how to solve. But there is hope. 

However, I do want to be clear that this hope is not enough if we remain complacent. That’s why, in addition to voting next year, I am personally committing to climate action.

  • Over the next few months, I will ensure my banks do not support the fossil fuel industry. I already checked with both of my credit unions, and while one does not support fossil fuels, the other does. So I will be moving my money from that one.
  • Though I drive more than I’d like, I rarely use more than a tank of gas per month. I will try to decrease that more. My budget does not currently allow for me to purchase a new electric car, but I will get an electric bike, which will make the hills where I live easier to deal with than the manual bike I currently own.
  • I will consume less meat
  • I will continue to consume less overall, I will continue to do my best to avoid single use plastics, and I will continue to try to use a drying rack more than a dryer for my clothes.
  • I’m happy to report that the electricity in our house is already powered by wind, which was an option the utility gave us.
  • I also live in a town with curbside recycling and composting, which I already use. 

It’s worth noting that those last couple of options are available to me because of policies put in place by my town and the utility, which does also highlight how critical policies are toward driving individual action. 

The area I’m less certain about how to address is flying, because it’s often necessary for the work I do. But I can at least purchase carbon offsets, and I will try to figure out how to fly less for work in the coming years.

All that said, there are still a lot of questions I would like to get answered related to the climate crisis, and I’m looking forward to exploring these more in the future, though likely in other formats. 

I have loved every minute of these interviews, and I cannot thank our guests enough for talking with us and sharing their insights. I hope you have enjoyed this series, and that you’ve found it helpful. Even though the series is ending, your support is still valuable to FLI, so, as always, we’d love it if you took a moment to like the episodes, share them, and maybe even leave a good review.

Not Cool Ep 26: Naomi Oreskes on trusting climate science

It’s the Not Cool series finale, and by now we’ve heard from climate scientists, meteorologists, physicists, psychologists, epidemiologists and ecologists. We’ve gotten expert opinions on everything from mitigation and adaptation to security, policy and finance. Today, we’re tackling one final question: why should we trust them? Ariel is joined by Naomi Oreskes, Harvard professor and author of seven books, including the newly released Why Trust Science? Naomi lays out her case for why we should listen to experts, how we can identify the best experts in a field, and why we should be open to the idea of more than one type of “scientific method.” She also discusses industry-funded science, scientists’ misconceptions about the public, and the role of the media in proliferating bad research.

Topics discussed include:

  • Why Trust Science?
  • 5 tenets of reliable science
  • How to decide which experts to trust
  • Why non-scientists can’t debate science
  • Industry disinformation
  • How to communicate science
  • Fact-value distinction
  • Why people reject science
  • Shifting arguments from climate deniers
  • Individual vs. structural change
  • State- and city-level policy change

References discussed include:

We have people out there who are just doing everything in their power to keep the fossil fuel economy alive and to continue to make profits by selling fossil fuels, come hell or literally high water. That tells me that this is fundamentally a political problem, that we have to fight the political power of the fossil fuel industry.

~ Naomi Oreskes

Ariel Conn: Hi everyone. I’m Ariel Conn, host of Not Cool, a climate podcast. Today doesn’t just mark the 26th episode of the show. This is also the last interview we’re releasing for the series. Though tomorrow, we’ll also release a brief epilogue where I’ll highlight some of the more interesting things that I learned, as well as some of the things we didn’t get to cover that I would have liked to talk about. 

But for our last interview, I’m honored to have Naomi Oreskes joining the show. Naomi has written extensively about climate change and the scientific consensus surrounding climate change. Her most recent book is Why Trust Science?, which is what we’ll primarily discuss on this show, since the question pertains so directly to climate change. 

Naomi is a Professor of the History of Science and Affiliated Professor of Earth and Planetary Sciences at Harvard University. She is a world-renowned geologist, historian and public speaker, as well as a leading voice on the role of science in society and the reality of anthropogenic climate change.

Naomi is author or co-author of 7 books, and over 150 articles, essays and opinion pieces, including Merchants of Doubt, The Collapse of Western Civilization, Discerning Experts, Why Trust Science?, and Science on a Mission: American Oceanography from the Cold War to Climate Change. Merchants of Doubt, which she co-authored with Erik Conway, was the subject of a documentary film of the same name, and has been translated into nine languages. A new edition of Merchants of Doubt, with an introduction by Al Gore, will be published in 2020.

Naomi, thank you so much for joining us. 

Naomi Oreskes: You’re welcome. Nice to be with you. 

Ariel Conn: All right, so your book is Why Trust Science? Why did you write the book? What problems are you hoping to identify or address? 

Naomi Oreskes: That’s easy to answer because this book, more than some things I’ve done, had a very specific beginning. After Eric Conway and I published Merchants of Doubt in 2010, I went on the lecture circuit, found myself giving a lot of public lectures all across the country, and making a point to try to accept invitations from places that might not always be friendly. And often I would give these very well-constructed talks where I would explain the history of climate science, and all the details about how scientists have come to understand it, and what the evidence was, and how the evidence had been collected by a lot of different people in different places over a long period of time. And once I was giving a talk and a man stood up afterwards and he said, “Well, that’s all very well and good, but why should we trust the science?” And in that moment I thought, fair enough. And I started thinking about that, and so a couple of years later when I was invited to do the Tanner Lectures on Human Values at Princeton, I thought, “That would be a good topic. Let me see if I can try to answer that question.” 

Ariel Conn: I guess you list five tenets of reliable science that I found, and that was consensus, method, evidence, values and humility. Can you just briefly explain what you meant by each of those — and if there’s something I missed, mention that as well? 

Naomi Oreskes: Sure. Although I think if it’s okay with you, I might back up. Those five things kind of fall out at the end of the book as important themes that I ended up thinking were important things for us to think about when we think about the reliability of science. Before we get there, there’s a more basic argument about the basis for trust in science, and that’s essentially two things. One is the argument for expertise. Even though it’s very fashionable these days to be skeptical of experts, the reality is that there’s good reason to support experts. And the reason is that they have knowledge and information and experience that we don’t have. So just like we need plumbers to fix our plumbing — sometimes we can fix it ourselves, but a lot of times we can’t — or if the electricity goes on the fritz, most of us are not in a position to safely fix our own electricity. 

So we call in an electrician, and most of the time that’s a good thing. Scientists are our experts on the natural world. They are the people who have studied it, who have specialized training and knowledge, and who know things that we don’t know but that we need to rely on — just like we rely on our plumbers or electricians or dentists or doctors or nurses, whatever. And without expertise, civilization would come to a standstill. You wake up in the morning and you turn on the radio and you listen to the radio, you listen to the weather. You get in your car and you drive to work; when you get to work, your office hopefully has been cleaned the night before. I mean, everything we do, there are other people around us helping us out, and in many cases those people are experts. 

We don’t really think about that. But when you begin to think about expertise in that way, you realize that it’s foolish to be disrespectful of experts. A little healthy skepticism here and there — some electricians are crooks, you know — but in general, most experts do jobs that we need them to do, and scientists are our natural world experts. The second part of the argument is the argument for the critical vetting of claims. In science, it’s not enough to be an expert, do work and say, “Okay, I’ve spent the last 15 years studying these mineral deposits in Chile and now I’m going to tell you all about them.” No, there’s a second step. And that second step is the critical vetting of the claims by the community of other experts. I have to present my evidence, I have to show the data, my colleagues get to ask questions, and they get to ask tough questions. And then I submit it for publication, where there’s another round of questioning, and if my colleagues are not satisfied with my arguments, I have to fix them. 

This process is the key to yielding claims that have been vetted. They’ve been tested, and in general, history tells us that by and large they turn out to be pretty reliable. So that’s the basic structure and framework for why we should trust science. Out of that basic framework, in the book I look at the larger history of different attempts to try to understand science, but then I also look specifically at a couple of cases where we would say in hindsight that scientists did get it wrong, and ask the question, well, what can we learn from those experiences? And so I pull out five things that I think are important. 

The first and most important is the whole notion of consensus. So again, it’s fashionable in some quarters to criticize consensus, to say that science isn’t about consensus. But actually science is about consensus, because that’s what you get after you go through this whole process — or maybe you don’t get it, but when you do have consensus, that’s when we say, okay, we know something. 

And what I found in my examination of examples where supposedly scientists had got it wrong was that actually in every one of those cases we find that there actually wasn’t a consensus, that even at the time there was significant disagreement within the scientific community. This means it’s very important for us to look closely in some issue that might be contested — like climate change — to really find out, is this contested by scientists within the scientific community, or is the contestation political contestation, which is what we see in the case of climate change, or is it some kind of social or cultural contestation, which is what we see in the case of vaccinations. These are two very different things, and they need to be addressed in different ways. So consensus is really important. 

The second thing is method. And a big part of the book is to refute the popular conventional wisdom that there is a scientific method. Historians and philosophers have been saying for a long time now that that’s wrong. We have a huge amount of evidence from the history of science that scientists actually use very diverse methods. So when we look at science, what we have to accept is that there are different tools for different kinds of problems, but that’s okay. And what is not okay is when we get fetishistic about method, when we insist that there’s only one right way to do science. And this was on full display just a few weeks ago in the recent debate that erupted over the question of whether or not it’s healthy to eat red meat. And it comes up in all the cases that I looked at in my study too: that where you have scientists going wrong, it’s often where they become obsessive — I use the word fetishistic — about a certain method, and then that blinds them to important evidence that comes from other places. 

And sometimes this is done in a principled way, that scientists persuade themselves that only a randomized clinical trial is legitimate. Or sometimes it’s exploited cynically, let’s say by the tobacco industry, that used it to try to deny a significant part of the evidence of the harms of tobacco. And we have seen this just two weeks ago: the people who are now claiming that red meat is fine and you should eat as much red meat as you want, have, in my opinion, cynically exploited the whole notion of RCT. So, this may be more detailed than you want, but in their paper they used a methodology that was designed to prioritize RCTs on the grounds that randomized clinical trials are the gold standard in epidemiology and clinical trials. Well, that’s true; if you can do an RCT, then it’s definitely a good thing to do. But there are many problems for which RCTs are not suitable. 

And nutrition is probably the most important example because you can’t do a double-blinded clinical trial; very difficult to randomize a population; people lie about what they eat — I mean, there’s all kinds of reasons why it’s hard to do RCTS in nutrition. However, we have an awful lot of good information from other sources: population studies, cohort group studies, animal studies. It’s true, these other methods are not as good as RCTs, but if you can’t do an RCT, then obviously you have to rely on other information. And we now know that these authors did in fact have links to the food industry. I think this was a cynical ploy to rule out a lot of important evidence and to say, “Oh, we have no good evidence that red meat is bad for you, and therefore you should just keep on eating red meat.” So this can be exploited cynically, or it can be used in a kind of authentic, but I think misguided, way. So a really important message of my book is don’t be fetishistic about method. Accept the fact that evidence comes in a lot of different sizes, shapes and colors. It’s not always perfect, but the fact that evidence is imperfect is no reason to throw it out. 

Ariel Conn: Do you see scientists recognizing that there’s lots of different types of methods, or do you think this is something that scientists need to be reminded about as well? 

Naomi Oreskes: Both. I think there are a lot of scientists that do recognize it. Certainly, scientists who are in fields like nutrition, who realize the difficulty of doing RCTs — they certainly know and accept that you need to be able to do other things like animal studies, for example. But I think there are other scientists who need to be reminded. I think it’s easy to fall into the trap of thinking a certain method is the gold standard, a certain method is better — and then because it’s better, you become a little bit narrow-minded or fixated about the idea that that is what you should be working for. And again, if you can do it, great, but if you can’t do it then you have to be willing to accept that there are other ways. 

Just as there are many different methods, so evidence comes in lots of sizes, shapes and colors. And the key thing in science is as much as possible to be open minded to all of the evidence, to look at the weight of evidence and not to discount evidence just because it’s not in your preferred form. And so, many of the cases that I looked at in my book where we see scientists in hindsight making mistakes or going awry, we find people discounting evidence because they didn’t like where it came from, or they didn’t like who was supplying it. And in hindsight, many times we see that this discounted evidence was actually correct. And so a big part of my argument is to be open-minded about evidence. It doesn’t mean that you accept any old claim, but it does mean that you realize evidence is complicated and it may sometimes come from places that you didn’t always initially expect. So being open-minded about evidence and weighing the evidence and really being able to encompass the full availability of evidence: the evidence in my study supports that that’s the appropriate approach. 

Ariel Conn: And then values is actually one that I thought was really interesting, because I do think that that’s one that’s especially important when trying to communicate the science to such a diverse group of people. 

Naomi Oreskes: Many scientists think that to be scientific is to suppress your personal values, and that it’s inappropriate to talk about values in science because if you do, then it will appear that you’re not objective. And I think this is mistaken on a couple of levels. I think it’s mistaken as a matter of fact, because the reality is that scientists are people, we’re human beings, and we all have values and preferences — and it is simply not possible to expunge your values. The idea of being a completely value-neutral objective scientist is simply a fantasy. Maybe someday in the future there’ll be a robot that could do that, but no human being can do that. So if you set that as your goal, you will necessarily fall short. And then if people discover you actually have values — which of course you do — then it’s, “Aha, so you really do have values!”

And then you can be potentially discredited by people who would like to discredit you. Or even if nobody’s deliberately trying to discredit you, it just may come across as inauthentic or dishonest because you say, “Oh, I have no values,” and your audience is thinking, “Yeah, right.” It also comes out of my experience trying to communicate to a wide range of different people about climate change, and one of the things that I’ve discovered is that not only is it impossible to completely hide your values, but it’s not even a good idea. Because what I’ve found in my own work was that when I would talk to people about me — who I was, and my own personal values — very often people resonated with that.

Even people who might have been skeptical to begin with about climate change, when I would actually talk about why I got involved in this issue, why it matters to me, why I act on climate, to use the hashtag, I found that often people would suddenly be listening more closely. Then I become a person just like them, grappling with a complicated issue, caring about my children just like them, and I think that opens up a space to make a human connection with people that maybe otherwise you might think you have nothing in common with them. 

That happens a lot with scientists. They think, “How can I possibly talk to somebody who thinks the earth is 6,000 years old?” Or, “How can I possibly talk to somebody who hasn’t vaccinated their children?” This is one way to answer that question: to say, “Well, look, you have values, they have values, and it turns out actually many of those values may overlap. Those people who aren’t vaccinating their children, they love their children just as much as you do, but they have some kind of conceptual framework that has made them think that not vaccinating their children is an appropriate expression of their love. And if you can find a way to say, ‘Well, I love my children too and here’s why I vaccinate my children’ — sometimes that can open up a space that would otherwise not be there.”

Ariel Conn: I’m going to come back to this in a minute, but let’s finish with this list. All of these really tie nicely, link nicely together. So humility is the last one. 

Naomi Oreskes: Right. Well, humility is the last one; in a way, it’s the first one, because it’s something I’ve been thinking about for a long time, but I always keep coming back to it. As an academic, it’s a tricky thing because you do all this work and then people press you to say, “Here’s my conclusion, and here it is in a soundbite without any qualifications or caveats.” And of course we know that’s not right, because everything we’ve done is potentially subject to revision. So a long time ago when I first started writing about climate change, my very first article on it was my 2004 article on the scientific consensus on climate change. And one of the things I specifically said in that article, after demonstrating that there was indeed a consensus, that of course the history of science tells us that we might be wrong. And I wrote, “If history proves anything, if it teaches anything, it teaches humility.”

So we should always be aware of the possibility that in the future we will learn new things and that our ideas may need to be revised. and we should therefore not be too self-satisfied, not become auto-intoxicated. But at the same time, if we need to make an important decision, then it makes sense to make our decision based on the best information we have. So we can be clear and firm about what we know while at the same time still recognizing that yes, it’s possible that we will revise this in the future, but it’s rather unlikely that we’re going to find out that there’s no climate change because all of the available evidence tells us there is. 

Ariel Conn: As I was reading this, I initially went into the book with the title Why Trust Science? — I assumed it was geared towards the public. And maybe that was the goal, but as I was reading it, it seemed to me an awful lot like really the audience who needs to be reading this are scientists. And so I was curious who you intended this for.

Naomi Oreskes: Yeah, that’s a good question. Sometimes when you write you have a very specific audience in mind, and sometimes it’s a little bit less specific. I think in this case, who I had in mind were the people who come to my talks. When I give public talks, a lot of people come; I mean, I’ve lectured to many, many thousands of people across this country and I’ve written op-ed pieces that have been read by an order of magnitude more. And I don’t know who all those people are, but there’s a lot of people out there who read my books, and most of those people are not scientists, most of those people do not have PhDs and most of them are not academics. But they’re educated enough to be engaged in a serious conversation about science. So whoever they are, I’m very grateful to them, and this book for you. 

There is some audience out there of educated people who care about these issues, and it does include scientists. I think many scientists need to have these broader, more philosophical conversations about the nature of science and the relationship between facts and values, for example, but I don’t see scientists as primarily my audience. I see it primarily as all those nice people in Iowa and North Dakota and Utah who have come to my talks and listened to me on public radio and might be listening to this podcast.

Ariel Conn: To keep up with all scientific fields — that’s impossible for scientists, let alone the general public. And so then you start trying to get people who don’t have a scientific background, who can’t read these peer-reviewed papers: how do they reasonably keep up with what information they need to keep up with and find reliable mediators and communicators that they can trust? 

Naomi Oreskes: Well of course part of the answer is, they don’t. I don’t expect any ordinary citizen to keep up with science writ large. I mean, I do this for a living and I still wouldn’t claim that I keep up with all science. I keep up very closely with earth and environmental science, and to a lesser extent with a set of issues that sort of overlap with it that include nutrition and health and smoking and a few other things. But the whole point of the book — and of course one reason I worked really hard to keep it under 250 pages — was to say that there are some kinds of principles that you can begin to think about that can help you and give you guidance. And so one of the principles is the principle of expertise. It doesn’t take a lot of work to ask the question — if some so-called expert is on television or on the radio or being quoted in the newspaper — it doesn’t take a lot of work to say, “Well, who is this person?” And if the person is talking about science, but they’re not a scientist, that should be a red flag. 

I have noticed in my own work that an enormous number of people who get quoted on television, on the radio, making scientific claims — or I should say really making anti-scientific claims; claiming there’s no climate change or claiming that vaccines cause autism — these people are not scientists. So, obvious example: Jenny McCarthy saying that vaccines caused her son’s autism. She’s an actress. She may be a fine actress; she may be a fine person. I have no question whatsoever that she loves her son. She’s not an expert about autism. And her experience as a parent does not make her an expert on the causation of autism. 

It may make her an expert on the experience of frustrated parents who are trying to grapple with a society that doesn’t do a really good job of helping people who have autism. And that’s totally legitimate. If you were doing a program about the difficulty of being a parent of autistic children, then it would be absolutely legitimate to invite Jenny McCarthy on that program. But if the program is about the causes of autism, then she’s not the appropriate expert. And I think once you begin to think in those terms, a lot of things get sorted out. 

So you asked about the audience for the book: part of the audience for the book is you, and journalists, because I think journalists have really dropped the ball on this one. And the number of times that I have seen journalists interviewing some shill for the oil industry or somebody from a libertarian think tank like the Cato Institute — and this is something that has been driving me crazy for years: climate scientists get up and talk about climate change and then a journalist will interview someone from the Cato Institute challenging the science. That’s completely inappropriate. If you want to talk about the policy aspects — like now that we know that this is happening, what do we do about it? — fair enough, invite the libertarians. But then you should also invite Greenpeace. The appropriate counter to Cato is Greenpeace. The appropriate counter to science is not. It would be other scientists if there’s an actual debate. 

In the case of the causes of autism, yes, we don’t know what causes autism. So there, let’s say you had some guy on who has a theory that autism is caused by sugar — this is a real thing; I was just reading about this the other day. I have no idea if that’s true or not, so don’t quote me as saying that sugar causes autism, but if you thought it was an interesting hypothesis and you wanted to invite him on board and you wanted to see what evidence he had, then the appropriate counter is some other scientist who thinks that the cause of autism — I mean, I don’t know, who doesn’t think it’s sugar. There are real scientific debates, and that’s when you get scientists together. But when it’s a political debate, then you don’t invite a political person to counter scientific evidence. That’s what philosophers would call a category mistake. 

Ariel Conn: Do you think we’re sort of falling — I don’t know if fallacy is quite the right word, but sort of this idea that we need to get both sides of an argument, even when there isn’t both sides, there isn’t another side?

Naomi Oreskes: Yeah, absolutely. And I talk about this in the book. So it is a fallacy; it’s the fallacy of false equivalence — the idea that every story has two sides. And you hear this all the time, but it’s not true. I believe I say this in the book; I’ve certainly said this many times in other places: if there’s a genuine scientific debate, then typically there’s a lot more than two sides. My first book was on the debate over continental drift in the early 20th century, and in that debate there were five or six or seven major schools of thought about how to explain continental motions. And in my book I have a diagram that I love, an illustration that came out of the classroom notes of a geologists in the 1920s who studied tectonics with one of the world’s most famous seismologists, Beno Gutenberg. 

And in that class he listed 21 different hypotheses to explain the motion of continents. So if you were doing some kind of TV show — we didn’t have television in those days, but imagine we did — it would be reasonable to invite six or eight or even ten scientists on board to talk about all these different hypotheses. But when scientists come to an agreement on something and conclude that something is known — like we would now say we know the continents move — then the whole notion of sides makes no sense. And the whole framework of sides is very unhelpful. And so I think what a lot of journalists have done is they’ve taken a framework out of politics, where the notion of sides in a two party system is sort of understandable — although even then you might argue that it’s not all that helpful, but at least you have a political debate; you have Democrats and Republicans. Okay. That’s a framework that we understand, and has some logical relationship to the political system that we live in. But the framework of two sides has no logical relationship to science. 

Ariel Conn: I’ve often wondered — and suspected, frankly — that one of the things that hurts science, and people’s understanding of science, is maybe poor reporting of health-related issues, but even just reporting of health-related issues. We’re constantly getting new updates to our scientific understanding of health, and sometimes that means that what we previously thought turns out to be false. My theory is that what happens is most people aren’t really making a strong differentiation between health science and any other type of science. And so when they see all these issues related to health science and all the inconsistencies and changes, they then turn to all the other sciences and say, “Well, all science is like that.” 

Naomi Oreskes: I think that’s correct. When I was giving these public lectures and people would sometimes say, “Why should we trust the science,” the other thing people would sometimes say is, “Well, why should we trust the science when we know that scientists are always changing their minds or always getting it wrong?” I got that a lot. So sometimes I would ask people, “Well, what science in particular are you thinking of?” And it was interesting: very often people would have no answer to that question. It was just a sort of vague sense that scientists are always changing their mind. But if they did have an answer, it was always nutrition, always. And this is why I started getting more interested in nutrition, to try to get a better understanding of what was going on there. So I think you’re right, I think there’s a few things going on. I think one is that nutrition is a very tough science; it’s hard to pin down. 

So it means that you have a lot of suboptimal studies, and that means that drawing very firm conclusions is difficult. And it also means that new studies could challenge existing ones. It is true that shifting nutritional advice can give the impression that science is very unstable. And I do think you’re right, I think people who don’t follow other areas of science might falsely generalize from that to, say, climate science. Because if you look at climate science, you see that actually the advice from climate science has been extraordinarily stable for about 30 years now. There’s actually been no reversals of fortune in climate science. 

But it’s not just that. There’s also, I think, two other things that are in a way worse than that. And one is the confounding effects of industry disinformation. One of the things that we’re increasingly understanding is that the industry has actually been responsible for some of the misleading and confusing information. We now know that there was a lot of industry funding of research designed to blame fat for nutritional problems in order to distract attention from the harms of sugar. And this has been quite well-documented now. We also know that there’s a lot of industry funding by the meat industry, and this appears to play a role in the papers that came out two weeks ago saying that meat is fine and just keep on eating. So whenever you have an industry with a vested interest in defending a product that is potentially harmful, if that industry gets involved in funding distracting research, then that muddies the waters very quickly. And we know that this has happened in nutrition.

And then the third thing has to do with the way journalists report on this. So a new study comes out, and if the new study contradicts accepted wisdom, often journalists will run with that story because this is exciting, and this is what happened with the meat story. Some papers get published that say the evidence for the harms of meat is weak — that was their claim; therefore, since people like meat, they should just keep on eating it. Now that was a very illogical claim, because even if the evidence is weak, it’s still evidence — this gets back to the argument on evidence — and whether people like something and whether it’s good for them are two different questions. We could say, “Yes, it’s true. People like meat, and if they want to eat meat knowing that it’s bad for them, it’s a free country and they should have the right to do that.” And you could say the same thing about smoking, right? Yes, smoking is bad for you, but if knowing how bad it is, you still choose to smoke — well, there we have to have the caveat that actually it does harm other people, so you also have bunch restrictions there, but it’s perfectly legitimate for you to smoke if you make that decision as a grownup. 

But those papers deliberately conflated those two different things, and to me that’s highly suspicious. To say, “Well, you should keep on eating meat because you like it,” is to me an illegitimate argument in a paper that’s supposed to be about the question of whether or not it’s harmful. There’s some real industry conflation here — distraction, disinformation — and that’s made it very, very hard for people to figure out what’s going on. But now add the journalists to it. This set of papers comes out with an aggressive press release from the journal, which is a whole other issue which we could talk about or not, depending on if you want to go there — there were a lot of layers in this beef issue. But the journalists ran with it, and had big headlines, “Maybe red meat’s fine after all; keep on eating meat.” And so of course this got a huge amount of attention because it was unexpected, because it seemed to go against everything we know. 

And then within a couple of days — I mean the New York Times did a big spread on this and the very next day they’re like, “Well, actually it turns out some of the authors might be linked to the beef industry, so maybe it might not be as good a study as we thought.” So right away, immediately, you can imagine a meat lover says, “Oh my God, first it’s bad for me, then it’s good for me, now we’re not sure. Guess what? I’m going to just keep on eating hamburgers.” Which of course is exactly what the industry wants. So journalists are actually playing into the hands of the industry when they do this, and one of the things we know from our work is that the industry knows that and they do this deliberately. They deliberately try to get the media to cover confounding or distracting studies in the hopes that people will be confused, and therefore they’ll say, “Okay, well it’s too confusing, so I just keep on smoking, I just keep on eating meat, I just keep on eating sugar.” Because that’s what they want. 

Ariel Conn: The journalists are clearly a problem there. And I guess the other question I have, then, is to me it doesn’t seem that people who are not into science really understand the difference between profit-based industry science and, say, academic science. 

Naomi Oreskes: Yeah. I think that the distinction between profit-based science and academic science is not appreciated by most people — and frankly, here’s where now we have enough blame to go around. I mean here’s where academia and universities have played a role too. Because of the decrease in funding for scientific research in the last 30 years, universities have been very aggressive about soliciting industry partnerships, industry funding, and have really encouraged faculty to actively seek out private sector support. And that’s not necessarily bad. There are certainly examples of private sector support for research that are good; I always do full disclosure, my PhD was funded in part by a mining company. So it’s not that industry funding is necessarily bad or corrupting, but it can be bad. If we’re going to have industry funding, we have to be much more careful, in my opinion, about how we do it, what our disclosure rules are. 

So for example, the Annals of Internal Medicine does have a disclosure policy, but it’s a very weak one. And so what we found out in this beef story was that these authors did file a disclosure claiming they had no conflict of interest, but very quickly it came out that actually they did have conflicts of interest. But technically, they had in fact followed the disclosure policy of the annals of internal medicine — they had followed the letter of the law, if not the spirit. 

And the journal said, “Well, we don’t check; we rely on the good faith of the authors to reveal potential conflicts.” I mean, I get it — the journal probably doesn’t have the capacity. But if they’re not checking, then how do we enforce it? And so my view is — two views on this. One is that, actually, a certain amount of checking would be in order. I think for a study like this that was so contra-suggestive, so counterintuitive, and which to my mind actually had a number of red flags that we could talk about if you’re interested — but I think a study like that, the journal actually did have an obligation to do some due diligence. Because it only took the New York Times 24 hours to find out that a lot of these authors did in fact have industry connections, so that tells us that the journal could have found that out pretty quickly too. 

So I think that for really consequential papers having to do with public health, that seem to be surprising, I think journals do have an obligation to do some due diligence. However, I also think that the journal is right to say that they can’t really be expected to be policing the disclosures of people. So I think that if it comes out after the fact that people have not disclosed relevant conflicts of interest, I think the papers should be retracted. Because unless there’s some consequence to malfeasance, then the policy isn’t really worth the paper it’s written on. 

Ariel Conn: Could that be something that’s asked of the reviewers of the paper, to also just do a quick Google search of the authors? 

Naomi Oreskes: Yes. I think it would be reasonable to ask reviewers to at least take into consideration whether there could be, or appear to be, the suggestion of potential conflicts. I will tell you — I have it right here on my desk, so I will read you something that I think is a red flag. The editorial is called Meat Consumption in Health: Food for Thought, and this ran in the Annals of Internal Medicine in the same issue that published the paper saying that there was no good evidence of any harm in eating as much red meat as you want. And the editorial was basically saying how great these papers were. So that already is sort of taking sides in a way that I think was unhelpful. I think it might’ve been more helpful to have an editorial that was a little bit more neutral, to say, “These papers will be controversial; they go against tremendous amounts of evidence we have, but it’s right that we should have a serious discussion of them. It’s right that they’re being published.”

But here’s the interesting thing. He says, “It may be time to stop producing observational research in this area.” This is the exact same thing that the tobacco industry did. The tobacco industry tried to claim that the whole science of epidemiology was no good because you could never prove causation, and therefore that epidemiological studies should not be allowed to be used. Well, we can laugh at that now, because obviously we know that epidemiology is really important and we know that it played a crucial role. But at the time, many people took that argument seriously and epidemiologists were put in this very defensive position where then they had to explain why their science was legitimate. The same thing has happened now: all the people who’ve done observational studies, now they have to defend the legitimacy of observational studies. So that’s a huge red flag to me. Nobody should saying that. A person should say, “Sometimes observational studies are the best thing we have. If that’s all we have, then we have to use it because that’s what we have.”

And the same with animal studies. Animal studies obviously are imperfect; no animal model is exactly the same as people. But we use animal models because there’s all kinds of things we can’t do to people, and we know that there are some animals — particularly pigs, for example — whose metabolism is a lot like people. So it’s not perfect, but we can get really good information out of animal studies. I raise this because there are now people in the industry saying we shouldn’t use animal studies, that EPA should not be allowed to use animal studies to prove toxicity. So now if you eliminate animal studies, what’s left? 

Ariel Conn: The issues that you’re talking about with people who now have to defend their science and all of that, I think that ties back to the question I asked much earlier — for you to talk about the difference between facts and values and what scientists need to understand about communicating both. 

Naomi Oreskes: Well, the fact-value distinction is one about which hundreds of articles and books have been written. So people have spent a lot of time trying to sort this out, and I don’t pretend that I can solve a problem that hundreds of people before may have not solved. But in a broad way, I think we can say the following thing: there are certain kinds of questions about the natural world that we believe science can answer. And that’s why science exists: to answer questions about the laws of nature, about the origins of species, whether continents move. And these are questions that exist, in a sense, prior to us. The continents don’t care what we think about them. Gravity doesn’t care if you’re a Republican or a Democrat. Acid rain falls on golf courses as well as organic farms. So nature exists prior to us — I mean, of course we have changed it in the Anthropocene, but it exists prior to us and it operates according to what we conventionally call the laws of nature. 

And the purpose of science is to understand what those laws of nature are, using the word law broadly. And traditionally, we view that project as being distinct from what we would call value questions such as what is the meaning of life? Is there a God? Is it better to smoke and be happy than not smoke and be unhappy? You know, anything that has to do with our preferences — what we like or don’t like, what we want to be true, what we care about. And there’s a long, large literature that traditionally has supported the notion that these two domains can be cleanly separated, and it’s the job of science only to answer the fact questions. 

Now, in recent years that’s been challenged for a variety of reasons, one of which is the one we’ve already discussed, that in reality human beings are not really able to separate these things so cleanly. And particularly, if I study something like coral reefs, it may be the case that I am motivated to study at them because they’re threatened and because I think they’re beautiful and because I care about coral reefs, I want to study. And therefore, my scientific work is actually intercalated with my values that tell me that coral reefs are beautiful and should be preserved. 

So the traditional scientific response to that is to say that I have to try to unpack those two things — even though in reality they’re intercalated — and when I talk about my science, I should only talk about the fact piece. But I think one of the things we’ve learned is that it doesn’t really work. We are motivated by the values and our listeners are motivated by the values, and in fact, when you bring up the value — like the fact that coral reefs are amazingly beautiful and awe-inspiring and might even actually make you believe in God — when you talk about those things, then you suddenly find that people who might not otherwise care about coral reefs and might be completely — if you start talking about the facts, they’re totally glazed over, but you start talking about the values, suddenly they’re listening. This idea that we can actually connect with people through the values piece, which has led me to believe that — it’s not to say that facts and values are the same thing, I’m not arguing that, and it’s not to say that there isn’t some virtue in still trying to be clear about what parts of the story are factual and what parts are value-based, but it’s to say that some integration of the two could turn out to actually be a useful thing, particularly when we’re trying to communicate to people why the science matters to them and to their lives. 

Ariel Conn: What do you think are some of the biggest misconceptions that scientists have regarding public perception of science? 

Naomi Oreskes: I think one perception is that people are stupid. A lot of scientists wouldn’t say this out loud because they know it’s not socially adept to say that, but I think a lot of scientists think that the reason why people don’t understand science is because they’re stupid or ignorant. 

Ariel Conn: I feel like we do get that a lot against people who don’t want to vaccinate their kids. They’re constantly attacked for their intelligence. 

Naomi Oreskes: Right. But that’s false, and we have lots of evidence that it’s false. And I always say scientists are actually being very unscientific when they say that, because they’re not actually looking at the evidence. We have a lot of evidence that there are many highly educated people who reject science in particular domains — for example, particularly in climate science. One of the things we know from the evidence is that among Republicans, the more educated you are, the more likely you are to reject climate science. That’s a little bit of a scary statistic, especially for those of us who believe in education. 

Ariel Conn: Are there theories about why? 

Naomi Oreskes: Yeah, there are. The theories are that the more highly educated Republicans are more likely to read The Wall Street Journal or Forbes, some of these magazines that have promoted climate change denial. Or they’re more motivated: maybe you run a business that’s dependent upon cheap fossil fuels. Then you are more motivated to try to find denialist arguments, so you go on the internet and you look for those arguments and you find them. There could be a number of different explanations for it, but that tells us this is not a problem of ignorance. Many of these people are intelligent, and the same with vaccine rejection. 

Seth Mnookin has a great book called The Panic Virus. One of the things he talks about is the families of children with autism who blame it on their vaccinations. And many of these people are not uneducated, but they are sad. Their children have a situation that’s very hard to deal with and they don’t know how to help their children. And frankly, modern medicine doesn’t have a lot to offer them. And they’re looking for someone to blame. And so if someone comes along and says, “Well, it’s the vaccinations,” and sure enough the child’s autism developed just around the time that they got their vaccinations, it seems to make sense. It’s not that they’re uneducated or stupid, but they’re in a situation in which they’ve become motivated or incentivized to look for other explanations. 

The other big misconception is the one we started with, that there’s a general crisis of trust in science — that’s false, all the evidence shows us that’s not true. But people do reject science in specific areas where they think the implications of science threaten their worldview or their economic interests or their religious beliefs. And that’s crucially important because it tells us that you will not reach those people simply by giving them more factual information. 

This is what sociologists call implicatory denial. You deny something because you don’t like its implications. The only way to address that is to talk about the implications. Here evolution is a good example: we know that many people who reject evolutionary theory reject it because they think it means that life is meaningless. If life is produced by a random purposeless process, then my life is meaningless. That’s not true. I mean, life can have all kinds of meanings, and there are many atheists who think that life is very meaningful. There are many evolutionary biologists who are religious believers. So there are many ways to adjust the question of meaning within the framework of evolutionary biology. 

And there are people who’ve done this. John Howden is very articulate on this; Kenneth Miller from Brown university. There’ve been studies: Arizona State University, they’ve done some very nice work where they show that if you take children, or I should say college age students, who come from, say, evangelical Christian backgrounds and who begin with this idea, that evolutionary theory is something that they do not like, but then you talk to them about this question of meaning and how biologists who are religious believers find meaning even in the face of random evolution, this can be transformative for many of these young people. So if you correctly diagnosed the problem, and you don’t blame it on stupidity or superstition but you actually engage with what it actually is, then you realize that there are options that can work. 

Ariel Conn: Climate change, I think, does hit all three of those points that you mentioned in terms of why people don’t trust science. As we’re doing this interview, The Guardian just came out — well, I read it in The Guardian, I don’t know which paper published it first — but a discussion about how arguments against addressing climate change are shifting. We’ve established that climate change is happening, and so now the shift is to this idea that well, if it’s already happening, it’s too late for us to do anything, so there’s no point in trying to address climate change. I guess I have a two part question for you there. One, what’s your response to that? 

Naomi Oreskes: I mean that’s just idiotic. Anybody who says that actually is either an idiot or they’re a shill for the industry because that’s just an extremely foolish thing to say, because we know that the more greenhouse gases in the environment, the worse it gets. Every day that we continue to delay, the problem gets worse. But if we get it under control, there’s still the opportunity to the worst case disaster scenario. So that’s just a factually incorrect argument. 

Ariel Conn: I think the next part is we’re likely to continue to see the sort of evolving argument against climate change. Do you have ideas for how we can try to minimize that? 

Naomi Oreskes: What people have to understand about this is that it’s not that the arguments are evolving; it’s that the climate change deniers have a Rolodex of different arguments that they pull out at different times. And we have seen many arguments go away and then come back. So you could say, “Well, nobody now would say there’s no climate change because you can’t just say that with a straight face.” But actually, back in 1997, people said the exact same thing and, guess what, it came back with a vengeance. And we have seen this now; if you’ve been following this issue for 20 years as I have been now, this is what you see. 

It means A, you can’t get complacent. You can’t believe that, okay, we’ve solved the outright denials of climate change; now it’s this denial of fatalism or nihilism. No, that rationale will come back. In fact, it’s still there on the internet. The blaming it on other things, we’ve seen that argument come and go. It’s like the game of whack-a-mole. These arguments pop up and they get beaten down by scientists, so they go away for a while and then they shift your attention to a bunch of arguments and then they say, “Oh, but wait, what about this one?” And then it comes back. This is part of how we know how cynical it really is, because if these were good faith arguments, they wouldn’t return to an old discredited argument. And yet we see that happening all the time. 

Ariel Conn: Do you think we might do better if, rather than talking about all of the awful things that climate change is going to cause and all of the changes everyone needs to make, et cetera — I mean, we still need to talk about all of that — do you think we should be focusing more on how much better things would be if we do this? 

Naomi Oreskes: I think that’s a “yes, and” or “yes, but” question. I think you’re right and certainly Nick Stern, with whom I recently wrote an op-ed piece, is very strong on making that argument, that there’s a positive vision of what a new economy based on renewable energy can look like, and it involves in many ways a much better life. I mean think about all the time we waste in traffic every day. How is that a good thing? And this is why I put the cartoon in the book. Well, what if we create a better world for nothing? If we address the climate change issue, we can make a lot of other things better too. I definitely agree with that, and I have been making that case for a long time and I think a lot of people have. But at the same time, one of the things we know is that even though that positive vision has been painted by a lot of people, we still don’t get rid of the denial. 

And that’s because we have people out there who are just doing everything in their power to keep the fossil fuel economy alive and to continue to make profits by selling fossil fuels, come hell or literally high water. That tells me that this is fundamentally a political problem, that we have to fight the political power of the fossil fuel industry. And a lot of scientists don’t like to talk about that because they don’t want to be political. They went into science because they like science and they like things that are not value-laden. And now you say to them, “Well, actually this is a political problem.” That’s a hard sell for a lot of scientists. So my view is, okay, that’s fine. I mean, let’s face it, there aren’t really that many scientists in the world anyway. The scientists can keep doing science, because that’s what they love and that’s what they’re good at. 

But for the rest of us, the message is we have to become politically activated, we have to fight against this industry that has basically bought congress and is doing something that most of us don’t want, that’s not in our interest — it’s not in our economic interests, it’s not in the interest of our health, certainly not in the interest of the future prosperity of our children and our grandchildren. This is a really, really bad thing. And the only people who want it are the people who either are profiting from it or who have been misled by the arguments of the people who are profiting from it. And so we have to fight that. We have to find the disinformation and we have to fight what’s essentially the corruption of our political system. So that’s something that’s hard. A lot of people don’t want to hear that, especially people who thought they were coming to hear a talk about science, who thought they were going to listen to a podcast about science. But that’s the lesson of all this, is that fundamentally it’s about politics, and it’s about fighting for a democracy that actually represents the interests of the American people. 

Ariel Conn: That is a perfect connection to the last question I have for you. What do we do? I think I’ve interviewed almost 30 people at this point, 30 experts — maybe even more because I’ve had multiple people in a couple of the shows — all talking about climate change, the threat, what we do about it. And honestly I feel a little bit more comfortable knowing some of the things we should be doing. I think it’s easier to identify individual actions we should be taking. But in terms of getting political and trying to help get power away from the fossil fuels, that seems really daunting. 

Naomi Oreskes: It is daunting, but it has to be done, because the whole personal responsibility thing — that’s a very tough one. Obviously, absolutely everyone should do what they personally can do, and if you have it in your power to make changes in your life, then you by all means should do it. I have solar panels on my roof, and I have greatly reduced the amount of meat I eat, and I’m trying as much as possible, when I get invited to conferences in far away places, to ask them if I could Skype instead. We definitely have to do the personal thingsm because otherwise we can feel incredibly disempowered if you feel like there’s nothing I can do except change the entire political system, right?

Ariel Conn: Uh-huh.

Naomi Oreskes: It is important to do those personal things. But as I like to say, I can change my light bulbs by myself, but I can’t change my electricity grid. There are big structural issues that have to be addressed and we cannot solve this problem simply by changing our light bulbs. What you can do that’s a little less daunting is, a lot of this could be done on the state level. Here in Massachusetts we have a renewable portfolio standard that’s making a difference. I was able to do my solar panels in part because we got tax credits due to the renewable portfolio standard. The same thing in California, the same thing in New Jersey. We know that these policies make a difference, and they make a difference in part because they help empower people to do the right thing on the personal level. 

And it turns out that on the state level, it’s a whole lot easier than on the federal level for a variety of different reasons. And when you get involved in state politics, I don’t want to say that it’s always great, but I think that for many people there’s a sense that our state government is more responsive than the federal government. In many states, not all, but in many States there’s a feeling that it’s not as utterly bought as the Senate is right now, let’s say. That can be a place to start. And also cities: cities have tremendous power because the vast majority of carbon emissions come from cities, because carbon emissions are linked to economic activity and most economic activity is taking place in cities. 

And here’s something to feel good about: most cities in this country are progressive. Polls show the people who live in New York, Boston, Philadelphia, Chicago, Los Angeles, San Francisco, Denver, Seattle — all of the major cities in this country — all the major population centers are filled with people who want action on climate change. And if those cities would install renewable portfolio standards, carbon taxes, it would make a giant difference. And one of the things we know from history is that when cities and states act, sometimes the federal government follows. 

If we think about air pollution regulations, Clean Air Act, all of those great laws that clean up the air in the United States: in the 1960s, people were dropping dead in the streets from air pollution. This is something a lot of people have forgotten, or maybe young people never knew, but literally dropping dead on the streets of Los Angeles from air pollution. That doesn’t happen anymore. We fixed that. And we fixed it through sensible laws. But who led the way? It wasn’t the federal government; it was the state of California. And when the state of California began to move on air pollution control, the federal government followed. And I think that’s what we’re going to see here too. I mean, right now we already have California moving in a big way. We have New York, Massachusetts, New Jersey, some other states also starting to move. I think if enough of the states begin to move, we will see the federal government follow. Maybe not in this administration, but quite possibly in just a year or two from now. So that’s the optimistic, don’t-feel-depressed pep talk with which we can end the podcast. 

Ariel Conn: I like it. Is there anything else that you think is important to mention that we didn’t get into? 

Naomi Oreskes: So it’s a both end answer. Yes, you should absolutely do what you can do on a personal level. And this is one reason why the nutrition thing is so important, because food is the thing that, as individuals, we have the most control over. We can start changing the way we eat tonight. And if you cut back on beef — and this is something that frankly the beef industry doesn’t want you to know, but it’s true — this is the total absolute win, win, win solution because A, it’s better for your health; B, it’s better for the planet; and C, it’s cheaper. A healthy vegetarian meal costs a whole lot less money, in general, than a beef meal. So nutrition is a really, really good place to start. And then you can build out from there and then you’ll feel better and you’ll be healthier, so you’ll be more empowered to take political action. 

Ariel Conn: All right. Well, thank you so much. I personally really enjoyed your book. I encourage everyone to read it. I will also add, there was a question I was going to ask about some of the different sciences that you looked at and since we didn’t get into that, I will mention it’s limited energy theory, continental drift, eugenics, birth control and depression, and the debate about dental floss. And I’m hoping that will help entice people to check out your book.

Naomi Oreskes: Great. Ariel, very nice speaking with you.

Ariel Conn: Yeah, you too.

I truly hope you’ve enjoyed these interviews and this episode specifically. As I mentioned at the beginning, we’ll round out the Not Cool climate podcast series with a short final episode recapping some of what we covered and some things I wish we’d covered. Thank you so much for listening, and as always, if you enjoyed this episode, please like it, share it, and maybe even leave a good review.

Not Cool Ep 25: Mario Molina on climate action

Most Americans believe in climate change — yet far too few are taking part in climate action. Many aren’t even sure what effective climate action should look like. On Not Cool episode 25, Ariel is joined by Mario Molina, Executive Director of Protect our Winters, a non-profit aimed at increasing climate advocacy within the outdoor sports community. In this interview, Mario looks at climate activism more broadly: he explains where advocacy has fallen short, why it’s important to hold corporations responsible before individuals, and what it would look like for the US to be a global leader on climate change. He also discusses the reforms we should be implementing, the hypocrisy allegations sometimes leveled at the climate advocacy community, and the misinformation campaign undertaken by the fossil fuel industry in the ’90s.

Topics discussed include:

  • Civic engagement and climate advocacy
  • Recent climate policy rollbacks
  • Local vs. global action
  • Energy and transportation reform
  • Agricultural reform
  • Overcoming lack of political will
  • Creating cultural change
  • Air travel and hypocrisy allegations
  • Individual vs. corporate carbon footprints
  • Collective action
  • Divestment
  • The unique influence of the US

References discussed include:

It’s important to know that there are 25 companies in the world that are responsible for 50% of global emissions in the last 30 years. And it’s about 50 companies in the world that are responsible for about 85% of global emissions.

~ Mario Molina

Ariel Conn: Hi everyone. Ariel Conn here with Not Cool, a climate podcast. For episode 25, we’ll be joined by the executive director of Protect Our Winters, Mario Molina, who will continue our discussion about what people can realistically do to help address climate change. We’ll also tackle some of the myths and misunderstandings surrounding the hypocrisy accusations that often get directed toward people who care about the environment, but who still do things like drive cars or fly. And, of course, we’ll consider what winter will look like in the future.

In addition to being the current executive director of Protect Our Winters, Mario previously served as international director at The Climate Reality Project, where he designed the organization’s climate leadership trainings and oversaw its post-Paris Agreement international strategy. Prior to his work at Climate Reality, Mario led strategy and programs as deputy director at the Alliance for Climate Education (ACE). He has trained corporate leaders, government officials, NGO groups, athletes and activists, on climate change strategies, communications, and engagement. He has spoken widely on climate policy including for the World Bank, IBM, the Mexican Senate, the Brazilian Forum on Climate Change, and various global stages.

In his free time, he’s an avid alpinist, snowboarder, mountain biker, guide, and life adventurer. 

Mario, thank you so much for joining us.

Mario Molina: A pleasure to be here. Thank you so much for having me.

Ariel Conn: My very first question for you is just what is Protect Our Winters?

Mario Molina: Protect Our Winters is a nonprofit, and our mission is to turn passionate outdoors people into effective climate advocates. We work with elite athletes, forward-thinking business leaders and brands, outdoor recreationists as a whole to advocate for systemic climate change policy. That involves working with top-tier athletes across multiple fields — whether they be snowboarders, skiers, climbers, mountaineers, ski mountaineers, trail runners, mountain bikers — to use their voices and their platforms to mobilize both their constituents and their audiences, as well as using their voice and their platforms to show up at public utility commission hearings, to show up to lobby in DC, show up to lobby at the state level, and ultimately to motivate people to get civically engaged with climate change as a top priority in their civic engagement agenda.

Ariel Conn: We’re obviously struggling to get more people to do more with climate. Do you find that it seems easier to get people who are already interested in the outdoors to be more active and stronger advocates, or do you find that it’s just a challenge, period, to get people to take action?

Mario Molina: I think it depends on what group you’re looking at. People who are passionate about the outdoors are naturally going to be more inclined to care about climate change. But there’s a lot of misinformation and there’s a lot of confusion as to what people can actually do and what the solutions actually look like. And so educating the outdoor sports community is just as important as it is educating any other community, because that information is not widely spread across the outdoor community yet.

Having said that, I think that overall, the Yale study on Americans’ attitudes on climate change actually shows that most Americans — 76% of Americans — actually believe that climate change is real. 64% of Americans, regardless of political affiliation, believe that not only it’s real, but it’s human-caused, and that the government should do something about it. And so what we’re really trying to do is not necessarily convince people who don’t think that climate change is real; we’re looking at people who don’t quite understand the issue as well, or who are not as concerned as we all should be about the urgency of taking action.

Ariel Conn: And so with your work: how is it similar to, and how does it differ from, many of the other climate advocacy organizations?

Mario Molina: The traditional environmental base, or climate organizations, have done a really good job at building the base for the last 10, 20, 30 years: people who identify as climate advocates, and for whom climate change has been and is the top priority, and continue to engage on the issue. But what we’ve seen is that that base has not been enough to actually make the progress that we need to at the speed that we need to. 

We’ve seen it over and over again. We saw it in 2010 with the failure of Waxman-Markey bill, which was a cap-and-trade bill that passed the House but did not make it through Congress. We even saw it in the first term of the Obama administration, in the failure of the movement to make climate change a top priority for the administration over healthcare. And then we saw it with a slew of rollbacks that this administration has put into place that’s pretty much full on assault on any kind of progressive climate change policy that we’ve seen — from the rollback on methane regulations to the leasing of public lands for fossil fuel extraction, the elimination of fuel standards for vehicles, tariffs on solar panels, etc, etc, etc.

Where we differ is we believe that we are bringing to the conversation a group of people who has traditionally not been seen as an important block on this issue, and that’s the outdoor sports community. These are people who first identify climbers, skiers, snowboarders, etc, whose passion really lies in the outdoors, who have not yet made climate change a top policy priority when they vote for their elected officials or on the things that they prioritize their civic engagement on. And that’s where we feel we can add that voice.

There’s 36 million people in the US who identify as either skiers, snowboarders, mountain bikers, climbers or trail runners. We don’t necessarily need all 36 million people; we need a few thousand people in the right places at the right times to show up and say, “Hey, this is something that we really care about.”

Ariel Conn: And how long have you guys been around?

Mario Molina: We’ve been around for 10 years.

Ariel Conn: In that time, what are some of the successes that you’ve had, especially in light of some of the rollbacks we’re seeing? What have you guys achieved that you think contributes most to helping?

Mario Molina: We see our success in two particular areas. One is the political will for change amongst the outdoor sports community, and the other is a shift and a cultural influence within the outdoor community to make this a priority. And so along those lines, in 2018 our sister organization Protect Our Winters Action Fund engaged in electoral work, trying to elect people who would be climate champions into office in mostly the House and the Senate. And then Protect Our Winters has done a lot of advocacy for state-level policy work.

And so in 2018, I think the biggest success that we had was helping to make voting a cultural norm amongst the outdoor sports community and educating people on the importance of voting, helping people make sure that they were registered to vote; then helping them make a plan to vote, making sure that there was the social pressure to get out and vote, as well as getting out the vote efforts.

In 2019, a lot of our work was at the state-level policy, so we were part of the coalition that supported the passage of HB 1261 here in Colorado — which, for those who don’t know, is the most aggressive climate change bill to pass any state legislature. And it seeks to make Colorado 80% renewable by 2030, and it does so across all sectors of the economy. So we mobilized the outdoor sports community in support of that bill.

We did it in Nevada in 2018 around the vote YES on 6, which was a ballot initiative to increase Nevada’s renewable portfolio standard, the amount of renewable energy that must be carried by a particular state in their energy grid. And then actually working to pass that ballot initiative: that one was signed into law as well earlier this year. We were part of a coalition in Maine, working also for an increase in RPS standards in Maine; and we’re now working with a coalition for 100% renewable municipalities in Utah.

So, our success really lies in bringing that additional voice to the conversation, and either leading where leadership is needed, or working in coalition where coalitions can really use the value of the outdoor sports community voice.

Ariel Conn: How many is your alliance?

Mario Molina: All total together across all three areas of our alliance — there are three types of alliance members: athletes, scientists, and CEOs and brands — there’s about 200.

Ariel Conn: If I understood the website correctly, you’re also global?

Mario Molina: Yes, we are. We have chapters in 10 European countries, and Europe is coming together under a single strategy umbrella this year that will launch a campaign on mobility in 2020, prioritizing low emissions mobility solutions in Europe. We have chapters in Australia, New Zealand and Japan as well. Now, most of those act pretty independently of headquarters; we started working with a lot more closely with Europe this year and we plan to expand to Asia and South Pacific in 2021.

Ariel Conn: One of the questions that I’ve been asking people off and on a bit is understanding what we can and should be doing at a local level, versus what we can and should be doing at a global level. What are you finding most effective so far?

Mario Molina: I always have a little bit of a hard time with the distinction between what we do at the local level and what we do at the global level. I don’t remember exactly who it was that famously said, “All politics is local.” Because climate change is a global problem with local sources, to me it’s very difficult to distinguish those two.

Having said that, supporting organizations that are doing the work and that care about the work is obviously number one. There are organizations that are working on climate in the Amazon; there are organizations that are working on climate and oceans. There are organizations that are working on climate in winter, like we are, or adventure sports. So figuring out which organization best fits your values and your lifestyle, and supporting those organizations, I would say, is the first step — if not the most important step.

But then also being really well-informed and learning about the issue. It is a complicated issue. It’s hard to actually expose both the problem and the solutions in 30 seconds during a presidential debate, for example, or in tweet fashion. It’s a complicated problem; it’s a large problem, and it has both local and global implications. But the information is there. The science is far, far ahead of the public’s knowledge. The policy solutions are far ahead of the public knowledge, and the technological and financial solutions are actually far ahead of what’s being implemented.

So studying those, understanding what are those solutions, what does the science say, and then from there getting an example — okay, what is keeping us from actually implementing those solutions at the scale that we need to in the timeframe that we have? Because the answers, in terms of what should I do and what can I do, start becoming far more obvious once we start understanding what the problem is and why we’re not actually taking the solutions that we need towards it.

There’s three components to the solutions, and one is we need the technology and the financial instruments to be deployed at scale in the timeframe that we have. So we need renewable energy, we need storage, we need electric vehicles and low emissions vehicles. Then we need the financial mechanisms that will incentivize research and development and investment in those technologies. Things like carbon pricing, but also incentives, stability in the production tax credit and the investment tax credits, which are tax credits for solar and wind.

And the thing is, we know that those exist. The technological solution exist, as do the financial instruments to deploy them. But what’s keeping us from deploying them at scale and in rapid fashion is the lack of political will. So we’re seeing states showing leadership, but what we really need is we need a full on transformation of what the priorities are for the country that put climate change at the very top — so that we address not only energy and transportation, but also agriculture, and start transitioning to regenerative agricultural practices that can actually help us sequester carbon rather than continue to emit more carbon and methane. That will happen when we have a political critical mass that makes it unacceptable not to prioritize climate change action in either one of the parties. And I do believe that we are getting close to that. It’s becoming harder and harder for politicians and elected officials of any party to deny the reality of climate change.

But then the third piece is we also need a cultural change, and we need to make sure that those policies are not only politically resilient — that they don’t go away with the shifts in administrations, where they go from Republican to Democrat, or whatever it might be in the future — so that they stay in place and that people will adopt those policies. So it’s one thing to have an offering of electric vehicles; it’s another thing to make sure that the public is invested in wanting those electric vehicles and making sure that the market is driving it.

That cultural change is really important. The example that I give is if anyone running for office were to stand up on a platform and say, “My platform is I think we should do away with drunk driving laws. We could sell more alcohol, which would benefit a lot of states. We could boost the economy; we could generate jobs by selling more alcohol to people who are on the go.” You’re laughing. We would all laugh. It’d be ridiculous. People would be laughed out of the campaign trail regardless of what political party they belonged to. But that was actually not that far fetched 20, 30 years ago. Drunk driving laws came about much by the advocacy of Mothers Against Drunk Driving. We might all remember those campaigns, and they won that battle legislatively state by state. But the reality is that even though those laws exist now, it’s become a cultural norm that it is unacceptable to drive drunk, right? It’s unacceptable to drive while drinking.

It’s good to still have the laws, but culture has actually enforced those. We could say the same thing about tobacco, right? The decline in smoking, especially under age smoking, and the effects of the truth campaign: we need to get to a point where we hold the fossil fuel industry accountable the same way that we held Phillip Morris and the tobacco industry accountable.

Ariel Conn: And you feel like we’re getting close?

Mario Molina: I feel like we’re getting closer. I think our challenge, unlike that of any other massive social change that we’ve experienced, is time. Time is the enemy. I think it was Sheikh Abdullah Muhammad who said, “The stone age didn’t come to an end because we ran out of stones.” Fossil fuel is not going to come to an end because we run out of ways to figure out how to extract fossil fuels. You now have fracking, you have deep sea exploration, you have deep mining, etc. We can blow far past the carbon budget with the fossil fuel reserves that are still in the ground.

But the point is that we have to actually transition a lot quicker. We have to transition before we hit that carbon budget limit. The IPCC report says we’ve got about 12 years to really drive a significant transformation. I think we are far, far closer than we have ever been politically, in terms of making this a priority. There’s a famous economist who said, “Change takes longer to happen than you thought it would, but when it does, it happens far quicker than you thought it could. And I think that what we will see is it’s not going to be the gradual transformation that we hoped would happen 30, 40 years ago, when we could have taken this step-by-step approach to it. I think it will be something to the scale of the Marshall Plan, where we actually transform the entire economy, geared towards getting to net zero emissions by mid-century.

Ariel Conn: You’ve mentioned a few times now that basically the technology exists. But there are some places where, as far as I know, it doesn’t exist, and that’s things like flying. I don’t think we’re there with planes yet. One of the things that I saw — I see this generally, but also when I was researching Protect Our Winters — were attacks about hypocrisy. As far as I can tell, it happens to everyone who’s trying to address climate change. They’re being accused of being hypocrites; the idea of, in order to take these ski vacations, you have to fly places — it’s all fossil fuel based. How do you respond to that?

Mario Molina: I love that question, because it’s so ubiquitous and yet at the same time when you break it down, it stands on a very weak argument. Let’s break this down and start at the beginning. Understand that the fossil fuel industry — it is well, well documented that ExxonMobil, Chevron and a lot of the fossil fuel industry, through the American Petroleum Institute, actually funded a misinformation campaign starting back in the 1990s whose explicit goal, as described in the memo, was to make sure that there was enough public debate about whether climate change was real or not; that it was not perceived as established science. This was in response to the Kyoto protocol in 1998. One of the lesser known tactics of that campaign was to actually fund communication strategies that shifted the blame and the responsibility for carbon emissions from the corporations that are responsible for the systems that we rely on to get our energy from, to the individual.

And so you can go back through archives and you’ll find records of ExxonMobil actually funding environmental organizations that encourage people to recycle and to drive less and to eat less meat, etc, etc. I’m not saying that we shouldn’t do those things; we should absolutely do everything that we can to reduce our personal carbon footprint. However, having said that, it’s important to know that there are 25 companies in the world that are responsible for 50% of global emissions in the last 30 years. It’s about 50 companies in the world that are responsible for about 85% of global emissions.

Ariel Conn: Wow.

Mario Molina: And when we talk about individual carbon footprint versus the carbon footprint of some of these corporations: on average, let’s say, the typical American citizen — just by the nature of living in the U.S — has a carbon footprint of about 20, 22 tons of carbon dioxide per year. That is because we rely on electricity that is powered by coal. That is because we rely on transportation that is powered by gasoline, and we have longer commutes than most of the rest of the world, etc, etc. People in South America, Guatemala, they’ve got carbon footprints about two or three tons. However, the reality is this: most of that carbon footprint is because of the systems that we rely on to live the lifestyles that we have. 

And so when you think about your individual carbon footprint — let’s say, okay, we’re going to take a ski trip. We’re going to fly overseas to take a ski trip. A pretty high carbon footprint for an overseas trip would be about six to eight tons of carbon dioxide. That would put your carbon footprint at about 30 tons. That is massive. That is 10 times more than the average carbon footprint of someone in the third world. Sure, not good. Problem. 

Now, let’s look at something like the Clean Power Plan. The Clean Power Plan was, during the last administration’s EPA, they proposed a plan to actually cut carbon emissions from coal-fired power plants by 20% to 30% on their 2005 levels. Just from the top 10 plants in the US, that would have saved over 200 million tons of carbon dioxide per year. We’re talking completely different orders of magnitude in terms of what the priorities are. When we are talking about shifting policies, we can put policies into place that would require relatively small changes to our lifestyle that could save, collectively, millions of tons of carbon dioxide, versus the 8 to 10 that we could save by individuals.

Because, let’s admit it, the majority of the population is not going skiing once a year. Yes, we can address that, but those are very marginal gains when we’re talking about what the massive bleeding is. What I compare it to is, when you train to be a wilderness first responder, you address the hemorrhage first. You don’t go for the little cuts and put bandaids on the little cuts; you address the arteries that are bleeding first. 

And so once you get to something like a country like Denmark: in Denmark, their average carbon footprint is, last I heard was about five, six tons. The argument like, “Oh, we can’t cut back on fossil fuel consumption, because we need it to live a first world lifestyle, or we’d have to cut back on our first world lifestyle” — nobody thinks that the Danes are living in caves. The Danes are doing just fine. But they have decarbonized their electric grid; they have improved their transportation system; they’re looking at agricultural solutions, etc. 

Once you get to that level, then it’s a matter of, yes, how do we actually change lifestyles? So our Danish chapter is working on, how do we encourage people to recreate locally or to take the train instead of flying? How do we increase local tourism, rather than trying to promote tourism coming in from China? Those are very valuable and valid approaches, trying to get from a per capita carbon footprint of six or four to three or two. But when we’re living in a society right now where most of our emissions are coming from the systems that we depend on, it’s not going to change because people stop flying to Whistler or stop driving to a crag to go climbing. That’s not going to get us there. We need large, aggressive, economy-wide approaches to climate policy that will cut emissions from the major polluters. That continues to be the fossil fuel industry. 

That’s the hypocrisy question. So when I advocate for climate policy but I’m still driving an internal combustion engine, I realize that there is a tension there, but I don’t feel like a hypocrite. Because as soon as we have more affordable electric vehicles in Colorado and I can upgrade my car at an affordable cost, because there are policies that are making that possible, I’ll be switching. In Colorado, the zero emissions vehicle executive order is going through and will likely be implemented here in the next year. I’m not doing a plug here, but I think it’s a Nissan Leaf — you can get a brand new electric Leaf for $17,000, $18,000. That’s far more affordable than electric cars used to be, but that’s thanks to incentives that are at the state level, the existing incentives at the federal level. That will actually help move the needle and transition the economy. So those are the choices that we’ll be able to make once we’ve addressed the policy and once we’ve addressed the political will piece.

Ariel Conn: To what extent can we influence change through how we’re spending money? There are corporations that are choosing to try to be as responsible as possible. How effective are those at driving these policy changes that we need?

Mario Molina: Hugely effective if we do it collectively. Something that people don’t think about is not just where we spend our money. Because let’s say I live about an hour from here. My gas was probably $80. Some people have $100 gas bill, $200 gas bill. Let’s play that out throughout the year: you’re talking about $2,400 that are going pretty much directly into the pockets of fossil fuel companies.

But we have to drive in this society that we live. We can go back and look at the history of why it is that public transportation is so ineffective in most parts of the U.S, and how it was that back in the 1920s you had companies that had a vested interest in having more cars on the road actually kill public transportation systems in Pittsburgh, in Boston, in many of the large urban centers. But this is the reality that we have right now. So, yeah, we can definitely try to drive less. We could all probably, without huge changes to our lifestyle, drive let’s say 30% less. That would cut our gas bill to $1800. That would be significant if we all did it collectively.

What we don’t often think about, however, is where is our money stored? Where are we banking, and what is that money being used for? Because I would dare say that, at least across most of middle-upper class America and above, you’re probably keeping more money in the bank than a year’s worth of gas. And that money is yielding interest, and that money is being invested, and that money is being used to leverage, to support debt, or to buy debt, etc. What is your financial institution doing with your money? 

Yes, there’s a political will, and you can tackle it through regulation and through legislation, and that’s very effective for sure. But there’s also the cash. How are companies being evaluated, and where’s the cashflow coming from, and how are they borrowing money? So if they can borrow money for cheap — I mean the reality is that most fossil fuel companies have either direct or indirect subsidies in the form of leases of public lands for coal extraction at under-market rates. Or, most recently, we’re fighting a battle to keep the Arctic refuge from being opened up for drilling; that’s public land. So there’s those subsidies, but there’s also the financing from private institutions.

Just as or more impactful than voting with our wallets at the supermarket or the gas pump — which yes, it’s an all out approach — is your financial institution divesting from fossil fuels? And not only is it divesting, but then especially when you’re talking about investment, there are plenty of well-performing funds in the market that will not invest in fossil fuel, either directly to the companies or to the infrastructure that supports it, but then will invest into renewable energy development, usually the catch-all term is socially responsible funds.

So to me, that is an often overlooked action that most of us can take that would have significant impact. Because if you talk about actually moving your 401K, that’s far more impactful in terms of what cashflow is available in the system than saying, “I’m going to reduce my gas bill by $800 a year.” There are banks who, as part of their investment strategy, they are not investing in fossil fuels. So a couple of examples that I can throw out there: Bank of the West, Alpine Bank — these are banks that you can rest assured that if your money is with them, they’re not investing in fossil fuels. And there are more and more of these institutions coming online. So an easy switch is just moving the money over.

And then your retirement plan, or your investment portfolio, sits within the company. Then that’s a form of advocacy, right there: actually asking your company to offer funds. A company doesn’t have to move their 401K provider in order to have the 401K provider, or their 43D provider, whatever it might be, actually offer portfolios that are socially responsible. It can actually be an offering, and give people the choice. And if that’s not the case, I think that is a form of advocacy right there within the workplace: it’s talking to your HR provider, getting enough people interested in it. And it doesn’t cost the company anything.

Ariel Conn: It seems to me, without having really looked into this — it seems like if you can get more influencers involved, that’s going to drive cultural shifts. Is that what you were seeing?

Mario Molina: That’s our hope. That is what we are hedging our work on.

Ariel Conn: And are you seeing that happening so far?

Mario Molina: In 2018, what we saw is we saw a cultural shift with respect to the outdoor sports community attitude towards voting, and all of a sudden it wasn’t a fringe topic; it wasn’t a boring topic. It was, that’s what people were talking about at the ski lift. That’s what people were talking about at the trail heads. We were driving the message of the importance of voting really, really, really hard. As for others, like Patagonia and Burton: influencers are not only the individuals, like our athletes — there are brands that are incredibly influential within the outdoor sports culture. REI, Burton, Patagonia, Northface.

Our hope is that by pushing this agenda as hard as we have been, we’re able to also get our partners on board. And we have been able to get partners on board that make it a priority as well for their employees, but also for their customers. It’s simple; it’s not easy. It’s a simple way for brands to actually stand by the value of civic engagement, and of climate. And that’s to get a message out around the importance of climate, and the importance of voting. We’re starting to see that more and more.

Ariel Conn: One of the things that I learned recently, that I was actually surprised by how shocked I was by it: we know that climate is getting hotter and hotter, and so we’re seeing these increasing extreme high temperatures. So it makes sense that we’re then not getting as many cold days. And it’s almost like it drove it home for me more to learn that we really haven’t had global cold extremes in the last few years. Those seem to be going away completely. We’re not getting those record breaking cold temperatures that we are very much getting on the other end of the temperature spectrum. So with news like that, you still seem very hopeful throughout this interview, and your whole organization is about protecting our winter. So I’m kind of curious, how hopeful are you? How do you remain hopeful? Do you have tips?

Mario Molina: We’re seeing a shift from the mean. I always want to be careful when we talk about weather to caveat it with the difference between climate and weather, because climate is the long-term trend, and weather is what we experience day to day, or week to week. And it’s still possible that we can see below-average temperatures on a given day. We still have this window. We have a relatively short, and shortening, window where we can avoid the worst impacts. That gives me hope because we have the solutions. We have the solutions; what we need is that political will to actually put them into place. Now, guaranteed, there’s enough latent heat in the system that we are still going to experience dramatic impacts of climate change over our lifetimes that we just can’t avoid. But what gives me hope is that if we are able to preserve some climate stability, we’ll still be able to find winter in places. It’s just not going to be as predictable as it has been.

What I’ve been trying, in order to protect our winters, has been trying to tell the ski industry is it’s not that we’re trying to preach doom and gloom, but it is going to get bad. It is going to get bad. The reason that you should care, as an industry, is because while we will still have places that experience winter, it will be a question about the reliability of the winter season, the duration of the winter season, and the predictability of where that winter is going to happen. So in the winter of 2017 to 2018, we actually saw the northeast had a lot of precipitation, and they actually had very cold temperatures. The west, we had a terrible winter — very low precipitation, above normal temperatures. President Trump said, “Oh, how about that global warming? Give me some global warming. It’s so cold out, and it’s snowing here.” Right?

And the reality of it is, it’s because of global warming. It’s because the jet stream, which usually keeps the cold low pressure systems in the Arctic, is becoming wobblier and wobblier as the temperature difference increases between the Arctic and the temperate and tropical latitudes. So that wobbling of the jet stream has these incredible effects of dumping a lot of cold, low pressure air further south, further into the continental US than it would otherwise. And if it hits a moisture pocket, then yeah, you’ll get snow, and you’ll get a winter. But that is variable. You cannot predict that. Three or four months ahead of winter, I think, is where the models are at right now. But it’s like, “Oh, this year it looks like the west is going to have a really good winter.” But we don’t know what’s going to happen next. 

So I find hope in the fact that we’ll still be able to chase winter, for those of us that are into winter sports; the fact that if we get this under control in the timeline that we have, we should be able to preserve a lot of the places that we have for other activities as well. But what gives me the most hope is the awakening that is happening. This is becoming a mainstream subject, and people are starting to really care about both the issue and what we’re doing about it. And that’s where I think the shift happens. We’ve known the science for the better part of 200 years, and really known the science for the better part of 50 years. We didn’t have the technology at a market competitive cost until, I would say, 15 years ago. But then something else that gives me hope is the price of the technology. Solar and wind now out-compete coal in every market in the U.S.

So the cost of the technology is dropping to the point that it’s market competitive. So to me that is really hopeful. And then, the question that we get often from people who may accept the reality of climate change — especially elected officials who accept the reality of climate change — but argue against the need for the US to take leadership, or to do more about it. And the argument is usually the following: “Yeah, it’s happening. But in the US we’ve actually reduced emissions, and we only account for 16% of global emissions. And no matter what we do, India and China are going to continue to increase their emissions as they ‘modernize.’ So we should not bear the brunt of the responsibility.”

There’s a logic to that argument, but what it fails to see is that there is no other country in the world that has the political influence, but also the cultural influence, that the US has. The reason that India and China are developing the way that they are developing is because people in those countries have seen the lifestyles that the people in the west — specifically in the US — live, and how those lifestyles are fueled. What they see is, that is the model of lifestyle that we would like to achieve, that we would like to be living, and the way to get there is through increased energy consumption. And the way to increase our energy consumption is through increased fossil fuel extraction.

If, as a country, we are actually able to maintain most of the lifestyle that we cherish, and actually shifted to be emissions neutral by driving electric vehicles, powering our grid with renewable energy, shifting our agricultural system to regenerative agriculture, etc, etc, etc — that model of a lifestyle, that’s what leadership looks like, when we talk about US leadership. That means that we’re leading not only technologically, but we’re leading culturally; that it is possible to live this fulfilling lifestyle — and in our case, for Protect Our Winters, that we are able to live a lifestyle where we go to ski resorts where the lifts are powered by renewable energy, and we either take public transportation that has low emissions, or we drive electric vehicles to get there, and the gear that we’re using is plant-based polymers, or whatever’s coming down the pipeline — so that we’re still able to do all of these things with a minimal carbon footprint. And if we’re able to model that to other countries, then they’ll see that they don’t have to develop based on a fossil fuel model. They can develop on a renewable energy model, and a regenerative agriculture model.

Ariel Conn: Is there anything that we haven’t brought up yet that you think is important for people to either understand, or something else that you think you’d really like to see listeners be doing more of?

Mario Molina: I would encourage listeners to follow and track any legislative bill that’s moving through either their state legislature, or through Congress, in the 2020 cycle. As well as join POW, and find out more about our organization, and our initiatives. And they can do that by texting ACT4POW, the number four, ACT4POW, to 52886. And make sure you’re registered to vote, and that you vote in 2020.

Ariel Conn: All right. Thank you so much.

Mario Molina: Thank you.

Ariel Conn: I’m both excited and sad to announce that the next episode of Not Cool, a climate podcast will be my last interview. But I’m definitely excited that our final guest will be Naomi Oreskes, who will join us to talk about her new book Why Trust Science.

Naomi Oreskes: t’s fashionable in some quarters to criticize consensus, to say that science isn’t about consensus. But actually science is about consensus, because that’s what you get after you go through this whole process — or maybe you don’t get it. But when you do have consensus, that’s when we say, okay, we know something. 

Ariel Conn: If you’ve been enjoying these podcasts, and if you think other people might as well, then please take a moment to like them, share them, and leave a good review.

Not Cool Ep 24: Ellen Quigley and Natalie Jones on defunding the fossil fuel industry

Defunding the fossil fuel industry is one of the biggest factors in addressing climate change and lowering carbon emissions. But with international financing and powerful lobbyists on their side, fossil fuel companies often seem out of public reach. On Not Cool episode 24, Ariel is joined by Ellen Quigley and Natalie Jones, who explain why that’s not the case, and what you can do — without too much effort — to stand up to them. Ellen and Natalie, both researchers at the University of Cambridge’s Centre for the Study of Existential Risk (CSER), explain what government regulation should look like, how minimal interactions with our banks could lead to fewer fossil fuel investments, and why divestment isn’t enough on its own. They also discuss climate justice, Universal Ownership theory, and the international climate regime.

Topics discussed include:

  • Divestment
  • Universal Ownership theory
  • Demand side and supply side regulation
  • Impact investing
  • Nationally determined contributions
  • Low greenhouse gas emission development strategies
  • Just transition
  • Economic diversification

References discussed include:

You can use the financial system, and use investors and banks, to delegitimize the fossil fuel industry. Strip them of financing, and also strip them of the moral license to operate. And once you don’t have a moral license to operate, that’s when governments can get in and start doing interesting things.

~ Natalie Jones

Ariel Conn: Hi everyone and welcome to episode 24 of Not Cool, a climate podcast. I’m your host Ariel Conn. This week we’ll be focusing more on actions you can take to address climate change. We all know we should be driving less, flying less, and eating less meat. But things like where you bank and whether you express your climate preferences to your 401k manager could have a direct and powerful impact on fossil fuel companies. And then, since individual action, no matter how powerful, isn’t sufficient, we’ll also look at some of the various types of global policies that could be most effective at slowing down both carbon emissions and fossil fuel production. And we’ll talk about much more. For this discussion, we’ll be joined by Ellen Quigley and Natalie Jones who are both researchers at the Center for the Study of Existential Risks, also known as CSER, at the University of Cambridge. 

Ellen is a Research Associate in Climate Risk & Sustainable Finance. She works with CSER on addressing climate change in the investment policies and practices of institutional investors. She holds a B.A. in English literature from Harvard College, an MSc in Nature, Society, and Environmental Policy from the University of Oxford, and a PhD from the University of Cambridge.

She is also the Advisor to the Chief Financial Officer of Responsible Investment at the University of Cambridge; and a Postdoc Researcher at the Centre for Endowment Asset Management at the Cambridge Judge Business School.

Natalie works on global justice and existential risk at CSER, and recently submitted her PhD thesis in international law at the University of Cambridge. She consults for the International Institute for Sustainable Development (IISD) as a Staff Writer for the Earth Negotiations Bulletin, which is the de facto record of multilateral environmental negotiations. 

Before coming to Cambridge, Natalie worked as a Judges’ Clerk at the High Court of New Zealand, and has completed shorter stints at the Stockholm Environment Institute, the Urgenda Foundation Climate Litigation Network, and the Inter-American Association for Environmental Defence. She holds undergraduate degrees in law and in physics from the University of Canterbury, and an LLM from the University of Cambridge.

Ellen and Natalie, thank you so much for joining us.

Natalie Jones: Thanks for having us, it’s great to be here.

Ariel Conn: You’re both doing sort of different work — one of you is working on financial issues; one of you is looking at climate change through the lens of policy. And before we get into some of the more specifics about what you’ve both been working on, I was hoping you could both just briefly talk about how you started looking at climate change through these different perspectives.

Natalie Jones: Okay, I can go first if you like — this is Natalie speaking. I did my undergraduate studies in law; I was legally trained. And I was always quite taken with the idea of how law and policy can be a tool for the purposes of change. And I got out of law school, I was working as a judge’s clerk, and I was like, this isn’t really it. And actually that year I got this incredible opportunity to attend the UN Climate Conference — it was COP19. It was this time when the world was preparing for what was going to become the Paris Agreement, and I was there as a youth activist. 

Around same time I started as a volunteer with a local youth climate activism organization in New Zealand — it’s called Generation Zero. So, at this time I was really experiencing attempts to change or influence policy regarding climate change at the local government level — with stuff like public transportation and bus lanes and cycle lanes; these really small scale things — all the way up to what was happening at the intergovernmental level. 

And I eventually went back as a New Zealand youth delegate in the following year and also in Paris, COP21 — with, again, like a New Zealand youth group. And also working with a coalition of other young people who were trying to influence what happened in that agreement. It really catapulted me into the policy realm and I decided to keep on working in this area.

Ariel Conn: Excellent. Ellen?

Ellen Quigley: I think I started to freak out about the climate crisis in my very early 20s, as I was finishing undergrad. I actually took four years off in between degrees and was a community organizer back in my hometown of Saskatoon, Saskatchewan, Canada, and worked part-time in an alternative bookstore and just did a lot of stuff on the ground. But, some of it worked and a lot of it didn’t, which was actually really helpful. And I worked on so many losing election campaigns, I can’t even tell you. A bunch of us put together an arts and environmental festival that brought in about 15,000 people, which was kind of the main large-scale effort — garlic self sufficiency projects and stuff like that — to kind of bring some humor and art into the space.

But I think what I realized is that I didn’t know what the levers were even, let alone how to pull them, when you consider that any local activism was going to be counteracted by just tremendous forces that really couldn’t be fought at that level. So I went back to school to do a master’s in geography and environmental policy, and then got really obsessed with economic geography, and then joined a divestment campaign, and then learned a little bit too much about that whole question, which complicated my views such that divestment became one of a list of tactics needed to shift the financial sector.

Ariel Conn: I’m assuming that is connected to a paper that you recently published on Universal Ownership theory. Before we go any further with that, I was hoping you could just explain what universal ownership theory is, and maybe also what universal owners are.

Ellen Quigley: I personally think that Universal Ownership theory is the paradigm shift that’s required to make a whole suite of changes that would fit well into that framework — to transform our financial system; to address not just catastrophic climate change, but issues like inequality, and forced migration and mass animal extinction. These are all things that count as externalities, if you’re an economist. I think that they should be internalized in the current system. The only way you do that is with the Universal Ownership lens. Universal Ownership: the traditional definition is a very large fund — like a pension fund, or a university endowment, or a sovereign wealth fund — that basically owns a more or less representative slice of the financial system or the economy as a whole. That can mean that they just own shares in every sector and in every geography, which would describe almost every fund that we can think of.

I also think it encompasses basically all young people who have any money at all invested in any which way; anyone who’s invested in a tracker fund, which is just a fund that tracks all of the stocks in a particular index, so you basically own a little slice, a representative slice, of the whole market — anybody who owns one of those for at least a medium amount of time. And young people in general, plus all these huge funds like pension funds, would count as universal owners. Because what unites them all is that what affects them much more than the performance of any given stock is the performance of the economy as a whole. They could outperform the market, and that would be nice and everything, but that pales in comparison to the effect that the performance of the whole economy has. Alpha is outperforming the market in financial speak, and Beta is the market itself: the base performance of the market as a whole. 

And I think that what we need to do is to have those groups realize that any externalities that one company produces, the cost of those get picked up elsewhere in the portfolio. So there’s no escaping them; there are no real externalities if you’re a universal owner. If you believe that and if that is indeed the case — which it sure seems to be — there needs to be coordination among universal owners to push for things that can only happen at a systemic level. For example, different countries feel pressure to keep regulations at a minimum to attract multinational corporations. A universal owner could help push those companies to meet standards that would cross borders. You could have a 1.5 degree compliant portfolio requirement for every company that you own, and if you had a large enough ownership share within all of these companies, they could no longer argue that they are at a disadvantage relative to their competitors, or their peers, because they would all be basically forced to meet the same standard.

And by the way, the thing that is currently happening on that front is that a bunch of shareholders are working together to pass shareholder resolutions and other things like that — just resolutions that shareholders can vote on at annual general meetings of these companies. But what we see is, A, most of these resolutions are about disclosure only. And disclosure is just a means to an end; it’s not an end itself. And the other thing is that almost all of these shareholder resolutions are advisory, which means that even if you win them, the company doesn’t necessarily have to adopt them. So I personally think that shareholders should be using the tool they definitely have, which is the power to vote in and out the board. This seems like a much more direct route to influence whether or not these companies are en route to rapid decarbonization, which is what we desperately need.

And I think it’s better for everyone if people don’t feel as though they have to take a hit that their competitors don’t have to take. This also applies to inequality, which is an intensifier of a lot of the effects that we see from catastrophic climate change. If you care about the performance of the economy as a whole, you want a robust middle class — whereas if you have vast inequality or a large poverty stricken population, that isn’t good for the whole system. So universal owners should care about that as well.

Ariel Conn: So just to make sure I’m clear, universal owners already exist. I guess what you’re suggesting is they’re not influencing either their power or corporate decisions as much as they could?

Ellen Quigley: Yeah, they already exist, but they may not realize that they are universal owners. They might just think, “Oh, I’m a pension fund.”

Ariel Conn: Okay.

Ellen Quigley: Some of them already are spreading the word about this; they have very much this paradigm in place, but it’s by far not the majority of people I think we could consider to be universal owners. So they need to kind of familiarize themselves with the concept, but also what sorts of actions would naturally flow from the concept.

Ariel Conn: So for example, if I have funds in Fidelity or in Vanguard or in some other organization like that, and they send out notifications that there’s some vote coming up, you’re saying that we should be paying close attention to those votes, so that we can be influencing who is on the board. Is that correct?

Ellen Quigley: Yes. I mean, currently Fidelity is not quite as bad, but Vanguard has among the worst voting records, and they’re the second largest fund manager in the world. So there’s a huge lever to be pulled.

Ariel Conn: So when you say that, do you mean people who are invested in Fidelity are more likely to vote, or the impact of votes are more meaningful at Fidelity? Or something completely different?

Ellen Quigley: This is a really good way to clarify what I’ve been trying to say. Fidelity and Vanguard will vote on your behalf. And most people don’t even realize that they are voting; it’s all just happening within a kind of central decision making apparatus. And I think almost none of them would ever consult with their actual beneficiaries about how they would want to vote, which is also an issue, you might argue.

Ariel Conn: And so how do people who are invested change that?

Ellen Quigley: Well, you should write to Vanguard, and also a lot of these companies themselves have shareholders. If you are part of an institution, you can engage with these fund managers as companies; I know that sounds strange. But as an individual, that’s a relatively rare position, relative to what your roles might be with pension funds and so on. If you’re a beneficiary of a pension fund, you should definitely ask your pension fund to engage with your fund manager and try to get them to change their practices on this. Frankly, they don’t hear from too many people, so even being bothered by one large institution is often enough to at least nudge things somewhat. But if you’re an individual, and you invest via Vanguard, I would highly recommend writing to them — and write to the whole board, write to the chief executive, et cetera. Again, not too many people actually contact them for any reason, so it’s actually pretty high impact. Some of these things turn on five emails from members. It’s crazy.

Ariel Conn: Are there templates or something like that? Is there guidance somewhere, or are we sort of doing this blind?

Ellen Quigley: There isn’t enough. And honestly, we should probably get going on that and do something. But, I do know two organizations that are doing interesting things on this front. One of them is something Natalie and I have both been involved with, Positive Investment Cambridge, or the kind of umbrella group Positive Investment. And they’ve put out a tool that allows you to switch commercial banks and explain why — and write to the old bank and give the reasons why. This relates to fossil fuel funding, specifically. And that, actually, I think is even more high impact than writing to a fund manager, because these banks actually are providing direct financing of new projects, so it’s really, really high impact. And also they really desperately don’t want to lose your deposit. 

The other group that I know does work around this is SumOfUs. And they occasionally do letter writing campaigns on particular issues, and they have a tool that you can use to select which pension fund you’re part of, or what fund manager you have, and then you can write to them directly to get them to put pressure in various places in the system that there isn’t enough.

Ariel Conn: That’s actually really interesting. You’re suggesting that we can just look into how our banks are investing and loaning out money, and if we don’t approve, we can switch to another bank that is more environmentally friendly? 

Ellen Quigley: Yeah, that’s actually probably one of the most high impact things you can do as an individual. People are more likely to switch spouses than bank accounts. And banks know this, so they’re terrified to start losing customers or gaining the knowledge that they’re likely to be scaring off new customers. Especially young people, because they know if they sign up young people, they’ll basically have them forever. If you do switch banks, and you have a lifetime of deposits on the books for the bank, they are able to lend out on the basis of those deposits. If enough people did this, and especially if large institutions did this, they would actually be able to functionally lend less, if they have fewer deposits on their books. But that said, I actually think the effect would come long before there is a measurable effect on their actual ability to lend. Because the fear of large institutions switching away is a really big stick for a bank.

Natalie Jones: You might be wondering, well, if I move my money away from Barclays, or from another bank that does actually fund a lot of new coal or oil and gas products, who do I switch to? There are some organizations that have done some quite good work on which banks are worse than others, or which banks are better. And one of those is Positive Investment, but in the US also I I’m thinking of Oil Change International, who have quite a good report comparing all of the commercial banks and kind of ranking them.

Ellen Quigley: Although Personally, I would say go for a credit union or a cooperative bank or a building society. This might not actually be true in the US, but almost everywhere else that I know of, credit unions have nothing to do with capital markets. They tend to loan locally; a lot of them will have a mandate to improve lives within their own geographical sphere. Through some of these tools, you can actually figure out which ones are not so much avoiding causing active harm but actively doing something good.

Ariel Conn: If you were, say, a large institution like a university or some other big organization, would you say then that it’s more impactful to divest from fossil fuel companies or to change banks? Or should not be an either/or?

Ellen Quigley: I mean, I think we should be doing all of the things we can. Depending on your theory of change, both tactics could be good. I think that there is a direct effect on banks that is hard to argue with. I would also say you could bring in some of the reasoning in the divestment movement and kind of intensify the effect of switching banks if you announce that it has that effect on public discourse that you want, which is the effect that divestment has. Divestment doesn’t have a direct effect on where capital goes — it doesn’t shift capital. But it does have an effect on how we view companies. And I think that if you switch banks and explain publicly why, and put pressure on them to change their lending practices, I think that could have a huge effect, especially if you are a well-reputed institution.

Ariel Conn: Wow, okay. I’m going to come back to your Universal Ownership theory paper, and I still am sort of trying to make sure that I’m getting terminology and understanding what these different concepts are. So how does being a good universal owner differ from various types of responsible investing? And I’d actually intended to ask you about this Positive Investment program. Is that only banking?

Ellen Quigley: No, that’s just one project. But yeah, basically I have the perhaps unpopular view that most ESG investing — that’s Environmental, Social and Governance investing; SRI investing, which is Socially Responsible Investing; or RI, which is Responsible Investing; or Ethical Investing, is all kind of the worst of both worlds. Because almost all of that does not involve the announcement that we were talking about earlier. It doesn’t have the effect on social discourse that you might have by saying publicly, “We don’t want to be associated with this company that’s causing harm.” But it also doesn’t shift capital, because almost all of it happens within what I call the secondary market. The secondary market is all of public equity, so that’s every company that’s listed on a stock market. When you first list on a stock market, you do what’s called an Initial Public Offering, or an IPO. When you do that, what you’re doing is you’re basically selling shares for the first time so that you are spreading the ownership around.

And when that happens, the company that’s listing on the stock market gets an influx of capital. So, it can do things like buy out all of its founders, or expand greatly, or have a growth plan that can be fully funded with the money that comes in from the people who’ve just bought these shares. After that point, they don’t get any money from when their shares are bought and sold. They can raise more money, by issuing bonds, for example, which means that they do get an influx of debt financing to do something. When they go to a bank for a bank loan, they can also do project financing that way — that’s more new money coming in. Or they can issue more shares. But just buying and selling shares on the stock market does nothing to the company. It doesn’t help the ones that you would want to help and it doesn’t hurt the ones that you might want to hurt. It doesn’t matter to Exxon who particularly owns their shares unless they announce the fact that they’re selling them, in which case there is this public effect.

The social discourse shift is meant to result in government action: that’s what needs to happen. There isn’t good enough evidence to suggest that it affects share price at all — let alone enough to make a difference — or cost of capital, which is the other thing people cite. So the effect really is supposed to be that you put pressure on a sector to be regulated by the government in various countries, which is exactly what happened with apartheid in South Africa; enough pressure was put on through the divestment movement that countries started to enact sanctions against South Africa, and that’s what brought about the end of the regime. Boycotts and sanctions were what did it, but those were government legislative actions, not actually shifting capital. There was really none of that. It was a social movement.

Natalie Jones: And I think this works in really well with what we’re going to talk about a bit later on with the policies on the supply side.

Ariel Conn: I think would be good to bring some of the questions about policy in now as well. So, if you could explain the difference between demand side and supply side policies when it comes to fossil fuel use and extraction.

Natalie Jones: Yeah. So, a demand side policy on fossil fuel use is, I guess, a policy that would tend to constrain or limit the demand for fossil fuels, and thereby limit the amount that are burned and the amount of carbon emissions. So, it’s the idea that you reduce the emissions by constraining the demand for the coal, the oil and the gas. It’s basically everything that nearly everyone has been talking about for a couple of decades now. So, an emissions trading scheme where you trade emissions allowances, and ideally have a cap on those; or a carbon tax, where you impose a tax on emitting; or measures to improve energy efficiency, or promote renewable energy. These are all examples of what many people would call a demand side policy. Now this, as I say, has been really the predominant way of thinking about that kind of climate policy, at least among academics and economists.

But what this has tended to ignore is, in a way, the other side of the equation — and that is what happens at the supply end. The rationale for tackling the other side comes partly from the idea that it might be more economically efficient if you tackle it from both sides — e.g, there are fewer companies who make, who extract, who produce the fossil fuels than their are companies who burn them. You reduce the transaction and the administrative costs if you regulate at both ends; obviously, we need the demand side policies, but we also need ones at the supply. And so in terms of what those look like, it could be things like a moratorium or a ban on new coal mines, on new oil exploration, on oil extraction, on gas exploration, on gas extraction; also on the transportation, so on new infrastructure like pipelines.

On a micro scale, it can look like the denial of permission for individual projects where the planning permission is being requested. And the government or court says, “No, actually, that’s not in line with my climate goals, or public health, or any one of a myriad of reasons.” Another example is ending the subsidies on fossil fuel production side. And so these are all kinds of measures that a government can implement, and increasingly we have been actually witnessing this happening. And the example of moratoria on oil exploration or production: we’ve had this in the cases of New Zealand, Costa Rica, France, a handful of others. And we’ve seen moves to stop coal production in Germany and Spain. Those are a few examples where these kind of moves are already happening, and these countries are really at the forefront.

But, just to kind of link this back to what Ellen was talking about, these are some of the policies that can happen when you have the public support. What Ellen was talking about is how you can use the financial system, and use investors and banks, to delegitimize the fossil fuel industry. Strip them of financing and also strip them of the moral license to operate. And once you don’t have a moral license to operate, that’s when governments can get in and start doing interesting things — not only on the demand side, but also on the supply side. And there’s some interesting research, actually, that indicates that these kind of policies actually enjoy more public support than the demand side ones — because in a way, they’re more upfront. It’s like, “Okay, we’re going to ban oil extraction, we’re going to ban coal,” which is, in a sense, more of a root cause of the problem, rather than a complicated economic instrument that many people have issues getting their heads around, like a carbon trade scheme. And it often has more of a direct impact on people’s lives, in terms of the immediate environmental effects of these products, and the immediate health impact. So that’s quite an interesting finding.

Ellen Quigley: There’s also the demand side of the equation when it comes to the financial side of things. And there, you actually see more emphasis on the fossil fuel companies and not on the demand side of the equation. And I think that that’s a bit unfortunate, because let’s say you did or didn’t divest from fossil fuels themselves. You would still have exposure to all of the sectors that use the most fossil fuels. So, the auto sector, utilities, steel, cement: those you actually could — again, if you had a Universal Ownership lens — you could work together to rapidly decarbonize. Because again, all of those sectors have this issue that they fear that they will fall behind their competitors if they’re forced to do something that the others aren’t. And if you could decarbonize these high fossil fuel demand sectors rapidly, then it would make the argument about shutting down coal mines moot, because they wouldn’t be attractive anywhere in the world, even in places in which there wasn’t a moratorium.

Ariel Conn: Okay, so I’ve got three questions to try to make sure I’m better understanding all of this. I mean, ideally, we want to stop extraction and production, but right now we can’t because these companies are too big and powerful. Is that premise correct as a starting point?

Natalie Jones: Yeah. So it has been the case that the pressure exerted by these companies has been a major barrier. And a lot of people include it as a reason, for instance, why the Paris Agreement itself hasn’t got any mention of fossil fuels, or these kind of supply side issues; also, as to why at the national level, there’s been less action on this than many would have liked. So that’s an issue. Another one is that, I suppose, the level of awareness around these being actual policies that you can do, and the research around that. I think only in the last handful of years has this been a topic of major academic study, and you’re starting to actually see studies like, “Okay, so if Norway stopped oil extraction, what would happen? What would the economic effects be? Would there be like a spillover effect, whereby other countries would just make more?” And the answer is actually, no, you wouldn’t have as much spillover as you might expect. So, having more of an understanding about the downstream impact of these kinds of changes is, in my opinion, helping a lot.

Ariel Conn: So, we have this premise that it has been difficult, obviously, to stop production and extraction. And if I’m understanding what you guys are saying, we can divest, which doesn’t actually take money out of the system, but it helps delegitimize the companies. Is that correct?

Natalie Jones: Yes. It’s also worth mentioning that, that isn’t the only action that can help with the delegitimization. Lots of examples in recent years, when non-governmental groups have applied various forms of pressure, e.g, a protest in a coal mine — there was a massive one in Germany recently, where you had a few thousand people rocking up in a coal mine to stop it from operating on one particular day. Obviously it doesn’t have much of an impact on the long-term operation of that coal plant; it has a massive impact in terms of raising the public awareness of this being not a good state of affairs, not a good activity.

Ellen Quigley: It might also be worth just reiterating something that Natalie brought up earlier, which is about subsidies and lobbying activity. You’re asking, “Is it because these companies are simply too powerful?” Well, they are incredibly powerful, and part of that is because they help to shape regulation that benefits them — including subsidies that mean that the cost of using these products never matches the actual price. Let alone the cost of all the externalities, like air pollution that affects people’s health, and so on so forth, and definitely not including the cost of catastrophic climate change. So those are two things that absolutely need to shift.

Natalie Jones: Yeah. And also on that point, there are some absolutely incredibly horrible statistics out there, along the lines of more money is spent by governments on these subsidies every year than is spent on renewable energy investment, for instance, or spent on basically any other policies that would help the climate. You see the same trend with some international financial institutions, where they are investing often more in fossil fuels than in renewable energy. That really, really needs to change.

Ariel Conn: So we have the premise that for many reasons, the oil companies and the fossil fuel companies are very hard to stop. Divestment and other means can help delegitimize that. And then with banking, either by people or institutions changing their banks, or I’m guessing there’s other ways to convince banks not to loan to these companies — that can help start to defund them. Is that correct?

Ellen Quigley: Yes. And actually, it’s also worth mentioning that if divestment did extend past public equity and into other asset classes, such as bonds, for example, it actually could starve fossil fuel companies of the financing that they require to do things like exploration and development, or build a new pipeline or whatever else. A lot of that is debt financed. And some of these companies come to the market twice a year to issue new bonds to get more money to work with. So, if everybody who had divested from fossil fuels also ensured that they weren’t buying any of the bonds of these companies, and that they didn’t have a relationship with a bank that was using their deposit to finance fossil fuels, that could make a really big difference, actually.

The way you establish whether a fossil fuel company is serious about transition doesn’t have anything to do with their current assets, but where all of their new money is going. So, what you care about is, A, if they’re doing something terrible — which, I mean, none of them is aligned properly with the 1.5 degrees scenario. So I think we can say, where’s their new money coming from? Their new money is coming from bank financing and from bonds, sometimes issuing new shares, but we really don’t see much of that these days. And then where is their new money going? So what is their capital expenditure? What is their research and development spending? What are their acquisitions? That’s where they’re headed. If you look at those numbers, that gives you an idea of whether or not they are on a path to transition. So, if you see that a company has 97% of their capital expenditure going towards more exploration and development for extraction of fossil fuels, you know you’ve got a problem and that you shouldn’t be buying the bonds of that company.

Natalie Jones: And this is what we see in the case of companies like BP and Shell, for instance, and I highly suspect in the case of Exxon and Chevron as well.

Ariel Conn: I’m going to keep going with my clarification here in a minute. But, I want to bring this back to the idea of the universal owners. When you’re talking about things like purchasing the bonds, how do you keep track of what’s happening?

Ellen Quigley: Well, most universal owners are going to be operating through fund managers, and it’s literally their job to do that. Let’s say that a universal owner has a fund manager and they’ve been told not to purchase new bonds that are issued in fossil fuels. That means that if a whole bunch of investors had had that policy when Saudi Aramco listed earlier this year, you might have seen less of a success in the part of that newly funded institution. That bond was oversubscribed, but a lot of people didn’t realize that they were buying it, and wouldn’t have consented to that. But it was such a large issuance that it automatically was included in bond indices, which meant that a whole bunch of people automatically bought it.

And that just seems like something that shouldn’t happen in this day and age. And the only way that you start to question that, and to question automatic inclusion of bond issuances like this, is by having that conversation with fund managers. That is something that anybody who has a divestment mandate should just go back to their fund managers and insist applies to their bond portfolio. They’re doing exactly the same thing; it’s often the same companies.

Ariel Conn: So if, say, you’re with an institution that has divested from fossil fuels, is it still possible that the portfolio includes bonds for those very companies?

Ellen Quigley: Yeah, often. It’s just a different asset class, and people just don’t think about the other asset classes when they’re doing this work. And that’s fair enough, because a lot of the people who are putting pressure on institutions to divest don’t necessarily have a degree in finance, nor should that be required. So it’s just a level of detail that would bring all these other asset classes into view, but they’re absolutely essential when it comes to new money being allocated to new fossil fuel projects, which is really what we need to stop.

Ariel Conn: This brings me to another question that I had specifically about the Universal Owners theory paper. And that was that it seems that basically divestment isn’t enough; that even if you are part of a group that is divesting from fossil fuels, there’s still a lot of ways that you are putting your money towards either the burning of fossil fuels, or, as it sounds like, bonds that are associated with them. Can you talk a bit more about where the investments are going and what people should be looking out for? And then also, how do you remain invested and not have money in something that’s associated with burning fossil fuels?

Ellen Quigley: That’s an excellent question. Personally — I mean, I don’t have very much to invest — but mainly I just invest directly in solar construction bonds and stuff. In the UK, there are actually quite a few options for things like that; in Canada as well, it turns out. There are quite a few options for those who’d rather just directly invest in something good and help make it happen. This is usually called impact investing, but I think it applies to kind of a broader swath of investments now that there are commercially viable solar installations and wind farms and so on and so forth. For a pension, it gets more complicated, but that’s where I think — you know, universal owners don’t get to just exempt themselves from the fate of the whole of the economy. They have to figure out what to do with Shell. So, either they have to help Shell transition, if that’s possible — and they have to do it rapidly; let’s be clear — or they need to wind it down. But they have to take responsibility either way.

And if you’re a universal owner you care what happens to workers in the economy as well, because you need a healthy, vibrant workforce and a robust middle class to have a working economy. You can’t exempt yourself from the fate of the coal miner or the coal mine. It’s all your responsibility if you’re a universal owner, so you need to either shut things down or transition them. You have to be part of all of that, no matter what the asset class; it’s part of your mandate and purpose, I would argue.

Ariel Conn: And so in this instance, are you differentiating between a universal owner in sort of an ideal sense, and a pension fund holder at a university?

Ellen Quigley: I think that I’m speaking from an idealized standpoint, unfortunately, but it’s still true. The largest pension fund in the world, which is GPF in Japan: the Chief Investment Officer of GPF will tell you that he’s a universal owner, because he can’t stock pick his way out of the climate crisis, for example. It’s both idealized in that we would hope that people like him would think that way, because it’s absolutely essential to fixing our current problems, but it’s equally true that that is the situation. It’s just whether or not people recognize it as such.

Ariel Conn: What advice do you have for people who do want to be responsibly investing, but who also don’t have a background in finance and who are reliant on some major funder pension?

Ellen Quigley: First of all, switch to a credit union with a good green track record, and then find impact investments in your jurisdiction. And when I say impact, I don’t mean anything on the stock market. I don’t think you can have a true impact investment through buying a stock in a company that’s listed on the stock market, because it’s the secondary market, for reasons that we’ve discussed. I’m a particular fan of diversifying the types of institutions that we have in our economy. So I particularly target coops: I like to fund cooperatives in renewable energy and energy efficiency, and so on and so forth — that’s my preferred method, but reasonable people disagree about this. I just think those are the first two things that you can do that have a real direct impact.

But then the other thing you need to do is go to all the institutions of which you are a part and push for a whole broad swath of actions that would actually allow us to collectively transition rapidly and justly. And that would look like a whole bunch of the things we’ve already been discussing. It means firing the directors of companies that do not have a 1.5 degree-compliant plan. But also it has to be reflected in their capital expenditure and in their research and development, spending, et cetera, as we’ve discussed.

Ariel Conn: Let’s switch over to some of the policy stuff. On the finance side, we’ve got these steps of delegitimizing and defunding the fossil fuel industry. Once we’ve done that, then we turn to countries to sort of take the final step. And I was hoping you could talk a little bit more about what ideally that would look like, and what we’re seeing today.

Natalie Jones: I guess what ideally that would look like is a bit like what I’ve already been speaking about — so these policies which you would have on the supply side as well as on the demand side. In the case of any major economy, or in fact any economy that is currently extracting fossil fuels, you basically want that to stop. And not necessarily immediately: we know that to stay within like a global warming limit of 1.5, we need to half emissions by 2030 and reach net zero by the middle of the century. So we need to stop quite quickly, which basically means not investing in any new fossil fuel projects. It means closing some substantial amount of the ones that we already have. And these kind of questions, in addition to the finance realm, also need the government policy to provide the incentives and the constraints which will allow that to happen.

But also all these policies have to be undertaken with a sense of justice for the workers and communities who will be impacted, who often are relatively poor and marginalized, possibly — and also, historically speaking anyway, haven’t really been involved in the decision making processes. So it’s vitally important to involve those who you’re going to affect when you close down these industries, as must happen. Because what cannot happen is leaving people behind in a systematic way, as we have seen in some cases, e.g, in the UK with the closure of coal mines. And what we are actually seeing, quite hearteningly, in the cases of the countries who are actually adopting these policies — I’m going to speak about New Zealand, because I am in New Zealander — slightly biased — but adopted a policy regarding the banning of all new offshore oil and gas exploration. Which, of course, was not a perfect policy by any means; it still allows for the extension of existing exploration leases, for instance. But what has been a crucial part of that is a planning process regarding what happens with the workers and the particularly affected regions.

So that’s one crucial element of it. Another crucial element is equity, so looking at which countries maybe have extracted more than others in the past and have gained all the profits associated with that; and then looking at ideally, which countries would stop quicker than others. That’s a really active research area that needs more work, I think, but there are some good papers there. So I looked at this in the context of the international climate regime, so under the Paris Agreement where all countries have to make their pledges, right? So the whole idea is that they have these NDCs, which stands for nationally determined contributions, whereby if you’re a country, you hand in basically your plan regarding what is going to happen over the next five years. And most of them were handed in just around the time of the Paris Agreement and are due to be updated or enhanced in about a year’s time. And so what we found when we looked at these is basically that hardly any of them even mentioned production of fossil fuels in their countries.

And that’s not surprising, because there is no indication in the Paris Agreement that countries ought to include this; as I mentioned, it’s all about what’s happening on the demand side and on emissions reduction. So these NDCs include lots of targets along the lines of, we’re going to reduce our emissions by a certain percentage regarding like a given base year, a given target year — all of that kind of stuff, which is good and great, and we need more of that, and we need those pledges much higher ideally, because there’s a massive emissions gap, which is the gap between what countries have planned to emit and then what we can emit in what’s called the carbon budget for staying under a 1.5 or two degree limit. So that’s one aspect of the NDCs, but the aspect that we looked at was if they mentioned production. And what we found was that only one country, which was India, mentioned that it has a tax on coal production, which is a really great supply side policy from India. And it’s great that it’s mentioned it in this international context, because one of the interesting elements of these NDCs is that, I mean, everyone else reads them; they get scrutinized by the international community.

And so, even if the Paris Agreement isn’t mentioning oil, coal and gas, if you’re a country that has a policy like this, you can include it in your NDCs; there’s nothing stopping you from doing so. And so what would be quite interesting is if all the countries that had already started making these policies would include them in their reporting, which is these NDCs, and also this other document, which is our low greenhouse gas emission development strategies, which are like NDCs but more long-term and they aren’t mandatory; they’re voluntary only. The key point is that countries have these two mechanisms where they can say, “Here’s our plans, here’s what we’re doing.” In both cases, they actually have an option, and they can say, “Actually, we’re taking these other kinds of policies — we’re banning coal mines, we’re banning oil exploration.” And that can help institute a norm that can help with this process at the international level, which we’ve been talking about kind of at the national level: of making it more of an accepted idea that you would close down the supply.

So what we’ve been talking about is at the national level removing the moral license; this is part of removing the moral license at the international level — is by including these in these key documents; in these key documents which form part of the Paris Agreement. So what we’re seeing in those documents is a very small minority of cases that actually mention these measures, but when countries actually mention the production of fossil fuels, they mostly do so either in the context of reducing the emissions associated with the operation of the fossil fuel industry itself  so, reducing emissions from the flaring and venting of methane gas, or making the extraction operations slightly more energy efficient, which would reduce the emissions that go into drilling, and all those kinds of things.

And the other aspect in which production is mentioned is in the context of economic diversification and just transition. And we’ve already kind of touched on a just transition, this idea where you need workers to be carried along rather than left behind. And economic diversification is kind of associated: it’s where a country relies, really, on oil and gas exports, for instance, and really needs to move its economy away and have other sources of national income, which is a really large problem. But what these countries have included in the NDCs is an acknowledgement of this and maybe some plans for moving away. But that’s rather different from actually including plans to reduce the problematic area. It doesn’t necessarily go along with that. So that’s, I guess, the two interesting findings from a study that I did with some other people recently.

Ariel Conn: So in that study, you talk about six elements that you would like to see included in the NDC’s and LEDS. And you’ve just been talking about a couple that a handful of countries are actually implementing. But there are, I think, four that basically aren’t included at all. Could you maybe talk a little bit about some of the elements that countries haven’t included yet that you think are really important?

Natalie Jones: Yeah. One of these elements is, I guess, the pathways and measures to reduce the production of fossil fuel. So this is what I was talking about, where only in one case, in the case of India, we really see the inclusion of a policy that would constrain production of fossil fuels — where in actuality a number of countries are taking these measures, but they’re not reporting them. And this kind of comes back to this point of, you can take a measure, and that’s great — like you can make a policy in your national context and it will have an effect, but you can magnify that if you report it. The other aspect that’s been basically missing is what we’ve touched on regarding equity. So with the case of NDCs, when countries are making pledges regarding emissions reductions, they are obliged to also include information regarding the equity of that, and why they think that that is an ambitious and just response, taking account of their national circumstances. But what would be great is also if countries would include the same equity analysis of why their policies and measures on the supply side are also just. 

Another thing is the general context, and I guess before you actually go into any of these, what are the measures you ought to be taking. But the other thing is just acknowledging that you have a problem — or not even that you have a problem, but that you are a producer of fossil fuels. In these documents, you see countries reporting all kinds of things like, “We are extremely vulnerable to the effects of climate change.” You see countries reporting, “Here are our main industries.” You see a lot of background information. And what would be really helpful is if countries also included it in that background information, “Yeah, and we extract coal and here’s our projections as to how that’s going to change in the future,” or, “Here’s our plans to increase the production of coal,” — which many countries in fact have, particularly regarding oil and gas, plans to increase. So it’s owning up to that, because that’s the starting point for where these plans work from. 

There are a handful of countries that have started implementing these policies, but are not including them in these documents which report back to the international process. Of course, there are many other countries that have so far not implemented these policies, and there are others that maybe have, but could improve. There’s a lot more space for action. Individuals can be really instrumental in where they put their votes, in terms of individuals or parties which have these policies. Because I know in the key western states there are candidates or parties that do have better manifestos on this, and others which do not. So that’s one thing that individuals can do.

Ariel Conn: I think this is a nice transition to ask my final question. And that is, are you still hopeful that we’ll be able to take enough action in the next 10 to 30 years to keep global temperatures ideally below 1.5 degrees Celsius, but even below two?

Ellen Quigley: Well, you have to be hopeful. It is technologically feasible. I believe that it is possible. I think the only thing that’s lacking is political will, but that’s starting to be generated on a scale and at a speed that I don’t think any of us imagined about a year ago. And because of the school strikes for the climate, because of Extinction Rebellion, finally civil society is starting to put pressure on politicians to do what’s necessary, which is — let’s be clear — a complete transformation of our economy. But the funny thing is, we’ve done that before. We did that during World War Two — almost every industrialized nation rejigged all of its industrial processes in a shorter period of time than we have now to cut emissions in half. So I think it’s really just, can we rouse ourselves to rise to the challenge? I think we can; I just hope we will.

Natalie Jones: And on point of this being an unprecedented or nearly unprecedented change, an alternative way to look at that is that we are standing on the brink of potentially one of the most exciting decades in human history, with the most innovation and the most change. So we have this opportunity to do something really massive and to be part of something great. Which I think is not a matter of hope, but it’s more a matter of we have to do this, and so this will change everything, and don’t think too much about it.

Ellen Quigley: Yeah, full steam ahead. But also the change will come — the status quo is not an option. So, we either have a really terrible forced transition that leaves a bunch of people behind and means that we end up in a catastrophic death loop, climate wise. Or we do it in a way that, as Natalie is saying, takes advantage of human curiosity and ability to cooperate, and get something tremendous done in a short period of time. We’re absolutely capable of that.

Natalie Jones: Yeah. The real challenge, I think, which is something I’m quite concerned about, is doing it in a just way, so not leaving behind those who are most impacted either on the industry end or on the impacts end. Basically not doing it in a way that militarizes borders and leaves people out in the cold, as it were. You said something, Ellen, like, “We’re rising to the occasion.” I just want to caution against this kind of universalist “we” a little bit. This is a whole other podcast.

Ariel Conn: I really like this idea that we’re sort of on this precipice. And if we do this right, we’re sort of initiating this huge change for the better, I guess. This should be a really exciting time, actually. I think that’s a really nice perspective.

Natalie Jones: It’s important that whether you have been working on it for decades and decades or if you’re just coming to it, just hop on board, is what I have to say.

Ellen Quigley: I mean, we could end up with a world in which it’s a lot more fair and equal, and we all breathe much cleaner air, and get a lot more exercise and eat healthier food. And that is an option in all of this; it’s just one that has to be created politically — and technologically, but primarily politically.

Ariel Conn: All right. Well, thank you both so much for joining. This has been really interesting for me. I learned a lot.

On the next episode of Not Cool, a climate podcast, we’ll be joined by the executive director of Protect Our Winters, Mario Molina, who will talk about what it takes to get both the technological and financial pieces in place to address climate change, as well as the political and cultural will necessary for change.

Mario Molina: The information is there. The science is far, far ahead of the public’s knowledge. The policy solutions are far ahead of the public knowledge, and the technological and financial solutions are actually far ahead of what’s being implemented. But what’s keeping us from deploying them at scale, and in rapid fashion, is the lack of political will.

Ariel Conn: As always, not only do I hope you enjoyed this episode, but if you did, I hope you’ll consider liking it, sharing it, and possibly even leaving a good review.

Not Cool Ep 23: Brian Toon on nuclear winter: the other climate change

Though climate change and global warming are often used synonymously, there’s a different kind of climate change that also deserves attention: nuclear winter. A period of extreme global cooling that would likely follow a major nuclear exchange, nuclear winter is as of now — unlike global warming — still avoidable. But as Cold War era treaties break down and new nations gain nuclear capabilities, it’s essential that we understand the potential climate impacts of nuclear war. On Not Cool Episode 23, Ariel talks to Brian Toon, one of the five authors of the 1983 paper that first outlined the concept of nuclear winter. Brian discusses the global tensions that could lead to a nuclear exchange, the process by which such an exchange would drastically reduce the temperature of the planet, and the implications of this kind of drastic temperature drop for humanity. He also explains how nuclear weapons have evolved since their invention, why our nuclear arsenal doesn’t need an upgrade, and why modern building materials would make nuclear winter worse.

Topics discussed include:

  • Causes and impacts of nuclear winter
  • History of nuclear weapons development
  • History of disarmament
  • Current nuclear arsenals
  • Mutually assured destruction
  • Fires and climate
  • Greenhouse gases vs. aerosols
  • Black carbon and plastics
  • India/Pakistan tensions
  • US/Russia tensions
  • Unknowns
  • Global food storage and shortages

References discussed include:

What happens when you set a city on fire is you create this immense area that’s on fire all at once. The wind comes rushing in from all directions, and you get winds that are like hurricane force winds blowing into the fire. So you get this ferocious wind and and you get a smoke plume that goes very high.

~ Brian Toon 

Ariel Conn: Hi everyone. Ariel Conn here with episode 23 of Not Cool, climate podcast. As I suspect most of you know, at the Future of Life Institute, our focus is on mitigating existential threats. As such, global warming is not the only climate change threat we worry about, and it didn’t seem right to do an entire podcast series on climate change without also considering the other major and catastrophic climate threat that could destroy much of life on earth: nuclear winter.

We’ll get into this more in the podcast, but nuclear winter is essentially the theory that, if we had a major nuclear war, so much smoke and debris would get lofted high into the atmosphere, blocking the sun and dropping temperatures by as much as 20 degrees Celsius in many parts of the world. This theory was first presented in 1983 in what would become known as the TTAPS paper, where TTAPS is the acronym of the authors: Brian Toon, Rich Turco, Tom Ackerman, James Pollack, and Carl Sagan. And this theory was one of the factors that led the US and Russia to reduce their nuclear stockpiles

I’m thrilled to have one of those authors, Brian Toon, on the show today. In addition to having studied nuclear winter for over 30 years, Brian Toon is also a Professor at the University of Colorado at Boulder in the Department of Atmospheric and Oceanic Sciences for which he was the founding Chair, and he’s a Research Associate in the Laboratory for Atmospheric and Space Physics. 

His research group studies radiative transfer, aerosol and cloud physics, atmospheric chemistry and parallels between the Earth and planets. Brian helped conceive, develop and lead many NASA airborne field missions aimed at understanding stratospheric volcanic clouds, stratospheric ozone loss, the effects of aircraft on the atmosphere, and the role of convective and cirrus clouds in Earth’s climate system. He has been involved in numerous satellite missions for both Earth and the planets. He has published more than 300 papers in refereed scientific journals, and is one of the most highly cited researchers in Geoscience. 

Brian, thank you so much for joining us today.

Brian Toon: Well, thank you for inviting me.

Ariel Conn: Just as a reminder for our listeners, can you tell us what nuclear winter is?

Brian Toon: Nuclear winter is the idea that following a nuclear war, the explosions of high energy weapons in cities would start fires in the cities, and those fires would send smoke to high altitudes where it would stay for years and block sunlight from reaching the ground all across the globe. And as a consequence of that, it would get cold at the ground because there wouldn’t be as much sunlight reaching the ground, and it would also get very hot in the stratosphere because of all the light that’s being absorbed up there, which would destroy the ozone layer. And so you have a combination of the loss of the ozone layer, which protects us from harmful ultraviolet radiation at the ground, and it being cold at the ground. And there’s a whole range of effects that you can have depending on how big of a war you have.

So to have a real nuclear winter, which means that the temperatures at mid latitudes in grain-growing regions like Iowa, or Ukraine, are below freezing every day for several years. That would be a real nuclear winter. But you might have a smaller war — between India and Pakistan, for example — that might still cause it to be cool at the ground, but it wouldn’t be below freezing all the time. That would not be a nuclear winter, but it might still be devastating to agriculture.

Ariel Conn: You were one of the original people to start looking into this idea of nuclear winter. Can you talk a little bit as well about the background behind this theory?

Brian Toon: Well, there were several people involved in this, and most of us came into this problem by way of the extinction of the dinosaurs. We had been working on problems about supersonic aircraft polluting the atmosphere and volcanoes and how volcanic clouds might alter the climate. These were early days in climate modeling, so people were interested in all those issues. And then in 1982, a group of people at Berkeley discovered that an asteroid had hit the Earth at the time of the extinction of the dinosaurs, and we started working on that problem. We now know that the extinction occurred because everything in the surface of the earth caught fire, and because of the asteroid hurling material into the upper atmosphere, so that the entire earth was covered in what looked like to us a sheet of glowing hot lava. If you happened to be there, you would feel like you are inside your oven with it turned on broil, which would be very unpleasant.

Anyway, while we were working on that someone asked us, “What would happen if there was a nuclear war?” We had actually thought about this problem a year or so earlier, and we hadn’t really thought of any terrible environmental effects that would affect everybody on the planet. Obviously, if you’re in a city with a nuclear explosion it’ll be very bad, but nothing global. But when we were asked to think about this again, we started to work on it. And we first thought about dust being lifted by the explosions, but then it was pointed out by Paul Crutzen — who’s a Nobel Prize-winning chemist — that there would be a lot of fires, producing a lot of smoke, which actually was an idea he’d gotten from someone else who’d written a paper about it in Scientific American. So then we began to investigate the smoke, and it was very obvious even with a modest amount of smoke that the sun’s intensity would be greatly diminished, and it would get very cold at the ground, and the temperatures would actually stay below freezing for a long period of time.

This is all discovered in about 1983, and it was very controversial at the time. Huge numbers of people worked on it, although they were forbidden to work on it by most of the government agencies. For example, NASA only allowed our little group to work on it and actually stopped other people from studying fires. NOAA forbid any scientists in its organization to work on this problem, which is unfortunate because they have a lot of climate models. National Science Foundation wouldn’t let anybody work on it but two people at the National Center for Atmospheric Research. So this was a problem, really, in the long run, because basically all the scientists in the world who might have wanted to work on this, which would be the normal response of scientists if some hot new problem comes up — everybody leaps in to try to work on it — but they were prevented from working on it. Really only a group of scientists from the Department of Energy, which is the agency of the government that builds nuclear weapons, were really allowed to work on it.

There was a brief period of time for a year two when Congress required the Department of Defense to fund a bigger program, and so there was actually a huge amount of work done then by a broad range of scientists in the United States. But that funding didn’t last about two or three years. People did a lot of work on it; the US National Academy of Sciences had a panel work on it and look at the problem and they concluded that what we had said was plausible, and they couldn’t think of any issues with it at that time. A few years later, there was a study by the Scientific Committee and Problems of the Environment, which is a United Nations committee that involves all the Academy of Sciences in the world. And they wrote two books about the subject, and likewise couldn’t find anything wrong with it at that time. In fact, nothing has been found wrong with this theory so far after several decades of people looking at it — although there are scientific issues in here that need to be studied further, and one could find problems with it. There are definitely issues left to understand better. 

Since that time, of course, the politicians learned about these problems with a nuclear war. In about 1986, Ronald Reagan and Mikhail Gorbachev, who were then the presidents of the United States and the Soviet Union, decided that it was immoral for the world to have these big arsenals, which might destroy civilization. They actually both said that they understood the science behind this problem and that it wasn’t the right thing for people to do. Ronald Reagan gave interviews to the New York Times in which he described how the nuclear winter works and how dangerous it would be and that it was unacceptable. Gorbachev said similar things, and they both said, “We have to reduce nuclear arsenals.” And they did start reducing nuclear arsenals, and every American president and every Russian president since that time has reduced nuclear arsenals. So in 1986 we had 70,000 nuclear weapons on the planet; now we have about 14,000 nuclear weapons. We still have a lot.

Ariel Conn: How many nuclear weapons do you estimate would be required to trigger nuclear winter — or a cooling at all?

Brian Toon: Very few. Right now, the United States has about 300 cities that have more than 100,000 people; Russia has about 200 cities with more than 100,000 people. We could destroy all of Russia’s moderate-sized towns and cities with around 200 nuclear weapons. If you think some of them might not work, okay, maybe we’d need 400 nuclear weapons, assuming half of them failed — although most people don’t think the failure rate would be anywhere near that big. And Russia could destroy the United States with 300 weapons. The number of weapons you need to destroy the other country is not very large. You don’t even need that many weapons to cause a nuclear winter; we think you could probably do it with 100 weapons in large urban areas.

Ariel Conn: I want to come back to that, but before I get to that question, I want to go back to something else you were saying earlier, where you were saying there were still more scientific questions to answer. What are some of those?

Brian Toon: Okay. Well, there’s a whole chain of calculations you have to do to determine how cold it might be at the surface. If you want to know how many people would be killed by the initial blast, there’s a much shorter number of calculations you have to do. The first thing you have to know is what’s the target? Are they going to aim missiles at other missiles? For example, in Colorado here, there are about 400 missiles spread from here up through Wyoming and Montana. About 50 miles from where we’re sitting, near Fort Collins, there’s about 50 in the ground, and those might be targets for Russian missiles that would want to keep those missiles from being launched. So they might explode 100 nuclear weapons up near Fort Collins and Cheyenne, Wyoming, which is mostly a grassy area. So not many people would be killed there; there’s not much fuel there. The main danger from those would be the radiation that would be produced by the weapons, which could spread out for hundreds of miles down wind and produce a lethal dose to anybody who was exposed over the next few days.

The targets that are of most concern are cities, and that’s what nuclear weapons were built to do — they were built to destroy cities. That’s the lesson from the Second World War. In the Second World War, the United States originally tried to win the war by bombing military facilities with small bombs that were guided by Norden bombsights, and despite all the propaganda about that, those bombsites never worked very well and they were never able to hit their targets very well. And so in the last few years of the war, the United States and Britain would send hundreds of airplanes over German or Japanese cities. And instead of dropping explosive weapons, they would drop incendiary bombs, which were small things about the size of a brick — and their goal was to hit the roof of the building, make a hole in the roof and fall down into the building and start it on fire.

They started immense fires in German cities such as Dresden and Hamburg; in Japan, we burned 69 cities at the ground with great fleets of aircraft. Of course, if you send 500 airplanes over a city, some of them are going to get shot down and some of them are going to have problems just flying there. So the advantage of a nuclear weapon is you don’t need 500 airplanes — you just need one. You only need one bomb, and you can burn a whole city to the ground. So in the second world war Tokyo was burned to the ground by incendiary bombs, and killed more people than the Hiroshima bomb did. But there was only one bomb in Hiroshima. So despite what the Department of Defense wants to pretend — that they’re going to use these weapons on military targets — they were built to bomb cities and destroy huge urban areas, mostly by burning them to the ground.

So the first issue it just what’s the target? If it’s an urban area, you want to know how much fuel is there to burn? Wooden buildings, like houses people live in; petroleum and refineries; perhaps coal stored at a power of plant; there’re some trees around. There’s lots of things to burn in cities. But this is the problem: it’s hard to tell for sure how much fuel is in a particular city — especially in a city in India or Pakistan, which may be different than a city in the United States or Europe in terms of what they build their buildings out of. And it’s also that we don’t have experience with whole cities burning. We really don’t know what those fires are like, except for the experience in Hamburg and Dresden and Hiroshima.

Ariel Conn: I want to ask about that, because the theory of nuclear winter is based off smoke and soot and whatever else going up into the atmosphere and blocking the sun. But how is that different from the fire storms and fires that ravaged the cities in World War II?

Brian Toon: It’s probably very similar. Hamburg, the area that was burned there was about 13 square kilometers, and the area in Hiroshima that was destroyed by fire was also about 13 square kilometers. It’s interesting that although we think of the energy in this explosion — the bomb in Hiroshima had the explosive power of 15,000 tons of the conventional explosive — the fire, these fires are very energetic. There was probably 1000 times as much energy released in the fire in Hiroshima than was released by the bomb. These fires are something that — they do happen in natural circumstances: for example San Francisco, when it had its earthquake in 1906 — the real damage there was not done by the earthquake. It was done by a fire that was partly set by the earthquake and apparently set by people trying to fight the fire by setting backfires. And this whole thing was described by Jack London, the famous author who was in Oakland at the time, across the bay from San Francisco. That was the largest maritime evacuation in American history.

All kinds of boats from Oakland and Alameda went across the bay and rescued people who were trapped on the shore in San Francisco by the fire. And he describes this fire as the winds — there were no winds in Oakland, but there was a ferocious wind in San Francisco, a great tower of smoke coming up. So what happens when you sit a city on fire is you just create this immense area that’s on fire all at once. People see forest fires, where the wind is blowing in one direction and pushing the fire. But in these big fire storms, the wind comes rushing in from all directions, so it makes the fire burn much more energetically — it’s like blowing on a fire in your fireplace or something — it makes it burn faster. And you get winds that are like hurricane force winds blowing into the fire. People in Dresden and Hamburg described clothes being ripped off of people and people being blown into the interior of the fire by the wind. So you get this ferocious wind and you get a smoke plume that goes very high.

We see occasionally that there are forest fires that do this: there was one in 2018 in Canada that created a smoke plume that went into the stratosphere. We could see the smoke from that from satellites for about eight months. So that’s the second place where there’s a lot of uncertainty. The first question is how much fuel is there to burn, and how intense is the fire, and does it sit in one place or blow in the wind? The second thing is, how high does the smoke get?

Ariel Conn: In those examples that you just gave, did we see cooling effects at all?

Brian Toon: Well, for example, Hamburg: we know that the spoke plume there got as high as eight kilometers. So we know the smoke did go very high, and the Germans were very methodical there — they are they went out and analyzed the place that burned, and they computed the amount of fuel that was there. So they actually told us what the amount of fuel was, and we know how high the smoke went. That was pretty interesting data. But most of these fires happened over about two years, so it was a long period of these fires being set by incendiary weapons, and it was in the middle of a war. So there wasn’t much scientific measurement going on, so we have no record of how much smoke got into the upper atmosphere. People would have not really been able to measure it at the time anyway; they didn’t have satellites and advanced instruments.

Alan Robock has looked at the data in the Second World War, and there was a slight cooling right after the war, which could have been caused by smoke from these burning cities. But we just don’t know how much smoke was produced, and the evidence for the amount of smoke in the atmosphere is limited. So yes, it did cool off a little bit, apparently, but it’s hard to be certain if that was due to some natural fluctuation in the weather or whether it was caused by these fires.

Ariel Conn: Then, when we’re looking at your research, you’re clearly expecting that if we have a real nuclear war, something different will be happening. And is that that a fire in a single city would be much bigger? Is it that there would be more cities on fire? All of the above?

Brian Toon: All of the above, because there are 14,000 nuclear weapons out there. So you could attack basically every city of any size in Europe and Russia and the United States, plus other places which aren’t even the cities like missile fields. You’d have potentially all of Europe and the United States and possibly China on fire. And the size of modern nuclear weapons is much larger than the one in Hiroshima. So it was a 15 kiloton explosion, which means it was the explosive power of 15,000 tons of conventional explosive. But now the typical-sized weapon in the American and Russian arsenals and the European arsenals is probably around 300,000 tons — 20 times more powerful than the Hiroshima bomb — and there are some bombs that are much bigger than that.

Even a single Trident missile-carrying submarine — and the United States has always got four of these, at least, deployed and has 18 of them; Russia has similar kinds of submarines — a single American submarine is capable of carrying 200 nuclear weapons. Because of the treaty regulations, which were in effect until the Trump administration has walked away from them, restricted the number of missiles on a single submarine to about 100. But even that way, an American submarine with 100 Trident missiles: each one of those — the smallest one is 100 kiloton weapon — could destroy an entire city, instead of just a little fraction of it like the one that fell in Hiroshima. For example, if 100 kiloton weapon blew up over Denver, it would start fires within a circle six miles in diameter. So if you dropped it on the city center, the fire would go all the way out to the zoo. So the weapons are much bigger, and there are many more of them than the fires that were started in the Second World War.

Ariel Conn: You’ve done a lot of work looking especially in India and Pakistan, but also the US and Russia. I was wondering if you just talk about the differences between if India and Pakistan were to get into an all out nuclear war versus the US and Russia.

Brian Toon: The US and Russia, between them, have each got about 4000 strategic nuclear weapons. So this is kind of a game that politicians have been playing with us for about 20 years, and it used to be before 2000 we counted all the weapons. So Russia has all kinds of what are called tactical weapons that are used for fighting a battle in Europe, to blow up tanks or something, but that’s really misleading because those weapons have great explosive yields — bigger than the Hiroshima bomb. And they don’t get counted. The ones we count are called strategic weapons, which means they’re not used to fight a battle against soldiers and tanks; they’re shot off on missiles to attack long range targets in Russia or the US. And there are about 4000 nuclear weapons that are capable of being put on those missiles, but in another political dodge, only 2000 of those are counted on each side, because those are the ones that are actually on a missile and deployed. The other ones are just sitting in storage somewhere, which of course, in the event of a war, could potentially be brought out and used. There’s a lot of missiles there between Russia and the United States that are very powerful.

Now, in the early 2000s, Pakistan and India had several skirmishes. They nearly went to war with each other. They’ve had four wars since they separated from Britain following the Second World War when they became independent. They each had tested nuclear weapons in 1998, but not since then. So the reason I became interested in them was because during one of these wars, a reporter called me up and said, “Well, what would happen if there was a nuclear war between India and Pakistan,” which they were threatening each other with. I said, well, I didn’t know; I hadn’t thought about it. A lot of Indians and Pakistanis would get killed, but it probably wouldn’t affect the rest of the world. This was a usual response to a reporter who says, “I have to write an article in the next six hours; answer this question immediately.” So you’re not expecting this question. So I felt guilty about that, and I decided I had better go look up how many weapons they had. It took me a couple of years to figure out how many weapons India and Pakistan had and how big they might be and where they would likely use them.

I was very surprised to discover that at that time, they each probably had about 50 nuclear weapons, probably about the same size as the one that was used on Hiroshima, probably the same type of design of weapon. And I calculated how much smoke I thought they would produce. I was working with Rich Turco then, who had originally worked on the nuclear winter problem, and he and I tracked down Alan Robock, who we knew could calculate the effects of the carbon better than we could at that moment. He said, “Well, I don’t think anything will happen. But yeah, I’ll go do a calculation.” And he was surprised to learn that yes, actually, a severe climate change bigger than anything that had happened on the planet since the end of the last ice age would occur. So this situation has only gotten worse, because India and Pakistan are building up their arsenals at a rapid pace. They each now have about 150, and it’s expected if they keep up on this path that by 2025 Pakistan will be the third largest nuclear power on the planet by the number of weapons they possess; they’ll probably have about 250 then. So it would be the United States and Russia, which are about equal, and then Pakistan, and India probably right behind, would be the major nuclear powers on the planet.

Ariel Conn: Sorry, real quick, how many weapons does China have?

Brian Toon: France, Britain, and China each have some number that’s around 200 nuclear weapons.

Ariel Conn: Okay.

Brian Toon: It’s not actually easy to tell how many weapons these countries have because unlike Russia and the United States, which have treaties that require exposing the numbers of weapons they have or information from which we can learn that, the other countries aren’t required to do that. The way you determine the size of their arsenals is partly to look at the amount of material they’re producing from which they can make bombs, which is enriched Uranium — so you hear about Iran producing enriched Uranium — or it’s plutonium, which can make it a nuclear reactor. But a better way of doing it is to count the number of weapons systems they have that can deliver nuclear weapons. 

Pakistan and India both have cruise missile programs. They both have nuclear capable aircraft, mostly that have come from the United States or Russia or France. India has a nuclear powered submarine that it wants to use to launch nuclear missiles with. It has missile launching ships. Pakistan is building submarines, and also wants to have a nuclear navy. Both of these countries have advanced missile systems and aircraft systems and other things to launch nuclear weapons with. And India has launched numerous satellites; it’s launched American instruments to Mars; it’s put a spacecraft around the moon. They’re perfectly capable of advanced missiles carrying nuclear warheads anywhere on the planet, actually. 

If you read the Indian literature, it’s quite clear that it’s not just Pakistan that they’re concerned about. They also are concerned about China, which they’ve had some skirmishes with but are on better political grounds. But they also don’t like the United States meddling in their affairs. For example, not many Americans remember this, but it’s very clear to Indians that during the Nixon administration, we sent an aircraft carrier into the Bay of Bengal to get between India and Pakistan when they were having one of their conflicts. The Indians resent this interference by the United States in their affairs. Many Indians argue that’s a reason to have a powerful nuclear arsenal: to keep Europe and the United States from interfering in their affairs. So they’re not threatening us at the moment, and little reason to think they will — however, they could, and some of them have thought of it.

The biggest threat is a war between India and Pakistan, because they’ve had these wars. Some of your listeners may remember that in the beginning of 2019, India bombed Pakistan and Pakistan bombed India, all of which was connected to a terrorist attack in Kashmir, which killed a large number of Indian soldiers. Terrorists from Pakistan blew up the Indian Parliament in 2001; fortunately, it wasn’t in session — I think 12 people were killed. And then there was a later attack, I believe in 2008, in which terrorists blew up some hotels in Mumbai. So there are continuing terrorist attacks by Pakistan in India; Pakistan claims to try to control the terrorist groups, but obviously doesn’t have good control of them. And of course, the Indians don’t like this. A few months ago, in an unconnected event, India change its constitution so that Kashmir — which had been guaranteed autonomy in the Indian Constitution, and some self governance — was changed in its status so that its governance would come from the central Indian government. And they sent a large army into Kashmir to keep citizens there from rebelling against these new rules.

Of course, this made the Pakistani people very unhappy. Kashmir is a very complicated situation. There are conflicts there between China, India and Pakistan, although the India and Chinese one has more or less been resolved by agreements about where the border is. But Kashmir, when India and Pakistan separated, was a Muslim-dominated sheikhdom. But the person in control there decided he wanted to stay with India. That led to part of Kashmir being taken over by Pakistan and part by India, and there’s something called the Line of Control between them. And the two countries argue over who should control Kashmir. So it’s an unresolved problem, and external countries have not been able to resolve it. There have been war games between Indian and Pakistani generals and politicians who are retired, in which they try to evaluate what would happen if there was some conflict that was getting out of control. There are interesting aspects of this: they both envision that if a war starts to break out that Russia and the United States will get in between them and try to stop them from actually having a war, which is somewhat interesting since they objected to the interference of the United States before. But nevertheless, if that doesn’t happen, because the world is distracted by something else, or they don’t pay any attention to it, or whatever, they find that a war will quickly get out of control.

The reason for that is it India is much bigger than Pakistan. India has about 1.3 billion people; Pakistan has about 160 million people. Pakistan is only about 10% of the population. India has a million people in its army — one of the biggest armies in the world; Pakistan has about 500,000. Pakistan geographically is a small country, so India could easily overrun Pakistan with its army with just conventional tanks and airplanes and things. So if it appeared that India were thinking of invading Pakistan, there’s a great danger that Pakistan would feel it had to use its nuclear weapons before the invasion, because otherwise they might be taken by the Indians and then not be able to be used. And so Pakistan might be inclined to use weapons quickly. Pakistan now has tactical nuclear weapons, and so there’s a fear that if Indian tanks ever crossed the border that Pakistan might use nuclear weapons on its own territory against the Indian Army. And in these war games, that also leads to a war breaking out with nuclear weapons. So there’s a great danger there of a nuclear conflict because of the imbalance of power between Pakistan and India. 

And there’s additional problems here because of China. China is building this trade route going across the historic trade route from thousands of years ago between China and Europe, probably also into Africa, and a lot of that infrastructure goes through Pakistan. China is trying to use back Pakistani ports to facilitate this, and they’ve tried to start military installations in Pakistan — which doesn’t seem to have actually happened, but they were certainly discussing it. All those things make it a concern that China could enter such a war on the side of Pakistan, which would lead to an even worse problem, because India would then attack China with nuclear weapons and vice versa. That could be a global nuclear war — or even just India and Pakistan, a nuclear war with repercussions as large as a US-Russia war.

Ariel Conn: I want to interject here, because I have some questions about fuel that I think relate to especially India, and I’m not sure about China. If I’ve understood it correctly, essentially one of the bigger risks associated with nuclear winter is nuclear explosions in very dense cities, and India has very dense cities. How does that compare to — if we’re looking at, say, Delhi versus New York, or something like that — what are the impacts of a nuclear attack in, say, Delhi versus New York?

Brian Toon: Well, as far as we can tell, there’s about the same amount of fuel. Each person in the country has a certain amount of burnable material, either in their house or in the supermarket they use or the school where their kids go to school or the place they work — in general, where people live. We find that the fuel goes with population. Some of the bigger cities in India and Pakistan have immense fuel loads, so huge amounts of material to burn in them. Of course, there are controversies there. If you look at just forest fires — for example, the camp fire in California burned the city of Paradise California. And if you look at satellite images you’ll see there are individual houses, one or two story houses, and they’re just burned to the ground and everything in them was consumed by fire, while surrounding pine trees didn’t burn at all.

If you have residences or stores that are a few stories high, the evidence is pretty clear that you’ll burn everything in them. But if you have something like the twin towers in New York — which are huge, tall buildings, and when they collapse, a lot of stuff is buried — then a lot of the fuel in those buildings, which is mostly things like furniture and paper in offices and materials like that — that may be buried, and so it can’t burn. There is uncertainty about whether in dense urban areas some of the materials are protected by collapsing buildings. In most nuclear weapons, there’s a very powerful shockwave that comes out and can collapse big, strong concrete buildings, but that shockwave only extends out over about 10% of the area that will catch on fire. The place where these buildings will just collapse from the shockwave is probably a small fraction of the area in which fires will start. So then it becomes unclear, how do fires spread in cities?

This is something that’s actually a practical problem in the real world. There is a huge effort in the United States at the moment to understand wildfires, because they’re so devastating in the West, and their frequency is increasing and people are more exposed to them because of the growing population. We know a lot now about how much fuel there is in forest and grasslands and things like that, but we actually don’t know how much fuel is in American cities. That’s a problem when fires enter an urban area — they start in the forest, from lightning, say, and those fires burn into a city. And you’d like to know how much fuel is there so you can predict, will this fire spread across the city? Where should firefighters go to stop the fire? Where should firefighters not go because the fire might turn and blow toward them and kill them? So there is a lot of effort going on to build very sophisticated models of fires to help firefighters predict where to fight fires and how to protect themselves when they’re fighting the fires. So those people need to do the same things we do, which is what happens when fire enters a city.

Ariel Conn: I just want to get clarification. The amount of fuel is connected to the population, but a city like Delhi is, what, two and a half times as big as New York City? Do you expect a nuclear attack on those cities to be the same for some other reason?

Brian Toon: The Department of Energy has created a population database that, as far as I know, covers the entire earth and has identified the population on a grid that’s about one kilometer squared over the whole earth. In our most recent calculations we’ll pick a city by population, because we assume that Pakistan will attack the most populated areas in the Indian cities. And we’ll decide what size weapon they’re going to use — say it’s a Hiroshima size weapon, and we think that would burn an area of 13 square kilometers. So we would break down that region into 13 different little squares, a kilometer each on a side. And we’d go to this database and find out how many people live in each one of those little areas. And we’d say each person has, actually it’s about 11 tons of fuel. Then we’d compute how many people there are, and that would tell us how much fuel there is in this tiny little section of the city.

The weak point of this is that we don’t know that the average person living in Pakistan has the same amount of junk that the average American has. So right now we’re assuming that everybody in Europe, Russia, the United States, all has an average amount of fuel, which was developed in the 1980s based on European and Russian cities; we looked at NATO and Warsaw Pact cities and tried to calculate how much fuel was there. And so we’re assuming that whatever amount of fuel was there per person in the 1980s is still there per person — which may or may not be correct, because people are making more and more plastics and using less and less wood to build buildings. Then in India, we’re assuming that those people use the same amount of plastics and petroleum and wood, which may not be the same amount. It’s very embarrassing to go to India and walk around the city and try to figure out how much fuel there would be in case of a war. Plus, nobody has the money to do that.

Our group has got about 20 people in it, many of which have no funding — they’re just working on this problem, because it’s interesting. And that’s the only people in the world working on this problem. There were no other people in universities or in any of the government agencies working on it. There may be a few people in the Department of Defense or Department of Energy; if they are they’re not telling anybody about it, with a few exceptions. So this is a huge, complicated problem. If it were any other science problem — for example, I did a lot of work on the ozone hole: there were thousands of scientists working on that problem; you’d go to a meeting; you’d have a huge auditorium full of hundreds of people. There are only 20 of us. We can’t see send people to India and go figure out how much fuel is there. So we are actually trying to do this now by using satellite imagery and data collection from groups that do this for commercial reasons — like Zillow knows how much fuel there is in the United States because it knows that every house for sale; the census in the United States keeps track of how many houses and industries and things there are in the United States. But people don’t do that in other countries, so it’s harder to get the information there.

Ariel Conn: You mentioned that people have more plastics now. How does plastic burn compared to wood?

Brian Toon: Plastics produce a whole lot of smoke. In the 1980s, it was thought that about 40% of the smoke produced was coming from burning wood; about another 40% was coming from petroleum and plastics; then some other was coming from miscellaneous other things. But petroleum products and plastics are probably the main source of what we call black carbon. So if you have a fire in your fireplace, it’s all black and sooty, but in forest fires and in burning logs, things like that, there’s actually a lot of stuff in the smoke that is not black carbon. It’s some organic goop. If you touch a log that’s harvested recently and get sap all over your fingers, all that stuff is in the smoke. But if you burn petroleum — if you have a petroleum fire, or if you have a plastics fire, they produce almost entirely black carbon, which is very light absorbing.

So it takes only a small amount of that to absorb a lot of sunlight. For example, we just finished studying this fire that occurred a year or so ago in Canada. And the smoke that went into the stratosphere did something that had been predicted in nuclear winter studies but never before observed. Smoke was injected at about 12 kilometers, and then over about a month it rose in altitude to about 20 kilometers. There was a large amount of smoke injected, but only about 2% of that smoke was actually black carbon, which was what was being heated by the sun. And so 98% of the smoke wasn’t doing much, and 2% was just making the air hot. You could measurably see the air was hotter than normal there, and it was making it rise in altitude because it was buoyant like a balloon.

Ariel Conn: Most of that smoke was not having a cooling effect?

Brian Toon: It wasn’t contributing very much in that forest fire, but unlike forest fire material, wood in a house — in the studs in your house or in the floor in your house or in the furniture in your house — has lost a lot of its organic material when it died and dried, so it doesn’t produce that much organic material: it’s kind of equal amount of organic material and black carbon. Then petroleum and plastics produce almost entirely black sooty carbon.

Ariel Conn: Is it reasonable to guess then that our increased use of plastic could make nuclear winter worse if nuclear war did breakout?

Brian Toon: Yes, it probably will make things worse. Although once again, it’s not clear — we are making a lot more plastics, but it isn’t clear we’re making more plastics per person. So this comes down to whether the plastics per person are going up. I know of actually one study on the amount of plastics in the world. Expected plastics will rise rapidly in the future — more and more things are being made of plastics. But from that one study, it isn’t obvious that the per person amount of plastics is rising, or if it’s just plastics are rising with population.

Ariel Conn: I feel like this is a really nice transition into global warming, which is the opposite of nuclear winter. I guess I want to start with the wildfires where, as the earth continues to warm, we’re expecting to have more and more wildfires, especially with this one that you keep referencing in Canada where it did send smoke up into the upper atmosphere. Is there any chance at all that the silver lining of wildfires is that they could help cool? Or is that unrealistic?

Brian Toon: Well, surprisingly, wildfires are thought to cool the planet. So aerosols — like particles from smog, or dust storms, or material from fires; sea salt, little parts of insects, bacteria; all these little things floating in the air — almost all of those are light scatterers — they reflect light back to space — and not absorbers of light, so they cool the planet off. This is in opposition to the greenhouse gases, which warm things up. The aerosols don’t live in the atmosphere very long: maybe for a week on the average. So all the dust and other pollution in the air is replenished every week — which makes it very complicated to figure out what’s there, because it’s constantly changing with season and location and other things. On the other hand, the greenhouse gases — particularly carbon dioxide — have incredibly long lifetimes. And so they’re very uniform everywhere, which makes it very easy to predict what their effects are. This is a reason that carbon dioxide is such a problem: if you put more carbon dioxide into the air, some of it dissolves in the ocean.

So over about 50 years, the carbon dioxide will go into equilibrium with the oceans and to some extent the biota, which like to make trees out of it. But the carbon dioxide is not entirely removed from the atmosphere. When I drive home, and I emit carbon dioxide out of the back of my petroleum-based car, that carbon dioxide — about 20% of it — will still be in the atmosphere thousands of years from now. That’s why the carbon dioxide problem is so terrible. Smog-producing particles that come out of the back of my car — they’re going to be in the air for a week and then they’re going to disappear, and I get to restart again polluting the air. But the carbon dioxide is just going to build up and build up over my whole lifetime, over the lifetime of my children and my grandchildren. That’s why in order to get rid of the greenhouse problem, we have to almost entirely get rid of carbon dioxide emissions, and to lesser extent methane emissions. Methane has about a 10 year lifetime, but it produces carbon dioxide when it goes away, so it’s still something that we have to eliminate almost completely.

So the aerosols tend to cool the earth and the greenhouse gases tend to warm the earth. And because the aerosols are working against the greenhouse gases, the net effect is slightly less warming than if we didn’t have the aerosols around. This is very annoying because the aerosols are very complicated and variable. If they didn’t vary so much, it’d be much easier to calculate the climate change. Carbon dioxide is building up rapidly and it will overwhelm the aerosols — already does overwhelm the aerosols — it will overwhelm them completely by the end of the century. And part of the danger we have in coming decades is that people would like to reduce the aerosols because they are bad for human health. For example, the emission from coal-fired power plants in the United States is thought to reduce the lifetime of tens of thousands of people every year. So people want to get rid of this pollution. If they get rid of it, then it’s not balancing the CO2 warming anymore and the warming can accelerate even more rapidly.

Ariel Conn: So basically, the aerosols might help with cooling, but the other greenhouse gases are warming faster than anything is being cooled?

Brian Toon: That’s correct. The other problem is that the aerosols have a lot of uncertainty about them. That uncertainty contributes to an uncertainty in understanding global warming. If we didn’t have the aerosols there, we could easily tell from how much increase in temperature we’ve had historically in the last hundred years, and how much carbon dioxide went up, we could tell how fast the earth is warming in response to carbon dioxide. We can’t tell that because the aerosols are sitting there messing everything up, confusing what the sensitivity of the Earth’s climate is to the greenhouse gases.

Ariel Conn: You do study both nuclear winter and climate change. What do you find more worrisome? What’s more likely to keep you up at night?

Brian Toon: Well, I’m very concerned about nuclear conflict at the moment, because the Trump administration has walked away from all the agreements we have that control nuclear weapons. I mentioned that in the 1980s Ronald Reagan and Mikhail Gorbachev agreed to reduce the number of nuclear weapons, because they were afraid that they’d cause a nuclear winter and kill most of the people on the planet. Trump has now walked away from that treaty, which allows the introduction in Europe now of all kinds of short range weapons, so it’s a big threat to the people in Europe. There are all kinds of imaginative people that work for the Department of Energy that have thought of all kinds of new weapons systems that have all kinds of new capabilities. For example, Russia recently had an explosion, which distributed a lot of radioactivity in Russia, which was probably a drone cruise missile sort of thing powered by using radioactive fuels.

The United States had thought of building such weapons decades ago and decided not to, because when this crashes at the end, it’s going to spread radioactive debris all over the place. How do you test it? Which is a problem the Russians obviously had there when their thing blew up. So it’s incredibly dangerous to build a drone — the idea of this is it could fly a long time, so you just put them into flight and fly them around all the time and if you feel like it, you can just attack your enemy with it. And because it’s a cruise missile, it can fly below radars or it isn’t easy to see; we would never know when it’s launched because it can be launched it anytime. These things are incredibly dangerous because of the radioactivity in their engines. There’s no reason to build such a machine. We need not to get rid of our treaties. We need to work with Russia, and other countries like Britain and France and China, to reduce nuclear weapons. We have no reason for all the nuclear weapons we have now. They are a waste of money.

So the United States right now is spending about a trillion dollars over the next 10 years to upgrade nuclear missiles, to upgrade nuclear submarines, to upgrade warheads, to build different kinds of weapons, different warheads, lots of these things that have been banned in the treaties. What’s the purpose of these weapons? They have no purpose. You can’t use them, because they’d kill so many people. So you’re going to spend a trillion dollars to have a bunch of weapons sit in the ground, or to fly around in airplanes, or to be in submarines, or to fly around in the air with radioactive engines. They have no purpose; you can’t attack anybody with them. And so you’re just spending money for nothing. Why not have a treaty and build down the number of weapons? It’s still perfectly threatening.

Right now we have, under treaty, 2000 warheads in Russia and the United States; really, there’s more like 4000 in each country. But even 2000 is totally unnecessary — there’s only 200 cities in Russia to attack. There’s only 300 cities with more than 100,000 people in the United States to attack. We don’t need 2000 weapons each. We could easily reduce the weapons by a factor of more than 10 on each side and still be perfectly protected — for the people who believe it’s protection to have mutually assured destruction — if Russia attacked us while we destroyed every city in Russia. Surely, the Russians don’t find that acceptable as a punishment for attacking us. I think many Americans don’t realize the experiences that Russia has had with wars. Napoleon invaded Russia and overran most of it before the winter got to the French troops. Hitler invaded Russia: something like 30 million people died in Russia in World War II because of the seiges that Hitler put on Russian cities like St. Petersburg.

In the United States, almost no one died directly because we were not invaded. 300,000 Americans were killed in the Second World War, almost all of them overseas in some foreign country. That’s 1% of the deaths that Russia experienced. Russians do not want to have a war. They know much better than we do what it’s like to have a war, and to suffer for it and starve to death and be attacked. So Russia has to be amenable to treaty restrictions that prevent a war. They certainly don’t want one.

Ariel Conn: I think this next question for me is really quite obvious, but just in case, can you explain why it would be a terrible idea to use nuclear weapons to try to cool the climate? Obviously, you’d end up killing people with nuclear weapons, but then if you have nuclear winter, you have the starvation. And I’m assuming we can’t control the extent of the cooling. Is that correct? Would we be able to even estimate how much cooling would happen?

Brian Toon: Yeah. We’ve estimated that in a war between the United States and Russia — if they use most of their arsenals and they attack cities with them — it will be below freezing for a couple years in the places in the United States where you grow crops. You wouldn’t grow any crops. There’s two aspects of this to think about. One of them is, a nuclear winter would probably only last about 10 or 15 years, and when it went away all that carbon dioxide would still be there. So the greenhouse effect would last for 1000 years as I mentioned before.

The other aspect about this is that people don’t understand food. Lots of people have read the Bible or listen to the Bible stories, and the same story appears in the Quran, which is about Joseph telling the Pharaoh of Egypt, who was having dreams about cows, that his dreams meant that there would be seven years of good weather in Egypt, followed by seven years of starvation in Egypt, and that the Pharaoh should store up food so he could feed the Egyptian population through this starvation period, which he did. He was a hero to his citizens. But that’s not what happens in the modern world. Right now, we have a little over 60 days — two months — of grain in storage to feed the world population. If you don’t keep producing grain continually, then after two months, mass starvation sets in. That would be what would happen in a nuclear war: you won’t grow any food in mid-latitudes. You might still grow something in the tropics, but you’re going to lose most of your food production across the world, and people will start starving to death.

Right now what happens is if there’s a food shortage somewhere — for example, Russia has a history of grain failures: if they have a wheat failure, then other parts of the world ship them food. This happened in the Carter administration; there was a big green failure in the Soviet Union, so the United States sent the Russians huge amounts of food from the wheat we had in storage. There was a wheat failure in Russia just before the problems all developed in North Africa and the Middle East. Because of that wheat failure they were unable to ship wheat to the Middle East. And a large fraction of people’s salary goes to food in North Africa: they’re not able to produce enough food to feed their populations; they have to import food. As soon as those imports go away, they’re going to start starving. That is one of the things that set off all the riots in North Africa.

The Syrian conflict was set off by a bad harvest in Northern Syria, food shortages in Syria — and people were rioting over that. This happens even locally. For example, I live in Boulder, Colorado. Five or six years ago, just before Christmas, we had a big snowstorm; we had about three feet of snow that completely shut down all the transportation coming in and out of Boulder. And all the food quickly disappeared off the shelves in the grocery stores, and we started running out of gasoline for cars. The same thing happened in Seattle, and the Mayor of Seattle got thrown out of office because he couldn’t deal with the snow and keep the city running. Most cities only have enough food on hand to feed the population to the city for less than a week. So if you can’t bring in food from outside the city, people are going to start starving in the city within a week.

That’s how the world works right now: it’s assumed that if there’s a problem in one place, somebody else will make it up from another place that’s not suffering. That works very well as long as you’re having random problems with the weather. And so we’ll ship them food when we have it, and they’ll ship us food when they have it. But if you ever have a global catastrophe — which could come from natural causes like a giant volcanic eruption, or from human induced causes like nuclear war — the whole system is going to break down because no one will be able to grow food. And so when you start starving, there will be nobody to send you food. 

This is a cheerful conversation. I love thinking about this in my free time.

Ariel Conn: I was laughing because my last question for you is, all right, so now that we’ve gone through all of this, what gives you hope?

Brian Toon: Well, this doesn’t help me sleep at night. I have kids like most of your listeners do, and I don’t want them to be living their life worried about a nuclear war. And I don’t want them to live their life with the climate warming. It is a health hazard, but it’s largely a hazard to real estate, and a large number of cities in the United States are going to go underwater sometime in the next century. You can forget Venice, Italy — if any of you have ever been to Venice, it already is flooding. Venice is not going to withstand the end of the century. Miami is flooding already; Miami is going to have terrible problems by the end of the century. Large numbers of places all up and down the East Coast, along the Gulf Coast, are very low lying. There’s already problems, for example, in Virginia, where there’s a lot of coastal flooding going on.

And the same thing will happen in California. There are cities in California that have thought about retreating, starting to ban people from building on the beaches. That’s not very popular with you if you want to have your house on the beach — I think they gave up on this, trying to have people retreat, and they decided that people will start retreating once they get flooded. I don’t want that future for the population of the United States. And you can see that there are places — for example, Russia will benefit in a warming climate. The Arctic Sea is already opening up to shipping: there’s huge natural resources there; Russia will gain a lot of ice-free ports. It will be probably better for Russia, and maybe parts of Canada, in a warmer environment. So there are parts of the world that are resistant to this, but Canada and Russia are both involved in the Paris Treaty to try to prevent this from happening. It’s only the United States, is about the only country in the world that doesn’t recognize the threat here, and we’ll hold back the rest of the world in trying to solve it.

Ariel Conn: Are you hopeful that we will solve this?

Brian Toon: When you live in the current time, you feel surrounded by problems, problems of every type and kind. Somebody’s mad about something; somebody’s mad about something else; there’s crime; there’s problems with inflation, or Wall Street has some kind of issue. So we’re constantly bombarded by these problems. But if we go back and look at the history in your own lifetime, which for me is 70 years: when I was young, we thought we were going to have a war anytime with Russia — we didn’t ever have such a war. China and India looked like they would never be able to feed their populations, and both of those countries are booming now. The world is a much better place; the average standard of living almost everywhere in the world is much better than it used to be. And the problems that people have encountered, they’ve overcome in general. There’s still plenty of them around to be solved, but people have overcome them. 

If there’s a problem in the United States, everybody fights about it; everybody in Congress argues about — they should do it this way or the other way — but eventually, they solve it. That’s exactly what’s going to happen, in my view, in the next 50 years or so: we’re going to realize that on the planet Earth, we can’t afford to have these endless wars; all they do is hurt people and drag your economy down and nobody is gaining from that. And the greenhouse problem is going to become so obvious that everybody will see that we have to solve that problem.

Petroleum cars are a thing of the past; that industry is going to die, and it will die quickly. The people in the car industry know that. They’re not fools; they can see that the age of the petroleum car is over and electric cars are the future. People in the petroleum business know that that business is going to slowly fade away. They can fight an effort to slow it down, to make as much money as they can for themselves. But they have children; they know that the world is going to change, and that unfortunately they’re in a business that either is going to have a limited future or they’re going to find some way as part of it to sequester carbon or to convert carbon into something else that isn’t posing this threat.

So it’s possible that we’ll continue to use fossil fuels because somebody will come up with some way to solve that problem. It’s possible the Department of Energy or some entrepreneur will get fusion to work, which doesn’t produce radioisotopes like fision in the power plants we use for nuclear energy now. If none of those come to pass, there’s plenty of sunlight out there; there’s plenty of wind out there; there’s lots of running water. All of those things can be used to power society. We just need battery technology and storage techniques. My niece, for example, is involved in studies in which we use solar energy during the day when the sun is shining, not just to power the town but to produce hydrogen. And we take that hydrogen and we pump it into empty petroleum oil fields where the oil has been taken out and there’d be a hole in the ground, and we store the hydrogen until the night, and then we take the hydrogen out at night and use that to produce power from hydrogen — which doesn’t produce carbon dioxide; it just produces water. There’s all kinds of clever ideas around that I believe will solve these problems.

Ariel Conn: All right. Are there any other final thoughts that you want to leave us with?

Brian Toon: I mean, it is depressing to work on this, but somebody has to work on it and think about it and advise in the government. People won’t do things when they know there’s a problem and they understand there’s a problem and they see a way to solve it. That’s the job of academics like myself; I get paid to teach classes, but I also get paid to do research. The press, and other people who do the kinds of things you’re doing, play a very valuable role in informing people about these issues, and informing people about different viewpoints about these issues. Just because we fight about everything, that’s democracy for you.

Ariel Conn: All right. Well, thank you. I’m very hopeful that this will help in some way. Yeah, we really appreciate you taking the time to talk with us today.

Brian Toon: Sure, always happy to talk to you Ariel.

Ariel Conn: As always, I hope you enjoyed this episode of Not Cool, a climate podcast. But if you were hoping to hear Brian talk about the climate crisis more, I recommend you check out a previous FLI podcast I hosted with him and Kevin Trenberth that was entirely about climate change. Or, if you wanted to hear more about nuclear winter, I recommend listening to one of my first ever FLI podcasts, in which I spoke with both Brian and Alan Robock. We’ll include a link to both of these episodes at the bottom of the podcast intro at And on our next episode of Not Cool, we’ll go back to focusing on the climate crisis. We’ll hear from Ellen Quigley and Natalie Jones, who will look at how we can address climate change from finance and policy perspectives.

Ellen Quigley: It’s worth mentioning that if divestment did extend past public equity and into other asset classes such as bonds, for example, it actually could starve fossil fuel companies of the financing that they require to do things like exploration and development, or build a new pipeline, or whatever else. 

Ariel Conn:  I hope you’ll join us again for episode 24, and please remember, if you enjoy these podcasts, please like them, share them, and maybe even leave a good review.

Not Cool Ep 22: Cullen Hendrix on climate change and armed conflict

Right before civil war broke out in 2011, Syria experienced a historic five-year drought. This particular drought, which exacerbated economic and political insecurity within the country, may or may not have been caused by climate change. But as climate change increases the frequency of such extreme events, it’s almost certain to inflame pre-existing tensions in other countries — and in some cases, to trigger armed conflict. On Not Cool episode 22, Ariel is joined by Cullen Hendrix, co-author of “Climate as a risk factor for armed conflict.” Cullen, who serves as Director of the Sié Chéou-Kang Center for International Security and Diplomacy and Senior Research Advisor at the Center for Climate & Security, explains the main drivers of conflict and the impact that climate change may have on them. He also discusses the role of climate change in current conflicts like those in Syria, Yemen, and northern Nigeria; the political implications of such conflicts for Europe and other developed regions; and the chance that climate change might ultimately foster cooperation.

Topics discussed include:

  • 4 major drivers of conflict
  • Yemeni & Syrian civil wars
  • Boko Haram conflict
  • Arab Spring
  • Decline in predictability of at-risk countries:
  • Instability in South/central America
  • Climate-driven migration
  • International conflict
  • Implications for developing vs. developed countries
  • Impact of Syrian civil war/migrant crisis on EU
  • Backlash in domestic European politics
  • Brexit
  • Dealing with uncertainty
  • Actionable steps for governments

References discussed include:

Climate change is in effect loading the dice. So it’s making certain rare outcomes like armed conflict a little bit more likely to occur in a variety of contexts, with the most significant impacts on societies at lower levels of economic development, higher levels of dependence on agricultural livelihoods, and characterized by weaker state institutions and high levels of intergroup inequality.

~ Cullen Hendrix

Ariel Conn: Welcome to episode 22 of Not Cool: a Climate Podcast. I’m your host, Ariel Conn. Today, we’ll be joined by Cullen Hendrix who will walk us through some of the major drivers behind armed conflict and how climate change could exacerbate a violent situation. 

We’ll look at some specific examples of recent armed conflict, including the conflict in Syria, which many experts argue was triggered by climate change. And we’ll consider whether factors like climate change and emerging technologies could be changing these drivers of armed conflict. 

Cullen is a Professor and the Director of the Sié Chéou-Kang Center for International Security and Diplomacy at the Korbel School of International Studies, at the University of Denver. He directs the Environment, Food and Conflict Lab, which leverages collaborations between physical and social scientists and policymakers to produce scholarship and analysis on issues at the intersection of the environment, food security, and conflict. He co-created the Social Conflict Analysis Database, he is a regular contributor at Political Violence @ a Glance, and he’s a member of the Political Instability Task Force and Africa Board of Experts. He holds research appointments at the University of Texas at Austin and the Colorado School of Mines.

Cullen, thank you so much for joining us.

Cullen Hendrix: Happy to be with you.

Ariel Conn: Let’s just start by talking about what this paper is. It’s called Climate and the Risk of Armed Conflict, and it was expert elicitation. So can you talk about how people were picked to be involved in this paper and essentially what it is?

Cullen Hendrix: Sure, no problem. Let’s start with this question of what is expert elicitation. Expert elicitation is a process by which experts come to identify points of consensus and points of disagreement in a large and complex and sometimes contradictory body of literature that has emerged around the specific topic.

Beginning in the early part of the 21st century, there was a lot of policy interest coming from the national security communities, the intelligence communities, development communities, on links between climate change and security outcomes — in particular, US national security outcomes. And at that point there wasn’t a lot of evidence, so a lot of the thinking about it was dominated by science fiction, rather than scientific process or scientific discourse. In the intervening decade and a half or so, we’ve seen a rapid and massive proliferation in the amount of evidence that’s out there, so that there are now thousands of studies on links between climate change and armed conflict.

The issue being that those thousands of studies do not all point in the same direction or reach the same kind of conclusions. What do you do in an environment like this? Expert elicitation occurs when somebody — in this case, Katharine Mach and Caroline Kraan at Stanford — come along and say, “We would like to essentially be the arbiters in this literature, and we would like to interview a variety of experts coming from a variety of different educational backgrounds at different points in their careers who use different types of methodologies and see what they think about the links between climate change and armed conflict and, importantly, think about the risks associated with climate change in the context of other kinds of risk for armed conflict.”

And so what comes out of that process is a summary statement, like this article, that identifies those points where the experts agree, and identifies points where the experts disagree. For my own part, I was contacted by the main authors of the study, I think on the basis of my work in the past on climate change and social conflict, but also thinking about the role that climate change might be playing in affecting global phenomena like food prices and energy prices, which we also think have manifest effects for political stability in especially developing and middle income countries.

Ariel Conn: I want to ask about some of the drivers that influence conflict, but before I do that, just sort of quickly: did you find that the experts that were brought together for this mostly agreed or mostly disagreed?

Cullen Hendrix: That was one of the more gratifying parts of the whole experience. In order to kind of understand why it’s such a refreshing way of trying to make an assessment about links between climate change and armed conflict in this context, it’s important to put it in the context of how this kind of scholarly discourse normally goes — which is you get a couple of really smart authors or teams of authors duking it out in an academic journal. When they do that, they have an incentive to accentuate the differences in the way that they see the world. A couple of these groups of scholars might agree on 97% of the evidentiary basis, but they’ll end up harping on the 3% about which they disagree.

This process was really refreshing because it asked us first independently, in structured interviews, to reflect on the state of the literature, and then talk about the relative risks of these different factors that we think might contribute to armed conflict, and then place climate change in that context.

One of the interesting things to emerge out of that is that even though many of the authors on this paper had disagreed with one another — in some cases, pretty vociferously — in print, when they were asked to go through this kind of structured interview process, we wound up identifying a lot more points of consensus than we did disagreement, which I think is refreshing. And it’s also useful because if we’re going to try and communicate this to a policy audience, who are not specialists on these kinds of issues, being able to say that we have a fairly high degree of certainty, or at least a high degree of agreement about the relative risks associated with climate change both now and looking forward, is a nice position to be in in terms of trying to add some clarity to those kinds of discussions.

Ariel Conn: Let’s come back to some of the specifics then. You guys identified four drivers as particularly influential to conflict. And those are low socioeconomic development, low capabilities of state, intergroup inequality and a recent history of violence.

There’s other drivers that you mentioned as well, but those were the ones that were the ones most likely to lead to conflict. Could you talk briefly about what each of those are, and maybe even give an example?

Cullen Hendrix: Sure. Those four factors — low socioeconomic development, low state capacity or state capability, intergroup inequality and a recent history of violent conflict — are well understood that as drivers of armed conflict within states.

So here we’re talking primarily about things that look like the civil wars in Syria or Yemen, or the Boko Haram-related conflict in Northeast Nigeria. When we think about the relative contribution of these different factors to armed conflict outcomes, this is evidence that emerges primarily from these big data-driven quantitative kind of exercises. So it’s in many respects left up to the researchers to interpret what these correlations — say between low socioeconomic development, typically measured to something like GDP per Capita, and conflict outcomes — mean.

The standard interpretation is that low levels of socioeconomic development are a source of pretty significant grievances amongst the population, right? These are populations who have not been able to benefit from economic development and all of the really kind of life-changing sorts of technologies — and by life-changing technologies, I mean things as simple as say electrification or refrigeration or access to a clinic in which to give birth — that many people in comparatively well-off societies take for granted at this point.

When we think about the issue of low state capabilities, what this really refers to is the inability of the state to address dissidents, via either repression or accommodation: so identifying nonviolent mechanisms by which you can address the grievances that arise in society. Intergroup inequality is just simply talking about what social scientists refer to as horizontal inequalities: so inequalities in access to political power, economic resources and/or social privilege that break down across either racial or ethnic or religious lines. And then the recent history of violent conflict is simply based on the observation that there does appear to be a conflict trap: so once a society experiences an armed conflict, it is increasingly likely to experience one moving forward.

And so if we think about these four drivers in particular case contexts, I think it’s interesting to talk about it in the context of Syria because all of these different kinds of factors are present in the Syrian case. You have low levels of socioeconomic development, and indeed very highly uneven patterns of socioeconomic development, where you have very lagging behind rural areas that were particularly hard hit by droughts about 10 years ago, which play a pretty big role in the narrative about the links between climate change and conflict in the Syrian context.

In that context, you get kind of rapid urbanization, which really highlights the degree of intergroup inequality in that society — both in terms of who has access to government power, but also who benefits from government policies that are designed to step in and address issues like persistent drought. Then once you have the mobilization of a popular movement that is in the streets and protesting because of low state capacity, you had a tendency on the part of the Assad regime to respond to that with overwhelming shows of force that were completely disproportionate to the types of grievances and the modalities of protest that were being used.

And so you can use that as a case for thinking about the preeminence of these three kinds of factors. Syria is a little bit of an outlier because it did not have a recent history of violent conflict, but obviously moving forward, whatever the resolution of the Syrian civil war will be, that country will definitely be on the watch list for years, if not decades to come because of its recent traumatic experience with large-scale armed conflict.

Ariel Conn: When you identify these four drivers, is it most common that you do see the four together, or does one seem to be more problematic than others?

Cullen Hendrix: Without getting too wonky on this, I mean, one of the unfortunate things that kind of complicates our ability to talk about causality in this context is that multiple motivations or causes are you usually present in any given conflict. And it turns out that many of these “bad things” tend to go together.

So where you see low levels of socioeconomic development, you also tend to see low levels of state capacity or state capability. And in these same kinds of contexts, you’re much more likely to see high levels of ethnic and religious heterogeneity — that is, dissimilarity and diversity within the society — which isn’t in and of itself a bad thing, but when that diversity overlaps with inequalities of access to opportunity and standing before the government and citizenship rights, then yes, it can become extremely combustible.

And so it is the case that oftentimes many of these various important causes are present in the same conflicts. So we could apply each one of those three, and actually the fourth in this case — the recent history of violent conflict — to the conflict between the Nigerian state and Boko Haram, for instance.

Ariel Conn: In Syria, is there generally agreement that the drought was climate change-related and thus that climate change did play a role? Or is that still slightly contentious?

Cullen Hendrix: It is well-established that there was a historic drought that occurred in Syria that more or less immediately preceded the outbreak of the Syrian civil war. Now, whether or not that particular drought was caused by climate change is of course a very fraught kind of distinction to try to make. And as I’m not a climate scientist, I’m not particularly well-positioned to weigh in on that, but my sense is our best understanding of the impacts of, say, climate change on things like drought is that it makes it relatively more likely to occur, so it increases the frequency, but may also increase the severity of droughts when they do occur. 

If you get a once-in-a-500-year drought or once-in-a-thousand-year drought, those are increasingly likely to occur more frequently. And that’s consistent with the evidence that we see in the case of Syria, but it still is complicated to say whether or not the drought was caused by climate change.

Now, setting aside that kind of question, which is better interrogated by climatologists and the like, the question of whether or not the Syrian civil war would have occurred if that drought had not occurred is of course an unknowable kind of question. But it seems clear to me, and having waded into the really rancorous scholarly debate about the role of climate change in the Syrian civil war, it seems clear to me that the drought increased stress on social, economic and political systems that were particularly poorly designed and poorly structured to address a large-scale climate-related disaster like this.

Whether or not we think that the Syrian drought was caused by climate change, I do think it’s safe to say that the drought exposed problems with the Syrian state and problems with Syrian society that were precisely the kind of weaknesses that would predispose that society to experiencing a civil conflict.

Ariel Conn: Can we look at societies and recognize those traits even if the society might appear relatively stable? I don’t have a strong grasp of recent Syrian history, but my understanding was that the country seemed to be mostly doing okay until this broke out. So I don’t know if my own understanding is wrong or if the problems had been well-masked.

Cullen Hendrix: Well, I mean, so this speaks to another kind of issue which is the general decline in the predictability of the at-risk countries for these large-scale episodes of political instability. In the immediate aftermath of the cold war, we had a pretty good idea of what the risk profile looked like for a country to experience something like a large-scale civil war.

So it was a relatively poor fledgling democracy with weak state capacity, with high levels of infant mortality and in a bad neighborhood — so, neighbored by countries that also experienced these kinds of conflicts. And that at-risk profile was the standard risk assessment that the intelligence community and groups like the Political Instability Task Force were using in order to guide their mental models and their thinking about what types of places to look for outbreaks of large-scale political instability.

The uprisings associated with the Arab uprising, or the Arab Spring, completely threw a lot of that received wisdom out of the window. For the first time in a while, we started seeing these large-scale instability episodes occurring in relatively highly consolidated, long-lived authoritarian regimes of the Middle East and North Africa. I think that you can talk about the relative weight that the drought in Syria had on exposing some of the frailties of these systems, but the frailties of these systems were exposed in other places by, say, their inability to address surging food and fuel prices in international markets and shield their consumers from those negative effects.

It seems that there is something that occurred around 2010 that amounts to a structural kind of break, if you will, in the types of countries that are part of this risk profile. Unfortunately, we’re at a point now where even seasoned risk analysts don’t necessarily have a great mental model or empirical model for trying to anticipate these episodes. We went from having a very defined risk profile for countries that would experience instability, to now we’re seeing really kind of convulsive episodes of instability in consolidated democracies like Chile, right? That’s going on right now, and so the world has become significantly more complicated. Whether or not that’s due to climate change, or whether or not that is a long tail response to the seismic events associated with the global financial crisis and the great recession, is anyone’s guess. But we are dealing with a very different reality in terms of the nature of geopolitical risk and political risk in the current context.

Ariel Conn: There’s a couple of areas I want to go right now, but you mentioned Chile. I don’t know the extent to which you’ve looked into the situation in both South America and Central America. Have you been looking into those much? Are there takeaways from that?

Cullen Hendrix: Yeah. There’s little doubt that climate change is having really adverse effects for small-scale farmers throughout the world. This is something that we’re seeing in the United States as well. It’s certainly something that is more potentially destabilizing in places like central America where incomes are so much lower, insurance mechanisms may or may not be present, and you overlay those kinds of forcings associated with climate change and the decline of agricultural livelihoods with gang-related and drug trade-related violence. It creates kind of a perfect storm, if you will, to drive this desire to migrate in search of better prospects for the migrants, but also for their families and for future generations.

Ariel Conn: You’ve brought up Boko Haram in Nigeria a couple of times. I want to come back to that quickly. To what extent does the conflict there fall into the drivers that we have been talking about? Could we have seen this coming — should we have seen this coming? And does that seem to have any connection to climate change, or is that just an example of conflict that we’re experiencing now?

Cullen Hendrix: I wouldn’t say that climate change is a main driver of the Boko Haram conflict in the sense that it’s motivating Boko Haram leadership, but I would say that climate change, and in particular the declining viability of agricultural livelihoods in Northeast Nigeria, is really contributing to a large pool of potential recruits into these kinds of armed activities.

So we know one of the best explanations for why people join violent organizations of a variety of kinds — everything ranging from rebel movements to street gangs — is a lack of other employment opportunities and a lack of secure access to livelihoods, food, and shelter. These organizations, whether or not they actually can deliver on their promises to offer these things, often make that part of their sales pitch. So if you go to Northeast Nigeria in the context of climate change, desertification, surging populations and the decline in the viability of traditional agricultural livelihoods, you have a large-scale unemployment problem.

Now, most of the people who are facing those kind of circumstances would never in a million years join up with such an odious group and their ideology. But it’s a small numbers game and you only need a fraction of that population to be interested in taking up arms and to respond to those types of mobilizations and those types of appeals. So I do think that there is a role for environmental change more broadly and climate change more specifically in affecting whether or not there is enough tinder that can be sparked or mobilized in the case of these kinds of armed actors. Climate change did not cause Boko Haram or the Boko Haram conflict, but it is probably complicating efforts to end that conflict.

Ariel Conn: Do you and perhaps the other experts on the paper worry that climate change could directly impact these drivers we’ve been talking about and thus lead to conflict? Or do you think it could be more sort of a straw that broke the camel’s back, where these tensions are existing and if only that drought hadn’t happened, maybe conflict wouldn’t occur — but because temperatures are rising and people aren’t able to grow the food that they need, that’s what pushed everything over the edge?

Cullen Hendrix: So I guess the basic question is whether or not this is sort of the threat multiplier that you’ve probably heard a lot about, or whether or not climate change and environmental change and degradation are themselves actual causes of conflicts. My answer to that question is that it can be both — and that in reality, it actually is both. I think that the threat multiplier argument makes a lot of sense and climate change is in effect loading the dice. It’s making certain rare outcomes like armed conflict a little bit more likely to occur in a variety of contexts, with the most significant impacts on societies at lower levels of economic development, higher levels of dependence on agricultural livelihoods, and characterized by weaker state institutions and high levels of intergroup inequality. So that’s how it relates to the findings of the paper. 

But we are also seeing, in the context of climate-related events like droughts, an increase in actual conflict over the underlying resources: for instance, an increase in cattle raiding or fighting over cattle in the Sahel, in particular in places like Kenya but also in Nigeria as well. And we’re also seeing these kinds of very direct conflicts over the actual resources at the local level.

It’s conceivable that we will also see these kinds of direct large-scale conflicts over transboundary resources like water or rivers moving forward; though even under climate stress, most conflicts or at least competing claims over access to shared resources like water are handled cooperatively as opposed to violently. But there is some research to suggest that increasing climate variability and increasing aridity in river basins is making conflict between countries in those basins more likely.

Ariel Conn: So far we’ve been looking more at countries that are in developing stages as opposed to developed countries, especially as you’re talking about the increased risk of conflict between countries. Do you still see that happening between developing countries, or do you worry at all that we could also see an increased risk between developed countries?

Cullen Hendrix: The most obvious sort of risk vector for conflict between more developed countries probably has to do with multilateral or global collective efforts to combat climate change in the first place, and then also to deal with some of the negative consequences associated with climate change, and relatedly, political instability. The most obvious example of that is the stress that the Syrian civil war, and the migrant crisis that that created in Europe, has had for patterns of cooperation and conflict between and within European Union countries.

It’s less that I’m concerned that you’re going to see this kind of armed conflict over these transboundary resources like rivers and things; I don’t think there’s going to be militarization of the Rhine, for instance, under climate change. But I do think that we’re already seeing really significant backlash in the domestic politics of many European countries moving in a much more rightward direction, and one of the plausible reasons for that is that they are responding to social changes that are occurring as a function of global migration. And in a world beset by climate change, those patterns of migration are likely to accelerate and increase in overall volumes moving forward.

Now, I don’t want to overly problematize migration because in the vast majority of instances, migration is a peaceful, adaptive, and beneficial strategy for addressing climate risk. But there are certain contexts in which it is proving to be politically destabilizing, and maybe undermining more general cooperation between countries, for instance, in the European Union.

Ariel Conn: I don’t remember my timing on this. Was Brexit influenced by the migrations that we were seeing as a result of Syria?

Cullen Hendrix: Brexit I think is a little bit of a different case because while it was driven by issues related to immigration, I think it had much more to do with immigration within the European Union. A lot of the discourse in the UK is about this kind of fictional Polish plumber who comes in and drives down the amount of money that native born plumbers can charge. From my perspective, I think that overly attributing something like Brexit to something like climate change is a bridge too far and it really runs the risk of overly, and in sort of a cartoonish kind of manner, securitizing the real links between climate and security outcomes, which are substantial enough that they don’t need to explicitly be tied into these really unrelated or tangential problems for them still to be consequential security outcomes and issues.

Ariel Conn: Okay. So far, everything is sort of based on — at least to a certain extent — what we’ve learned from the past. But how do we deal with these unknowns? We don’t know if global temperatures will only rise two degrees or if they will rise four degrees. How do you deal with that uncertainty?

Cullen Hendrix: Yeah. So obviously when thinking about the future in general, uncertainty really rules the day. And it turns out that climate scientists can say with a lot more certainty what the likely future physical impacts of climate change will be, than they can say what are the likely social impacts or human impacts of climate change moving forward. That’s simply due to the fact that human beings and human societies are incredibly innovative, and we’re also notoriously inept at foreseeing our future technological or social solutions to present problems. And what that means is that it’s very complicated and very difficult to know whether or not political, social, economic systems 50 years from now will respond to, say, a drought or an increase in mean overnight temperature of two degrees Celsius the same way that we respond to them currently, which is what we’re basing a lot of our projections on.

We’re just essentially saying, “How does the world react to the environment right now?” and assuming it will continue to react that way moving forward. If you think about this in a long enough timeline, it’s kind of a ridiculous assertion, right? Our livelihoods and our lives look nothing like they did in the 18th century, but nevertheless we are still trying to foresee what a world 100 to 150 years from now is going to look like. And if we reflect on the level of technological change that’s just occurred in the last two to three decades, probably the safest bet is to say that we have literally no useful idea of what the future will look like.

Now, having said that, we have to start somewhere. And so really smart people have put together this set of shared socioeconomic pathways as a way of thinking broad aperture about what the future is going to look like. And under a scenario in which we have four degrees of warming, it will mean that not only are we going to be facing a changed physical environment, but that we will, to have gotten there, had to continue with business as usual — meaning that we are likely to be experiencing those problems in a social context and global political context that is much more fragmented and even more fraught than the one we currently inhabit. And that’s enough to keep somebody up at night.

Ariel Conn: What did you and the other authors come away with, in terms of actionable steps that you would like to see presumably governments, but maybe other organizations as well, taking?

Cullen Hendrix: For a broad aperture kind of exercise like this, I think that most of the recommendations — to the extent that there are policy recommendations that come out of it — are pretty anodyne and pretty consistent with the more general admonition that we as a global community need to shoot for two degrees Celsius at the absolute upper bound and would be better off if we could get to a degree and a half.

That was true, however, before this expert elicitation provided evidence linking climate change to armed conflict; that’s something that we knew already. In terms of the practical effects for the policy communities, I think that this will actually have a pretty big impact, especially in developed and advanced economies, the way that their national security apparatuses and their intelligence communities think about longer term systemic risks and start to understand addressing climate change as an issue that affects not just their threat assessments, but also will affect their ability to meet their more general missions and needs moving forward in a sustainable way.

Amongst the practitioner community that’s most directly affected by the links between climate change and armed conflict, I think that this is just another additional piece of evidence moving them in the direction of thinking in a much more holistic way about sustainability — not just as good environmental practice, but as fundamental to securing national and human security moving forward.

Ariel Conn: So, I want to step back to the uncertainty question once more. As I’ve been interviewing various people, one of the things that I think has been most interesting and surprising are some of the little unknowns or unexpected side effects of climate change that we just aren’t really necessarily planning for yet: things like, as the weather gets hotter, you may not sleep as well and thus people are crankier. To what extent are you considering those types of unknowns when you’re considering the uncertainty with which climate might impact future conflict?

Cullen Hendrix: Yeah, that’s a really interesting question because for those of us social science nerds who are interested in mechanisms, it speaks to whether or not the relationship between climate change or warming and conflict is biophysical or biological — like literally, this is how our organisms respond to these changes in the environment — or whether or not it operates through more general effects on things like the economy or the structure of society, et cetera.

So, yeah, there’s now a large body of literature that links warmer temperatures to a variety of outcomes. Some of them are poor sleep; a really interesting one is that in baseball games, you have more hit batsman — you have more bean balls thrown on warm days than you do on comparatively cooler days. You have more opportunistic crime and violent crime that occurs at warmer temperatures than you do at compared to the cooler temperatures. And so all of this suggests that at least part of our response to a warming environment is biological or biophysical.

That implies that we need to think about some technological solutions to make our environments more livable, or at least less crazy, from the perspective of our biological responses to temperature stimuli. As an explanation for a large, complex conflict outcome like the Syrian civil war or the Nigerian civil war with Boko Haram, however, these kinds of biological explanations fall flat, because these biological explanations are looking at variation over really kind of narrow time bands and saying, “Okay, on a given hot day, this pitcher is more likely to be upset with the batter showing them up and therefore they might throw at them.”

Well, that’s a good explanation for why something might occur on a given afternoon, but it’s not a great explanation for why a young person would risk life and death to join a violent armed insurgency and then stay in that armed insurgency for a decade, in some cases. So there is an unknown: the extent to which this is biophysical or biological response versus operating primarily through the structure of the economy, economic opportunities, grievances related to government, responses to environmental change and drought, things of that nature. But that uncertainty, I think, is more fundamental when thinking about how climate change affects peoples or may affect people’s willingness to become members of these more kind of armed, durable groups.

Ariel Conn: So these are all the ways in which people could have more disagreement, more conflict, but one of the things that I thought was really interesting in your paper is that in a lot of these circumstances, history also sees communities actually cooperating more and working together more as opposed to turning to conflict. Is there a chance that we could actually see more cooperation?

Cullen Hendrix: I think yes, there is a chance that we could see more cooperation. I mean, one of the really striking things to come out of all this scholarship on the links between climate change and natural disasters and conflict is this idea of post-disaster resiliency. And you see very dramatic, very relatable, very human examples of this any time you see the way that communities come together in the aftermath of a flood or a tornado, even here at home in the United States, where you see this outpouring of civic mindedness and the recognition that we are all fundamentally experiencing this traumatic event together. And this can be a really powerful mechanism for bonding communities together and producing kind of a social dividend or social benefits that extend far beyond the scope of disaster relief.

It’s my hope that humanity is going to respond to climate change eventually — and in fits and starts, but eventually, we’ll recognize that this is an existential threat that we face in common and therefore will strip away a lot of the identities that drive us apart, and we’ll refocus our attention on our fundamental humanity in a way that can provide a basis for moving forward and overcoming this incredible challenge that we face. I’m betting long on humanity because I don’t yet think we’ve had our finest hour. I’m hoping that our finest hour comes in the context of addressing climate change.

Ariel Conn: I love that. I’ve got my fingers crossed for that as well. Is there anything else you want to add?

Cullen Hendrix: I think this is a really cool podcast. I look forward to listening in some detail to some of the episodes, but I really like this kind of — it’s not diet science, right? Like this is really trying to get into what it is that scientists know about these various phenomena and really exploring it in detail. So I just wanted to thank you for doing the homework and really digging into this kind of published peer reviewed research. It’s a lot easier to have one of your buddies on and just kind of bat stuff back and forth and have some laughs. So kudos to you for doing the real work.

Ariel Conn: Well, thank you so much. This has been much easier for me than the people writing the papers, I think.

Cullen Hendrix: Okay.

Ariel Conn: Thank you so much for being on the podcast.

Cullen Hendrix: My pleasure.

Ariel Conn: I hope you enjoyed this episode of Not Cool, a Climate Podcast. On episode 23, we’ll be joined by Brian Toon who will talk about the other climate change threat: nuclear winter.

Brian Toon: To have a real nuclear winter, which means that the temperatures at mid latitudes in green growing regions like Iowa or the Ukraine are below freezing every day for several years. That would be a real nuclear winter.

Ariel Conn: If you’ve been enjoying these podcasts, and if you think other people might as well, then please take a moment to like them, share them, and leave a good review.

Not Cool Ep 21: Libby Jewett on ocean acidification

The increase of CO2 in the atmosphere is doing more than just warming the planet and threatening the lives of many terrestrial species. A large percentage of that carbon is actually reabsorbed by the oceans, causing a phenomenon known as ocean acidification — that is, our carbon emissions are literally changing the chemistry of ocean water and threatening ocean ecosystems worldwide. On Not Cool episode 21, Ariel is joined by Libby Jewett, founding Director of the Ocean Acidification Program at the National Oceanic and Atmospheric Administration (NOAA), who explains the chemistry behind ocean acidification, its impact on animals and plant life, and the strategies for helping organisms adapt to its effects. She also discusses the vulnerability of human communities that depend on marine resources, the implications for people who don’t live near the ocean, and the relationship between ocean acidification and climate change.

Topics discussed include:

  • Chemistry of ocean acidification
  • Impact on animals and plant life
  • Coral reefs
  • Variation in acidification between oceans
  • Economic repercussions
  • Vulnerability of resources and human communities
  • Global effects of ocean acidification
  • Adaptation and management
  • Mitigation
  • Acidification of freshwater bodies
  • Geoengineering

References discussed include:

The oceans actually now, just in general, hold 70 times more carbon dioxide than the atmosphere.The modeling studies that have been done have projected out that the oceans actually could continue to absorb, even as the last fossil fuels are being burned. That’s a lot of carbon dioxide.

~ Libby Jewett

Ariel Conn: Hi Everyone. Ariel Conn here with episode 21 of Not Cool, a climate podcast. We’ve been talking a lot about the climate impact of carbon and other greenhouse gases in the atmosphere. But not only will carbon increase global temperatures, leading to rising sea levels and warmer oceans in general, but a significant percentage of the carbon emitted into the atmosphere ends up in the oceans, leading to major problems like ocean acidification. To talk about these issues today, we’ll be joined by Libby Jewett, who is the founding Director of the Ocean Acidification Program at the National Oceanic and Atmospheric Administration, also known as NOAA. 

Libby co-led NOAA-wide meetings of scientists and policymakers to conceive and develop NOAA’s first comprehensive ocean acidification research plan. She chairs the Ocean Acidification Interagency Working Group (under the Subcommittee on Ocean Science and Technology) where she helped develop an ocean acidification strategic research plan for the nation. And she is co-chair of the Executive Council of the Global Ocean Acidification Observing Network. She earned a Ph.D. in Biology with a focus on Marine Ecology at the University of Maryland, a Master of Public Policy at Harvard University’s Kennedy School of Government, and a B.A. at Yale University.

Libby, thank you so much for joining us today.

Libby Jewett: Thank you for having me.

Ariel Conn: The very first question I have for you, since this is an episode about ocean acidification, is how do you define ocean acidification? What is it?

Libby Jewett: Very simply, ocean acidification is the changing chemistry of the oceans that’s happening as a result of increasing levels of carbon dioxide in the atmosphere. The more we look, the more we realize that chemistry is actually very complicated. We think of changes in chemistry in the global ocean as version 1.0; that was our initial understanding of what was happening. And then as we began to look more closely at the coastal ocean, we realized that the variability is actually very high there. But that’s the basic idea, is that the ocean is taking up the carbon dioxide in the atmosphere that humans are putting there through the burning of fossil fuels, and that causes ocean acidification.

Ariel Conn: Maybe this is in my own head, but I sort of lump ocean acidification and climate change all into the same earth problems. And so I was wondering if you could just quickly explain what the distinction between the two is.

Libby Jewett: We explain ocean acidification and climate change by explaining that these are two phenomena that are happening as a result of increasing levels of carbon dioxide in the atmosphere. So the 20, 25% that’s going into the atmosphere is actually causing climate change, and that’s temperature changes and sea level rise, changes in weather patterns. All of those things are derived from increasing levels of CO2 being in the atmosphere. And then about 25% or so, up to 30%, is going into the ocean, and that is what’s driving ocean acidification. And then about 40% is actually taken up by trees and grass and other things on land. So we look at climate change and ocean acidification as actually distinct processes; however, they do interact because temperature change combined with ocean acidification will have impacts on marine ecosystems.

Ariel Conn: The breakdown of how much is going into the atmosphere, versus land, versus the ocean, is sort of interesting to me. Right now my understanding is one of the ways we’re saying that we’re trying to address climate change is we can plant more trees, or improve our agriculture, so that more carbon is absorbed into plants and back into the land. But we don’t want that happening in the ocean. So why is it bad in the ocean?

Libby Jewett: So, because of the chemistry of the interaction of carbon dioxide with water molecules, we actually have the increase in acidity that results by the oceans taking up CO2. However, there are plants in the ocean which are, and will be, benefited by carbon dioxide. They don’t live very long, the way you have long-lived trees, or forests, or jungle, that are actually sequestering carbon. In the ocean, the greatest amount of primary productivity or the generation of oxygen through photosynthesis is happening by micro organisms, algae and stuff. And the algae doesn’t live very long, and some of it sinks to the bottom and some of it sort of recirculates there. So you don’t have the sinks, at least, in the surface ocean. So therefore more of the carbon dioxide is actually interacting with the water molecules and thus causing this acidifying effect of the water.

But it’s actually a great question. I don’t think anyone’s actually asked me that exact question before.

Ariel Conn: Yay.

Libby Jewett: I’m thinking on the fly.

Ariel Conn: So actually I’ve heard that about algal blooms, that they absorb carbon initially, but then as they die off they’re very damaging.

Libby Jewett: Most, not all, because there are large phytoplankton blooms that happened in the big deep open ocean — and this was my work before I started working on ocean acidification. When they happen in more shallow systems — like Chesapeake Bay for instance, or Puget Sound, or even the Gulf of Mexico — the algae blooms get very prolific, and then they sink to the bottom where there’s less oxygen, and they decay down there. They use up actually even more oxygen, so you have these areas that are actually considered dead zones now. And in that process, they actually put out CO2 as well. So they’ve sucked up the CO2 in the surface, but then they die and go to the bottom, and then they emit the CO2. So now you have low oxygen and high CO2 in the coastal ocean.

And so when I talked about version 2.0 of OA, that’s where we’ve made a lot of headway I think. Although we still have more distance to go in terms of understanding that chemistry of the coastal ocean.

Ariel Conn: When we talk about the oceans absorbing carbon, is it more the plants within the ocean that are absorbing the carbon, or is it actually changing the chemistry of the water itself?

Libby Jewett: The latter.

Ariel Conn: Okay.

Libby Jewett: I’d say the majority of the carbon dioxide that goes into the water is just basically diffusing into the ocean. And as it does that, some of it will remain in the CO2 form, but most of it actually combines with the water molecules to create carbonic acid; that’s the favored direction of the chemistry. So carbon dioxide combines with water and creates something called carbonic acid. And it’s called carbonic acid because it almost immediately disassociates and releases a hydrogen ion. The increase in the hydrogen ions is what’s causing the increase in acidity, or decrease in pH. And pH is a measure of hydrogen activity.

Ariel Conn: Also, another quick chemistry review: can you remind us what acidic water is versus basic, and why the pH balance is relevant?

Libby Jewett: One thing we want to make clear when we talk about ocean acidification is that we’re not heading anytime soon, and probably ever, to the water being actually acidic. We’re right now in the global open ocean at about 8.1 on the pH scale. So basic, which is where we are now, is anything on the pH scale above seven; and then anything below is considered acidic. And when we talk about ocean acidification, we’re actually talking about a directional process. We’re acidifying the oceans, but we would be incorrect if we said that the oceans were acidic. I hope that’s clear. And it is something we struggle with in terms of communication of the phenomenon.

Ariel Conn: It seems easier to say ocean acidification than oceans, I guess, becoming less basic?

Libby Jewett: Right. So it’s not quite as catchy.

Ariel Conn: Right. So what is the impact of acidification on the animals and plant life in the oceans?

Libby Jewett: Our program in NOAA started up in 2011, but actually scientists at NOAA had been studying the phenomena for many, many years. The harbinger of dismay started occurring in the middle of the 2000s — about 2005 or ’06 — when shellfish industries along the Pacific Northwest coast started experiencing mass mortality in their hatcheries. And the oyster industry out there is very reliant on hatcheries for seed in order to grow up oysters for market. And when the hatcheries started experiencing this, originally they thought it was probably one of the many other stressors that they knew about — diseases and viruses, bacteria, maybe low oxygen. It was only when scientists at one of the hatcheries actually attended a lecture by one of our NOAA scientists, in which the NOAA scientist — Richard Feely — was talking about ocean acidification and what its implications might be, that he actually connected that what was happening might actually be a real life example of impacts of ocean acidification.

And they started from that point on measuring the carbonate chemistry in the hatchery water that was coming in — they just use natural water and phytoplankton that comes with it to feed their baby oysters — that they realized that the water was now, at certain times of the year, very corrosive and was having an impact, and causing mortality as a result. And over the past 10 years or so, we’ve actually been able to help them develop technology so they can monitor that and actually figure out how to approach it — which is, for them, putting buffer in the water in those times of year so that the oyster spat can grow. So that’s an actual specific example where impacts have been seen.

Beyond that, we’ve actually done quite a bit of experimental work on a whole range of species from phytoplankton to fish, and trying to see are there direct effects, are there indirect effects because of the food that they eat, on a whole range of species. And it’s not only us in the US but scientists from around the globe who are doing this work. And we’ve begun to piece together a story which says on the whole, we’re seeing the potential for a lot of negative effects. There will be winners and losers, and as I said before, there are going to be some phytoplankton that are benefited by carbon dioxide in the water, and then whatever eats them obviously would be benefited as well. But then there are going to be others that maybe won’t be so affected, and then there are going to be a whole range of species that will be negatively affected over time.

Ariel Conn: The one that we hear the most about, or at least the one that I’ve heard the most about, is the reefs. How long have we been tracking that?

Libby Jewett: Well, through the NOAA program, we’ve actually been monitoring through something called the National Coral Reef Monitoring Program for probably 10 years, maybe a little bit less. As we became aware of the importance of monitoring the carbonate chemistry for any shell-building organisms, we’ve been trying to monitor that on reefs. I will say that OA is only one of the problems that reefs are encountering, and temperature and bleaching is a much larger effect — and of course that’s being caused by climate change, our related twin stressor.

Ariel Conn: I guess I didn’t realize that. I thought the bleaching was an effect of the acidification. But that’s not the case, it’s the temperature?

Libby Jewett: Yes.

Ariel Conn: Okay.

Libby Jewett: Now, the extent to which ocean acidification may be an underlying stressor that makes reefs more vulnerable to bleaching — that’s a hypothesis that’s been thrown around, but it’s not really one that’s been proven yet. The research has focused on looking at corals’ ability to keep up with sea level rise, and keep the structure intact that they are — the complexity of coral reef structure, keep building that up. Because all the time, just through natural processes, coral reefs are eaten by fish, and dying, and regrowing, and I mean they’re very vibrant, dynamic ecosystems. And one of the things that has been shown in laboratories is that the dissolution of the carbonic structure of reefs, which is the core component, is likely increasing over time as a result of ocean acidification. So it’s just that much harder for them to keep themselves whole, I guess.

And as a result of that, we actually have an increase in bioerosion, which is other organisms coming in and being able to drill down into the coral skeletons, because they’re less strong than they were before. But it’s all very hard to tease out, because it’s of course happening simultaneously. And you have the bleaching on top of that.

Ariel Conn: And sorry, were you saying that rising sea level also is negatively impacting that, or did I misunderstand?

Libby Jewett: Well, because the seas are rising, in order for corals to keep within the photic zone, which is where they need to be — part is their reason for existence is they have those zooxanthellae in their tissues that are photosynthesizing. So those are little micro algae that photosynthesize and support the growth of the coral, on top of the coral also eating zooplankton out of the water column. They’re so interesting, fascinating. But in order for those zooxanthellae to work, they have to be within a certain distance of the water surface, and solar radiation that reaches them through the water. And if the sea levels rise and they’re not able to keep within a certain distance of that, then they could be negatively affected over time. There’s a lot of different forces at play.

One of the areas of study right now — or a couple of areas of study — are, one, identifying areas around the globe, coral reefs out in the Western Pacific, or perhaps in the Caribbean, who seem to be actually thriving, and otherwise seem to be resilient to ocean acidification, because perhaps they’ve grown up in a little embayment where either temperature or pH has been stressful for eons. Just naturally, because of those conditions that I was talking about before where local conditions can affect the local waters.

And so, identify those groups of corals that are resilient — and there are resilient corals out there. So that’s actually very helpful. And in the Caribbean, which has actually been hit even harder by bleaching than even the Western Pacific, we’ve been looking at areas that are pretty stressed close in coastal region — some even in the port of Miami, where you would think no coral could live; and there are corals there — and looking at them and trying to think about could we use these to restore other reefs that have been otherwise damaged either by bleaching, or ship strikes, or something. And because these seem to be a resistant breed of coral, using them as restoration target. So there are pockets of hope.

Ariel Conn: Yeah. You’ve mentioned a couple of times now some solutions that people are looking at, and I’m going to want to come back to that; that’s definitely one of the big questions that I have. But first, where you’re talking about some corals are more resistant than others: how are we seeing variations in the impact of ocean acidification, and I guess temperature increases, around the world? Are there places that are less affected? More affected? Or is it pretty evenly spread around the globe, and it’s just regions where the animals were already stressed that they’re able to adapt?

Libby Jewett: The entire ocean is in contact with the atmosphere. And so there’s the global phenomenon of ocean acidification because of that. The atmosphere is pretty well mixed. As CO2 goes up in the atmosphere, it’s taken up by the ocean. However, that rate of uptake is variable because for one, cold water can hold more gas than warm water. So we’re obviously more worried about our polar regions for that reason. They actually just naturally have higher CO2, and they’re sort of reaching some threshold, perhaps, because of the increased level of CO2. And on top of that, in the Arctic we’re losing ice. And ice was a barrier between the atmosphere and the ocean — and now there’s more of the Arctic that’s open, which makes it more permeable to that CO2 going in.

So one, we have lower pH in our polar oceans — but again, that’s somewhat variable. We have upwelling regions; so when I talk about the Pacific Northwest, if you get to understand more of the oceanography of the global ocean, there are regions around the ocean where deep water — which has actually been out of touch from the atmosphere for, could be 50 years, could be a thousand years — is actually upwelling to the surface. And this happens in a few distinct regions, and the Pacific Northwest happens to be one of those. And because that water was in touch with the atmosphere, in the case of the Pacific Northwest, around 50 to 75 years ago, it actually was taking up CO2 levels that were in the atmosphere 50 to 72 years ago and is now upwelling along our coast.

So it’s actually an upwelling of CO2 levels that are greater than what you would see in the surface ocean, and also enhanced by what it saw when it subducted. And I won’t go into a whole lot of detail, but suffice it to say the oceans aren’t all uniform. So you have these upwelling regions, you have polar regions. And then you have the tropics, which, from our modeling exercises — unlike the poles, they’re actually very saturated in what we call calcium carbonate. And I haven’t even gone into all of that chemistry, but that’s what basically disappears as the pH changes. And that’s what shell-building organisms need to build their shells. That’s kind of a simplified way of approaching it. But the tropical oceans are very saturated, but they’re also changing the fastest in terms of the changing carbonate chemistry, because they’re warmer and they take up more CO2. So that’s worrisome.

And then we have what’s going on in the global ocean. They’re more or less acidifying in the global ocean, because there’s less complicated biology there, at a fairly steady rate. And then you have, very close to shore, estuaries where the carbonate chemistry is even more complicated. I would say we’re still trying to get a handle on exactly how atmospheric CO2 is affecting estuaries, because they actually are, in many cases — like at the mouth of a marsh — will be sources of CO2 to the atmosphere, because there’s so much decomposition happening within those regions. I mean, just think of that marshes, and there’s a lot of material in the water. That CO2 — because the atmosphere now has relatively, to that water, less CO2 — the CO2 actually off-gases. So it’s very complicated, but that differential will change over time as there’s more CO2 in the atmosphere. So that will actually over time affect that system as well.

Ariel Conn: Okay. Is there a maximum amount of CO2 the oceans can absorb?

Libby Jewett: Actually, no. The modeling studies that have been done have projected out that the oceans actually could continue to absorb, even as the last fossil fuels are being burned. That’s a lot of carbon dioxide. And the oceans actually now, just in general, hold 70 times more carbon dioxide than the atmosphere. So they’ve actually provided a service to the planet, because they’ve taken up the carbon dioxide that maybe would have stayed in the atmosphere. But the people who study this — and I’m actually not a carbon chemist, I just pretend I’m one — as they take up more carbon dioxide over time, the rate of uptake will decrease, because they just become full of carbon dioxide. There’s a bunch of different processes that happen, but they’ll keep taking it up. The rate will diminish over time.

Ariel Conn: So you’ve mentioned stuff happening in the Pacific Northwest a couple of times. Is that more because that’s a region that you’re personally working on? Or is that region interesting for some reason, as opposed to the Atlantic coast of the US, or the California coast?

Libby Jewett: I think one of the motivators for Congress passing an ocean acidification law, which they did in 2009, was what was happening in the shellfish industry in the Pacific Northwest. So it’s just an example of economic repercussions of this phenomenon. So it seemed like a natural place to focus our initial attention, but we’ve since expanded out. NOAA actually has a laboratory in Seattle, which is handy: the Pacific Marine Environmental Lab. And they have been very involved in leading the science on OA, leading the open ocean and also now even the coastal ocean understanding.

As the NOAA program, one of our responsibilities is long-term monitoring of ocean acidification around our coast. So we have moorings, and ship cruises, and autonomous vehicles, and underway systems, which we put in ships that are doing other activities, happening around all of our coasts and out into the remote Pacific islands, on routine periodic survey. So we’re trying to cover all the bases with the resources that we have, to try and track this phenomena over time.

Ariel Conn: So since we’ve started talking about the NOAA ocean acidification program that you’re running, why don’t we keep going with that? What all are you guys working on?

Libby Jewett: We have a multifaceted program. As I said, we’re very focused on ocean observation, so we do have that long-term monitoring program; but we also do research on impacts of ocean acidification on a whole range of species of fish, and shellfish, and crustaceans, and you sort of name it. Anything that’s related to either commercial or recreational fishery species around the US — we’re trying to do work on that. And that both in partnership with academic institutions and through our NOAA fisheries science centers, which are our laboratories that are all around our coasts and in the Pacific islands.

The basic aim, I would say, is that we’re trying to get at understanding the vulnerability of our marine resources — and the humans that rely on them — to ocean acidification. So we do work monitoring, understanding the stress that species are experiencing, or will experience; and then doing actual laboratory experiments, or sometimes in situ experiments, on the species to figure out their response. And then looking at human communities as well: for instance, we funded a project that’s working with four tribes in the Pacific Northwest, to try and look at their reliance on coastal ecosystems and figure out what we know about those species that are culturally important to them. And we hope that that will help inform the research that we do in the future, and what adaptation strategies we might help develop for those communities. So it’s sort of the gamut from socioeconomics all the way back down into the ocean and how the chemistry is changing.

And I will say, so when we first started this work, when we founded the program in 2011, people were doing experiments and they were using treatments that were really based on open ocean levels of ocean acidification. And that is actually, as I said, very different than what happens in the coastal ocean. And so by doing this monitoring more locally to where the species actually live, we’ve over time been able to develop more appropriate treatment, so that we know that the results of the experiments that we do are actually showing what we think are the vulnerabilities in the future.

I think it’s a good robust approach. And we work, again, with academic institutions; we also are part of leading a global effort called the Global Ocean Acidification Observing Network. We helped found that, and it’s been around since 2012. And we now have over 700 scientists from 93 countries that are part of the network, and they really look to NOAA and the US, really, to help define and lead the research, and help them have the capacity to do the monitoring they may need in Africa, or Latin America, or small remote Pacific islands. So we’re very excited and proud about the leadership we’ve been able to show on that.

Ariel Conn: Why is it so important for us to understand this? We can see that it impacts local coastal communities, but why is it so important for all of us to understand and be concerned about ocean acidification?

Libby Jewett: We need to know what impact we’re having on the ocean. I mean the ocean is important, not only because of the seafood that we eat from it, but because it’s a driver of larger processes on the earth. And every other breath, they say, that we breathe comes from phytoplankton in the ocean. So the fact that we might be having this negative impact, that we might in some cases be able to remedy through local approaches. In the case, for instance, of the Pacific Northwest, where those hatchery failures were happening, we didn’t know what the phenomena was at first and we didn’t know what to do. But as that became clear over time, we actually brought that industry back from the brink.

We can’t manage what we don’t understand. And so by understanding this phenomenon is happening — we don’t know exactly what all those adaptations might be. But I think as our population is growing, there are more and more people living at the coast, there’s more reliance on food protein from the sea. I would say in the US, maybe because we’re a wealthier nation, maybe we have more flexibility to switch to other protein sources. But a lot of places around the world don’t have that flexibility. And so trying to provide them, equip them with the resources that they need to understand what this phenomenon is and how they might adapt to it — anticipating that, at some point, we will bring emissions down to zero, and the oceans will begin to basically off-gas.

We need to understand it to be able to forecast it, to be able to buy time, to be able to prepare communities for the changes that are coming. I think it’s better to know than not to know.

Ariel Conn: Are there ways to try to actually address ocean acidification? Or can we just try to help marine life adapt?

Libby Jewett: The big solution is to reduce CO2 going in the atmosphere, and to bring emissions to zero eventually. I think that is the large solution. That’s the solution for climate change; that’s the solution for ocean acidification as well. However, again, as we understand more what is driving species change, what their physiology is, what the responses are, new techniques may become apparent to us. And one of the things that we do know is that plant life does take up CO2. It takes it out of the water  We talked about that before. So phytoplankton does that, seagrasses do that: they sequester carbon. That’s how they’re thriving. They’re putting out oxygen and taking in CO2.

There have been, and there continue to be, investigations into how we could use those natural approaches to pull CO2 out of the water around other pieces of the ecosystem that might be more vulnerable. For instance, can we support the growth of seagrasses close to coral reefs that we’re trying to protect? And does that do enough to reduce the CO2 around them to enhance their grip? And there’s some indication that corals that are around seagrasses actually do do better; but seagrasses are also hard to keep going with all of the changes happening. So I think we’re going to see more and more effort being focused on those kinds of approaches, to understand from a research perspective how to approach that.

For shellfish as well, I mean we at least for the moment have figured out options for hatcheries — but those are enclosed systems. What happens next is that they take those oysters and they actually plant them out on the flats where they can be naturally growing and eating phytoplankton. What we can do in that case might be that we need to be growing kelp alongside the oysters. And this has actually been done for eons: in China, for instance, they do a lot of multi-trophic shellfish aquaculture, I believe. In their case, and what we’re increasingly looking at is, can we harvest both the kelp and the oysters so that they grow side by side, and then you pull the kelp out before it starts decomposing at the end of the season. Or finally, should we be trying to put oyster shells back into the systems where we take the oysters out — because when they’re in that system, they’re actually creating some buffer as they break down.

There are some rules about that, and you obviously worry about transmission of viruses and stuff. So if suddenly you’re eating oysters on the East Coast that were harvested on the West Coast, you may not want to put those shells in the water, because they might actually bring something new to the Eastern oysters that they hadn’t seen before. So you have to be careful about the approaches; that’s why you need to do some research around these options. But these are all very local, but they’re also very valid. It seems overwhelming and sad that we’ve gotten to that point, but at least we’re embracing the task.

Ariel Conn: So one of the things that I’ve heard, I think for sea level rise, is that planting mangroves more along coastal areas can help protect the inland coastal regions a little bit more. Does that have any impact on the acidification levels?

Libby Jewett: If I’m remembering correctly, there have been some studies in the Caribbean that have looked at ocean acidification parameters in and outside of mangrove areas, and the pH is actually higher amongst those roots that are sitting down in the water for mangrove. So yes, I think that is a double win there because it’s protecting communities, creating habitat for fish, and also has this environment that’s more healthy, I guess. There have been studies that have actually shown that in some of the mangroves, they’re beginning to see corals that have migrated in. It may have been that they weren’t really looking at this in the long-term, but it seems like it’s becoming a novel habitat where it’s actually cooler under the mangroves, and the pH is more amenable. We may see these shifts in habitats that we hadn’t really considered viable before, and that’s where nature is just doing its own thing without us having to assist it.

Ariel Conn: These are starting to seem like almost magical plants.

Libby Jewett: Right.

Ariel Conn: So coming back to sort of broader questions about ocean acidification: is it actually only just oceans?

Libby Jewett: In fact, freshwater bodies are also just as in touch with the atmosphere as the oceans are. Some monitoring work has been done in the Great Lakes. And the prediction is that basically the Great Lakes are, and will be, acidifying at the same rate as the open ocean. NOAA, I guess I should say, is not responsible for long-term monitoring the lakes. That’s actually more of an Environmental Protection Agency and a US Geological Survey responsibility.

One thing to keep in mind is that the Great Lakes, and also a lot of northern lakes, were very affected by acid rain. And a lot of the original research on effects of lowering pH on organisms came out of that period when industries were emitting those sulfur compounds that were causing acidification, in the same way that CO2 is doing it on a global scale. And so obviously, industries installed scrubbers and they weren’t emitting that any more and the lakes were able to rebound to a certain extent. So there is a precursor insight into the future story there that I think we need to probably keep in mind.

Ariel Conn: So in the time that you’ve been looking at ocean acidification, what has surprised you?

Libby Jewett: So one of the pieces of research — and this wasn’t even work that we did in NOAA; this was originally work that came out of Australia — was work done on clownfish. They determined that fish exposed to high CO2 levels actually had an impact on their neurotransmitters. And so that would be clownfish being attracted to their predator, instead of swimming the other way. Now, whether they adapt over time, and maybe those fish that are attracted get eaten and then the ones who are resistant — there’s a lot of variability in biology. That is the good story, right? That there’s potential for acclimation and natural selection. 

Ariel Conn: Is there anything else that you think is important to cover that we didn’t get into?

Libby Jewett: Can I touch on geoengineering for a second?

Ariel Conn: Yes.

Libby Jewett: That was a topic of interest definitely in the last year or so, and I just want to make the point that a lot of the geoengineering solutions that people are talking about, which are more focused on keeping the temperature of the planet cooler, and putting things up in the atmosphere that might reflect back the solar radiation that’s incoming. I think it’s sort of obvious, but it’s also important to point out that that’s not going to do anything for ocean acidification. Because unless we reduce CO2 — unless we figure out, maybe from a geoengineering point of view, how to take CO2 out of the atmosphere — or at the very least reduce our emissions to zero, we’re not going to have an impact on ocean acidification. Now temperature’s very important to focus on as well, so I’m not necessarily saying not to do that, but just we need to know that we’re still going to have ocean acidification happening.

Ariel Conn: Yeah, that one seems good to know. Are there efforts underway to do the equivalent of geoengineering for ocean acidification?

Libby Jewett: Not that I’m aware of. Years ago though — and I haven’t seen any recent literature on it — there were some thought experiments on what it would take to buffer the ocean, which would basically be mining limestone on land and spreading it over the ocean. And the long and short is that we determined that the amount of energy that it would take to actually do that would defeat the purpose. You can maybe do it, as I said, like putting oyster shells back in local embayments. You could do it on a very local scale, but trying to do that on a global scale.

So I will say, however, the earth is doing it naturally itself. So if we were not emitting at the rate that we’re emitting, and the levels of CO2 were going up over millions of years — instead of tens and hundreds of years — the earth has the capacity to buffer the oceans through the weathering of limestone and other substances, through those rivers that we were just talking about. So as they are making their way over land, they’re taking buffering substances with them into the ocean. We’ve seen events in the geological history where there’s been increase in CO2, but even when there were massive increases in CO2, we’re fairly certain they were happening over millions of years. And so the pH was not as diminished. But even then we actually were seeing some massive extinction. So it’s not great. It’s not a great story.

But the long and short is that the earth has a capacity to heal itself. And so if we can bring emissions down, and really bring them down to zero, we’re still going to look at temperature change, sea-level rise, but eventually the earth will come back into equilibrium at the pre-industrial levels because of that system that I talked about, the cycle. So that is good news, but it’s a long time away and it’s better to stop now because if we stop now — it’s like a car going really fast — if it stops, it’s still going to skid for awhile. It’s better to stop now and have that skid now rather than getting going really even faster. Then the recovery is even going to be longer.

Ariel Conn: All right. So, on that note, what gives you hope?

Libby Jewett: Well, I do feel like humans have a capacity for transformational change. I think my kids would be okay with me saying this: I will say that both of my children actually work in solar energy now. So I feel like I said the right things over time and influenced them that that was the way to make a difference. And there was actually an article in the New York Times by Al Gore, in which he was pointing out that even from an economic point of view, the number of solar installer jobs is growing faster than any job in the US — or maybe on the planet, but definitely in the US. And the second one is the number of wind turbine installers. So there’s a win-win here, in that there’s economic potential. But we need to make sure that these transformational changes to renewable energy are happening even faster than they’re happening now. I am hoping that we can do that. We have to. So we will. The political environment is in our favor around the globe, and that’s it. It’s the future.

Ariel Conn: I like the, “We have to, so we will.” All right. Well, I think that’s it for me. Is there anything else?

Libby Jewett: No, this has been a pleasure. I hope that I haven’t been too raving and long-winded.

Ariel Conn: No, this was great. This was great. I really enjoyed it. This is one that I’ve personally been interested in learning a lot more about, so I really appreciate you taking the time to talk with us today.

Libby Jewett: My pleasure. Thank you so much.

Ariel Conn: I hope you enjoyed this episode of Not Cool, a climate podcast. On episode 22, we’ll be joined by Cullen Hendrix who will talk about his work looking at the potential for climate change to increase the risk of armed conflict.

Cullen Hendrix: The world has become significantly more complicated. Whether or not that’s due to climate change, or whether or not that is a long tail response to the seismic events associated with the global financial crisis and the great recession is anyone’s guess. But we are dealing with a very different reality in terms of the nature of geopolitical risk.

Ariel Conn: I hope you’ll join us for the next episode, and as always, if you’ve been enjoying these podcasts, please like them, share them, and maybe even leave a good review.

Not Cool Ep 20: Deborah Lawrence on deforestation

This summer, the world watched in near-universal horror as thousands of square miles of rainforest went up in flames. But what exactly makes forests so precious — and deforestation so costly? On the 20th episode of Not Cool, Ariel explores the many ways in which forests impact the global climate — and the profound price we pay when we destroy them. She’s joined by Deborah Lawrence, Environmental Science Professor at the University of Virginia whose research focuses on the ecological effects of tropical deforestation. Deborah discusses the causes of this year’s Amazon rain forest fires, the varying climate impacts of different types of forests, and the relationship between deforestation, agriculture, and carbon emissions. She also explains why the Amazon is not the lungs of the planet, what makes tropical forests so good at global cooling, and how putting a price on carbon emissions could slow deforestation.

Topics discussed include:

  • Amazon rain forest fires
  • Deforestation of the rainforest
  • Tipping points in deforestation
  • Climate impacts of forests: local vs. global
  • Evapotranspiration
  • Why tropical forests do the most cooling
  • Non-climate impacts of forests
  • Global rate of deforestation
  • Why the amazon is not the lungs of the planet
  • Impacts of agriculture on forests
  • Using degraded land for new crops
  • Connection between forests and other greenhouse gases
  • Individual actions and policies

References discussed include:

There’s plenty of reasons why we want to keep forests. They regulate the hydrological cycle. They tend to minimize flooding; they manage flows in rivers. They are kind of like a sponge, so they take up rainfall or snowfall and then they trickle it out slowly, so that it’s available for us or ecosystems or agriculture.

~ Deborah Lawrence

Ariel Conn: Welcome back to Not Cool, a climate podcast. I’m your host, Ariel Conn. Today’s interview is one I’d been looking forward to for a while. To be clear: I have loved every minute of every interview I’ve done for this podcast, but trees hold a very special place in my heart. They can grow so tall, live so long, purify our air, positively impact our climate, improve our moods, they’re just generally awe-inspiring, and that doesn’t even get into the science of how they grow, thrive and possibly even communicate with each other. The more I learn about trees, the more amazed I become. So, I’m very excited that for episode 20, we’re joined by Deborah Lawrence, who will talk about the impact of forests on climate change, along with the impact humans have had on forests. 

Deborah is a Professor of Environmental Sciences at the University of Virginia, where her research focuses on the ecological effects of tropical deforestation. She has spent the past twenty-five years doing field-based research in Indonesia, Costa Rica, Mexico and Cameroon. She and her students conduct interdisciplinary research with partners in economics, anthropology, geography and hydrology to understand the drivers and consequences of land use change.

Focusing on tropical forests and climate change, she participated in the international negotiations of the United Nations Framework Convention on Climate Change (UNFCCC), she supported the US delegation to the World Bank Forest Carbon Partnership Facility and Forest Investment Program, and she was part of several inter-agency missions on reducing emissions from deforestation and degradation (REDD+) in Indonesia and Southeast Asia. 

Deborah, thank you so much for joining the podcast.

Deborah Lawrence: Glad to be here.

Ariel Conn: Pretty recently in the last month or so in the news, the Amazon rainforest was getting a lot of attention because it was burning — very, very significantly. So before I get into any other questions I have for you, I was wondering if you could just give us an update of what’s going on in the Amazon this year. Why were the fires so big? How do they compare to previous years? Why is this so bad?

Deborah Lawrence: Okay. The Amazon burns every year, so it’s not really new — but there were more fires this year, and significantly so. I don’t think it’s twice as many, but I think it’s high. So the question is, what does that mean and why is it happening? The reason it happens is because people are trying to cut the forest to either grow crops like soy or to create pastures for cattle. So these are big worldwide commodities. This is a major activity of the Brazilian Amazon for sure.

The question is, why would it spike this year? And I think the answer is not some quirk of climate. It’s not because it’s a super hot year. It’s because the president of Brazil has indicated that he is not going to be enforcing the existing laws that protect the Amazon. So that sounds kind of strong. But he has indicated that he is not really that concerned that the Amazon remain intact. He sees the Amazon as an incredible resource for Brazil, and he is interested in using that resource to advance the economic development of the country. That is a change. Formerly, the leadership has felt that the Amazon was important as a block of forest, and in fact respected the many laws that they had created over the past decade or so to protect it. Some of those laws are really quite progressive. They give rights to indigenous people to manage forests, and they promise that ownership is true and protected by the government.

So the wonderful thing about these laws that they created over the last 10 to 15 years is that they have dramatically reduced deforestation in Brazil. The increase in fires has to be taken in the context of the fact that there had been really an incredible success story in the Amazon over the past decade. Deforestation had come way down. So even though this year there’s a lot of fire, it’s not as bad as it was 10 or 15 years ago; not nearly as bad. What I think of when I think of the Amazon burning is this is just a harbinger of things to come. It’s not suddenly a problem. It’s the fact that it looks like it’s going in the wrong direction.

Ariel Conn: That’s actually really interesting, because I definitely remember for quite a while hearing about how we have to save the rainforest — and there was lots of news about it, lots of coverage, and then that sort of seemed to go away. So it sounds like maybe a lot of these laws had been to address that, and were working.

Deborah Lawrence: I think that’s the case. Now, the rainforest doesn’t just exist in the Amazon. There are really important forests throughout the tropics, and we still need to save the rainforest. There’s still a lot of threats to the rainforest. In southeast Asia they grow oil palm, and they do that by clearing rainforest. In central Africa they are putting in pastures and they’re also expanding oil palm, and in the Amazon they’re expanding oil palm. So there’s still a reason to worry about the rainforest, but things had indeed been getting better.

Ariel Conn: You mentioned some of these other forests. I guess maybe before we get to those — because I want to ask about them as well — why do we care so much about the Amazon, and also just how big is it?

Deborah Lawrence: So the Amazon is 2.1 million square miles.

Ariel Conn: Wow.

Deborah Lawrence: Yeah, that’s pretty big. It has pieces of French Guiana, Suriname, Guyana, a tiny bit of Venezuela, Colombia, Ecuador, Peru, Bolivia, and Brazil. It touches all those countries.

Ariel Conn: But it’s primarily in Brazil.

Deborah Lawrence: Brazil, Peru, and Bolivia, yeah. But mostly Brazil. That’s why we talk about Brazil.

Ariel Conn: Okay. So their policies have changed recently, but it sounds like that’s very short-term thinking because everything I hear is that the Amazon plays a major role in our climate, and so if we’re not taking care of it, not only does it affect the whole world, it’s still going to also negatively impact Brazil. Is that true?

Deborah Lawrence: That is true. The way we understand the importance of the Amazon is partly by using models to explore what happens when we take it away. You have to believe that a model can capture the dynamics of this very complex ecosystem and climate system, and they do a pretty good job. And you also look across many models to try to understand what happens if you take out the Amazon.

I think some of the most interesting work has been to look at what happens with the progressive deforestation of the Amazon: 10%, 20%, 30%, 40% gone. And what you see is that across different models with different modeling groups, it looks like there is some kind of tipping point at which you go from a system that it is stressed but still a rainforest to a system where suddenly it’s really much hotter and drier. And so even though you haven’t deforested the rest of the Amazon, you end up with a different kind of forest because it’s stressed out. It’s dryer and it has higher mortality, so it goes from something that looks more like a rainforest to something that looks more like a scrubby savanna.

There’s the notion that these tipping points can occur because of internal dynamics in the system. We’re not talking about climate change. We’re just talking about what I call the other climate change: the fact that when you cut the forest down, you affect the climate system right there, and you also affect the climate system elsewhere.

Ariel Conn: I’m going to come back to this idea of tipping points, but first, can you talk about the different impacts different types of forests have? If it’s not a rainforest, it’s having a different impact. In Colorado, I see lots of forests, but it’s obviously a very different type of forest than a rainforest.

Deborah Lawrence: Right.

Ariel Conn: So what’s the different impact on the climate?

Deborah Lawrence: Fundamentally, there’s two types of ways that forests affect climate. One is through their impact on the carbon cycle, meaning how much carbon do they store in their biomass, in their soils? Because forests take up CO2 through photosynthesis. They’re one of the ways that we get rid of the excess CO2 that humans add to the atmosphere — it’s through uptake of these forests. So one way to evaluate different types of forest is to say, well, how much carbon does it hold? How much carbon does it draw down every year? And on that metric, tropical forests are phenomenal. They take up so much carbon. There are some rainforests in the northwest of the United States; they also have high carbon. So rainforests everywhere have high carbon concentrations. Almost any other forest you have just doesn’t have as much carbon in it. So there’s the carbon story and there are some high carbon forests in the northern hemisphere, but taken as a whole, most of the carbon rich forests are in the tropics.

The other way that forests affect climate is through what they do to the balance of energy and water. And there’s sort of two things that happen. The sun shines down on a forest, and the forest has to do something with the energy. If it absorbs it, which most forests do because they’re quite dark, it has to do something with the energy. It can radiate it back as heat, or it can use that energy to transform water from liquid to vapor. And it does that by sucking water out of the roots, up through the leaves, and then out to the atmosphere. And when it leaves the leaf surface, it’s no longer liquid water — it’s vapor. And that process cools the atmosphere right above the forest; it also changes the energy balance there so that the dynamics of the atmosphere above the forest change.

So you might’ve heard about atmospheric rivers. These rivers are basically descriptions of the fact that the atmosphere has these circulation patterns in it, and that one of the ways that that circulation pattern is defined is based on what the plants are doing below that atmosphere. Trees move a lot of water, so even though they absorb a lot of incoming radiation, they take that and they turn it into water vapor. They change the energy form, they change the water cycle, and they actually turn that energy into something else, into latent heat. So it’s kind of wonderful that these forests, where there’s so much incoming solar radiation at the tropics — they take a lot of that and instead of turning into heat, they turn it into something that cools locally and eventually can cool further away.

Ariel Conn: You were talking earlier about how the forests impact the local climate, and I’m guessing this is what you were referring to?

Deborah Lawrence: Correct.

Ariel Conn: How far does that spread then?

Deborah Lawrence: Well, there’s another layer here. All forests tend to be dark, and all forests have the capacity to move a lot of water. It’s evapotranspiration. Whether they do that depends partly on where they are on the planet. It turns out that the forests respond to incoming solar radiation differently, and the further north you go — like up past the temperate zone into the boreal forest — those forests tend to absorb radiation and just hold it. Forests in the far north actually warm the planet. In the temperate zone, it’s a mixed bag; some forests are more warming and some forests are more cooling. But in the tropics, forests are really cooling.

The interesting thing is that when you put forests into the high north, like the high latitudes, they will actually absorb more heat and warm the local area, and because they mask the snow, they actually change the reflectivity of that whole area. They make a light surface with no trees into a dark surface that blocks out the snow. So what would have been a very reflective place, and very cold, suddenly is much warmer. In the boreal zone, those forests then not only warm locally, but through a lot of feedbacks with the ice and snow and the oceans, they send that warming around the globe.

The corollary is when you take forests away in the boreal zone, boy does it cool the planet down. Because they have so much snow cover, and ice, and those feedbacks that connect changes on the land to changes in the ocean, you get a really strong cooling. So it just shows how powerful those forests are in the far north. And again in the temperate zone, there’s a lot of variability in exactly what latitude forests go from being a net cooling to being a net warming. Just depends on the study. So there’s still work to be done to understand exactly whether those forests are generally warming or cooling for the planet.

However, ironically, the very local impact of forests is always cooling locally. And this might sound like it doesn’t make sense: how can you have local cooling but then global warming? And it’s because there is still that cooling effect of evapotranspiration in the summer. So if you think about where is it going to be hot in the future, it’s going to be hot everywhere in the growing season. So in the growing season it’s a great idea to have a forest nearby, because during the growing season evapotranspiration is high. They’re moving a lot of water because they have a higher level of incoming radiation, and they actually can get some cooling. But in the winter, in the spring, those same forests with their same forest cover — they end up warming.

So you can have this effect of, it’s good to have the forest in the summer when it’s hot because it’ll keep you cool, but in the winter and spring when you expect to get a bunch of cooling for the whole planet, you don’t get that cooling. You get warming. So for the local planner, they probably want to worry about extreme heat in the summer, so they probably want that forest. And that effect is true for everywhere. It’s just that that balance between a local effect and a global effect changes depending on latitude.

Ariel Conn: I want to go back real quick to something you said. Did you say that removing the boreal forests causes global cooling? Did I understand that right?

Deborah Lawrence: That is what the models show, that if you were to just get rid of all of the boreal forests, it would cool the planet a lot.

Ariel Conn: I’m assuming there’s a reason we don’t want to do that, though?

Deborah Lawrence: Well, there’s plenty of reasons why we want to keep forests. They do other things, like they regulate the hydrological cycle. They tend to minimize flooding; they manage flows in rivers. They are kind of like a sponge, so they take up rainfall or snowfall and then they trickle it out slowly so that it’s available for us or ecosystems or agriculture.

There’s other reasons to keep forests around. I don’t think we’re going to deforest the boreal zone anytime soon. I would say that if we had to figure out where we should be getting our timber, I would perhaps say that there would be reasons to think about timber extraction in the boreal instead of timber extraction in the tropics, because the tropics give us both the local and regional cooling and they do so much for the planet.

Ariel Conn: Let’s come back to the agriculture aspect too. So one of the things that you’re saying, if I’m understanding you correctly — in order for us to have better agricultural practices, it’s best to have a forest nearby, and yet we’re cutting down all the forests precisely for agriculture. Is that correct?

Deborah Lawrence: That is correct. That’s why you cut a forest; at least that’s traditionally been why. The thing that we’ve been talking about so much is temperature, and temperature is super important, but the other factor is rainfall. And the idea is that forests regulate water flows as well as flows of energy, and so when you have a forest nearby, and the air passes across that forest, research has shown that it will deliver more rain downwind. So if you have agriculture somewhere, you want to have a giant block of forest upwind. You want to have a supply of moisture.

Forests take that water out of the soil, they pump it up through their leaves and back into the atmosphere. They’re like a source for atmospheric moisture that ultimately, as it moves downwind, condenses and becomes rain. I mean, unless you’re right next to the ocean and you have a big source of water and moisture coming off the ocean, you really want to have forests nearby so that they can provide moisture to the atmosphere, which then provides moisture to our crops.

Ariel Conn: And so what happens if we don’t get this destruction of the Amazon rainforest under control?

Deborah Lawrence: It would be a really sad thing, not only because the agriculture that people were planning on might suffer, but because that rainforest is really quite amazing. It has an incredible diversity of flora and fauna and people, and it would be a shame if we lost it — especially if we lost it because of some tipping point where we thought we were only going to do so much deforestation and we were going to preserve the rest, but because of internal climate and land dynamics somehow we ended up triggering a drying of the Amazon and we ended up losing it not on purpose. That would be pretty awful.

Ariel Conn: Yes. It seems like a good time to get back into tipping points. Can you go into it a little bit more detail about how that works? What is the process there that could push us into a tipping point?

Deborah Lawrence: The person who knows the most about this is Carlos Nobre. He is a Brazilian atmospheric scientist and a brilliant man, and he has worked a lot on this and believes that if we get to the level of, say, 25 to 30% of the Amazon being gone, that we could trigger this warming and drying. So we know that when we clear forest, if you think about it just based on the fact that the trees themselves do all of this evapotranspiration: they have deep roots, they have lots of leaf area, they pull a lot of water out of the soil and put it into the atmosphere. When they are gone, when it’s just, say, soy or pasture grasses, they simply don’t access the same amount of water. They don’t pump the same amount of water into the atmosphere. So during critical times of the year, like during the dry season, there’s not as much moisture going into the system.

So it turns out that in Brazil — as I understand it — during the rainy season, they get a lot of moisture from the ocean. But in the dry season, that circulation changes and instead the land relies on recycled water to create whatever rainfall they have. And in fact, to promote the rainy seasons, you actually need to kind of seed the atmosphere with some moisture. So this happens way before all that moisture is delivered from the ocean. And if there’s no forest there, you can’t seed the atmosphere as well. Little short grasses cannot seed the atmosphere the same way that giant trees can.

What Carlos Nobre says is when we get to a certain amount of the forest gone, we reduce the ability of that forest to seed the atmosphere and we simply dry it out so that that dry season then gets longer. And if it’s longer, you can actually hurt the chances of those trees; you can actually stress them out. Maybe they can manage for a certain number of months, but you add two or three months to that and the trees are simply stressed. On top of that, imagine what we’d do with a warmer climate, so that the forests are stressed out by climate change and then in addition we stress them out with this other climate change due to deforestation.

Ariel Conn: Do we have reason to believe that we’re getting close to any of these tipping points, or is this something that we’re just sort of on the lookout for for right now?

Deborah Lawrence: Well, we are at about 17% of the Amazon gone, and Carlos Nobre thinks that the tipping point could be 25, maybe 30%. That’s pretty scary. That seems like it’s not too far. So it took us a while to get 17% gone — maybe the last 50 years or so — and it seems like right now we’re looking at increasing the rate. It’s been low, a low rate of deforestation for a while, but steady. If that rate were to go up, it would mean that we could reach that tipping point faster.

I don’t know where we really stand on that. I also don’t know that 25% is this perfect number. Some of my work, just reviewing the literature in general, suggests that it could be less of a cliff and more of a slope — maybe that it takes 30, 40, or 50% deforestation to really go over the cliff. So it seems like a safe idea to not get there.

Ariel Conn: That’s just for the Amazon, is that correct?

Deborah Lawrence: Correct.

Ariel Conn: Okay. And then you mentioned some other tropical forests. What’s going on with those?

Deborah Lawrence: The other big tropical forests are in the Congo Basin, and then centered on Indonesia. It’s pretty sad to look at a picture of Indonesia now, because a lot of the forest has gone. So Borneo used to look like a big Amazon. Borneo is about the size of Texas or France; It’s a big island, and it’s lost a lot of forest. The Congo Basin looks pretty good, but if you kind of zoom in closely, it turns out there’s already a lot of pasture and some forest degradation. So it’s not the same where you see giant swaths of forest gone, perhaps because they’re not as rich or perhaps because they’ve had a lot of conflict, but really there’s threats to rainforests everywhere.

Whether or not these tipping points exist, we don’t know. The rainforests in southeast Asia are very different. If you just think about what they look like, it’s a bunch of islands in the middle of an ocean; and that is very different from the Amazon, which is like a giant block of forest in the middle of a continent. So you can imagine that some of those tipping points are driven by these drying effects. Well, Borneo has lots of water near it. It’s got ocean nearby; it’s almost swamped — those water cycling impacts are almost swamped by the fact that there’s oceans all around. So it’s more like a maritime forest. The Congo is more like the Amazon. Africa is a giant continent. It’s a little bit higher than the Amazon. I don’t think people have really studied tipping points in the Congo.

Ariel Conn: So there’s lots of references to the Amazon being the lungs of the world. I was hoping you could sort of explain what that idea means?

Deborah Lawrence: So first of all, I think it’s not an adequate or appropriate metaphor. They are not the lungs of the planet. They’re much closer to the sweat glands of the planet — which is also super important, especially in a world that is warming. So the lungs of the planet analogy is that when plants take in carbon dioxide, CO2 plus water becomes a sugar plus oxygen. That’s the equation for photosynthesis. So you think, “Aha, oxygen.”

So, a couple of problems with that. Some of that oxygen is used immediately after that happened inside the cell to process the sugar that the plant just produced and to feed the plant itself. So half of the carbon dioxide that the Amazon takes up, it’s actually using just to exist. And the other half: some of it is stored in wood, some of it is dropped on the forest floor and decomposes. And when it decomposes, it’s combining with oxygen again and just going back into the atmosphere as CO2. Some of it is eaten by animals, and if it’s eaten by the animal, as soon as it gets inside that animal, it’s combined with oxygen and it goes out as CO2.

So really, the only oxygen that is produced by the Amazon is whatever its net uptake is: the stuff that’s not used up for the plants or the animals that live there. That’s not a huge amount. We have 21% oxygen in the atmosphere, 21%. And that’s a really big number. It came from algae, plankton, in vast oceans from, say, two and a half billion years ago. Before there was any atmosphere full of oxygen, there was a bunch of algae that produced a bunch of oxygen. It first was scrubbed out by the atmosphere itself, like it kind of rusted the entire planet. Once it’s rusted the entire planet, it finally could build up in the atmosphere.

So really if we’re thinking about the lungs of the planet, it was a bunch of algae that existed two and a half billion years ago. It’s not the Amazon. It’s just not. So I really don’t like that analogy, and I think the more important part is the sweat glands of the planet. It’s like our brow. Tropical forests keep us cool. They take the hottest solar radiation that we have on the planet, right at the equator, and they use the energy to take liquid water and turn it into vapor — just like the sweat off our brow — and it cools us down.

Ariel Conn: So my understanding is, we have these forests, they absorb carbon — which is great — and if we cut them down, then they’re not absorbing the carbon, and so it’s going into the atmosphere and warming things. But then my understanding is that, at the same time, when we’re cutting down the trees or burning the trees, all the carbon that’s in them is also going up. So not only are we not absorbing the carbon, more is emitted into the atmosphere. Is that correct?

Deborah Lawrence: That is exactly right. And it’s a double whammy, because the forests sitting there have a huge amount of carbon in them. It’s almost equivalent to the reserves of fossil fuels. I think I can check on that, but it’s like a huge amount of carbon in all the forests of the world. At the same time, unlike fossil fuels, which are not accumulating lots of carbon every year, the forest do accumulate carbon every year. They take it in and they bury it, part of it below ground and part of it in their trunks.

If we didn’t have forests, we would have a much hotter planet. The CO2 that comes out from fossil fuels and from deforestation: of that CO2, half of it gets taken up again by the oceans and the land — so about a fourth in the land and about a fourth in the oceans — leaving only half of what we put into the atmosphere actually remaining in the atmosphere. So that’s a huge service the forests and the oceans are doing for us.

Ariel Conn: How much deforestation do you fear could happen? I mean, 100% seems unrealistic. What levels concern you?

Deborah Lawrence: What concerns me is that I think — and again, I might be wrong, you can look it up — I think we’ve only protected about 15% of the planet. I’m not sure what that number is, but 15% of the forest — that is a bummer. That is really not a lot of forest. What worries me is that if you look at a graph of tropical deforestation, or just deforestation emissions, and you start at 1950, it’s really steady. It’s always been about a gigaton of carbon every year due to deforestation, and the fossil fuels number has gone from less than one gigaton, now it’s at nine gigatons. So it used to be that deforestation was half of our problem. Now it’s a 10th of our problem. But it’s been so steady. So to me that just says, “Why is it so steady?” We just keep deforesting at this steady rate that gives us one gigaton of carbon every year. It seems like we simply will continue to deforest at this rate, because we have been for decades.

I used to be interested really just in biodiversity. That’s what got me into rainforests. And as I became aware of their role in the carbon cycle, I thought, “Oh, this is it. This is the reason we’re going to save the rainforest, because it’s so important to the entire planet.” Somehow the diversity itself, while incredible and wondrous and sustaining in so many ways, it just doesn’t seem to resonate the way the climate crisis has resonated — that really we’re talking about changing the entire planet. And I thought to myself, “That’s going to save the rainforests, because they’re so important. They hold so much carbon, they do so much for the climate system.” And people have been working on this notion for a while, and it’s really hard to figure out how to put the mechanisms in place that can create financial incentives for these countries to save the rainforests so that we can save the climate system.

Ariel Conn: It sounded like it’s only just a few crops, really, that are replacing the forest. Is that correct?

Deborah Lawrence: Those are these big ones in big places. I think there’s probably people everywhere cutting down for us to just grow anything. Wherever they are, this is how you get new agricultural land. In much of the world, there’s still a need for new crop lands, and so I guess the big challenge is that we have 2 billion more people coming and we need to feed them. If we feed them the way we feed ourselves in North America, we’re in big trouble, because we really put a strain on the planet. If we can feed people better, if we can do better with our agriculture, if we can produce more food with fewer fossil fuel inputs and less land, we have a chance.

Ariel Conn: You mentioned that the deforestation sort of just keeps continuing at this constant rate. Is it consistent with population growth?

Deborah Lawrence: That’s a great question. I don’t really know, but part of me feels like, well, it can’t be exactly with population growth because we still have hungry people and we also have places where we produce way more crops than we actually eat. So I think there’s other dynamics going on, like our ethanol programs, and the fact that some of these crops are used not for food, but for other things. Like, oil palm is a really amazing crop. It can be used in industrial lubricants and it can be in your chocolate bar. It’s food, and it’s an incredible oil that can be used in all sorts of applications. I just wish it were always planted in places where it was best suited.

Ariel Conn: Are there other places that we could be planting these? The crops that are replacing rainforests — do they actually need that type of climate? Or could they be planted elsewhere?

Deborah Lawrence: I think even in places where it’s the same climate — like maybe they do love the tropics, maybe oil palm is born for the tropics — the question is, does it have to go into a brand new, primary, natural, beautiful forest? Or could it go into some degraded area that’s already been used for something else? And that something else is some other agriculture that maybe failed or maybe simply was poorly managed. So there is a role for taking existing lands and making better use of them. This is definitely true of the Amazon, where not all of those pastures are just the most efficient, most amazing producers of cattle. Sometimes there’s one cow per hectare. I think that’s a very low intensity. If there were better management, you could produce more cattle on less land, and that would then free up some of that land either to be forest or to be producing other kinds of food crops.

So degraded land is a great place to look for areas for some of these really important commodities that are globally traded. The other thing is, in Indonesia for instance with oil palm, they tend to go to the peat forests. We haven’t really talked about what peat forests are, but they’re really interesting swampy forests that have not only a lot of carbon in the above ground — in the trees themselves — but the soil is full of organic matter. It’s like a big peat bog, and so it has several meters of carbon rich soil. The only way you can plant oil palm there is to drain it and then to burn off the trees.

And even in that case, it’s not like it’s great soil. If it were great soil, there would be people growing crops there. But there aren’t. The irony is that that’s exactly why oil palm companies go to these peat forests: because there’s no conflict. What they’re really going for is not the land, but the lack of conflict with local people that they might have to make a deal with otherwise. So the reason I bring up the peat is they shouldn’t be on peat. They should be on upland forests. Peat has so much more carbon in it. If you’re going to put oil palm somewhere, don’t put it on a place where there’s a bunch of peat. Put on an upland soil that’s just a normal mineral soil, because it will grow better, it’ll take less work to put in the crop, and it will not release tons and tons of carbon into the atmosphere.

Ariel Conn: I don’t know if this is connected: there was an IPCC report that I think came out this summer about the interaction between land and climate. Were there some important takeaways from that that we haven’t gotten into yet?

Deborah Lawrence: Yes. So I think one of the important takeaways is that the land really does have an impact on our climate system. So I said earlier that deforestation is only 10% of our anthropogenic CO2. What I didn’t say was that agriculture is another chunk. So if you take agriculture and forest together, or basically if you take the land surface and what we do to it, it’s about a quarter of all the emissions. If you add to that transportation and processing of food, I think you can get up to a third. So the land is a big player. It’s easy to forget, because we think about our energy system and the transformation that needs to occur. It’s a huge player, but the land is also really important.

The other point about the land is that it’s interactive. So the land itself affects the climate system. And so there are feedbacks, and when we do something to the land system, we also impact the climate system, and then there are feedbacks from the climate system back on the land. There aren’t those same kinds of feedbacks when you think about wind turbines or solar panels — it’s just not really the same.

The other thing is that anything we can do on the land system to make it more climate friendly — especially things like avoiding deforestation, better forest management, better agricultural management — it all has multiple benefits. Whenever you do something that is good for the forest or good for agriculture, you’re feeding more people, you’re maintaining biodiversity, you’re maintaining flood protections by having intact forests and intact ecosystems. There’s really a lot of benefits that accrue when we think about nature’s climate solutions on the land.

Oh, and the other thing: the agricultural effects are interesting and somewhat different because they include things like methane and nitrous oxide, which are just different greenhouse gases that we don’t always think about. Both of them are really strong greenhouse gases, so they have really quite an important impact on the climate system.

Ariel Conn: I do have a question about that, because we do hear about carbon and trees and plants and whatnot. Do forests do anything with those other greenhouse gases?

Deborah Lawrence: So I’m not sure about nitrous oxide. The natural nitrogen cycle does produce some of those same-nitrogen based greenhouse gases — we have a natural system in place — but the perturbation that humans have done is just dramatic. I think we’ve probably doubled the amount of nitrogen that’s circulating in the atmosphere. I think it’s at least doubled. So we’ve done that by producing fertilizers.

For methane, there’s an interesting connection, especially in the tropics. In tropical forests, they produce these things called biogenic volatile organic compounds, BVOCs, and when they produce BVOCs, they go up into the atmosphere and they produce ozone and they prolong the lifetime of methane. So that’s actually a bad effect of forests, if you will, because those are greenhouse gases and so they’re warming. But the BVOCs also produce these aerosols that are highly reflective, so the BVOCs cool the planet as well — they have high albedo. So BVOCs is are interesting. That is a connection with the methane cycle and with ozone, but it seems to be counterbalanced by the fact that they increase albedo over these forests.

Otherwise, I don’t know. People have talked about methane and that forests may produce lots of methane. Well, my question is — I don’t really know this literature too well — but I look at the emissions of methane and the concentrations of methane in the atmosphere over the past 2000 years, and it looks to me like it was very steady when the forests existed intact. There was no problem of excess methane when we had forests all over the place. So I don’t see why forest methane would be a problem. The methane that I see, the increase in methane in the atmosphere, looks quite clearly related to our use of fossil fuels and our growing of cows. But it’s out there. People are interested in whether trees produce methane.

Ariel Conn: Interesting. So we’ve talked about some of the causes of deforestation and the contribution this has to climate change. What would you like to see policy makers doing, and what would you like to see individuals doing, to help address these issues?

Deborah Lawrence: I would like policymakers to think very hard about how to put a price on carbon, because if you put a price on carbon — and one that is fungible throughout the world — it really will build the case for maintaining those forests because the forests have so much carbon in them. For me, they have so much more than carbon; I think for most people they have a lot more than carbon, but they do have a lot of carbon. So a price on carbon, implemented at an international level, would do so much to incentivize people, local governments, national governments to protect their forests. There’s a reason to do it and I’d love to see that.

When I think about what regular old people — individuals like you and me — can do, I would say minimize our impact on the land and minimize our impact on the forest. The way you do that really is by watching what you eat. It’s not like Brazil sends us all their meat, but it’s part of a global market for beef. I think that those 2 billion people that are coming, really, if they’re all going to eat meat like we do, we are in big trouble. We will not have forests left, and we’ll have a much warmer planet because of all the methane.

The deforestation that produces beef is really, really the worst to me, because it’s got that two-fold effect: first to lose the CO2 from the trees, and then you get a bunch of methane from the cows. So I think our own personal choices around what we eat and the kinds of products that we use. As I said earlier, oil palm is in everything, and there are movements to clean up the supply chain for big commodities. I think if we can be a little bit more aware of what’s going into the products we buy, then we might be able to exert some pressure. I think that companies are interested in doing the right thing and consumers are too. So I guess we have to educate ourselves to figure out what’s in these products that I buy, what’s in my cosmetics, what’s in my food, what’s in the oil that I put into my car, or whatever it is. It could have a rainforest connection. And the more we’re aware of it, I think the more power we have to influence the businesses and the governments that provide us with those products.

I think it’s really important to recognize that individual choices alone really will not fix the problem, either for rainforest persistence or for planetary persistence. So the one thing that people can do is vote. People need to vote. They need to start feeling as if climate change, rainforests, the environment, this is something we care about deeply. Partly because we should, because it’s just the right thing, but partly because it’s our very own future that’s at stake. So I want people to vote and be climate voters.

Ariel Conn: Yeah. One of the reasons I wanted to do this this year is to help prep for voters next year. And so a final question for you. What gives you hope?

Deborah Lawrence: What really gives me hope is not just what’s going on in the forest. It’s hard; it’s really hard, especially when you say the Amazon burning. But what gives me hope is that we are tackling climate change. When I look at the energy transformation that I see around me, when I see the rate of uptake of electric vehicles, when I see the amount of solar and wind, it’s way faster than anyone thought was possible. So the transition is on. People are changing, with or without action by the United States government. We are moving forward, and I feel very hopeful in that way. I feel like, “Wow, this is way faster than we thought. It’s cheaper than we thought. It can only go in one direction.” And I feel very heartened by that. I feel like that is happening. It would be better if we had policy that was coherent and strong, but it’s happening anyway and that gives me great hope.

The other thing that gives me great hope is that it’s a lot of Americans who are concerned about climate change and know about it and believe it. It’s like 70%. it’s not some fringe radical tree hugging group. It’s really everybody. Everybody knows that this is important and that is heartening to me as well. So the real key is to figure out how to push that up in the priorities when people are voting. If they all know about it, they really need to understand that the consequences are great and they have to make it something they vote on.

Ariel Conn: All right. I think that’s a really excellent message to end on. Is there anything else that you want to add?

Deborah Lawrence: Doesn’t mean you don’t do your part. I don’t want to let anyone off the hook. Just voting is not enough, because part of what we need is a new normal, and I think the new normal is that we all think about these decisions every day. We turn off the lights, we don’t eat a ton of meat. It doesn’t mean we eat zero meat — it just means we think about it. There are so many decisions we make every day: do we walk or do we take the bus, or do we drive in our car? Do we go with friends on that trip home from college or do we actually fly home by ourselves?

There’s just a million decisions we make, and if we’re always thinking about the planet, just a little bit, I think we create this new normal. And then suddenly we’re frustrated because we can’t do enough. We’ve done all we can and it turns out we need to do more and we need our government for that. But the new normal says, “We all care about this. We all do everything we can. We also will have your back as elected officials if you do what you can to make our choices that much more effective.”

Ariel Conn: All right. That was even better.

Deborah Lawrence: Okay.

Ariel Conn: All right. Well, thank you so much.

On the next episode of Not Cool, a climate podcast, we’ll be joined by NOAA’s Libby Jewett, who will talk about another topic that I’ve been excited to get into: the oceans, and especially the problem of ocean acidification.

Libby Jewett: We need to know what impact we’re having on the ocean. I mean, the ocean is important, not only because of the seafood that we eat from it, but because it’s a driver of larger processes on the earth. And every other breath, they say, that we breathe comes from phytoplankton in the oceans.

Ariel Conn: I hope you enjoyed this episode, and I hope you join us for episode 21 to learn more about ocean acidification. As always, please take a moment to like the podcast, share it and maybe even leave a good review.

Not Cool Ep 19: Ilissa Ocko on non-carbon causes of climate change

Carbon emissions account for about 50% of warming, yet carbon overwhelmingly dominates the climate change discussion. On Episode 19 of Not Cool, Ariel is joined by Ilissa Ocko for a closer look at the non-carbon causes of climate change — like methane, sulphur dioxide, and an aerosol known as black carbon — that are driving the other 50% of warming.  Ilissa is a senior climate scientist with the Environmental Defense Fund and an expert on short-lived climate pollutants. She explains how these non-carbon pollutants affect the environment, where they’re coming from, and why they’ve received such little attention relative to carbon. She also discusses a major problem with the way we model climate impacts over 100-year time scales, the barriers to implementing a solution, and more.

Topics discussed include:

  • Anthropogenic aerosols
  • Non-CO2 climate forcers: black carbon, methane, etc.
  • Warming vs. cooling pollutants
  • Environmental impacts of methane emissions
  • Modeling methane vs. carbon
  • Why we need to look at climate impacts on different timescales
  • Why we shouldn’t geoengineer with cooling aerosols
  • How we can reduce methane emissions

References discussed include:

And we look at annual emissions of methane from human activities and we look at how those will affect warming of the planet over the next 10 years, we’ll actually have 30% more warming coming from methane emissions than we will from annual CO2 emissions from fossil fuels.

~ Ilissa Ocko

Ariel Conn: Hi everyone, Ariel Conn here with Not Cool, a climate podcast. Today, we’ll be looking at some of the other sources of climate change. We hear a lot about carbon in the atmosphere, and for good reason: CO2 accounts for about half of global warming. But what about the other half? Today we’re joined by Ilissa Ocko, who will walk us through the other greenhouse gases and aerosols that are impacting the global climate. 

Ilissa is a Sr. Climate Scientist at the Environmental Defense Fund, where she pursues climate science research and provides scientific guidance for climate change communication and policy. Her research focuses on the long- and short-term climate impacts of several greenhouse gases and aerosols. She is committed to communicating science to non-experts using plain language and powerful visuals, and she recently represented the U.S. in an international science communications contest.

Ilissa, thank you so much for joining the show today.

Ilissa Ocko: Thanks so much for having me.

Ariel Conn: So before we get into a lot of the work that you’ve been doing, I actually want to step back and ask a pretty basic question: what are aerosols? What are these things that are in the air that we’re breathing?

Ilissa Ocko: So there are millions and millions of gases and aerosols all around us. Aerosols are solid or liquid particles that are in the atmosphere, as opposed to a gas. And a lot of them are just naturally in the atmosphere. For example, when we have a dust storm over a desert, it kicks up some of the sand, and a portion of that can remain in the atmosphere. We can breathe that in; it can stay there. And that’s natural, for example. But there’s also a lot of human activities that are introducing even more of these aerosols into the atmosphere than otherwise would be there.

Ariel Conn: And can you give some examples of what anthropogenic aerosols would be?

Ilissa Ocko: Anthropogenic aerosols are the same type of aerosols that are naturally there, they just have anthropogenic sources. And when we say anthropogenic sources, we mean human activities that are also emitting them into the atmosphere. So for example, when we burn coal, it also introduces sulphur dioxide into the atmosphere, which is a gas — but then it quickly becomes sulfate, which is an aerosol. But sulfate is already in the atmosphere, for example from biological activity in the ocean that also emits sulphur dioxide into the atmosphere, which turns into sulfate. So the sulfate is in the atmosphere from both natural and human sources.

Ariel Conn: And so any issues that we’d have, it would be that there’s just more of these aerosols, not necessarily the type?

Ilissa Ocko: Yes, exactly. Sea salt for example is a natural aerosol that is in the atmosphere because it gets kicked up from ocean waves. But for example, sulfate and black carbon and organic carbon: those are all aerosols that are naturally in the atmosphere, but we also add to them in the atmosphere. So it’s a matter of us changing the composition of the atmosphere.

Ariel Conn: You were part of a report that came out in 2011, where you talk about things that policymakers can do to address non-CO2 climate forcers. What are climate forcers?

Ilissa Ocko: A climate forcer is any pollutant that we emit that can perturb Earth’s energy balance. So we have sunlight that comes into the earth, that warms up the earth, and then the earth emits some of this excess as heat. And then these constituents in the atmosphere can interact with either sunlight or heat or both. And so we call a climate forcer anything that can really change Earth’s energy balance. Carbon dioxide can trap heat in the Earth’s system, and so it is thus forcing the climate by changing the energy balance.

Ariel Conn: So your report was looking at the non-CO2 climate forcers. What are some examples of these non-CO2 climate foresters? You sort of got into it a little bit.

Ilissa Ocko: So, we focus so much on carbon dioxide because we emit so much of it into the atmosphere, and because it lasts for a really long time — and so it commits our planet to warming for centuries. But there are a number of other climate pollutants, or climate forcers, that we also emit that play a major role in changing Earth’s climate. So if we look at CO2’s contribution to today’s warming, it actually only accounts for half of the warming that we are experiencing. The other half of the warming is coming from what we consider non-CO2 climate forcers. We have other greenhouse gases that trap heat: for example, methane and nitrous oxide. And we also have these aerosols — which are not gases, because they’re solids or liquids — that are in the atmosphere, but they also change Earth’s energy balance and contribute to the climate change we’re experiencing today.

Ariel Conn: And you brought up black carbon earlier. Can you explain what black carbon is and what role that plays?

Ilissa Ocko: Black carbon is essentially elemental carbon. When you see big trucks drive by and you see this puff of black smoke that comes out of the engines, that black smoke is predominantly black carbon. It’s a solid particle; when we breathe it in, it can affect our lungs; it’s a major air pollutant. But it also is very effective at trapping energy. It can trap a million times more energy than carbon dioxide can, pound for pound. So it is an incredibly powerful climate forcer — we just emit a lot less of it than carbon dioxide, so it doesn’t contribute as much to warming today as carbon dioxide does. But it still contributes around 15% to the warming that we’re experiencing today.

Ariel Conn: So when we look at the non-CO2 climate forcers combined, how much are they influencing the warming that we’re experiencing, compared to carbon?

Ilissa Ocko: Around half of the warming that we’re experiencing today. 

Ariel Conn: Wow.

Ilissa Ocko: So this is why we need to focus on not just carbon dioxide but also these non-CO2 climate forcers, because they make up a considerable fraction of today’s warming. But they’re also more complicated than that; some of these non-CO2 climate forcers cool the earth. So it ends up being this balance between the warming pollutants and the cooling pollutants that dictates how our temperatures actually will change.

Ariel Conn: In terms of us emitting the non-CO2 climate forcers, are the processes basically the same for carbon? Are they part of most of the processes that are also releasing CO2? Or are there things that we’re doing that are releasing, say, more black carbon or more methane or some of the others that you mentioned?

Ilissa Ocko: There definitely is some overlap between the sources of a lot of these climate pollutants. For example, coal plants are a major source of CO2 but also a major source of the sulfate aerosol in the atmosphere. But there are also some really distinct sources that are separate for the non-CO2 climate forcers. For example, around over a third of methane is emitted from agriculture. A lot of this is coming from livestock, but rice production also contributes. So for example, these are activities that don’t necessarily contribute a lot to CO2 emission but contribute a lot of methane emissions.

Ariel Conn: We hear about fossil fuels a lot with CO2. Are those also a source of these other non-CO2 climate foresters?

Ilissa Ocko: Fossil fuels definitely contribute to the emissions of these other non-CO2 forcers to varying degrees. For example, the oil and gas industry is responsible for around a quarter of the methane we emit into the atmosphere. There’s also a certain fraction of black carbon that comes from vehicles that burn diesel. And so we see around 20% of black carbon coming from diesel trucks. We also see around 10% of black carbon coming from coal-fired power plants. So there definitely are some overlap with the sources, and if we were to address fossil fuel emissions, we would also reduce emissions of these other non-CO2 climate forcers.

Ariel Conn: And so now let’s go back to methane. It’s probably the one that I personally hear the most about, after carbon. Why are we worried about methane? What’s the issue with that one?

Ilissa Ocko: So methane, like you said, is one of the main contributors to climate change. If we look at it in terms of which pollutants we emit and how they contribute to today’s warming, it is the second largest contributor. It accounts for at least a quarter of the warming that we’re experiencing today. And this is from both directly as methane, the greenhouse gas, but also because when methane breaks down it turns into tropospheric ozone, which is another strong absorber of heat. And so methane overall is around 100 times more powerful at trapping heat than carbon dioxide. So that’s one of the main reasons we care about it.

Another reason we care about it is because we’re admitting a lot of it into the atmosphere, and if we don’t take actions to curb our emissions, we will see a lot more warming in the future — even if we work really hard to decarbonize society and wean ourselves off of fossil fuels — because methane has some distinct sources, such as agriculture.

And if we look at annual emissions of methane from human activities and we look at how those will affect warming of the planet over the next 10 years, we’ll actually have 30% more warming coming from the annual methane emissions than we will from annual CO2 emissions from fossil fuels. The main difference between methane and carbon dioxide is that it doesn’t last as long in the atmosphere. So it doesn’t build up over time and commit our planet to warming for centuries in the way that CO2 does.

Ariel Conn: So I’d like to follow up with that, because that’s one of the reasons that I’ve heard for not being as concerned about methane is that it won’t last as long. But you also just said that it breaks down into ozone, which can still absorb energy?

Ilissa Ocko: Yes. Tropospheric ozone is another strong greenhouse gas.

Ariel Conn: So how long does that last?

Ilissa Ocko: That actually only lasts for at most a couple of months.

Ariel Conn: Okay.

Ilissa Ocko: So the tropospheric ozone doesn’t last very long itself. Methane also breaks down into stratospheric water vapor, which also has a warming effect on the earth, but that again does not last very long. A small fraction of methane is eventually oxidized into CO2, which does last for a long time, but because the amount of methane that we omit is so much less than CO2 — around 100 times less — that is not a main contributor to long-term climate change.

But I want to mention two main things about why we care about methane and why it is essential that we reduce emissions now. The first is that even though methane will only last in the atmosphere for about a decade — and so it will be removed fairly efficiently — the warming that it causes in that short term can be absorbed by the oceans.

We know around 90% of the excess heat that have been trapped from human emissions of greenhouse gases has gone into the oceans. And so then that warming that came from methane in the atmosphere — even though methane was only there for let’s say, 10 years — is now in the ocean where it can last a lot longer and contribute to sea-level rise, for example, over the long-term. So even though methane is a short-lived climate pollutant, it doesn’t have short-lived impacts.

Ilissa Ocko: The second thing I want to mention is that because methane doesn’t last very long, if we reduce emissions, we can have a near immediate benefit to the climate. Methane accounts for at least a quarter of today’s warming, and if we were to reduce all of our emissions of methane, we would see about a quarter of today’s warming disappear over the next 10, 20 years, which is an incredibly powerful opportunity that we don’t have with CO2, for example.

Ariel Conn: So given that, as you said, methane is associated with agriculture and food production, how do we decrease methane emissions?

Ilissa Ocko: So we can reduce methane emissions from either production of our food: for example, we can improve manure management practices, we can provide feed supplements for cows to digest when they eat their normal food that can inhibit some of the production of methane in the cow’s gut. We can also improve some of our rice practices: for example, there’s different irrigation methodologies that can reduce emissions. And so there are a number of strategies that we already have available to reduce methane from the production side of things. But then we also could modify some of our dietary behaviors in the future, which is more of the social change, which obviously also would play a role in reducing emissions.

Ariel Conn: And so with regards to the methane being released from agriculture, is that still — as with carbon dioxide — connected to newer technologies and methods that we’re applying to agriculture? Or is this more an issue of growing populations eating more meat or something?

Ilissa Ocko: Yes, a huge portion of the methane that is being emitted from livestock and rice, for example, is just our increased demand for food as the population grows. But there are technological considerations as well. Around 10% of the greenhouse gas emissions coming from agriculture are associated with energy use. So we expect that as we trend toward renewables, for example, we can reduce a certain amount of emissions from the agriculture sector just by improved energy technologies. But a lot of these emissions are just coming from the livestock and how their biological processes function. So as long as we keep having livestock around, they will keep emitting methane into the atmosphere.

Ariel Conn: Okay. And so you wrote a paper called Rapid and Reliable Assessment of Methane Impacts on Climate. And one of the things that it seemed to me, looking at that, is that it’s harder to model methane than it is carbon. Is that correct?

Ilissa Ocko: It’s not necessarily harder to model methane compared to carbon dioxide. One could actually say it’s easier, because it has a fairly simple decay reaction in the atmosphere compared to carbon dioxide, which can have several different fates. Carbon dioxide can be taken up by plants; it can be taken up by the oceans; it also can just remain in the atmosphere completely untouched and lasts for thousands of years. So in that sense, methane can be simpler. The problem is that we focus so much on CO2 that we always look at how methane impacts the climate as a comparison to CO2. And that has led to some really simplified climate metrics that don’t do a good job explaining how methane impacts the climate over different timescales.

The problem we end up having is that we have these really sophisticated climate models that are incredibly impressive but take a really long time to run these simulations and require special infrastructure. And then you have these more simplified metrics that don’t do a good job elucidating these temporal trade-offs. And so what else can you use for understanding how methane impacts the climate? And what you can use are reduced complexity climate models, but they’re not necessarily calibrated or tested for how well they model methane just because we focus more on CO2. And so this paper was really just making sure that some of these simpler models are able to adequately portray how methane impacts the climate.

Ariel Conn: I want to follow up with this idea of the timescales. That’s another paper that you wrote that I thought was really interesting, was the comparison between looking at the impacts of greenhouse gases on 20-year timescales versus 100-year timescales. What does that mean to look at a 20-year timescale versus a 100-year? What types of projections are we making?

Ilissa Ocko: So we care about climate change over all timescales. That is very clear. We care about what’s happening today; we care about what happens during our lifetimes. But we also care about what happens for future generations — for our children, for our children’s children. And different climate pollutants affect the climate over different timescales. So we keep talking about carbon dioxide, how it builds up in the atmosphere, it stays there for a really long time. That climate pollutant strongly dictates what these long-term climate changes look like: how high the sea-level will get; how much warming will we ultimately have? Will any of our biomes shift? For example, will the Amazon turn into a grassland? All of those are really long-term issues that we care a lot about and that ultimately rely on how much carbon dioxide is emitted.

But then we have these short-lived climate pollutants, like methane, that are much more powerful at warming the climate in the near term, and therefore they end up dictating how fast the climate is warming. And that impacts the climate changes that we’re seeing today — for example, how fast the sea-level is rising right now; how much extreme weather events are occurring and how they’re intensifying; when we will reach certain tipping points, how fast will those happen? There’s all sorts of climate changes that are happening right now that we could mitigate if we reduce these short lived climate pollutants.

So overall, we care about climate change over all timescales. And basically when climate impacts are reported, it’s usually in this 100-year time horizon, it’s over the long term. And what we’re trying to say in this paper is that, well, the near term matters too. The 20-year time horizon matters too. So what you really need to do is look at both of these timescales. Whenever you report climate impacts, don’t just do 100-year, don’t just do 20-year, but do both. This is the way to give us the best understanding of what’s actually happening in the climate and how our activities are affecting climate change in both the near and the long term.

Ariel Conn: Why haven’t we been doing that?

Ilissa Ocko: There are always trade-offs that are going to need to be addressed, and ultimately it becomes a value judgment of, well, we have this tough decision to make; what do we care more about? But when we’re talking about using both time horizons, we’re just trying to provide the decision maker with the best available information. And then whatever they choose to do with that information is up to them and this ethical value judgment. But from a science perspective, if we’re not supplying the decision maker with all the information, then how could they make the best decision without even knowing how their decisions could impact climate over different timescales?

So one of the analogies that we often use is that it’s similar to your blood pressure measurements. You’re never just given one number; you’re given two numbers, something over something else. And if you were just given one number, you would think, “Wait, what about the other one? What am I missing? This is only part of the story.” And that’s what this is. We’ve been providing only part of the story for decades. And you ask, well, how this even happened? Well, it just evolved over time, as policy makers trying to understand how different emissions impact the climate just essentially and arbitrarily chose 100 years because they were provided three options in a report in 1990: 20 years, 100 years, and 500 years. And it seemed like 100 years was the middle of the road, so let’s just do that, and then it just kind of spread. And now this whole community just uses 100 years, when really there is no scientific basis for it other than it just evolved that way. So we’re trying to change that standard, such that people report both time horizons: 20 and 100 years.

Ariel Conn: So when we hear reports that say, “X is going to happen in the next 100 years,” and the response is, “Well, that won’t affect me. Maybe my grandchildren or something like that,” is that sort of an incomplete narrative — that there is stuff that’s going to be happening in the next 10, 20 years that we just haven’t been well-informed about?

Ilissa Ocko: Somewhat, yes. It is a very complicated issue because basically what we’re doing is we’re looking at, for example, how driving your car will impact climate over the next 100 years. And that’s just built into the metric, but a lot of people drop out the 100 years and just say, “Here’s how a car will affect climate compared to, for example, eating a hamburger.” And because those activities emit different climate pollutants that impact warming over different timescales, that’s why these metrics have to have a time horizon in order to compare the impacts to one another.

So what we end up doing by framing everything in this 100-year timescale, is that we’re masking any of the near-term impacts. They’re still part of the calculation, but they’re spread out over 100 years. So for example: you eat a hamburger that has a carbon footprint to it. The emissions from that hamburger will impact the climate mainly over the next 20 years. But what we’re doing is we’re spreading out those emissions over the next 100 years instead of just looking at over the next 20 years. So it ends up just being misleading, and downplays the role of eating a hamburger compared to driving your car.

Ariel Conn: And then, so to make sure I’m understanding this, this is where that trade-off would come in: with the hamburger, you’re going to have a much higher impact over the next 20 years, but with the car, it’s going to be a higher impact over the next hundred — and so trying to find that balance?

Ilissa Ocko: Exactly. And so that’s a challenge, and it will be inherent to a lot of decisions. But from a science perspective, we just want to provide all of the information so that we’re aware of these tradeoffs when we make a decision. The way it is right now, we’re not even aware of the trade-offs that we may or may not be making.

Ariel Conn: And so this paper came out in 2017. Are you seeing policymakers and scientists considering these two different timescales more? Or is this still a problem that needs to be addressed?

Ilissa Ocko: We are definitely seeing industries that are starting to adopt this approach, which is exciting. We’re definitely still working on governments adopting this. It’s a very complicated process because it basically depends on certain government organizations that set the precedent for everyone else. And then once those organizations — for example, the IPCC: the Intergovernmental Panel on Climate Change — if they were to recommend this approach, then you would see this approach being adopted by national and city governments worldwide. But a lot of those governments will look to those larger international organizations for guidance. And unless that’s happening, they won’t change their practices. 

So we are trying to work with the different entities to get them to adopt this still relatively easy approach, but one that provides a lot more information than they’re getting and giving right now.

Ariel Conn: Does it seem like you’re getting a good response to that?

Ilissa Ocko: It really depends. A lot of the push back we do get is that, “Well, as long as the IPCC tells us to use GWP 100” — which is global warming potential over a 100-year timeframe — “we want to be consistent with them and so we will do what they tell us to.” And the IPCC only comes out with new reports every five to seven years. So it ends up being this long process of getting to that point where we can shift the community towards that approach.

So I think that the main pushback ends up being, “Well, we want to use what’s consistent with everyone else, and if other people aren’t doing this then we don’t want to do it.” But we saw that, for example, with the hydropower industry, that were resistant to using this approach; but then the lifecycle community apparently started using this approach, and then all of a sudden the hydro-power community was on board and happy to adopt this. So it seems like an issue of, “If everyone’s doing it then I’ll do it too.” And it’s just getting to that point where enough people are doing it that everyone else follows suit.

Ariel Conn: I want to come back to a comment you made earlier where we were talking about the climate forcers, and you mentioned that some increase warming and some can actually increase cooling. And I’m curious about which ones can increase cooling, and to what extent that can help balance things out — what warms and what cools?

Ilissa Ocko: We have the greenhouse gases, which all trap heat; but then the aerosols are a lot more complicated than the greenhouse gases. They come in all different forms, shapes, sizes. And primarily because they’re bigger than greenhouse gases in terms of their size, they actually interact with sunlight rather than heat. And it depends really on the composition of the aerosol, but some of these aerosols are really good at absorbing sunlight, and therefore they end up trapping energy in the climate system and warm the Earth. And then some of these aerosols are more effective at scattering sunlight; and by scattering sunlight they reflect some of the sunlight back out to space, and so they in turn cool the earth.

The major cooling aerosol is sulfate — which comes from sulphur dioxide emissions, which have a number of both natural and human sources. Another cooling aerosol is sea salt and dust, which have a lot of natural sources. Also nitrate, which can be emitted also from agricultural activities, and I think it’s emitted as ammonia and then becomes nitrate in the atmosphere; and that also scatters some sunlight. And then organic carbon. Organic carbon is sort of the other side of the coin to black carbon. They’re always co-emitted, but depending on the fuel that’s being burned, they have different ratios of black to organic carbon. And black carbon is strongly absorbing of sunlight, and organic carbon is more reflective of sunlight. And so it ends up being that balance between the two that will determine how much warming we ultimately get from black carbon, because some of it is being offset by organic carbon.

Ariel Conn: And do you think we can use these types of aerosols to counter the warming? Or are you worried about risks associated with that?

Ilissa Ocko: We can use them, but it’s a terrible idea. And I do not think that we should pursue those types of geoengineering activities. And one of the main reasons why is because of the unintended consequences that may happen. Sulphur dioxide emissions were a main contributor to acid rain. And it wasn’t until we started reducing emissions of sulphur dioxide from coal plants in the US and in Europe that we started to see our acid rain problem, in I think the 1990s, playing much less of a role in impacting the environment.

These aerosols have other impacts other than just affecting the climate, but they also could completely change rainfall patterns. By changing the energy balance in the atmosphere, it affects the hydrological cycle. So then you can start having more rain in one area and less rain in another area. And so there’s all these cascading effects that can happen, and there’s no way that we can really predict all of them because we have one Earth and we can’t experiment with it. So even though yes, we can counteract some of the warming with cooling from these cooling pollutants, it’s not a good idea.

Ariel Conn: Okay. So what are some of the things that you would like to see society and policy makers doing to address climate change more broadly, but especially the non-CO2 climate forcers that we’ve been talking about?

Ilissa Ocko: We have so many already available opportunities to reduce methane emissions that we are not taking advantage of. Something that I would really like to see, that is technically feasible, is to pursue all of these methane mitigation measures that already exist — pursue them in parallel — and we can make a real dent in our warming over the next half century and full century. And so I think that’s something that we’re not taking advantage of now to the extent that we could be.

One of the main sources of methane emissions into the atmosphere comes from the oil and gas industry. And we have a lot of technologies available to detect natural gas leaks, to plug these leaks, to reduce methane emissions from the supply chain in a number of different ways. And so we could take initiative to enact these strategies that already exist and curb our methane emissions. We also have methane mitigation measures from livestock, and from rice, and from coal mining, and from landfills and wastewater. We have a lot of different technologies already at our fingertips. For example, we could capture some of the methane before it is emitted into the atmosphere from landfills. We could provide cow feed supplements. We could change our irrigation systems for rice production. So there are a lot of strategies that are already out there; they’re just not being deployed to the extent warranted.

Ariel Conn: Is it a matter of cost, or awareness that these solutions exist, or something else that’s holding us back?

Ilissa Ocko: So if you add up all of these different strategies that we could pursue, it amounts to around half of methane emissions that we could avoid and we could reduce. Around a quarter of all the methane emissions could be reduced at near-zero costs. So there’s a lot that can be done with no extra costs and is absolutely cost-effective. So in that sense, cost isn’t the main limitation. There is for the other methane emissions that we could reduce with available technology — cost is definitely a factor and so it does play a role. But there’s also just a lot of complexities involved with distributing some of these technologies to the places where they need to be, getting the right testing to be done for them to be commercially available, working with different industries and farmers to pursue them. It would be a whole collective effort that certainly would take a lot of work, but it’s definitely not impossible.

Ariel Conn: And are you seeing some of these being implemented then?

Ilissa Ocko: Yes. We are slowly starting to see some of these strategies be implemented. For example, for the feed supplements for cows: they’re working their way up through the chain of getting the approvals that they need in order to be deployed more globally. We’re definitely seeing the oil and gas industry commit to reducing emissions. Some of the largest oil and gas companies in the world last year made major commitments to reduce upstream emissions of methane from their activities. And so we are absolutely seeing some of the changes that we need to take place starting to happen, but they’re not happening at the pace that we really need them to in order to make an appreciable impact on reducing warming.

Ariel Conn: So my last question is, are you hopeful that we will be able to make enough of a difference in time?

Ilissa Ocko: I’m extremely hopeful. Part of that is being from the generation of knowing that climate change was mainly caused by humans, knowing that we need to do something about this. I absolutely have more of a positive outlook on things. Some of that comes from the fact that I surround myself with a community that is so focused on solutions that every day I’m hearing about small wins, and these small wins really add up. And so we’re seeing so much energy and activity from local governments, to city governments, to state governments. We’re seeing organizations all over the world taking actions. We’re seeing industries make commitments. And I’m also a big believer in technology, and I am very hopeful that we will find ways to reduce carbon dioxide emissions and other non-CO2 climate pollutants, but also even scaling up ways to remove carbon dioxide from the atmosphere, to capture carbon dioxide before it’s released into the atmosphere — I’m very hopeful that we will be able to scale up and fully deploy those technologies.

Ariel Conn: Excellent. Is there anything else that you think is important to cover that we didn’t get into?

Ilissa Ocko: I don’t think so. I think we covered a lot. I mean, there’s so much that we could cover but we’ve got to draw the line somewhere.

Ariel Conn: Yeah, it’s a huge topic.

Ilissa Ocko: Yeah, no, I mean these were great questions. And some of it is just really complicated, which is why it’s hard to even explain some of the nuances. And there’s a reason why people can get so confused, because the science can be extremely complicated.

Ariel Conn: All right. Well, thank you so much.

Ilissa Ocko: Thanks for having me.

Ariel Conn: You’ve likely heard a lot about the burning of the Amazon rainforest this year. Well for the next episode, we’ll be joined by Deborah Lawrence, a professor of environmental science at the University of Virginia, who will explain not only why the Amazon is so important to our climate, but the role that all forests have in regulating climate change.

Deborah Lawrence: I think some of the most interesting work has been to look at what happens with the progressive deforestation of the Amazon. What you see is that across different models with different modeling groups, it looks like there is some kind of tipping point at which you go from a system that is stressed but still a rainforest to a system where suddenly it’s really much hotter and drier. And so even though you haven’t deforested the rest of the Amazon, you end up with a different kind of forest, because it’s stressed out.

Ariel Conn: And as always, if you’ve enjoyed this show, please take a moment to like it, share it, and maybe leave a good review. I hope you’ll join us for the next episode.

Not Cool Ep 18: Glen Peters on the carbon budget and global carbon emissions

In many ways, the global carbon budget is like any other budget. There’s a maximum amount we can spend, and it must be allocated to various countries and various needs. But how do we determine how much carbon each country can emit? Can developing countries grow their economies without increasing their emissions? And if a large portion of China’s emissions come from products  made for American and European consumption, who’s to blame for those emissions? On episode 18 of Not Cool, Ariel is joined by Glen Peters, Research Director at the Center for International Climate Research (CICERO) in Oslo. Glen explains the components that make up the carbon budget, the complexities of its calculation, and its implications for climate policy and mitigation efforts. He also discusses how emissions are allocated to different countries, how emissions are related to economic growth, what role China plays in all of this, and more.

Topics discussed include:

  • Global carbon budget
  • Carbon cycle
  • Mitigation
  • Calculating carbon footprints
  • Allocating emissions
  • Equity issues in allocation and climate policy
  • U.S.-China trade war
  • Emissions from fossil fuels
  • Land use change
  • Uncertainties in estimates
  • Greenhouse gas inventories
  • Reporting requirements for developed vs. developing nations
  • Emissions trends
  • Negative emissions
  • Policies and individual actions

References discussed include:

So it’s pretty easy when you think of a carbon footprint and you look, “Well, there’s a lot of emissions coming from China and China’s using a lot of coal,” and it’s easy to think, “Well, therefore we just stop importing products from China.” But if you just cut someone off and say, “We’re not importing your products anymore,” then there’s a whole group of people that will suffer loss of income, etc. That’ll have big equity implications.

~ Glen Peters

Ariel Conn: Hi Everyone and welcome to episode 18 of Not Cool, a climate podcast. I’m your host, Ariel Conn. Today, we’re joined by Glen Peters, who will talk about, among other things, our carbon budget. We’ll learn what the carbon budget is and why it’s hard to calculate, why some causes of carbon emissions are harder to address than others, how the phrase “carbon footprint” is so often misused and why it’s also hard to calculate, how responsibility for emissions is attributed to different countries, and much, much more.

Glen is a Research Director at the CICERO, the Center for International Climate Research in Oslo. Most of his research is on past, current, and future trends in energy consumption and greenhouse gas emissions. He studies human drivers of global change, the global carbon cycle, bioenergy, scenarios, sustainable consumption, international trade and climate policy, emission metrics, and too much more. Those are his words, not mine.

So Glen, thank you so much for joining us today.

Glen Peters: Thank you. It’s good to be with you.

Ariel Conn: You have done a lot of work on the global carbon budget. I think my very first question for you is just what is the global carbon budget?

Glen Peters: Yeah, it’s a good first question. In the global carbon budget, we try and look at all the sources of carbon into the atmosphere and the sort of sinks of carbon into the atmosphere and try and understand where carbon is going. You could think about it a bit like a bathtub, where you try and look what’s going into the bathtub and see what’s going out of the bathtub and make sure they match. The carbon budget generally has two components: the source component, so what’s going into the atmosphere; and the sink component, so the components which are more or less going out of the atmosphere.

So in terms of sources, we have fossil fuel emissions; so we dig up coal, oil, and gas and burn them and emit CO2. We have cement, which is a chemical reaction, which emits CO2. That’s sort of one important component on the source side. We also have land use change, so deforestation. We’re chopping down a lot of trees, burning them, using the wood products and so on. And then on the other side of the equation, sort of the sink side, we have some carbon coming back out in a sense to the atmosphere. So the land sucks up about 25% of the carbon that we put into the atmosphere and the ocean sucks up about 25%. So for every ton we put into the atmosphere, then only about half a ton of CO2 remains in the atmosphere. So in a sense, the oceans and the land are cleaning up half of our mess, if you like.

The other half just stays in the atmosphere. Half a ton stays in the atmosphere; the other half is cleaned up. It’s that carbon that stays in the atmosphere which is causing climate change and temperature increases and changes in precipitation and so on.

Ariel Conn: Is that number usually about half? Or is it increasing?

Glen Peters: It’s a pretty robust number, and this is one of the great mysteries of the carbon cycle. Mystery is not really the right word, but it’s quite curious that no matter how much we’re putting in the atmosphere, this fraction that stays in the atmosphere, about 50%, has remained relatively constant. So if we go back 50 years in time for example, we still had about 50% stay in the atmosphere. Today when we emit, there’s about 50% that stays in the atmosphere, but then there’s a question of will this continue forever if we start to see the impacts of climate change — changing precipitation, maybe for example the land sink is not as good, so maybe tropical forests don’t take up as much carbon. Then we may see this share drop and more stay in the atmosphere.

We know — there is some evidence that it may change, so when there’s an El Nino and it causes hotter and drier weather in the tropics, less carbon is taken up by the forests, and so we see a greater increase in the atmosphere. This is sort of natural variability, but this natural variability gives us an idea of what may happen if temperatures increase.

Ariel Conn: One of the terms that I saw come up a lot is the carbon budget imbalance. What is that and how does that relate to what we’ve just been discussing?

Glen Peters: The carbon budget is like a balance, so you have something coming in and something going out, and in a sense by mass balance, they have to equal. So if we go out and we take an estimate of how much carbon have we emitted by burning fossil fuels or by chopping down forests and we try and estimate how much carbon has gone into the ocean or the land, then we can measure quite well how much carbon is in the atmosphere. So we can add all those measurements together and then we can compare the two totals — they should equal. But they don’t equal. And this is sort of part of the science, if we overestimated emissions or if we over or underestimated the strength of the land sink or the oceans or something like that. And we can also cross check with what our models say.

So this carbon imbalance is basically the balance between what we think is happening and whether those two things agree. And they don’t, but the good thing is that sometimes we overestimate the balance, sometimes we underestimate it — which means that they’re sort of bouncing above and below zero, if you like, so it averages out. Just like the weather, we can have hot years, dry years, and so on and so forth. So when you think about the global climate, we also have some years that are a little bit warmer, some years that are a little bit cooler, and this is propagating to natural variability in the carbon cycle. First of all, we can’t perfectly measure everything; and second, our models can’t protect all the natural variability that happens.

But if you average over a longer time period, over decades or whatever, this carbon imbalance averages out to zero, which is nice. It means that on average, we’ve got the science right. It’s just some of the details we’re missing. It’s like we’re not sure whether it’s going to rain next Thursday or not. So it’s that sort of variability that we can’t detect. But the big scale changes in the system we can detect well.

Ariel Conn: Okay. A minute ago, you mentioned sort of the chemical processes involved with cement. And that’s been one of the things that’s been sort of interesting for me, starting this process of interviewing people and trying to learn more about climate change, was seeing that cement seems to have this huge carbon footprint. And I was wondering if you could talk a little bit about why that is.

Glen Peters: Every sector you can look at in different ways, so the biggest probably single sector, if you like, is production of electricity. So cement is certainly an important sector, one of the most important ones. It’s about 5% of global emissions, or something like that, and it’s growing relatively rapidly. And it will grow more or less in line with, let’s say, growth in developing countries as they’re building infrastructure, new buildings, new roads, and so on. And it’s also very hard to find alternatives to cement. But the emissions from cement essentially come from two areas. So the first is a chemical reaction, so when you produce the cement, you’re taking limestone, basically, and taking the CO2 out of that, so you get a high level of CO2 through a chemical reaction. That’s about 5% of global emissions. And also to do this process requires a lot of energy, a lot of heat, so you burn a lot of fossil fuels in the process of producing cement as well. I’m not sure of the exact number, but it’s basically another 5%. 

So in total, cement is probably give or take, rounded numbers here, about 10% of global emissions. But the process emissions, the chemical part, is about 5%, and that’s the part that you most often see in emission statistics or in a report or something like that. But the good news, if you like, is that the chemical reaction produces quite a pure CO2 stream — quite a high concentration of CO2 — which means that it’s quite suitable for carbon capture and storage. The mitigation options for cement are in a sense quite obvious, but that will increase the cost, which no one really likes.

So there’s lots of sectors which let’s say are easy to mitigate, and some sectors which let’s say are hard to mitigate. If you think about electricity generation, maybe a good US example is there’s a shift away from coal to gas and to renewables, so there’s some sort of obvious and easy technologies where we can straight away shift production of electricity to different sources and have less emissions. There’s also various behavioral things we could do. We could use less energy or have different travel habits and so on, which can reduce emissions. So these are, let’s say in quotes, some of the easier things. Cement is usually classed as one of the harder things to mitigate, but this is more cost related. It’s not so easy to use a different material and it’s not so obvious how you could produce it differently to get the same product but lower emissions.

But when you produce the cement, it does have a very high concentration of CO2, so if you just put a bag over the top of the cement factory if you like, and capture the CO2, then you can reduce the emissions. It just costs a lot, that’s the problem.

Ariel Conn: And so I’ve been using this term carbon footprint a lot. But can you explain how that’s actually defined?

Glen Peters: Yeah. The carbon footprint is often misused. Basically you would say it’s the total emissions associated with an activity, and that could be very broadly defined. So it could be an individual, what’s my personal carbon footprint? When you talk about that, you would think about all the things that I do in my life, including the emissions in the supply chain to produce the products that I consume and to drive a car or whatever. You could also think about the carbon footprint of a business or a company or a country, just sort of the way you define the carbon footprint will slightly change because of the difference in scale. But overall, it’s all the direct and indirect emissions associated with the activity that you’re thinking about. Individual consumption is an easy one. All the emissions that I emit in my daily life, from driving a car or taking an airplane to using electricity, plus also the emissions to produce products which I consume, like food. Meat would be a big one. TV: the emissions to produce a TV; and so on and so forth.

Also services surprisingly have a large part of the carbon footprint, so going out for dinner or the hairdresser, or the gym, or the movies. None of these things are completely free of emissions when you consider the electricity use and so on. All the emissions associated with the activity is essentially the carbon footprint.

Ariel Conn: How do you deal with overlap? Like if I, say, go to the hairdresser, what’s more important to calculate: my carbon footprint in that activity, or the carbon footprint of the hairdresser itself?

Glen Peters: This is a good question that us carbon footprint nerds discuss all the time. So it’s quite a technical point and it relates a little bit to how you do the calculation as well. There are quite a few potential areas for, let’s say, double counting. And so getting a consistent carbon footprint that is comparable across different activities can be very hard unless you account for this double counting. So if you were going to the hairdresser, for example, generally that would include, let’s say, you going to the hairdresser, let’s say you took a bus; and it would include the emissions associated with the hairdresser, so you know to produce the scissors, to use electricity for the hairdresser to have lights on, and so on and so forth. Those things would be included in the carbon footprint, your carbon footprint, which means then essentially you’re saying that the hairdresser has no carbon footprint because you’ve taken their emissions.

But if you allocated in a different way, then you might want to consider the hairdresser’s carbon footprint. Then you’re considering a slightly different activity and it’s not really comparable to your personal carbon footprint. So you get all these quite detailed complications on how to avoid double counting. But if you do it correctly and you’re careful, you can set it up so it’s done consistently. You’ll always have some problems, but overall if it’s done correctly, then it shouldn’t be too much of an issue. Maybe some of the more problematic areas is when you go up to a national level, then the risk of double counting becomes much larger.

A car for example: a car could be your personal car that you drive to work or for a holiday or something, but a car could also be used by, let’s say, your hairdresser. Maybe the hairdresser’s a mobile hairdresser and drives around. Then that car used by the hairdresser is a part of their business activity and it’s not really a personal footprint. So separating transportation and cars into cars associated with personal activities and cars associated with business activities is a quite important split. The same happens with electricity: how much electricity goes directly to the household, how much electricity goes to industry to produce products that then I consume. So you get all these complications, but when you have a method, you can sort through these things and make sure you don’t do any double counting.

Ariel Conn: Something else that I’ve been confused by that I think is sort of along the same lines is — I hear at least — things like how high China’s emissions are. But a lot of China’s emissions, I think, are production. So if they’re producing things that are consumed by US citizens, who’s causing — I don’t know, I don’t really want to say blame, but —

Glen Peters: We can blame someone. I know what you’re saying. We have troubles with what word we use there as well. It’s more of an allocation issue.

Ariel Conn: Yes, I like that. Allocation. Who should that be allocated to?

Glen Peters: The way emission inventories are usually done or emissions are usually estimated is what is called a territorial perspective. Emissions are allocated to the place that they physically occur, so if there’s a factory in the US, then the emissions are allocated to the US — regardless of who consumes those products. And this is a sort of reasonable accounting system. It makes a lot of sense. It’s much easier to monitor and to keep track of what’s going on. But then when you start to zoom in, get to a smaller scale, such as if you look at the individual carbon footprint, your personal carbon footprint, in your house you’re probably not producing electricity and have a big coal power plant or something like that. So your emissions will look like zero, essentially. 

So then you want to start to estimate your carbon footprint, and then some of those emissions in a factory in the US will get allocated to you. This is sort of moving to consumption. So when you go to the national level, the territorial emissions, the way emissions are usually calculated: the emissions coming directly from a chimney in that country. And then some of those emissions — let’s say in the US it’s produced products which are then exported to China — you can do an accounting scheme and carbon footprint at the national level where China then would get the emissions that occur in the US to produce products that they consume in China will get allocated to China and vice versa. This is usually discussed the other way, in the sense that the US consumes a lot of products which are produced in China, so China is getting the emissions; the US is having the benefits of the consumption. It’s the same for the EU and also developing countries as well.

So about a quarter of Chinese emissions are to produce products which are exported. So when you shift to a carbon footprint, China’s emissions go down around about 20% or something like that. It makes a pretty significant difference, and it’s sort of a consequence of trade, that we trade with other countries; but then you sort of have to think a little bit about what are the implications of that. So in the US, if you consider the US states, you don’t usually get worried if a product is produced in one state and exported to another state. That’s not a problem, even if it’s across the US; no one seems to get worried about that.

But then all of a sudden if it’s China, that’s a different country, then we start to worry about this trading relationship and the effect it may have on emissions and so on and so forth. There’s lots of reasons that you might discuss it from a policy perspective, but it’s a different form of accounting and different allocation. When you allocate to consumption, there’s a little bit more uncertainty. It may give a better reflection of your emissions as a country, but it also has some policy complications in how you would implement policies.

Ariel Conn: Can you talk a little bit about some of the equity issues that we see, especially when considering things like the question of is it fair to blame China if I’m the one who’s asking them to produce this product that I can then buy, and how it deals with other countries as well?

Glen Peters: Yeah. It’s pretty easy when you think of a carbon footprint and you look, “Well, there’s a lot of emissions coming from China and China’s using a lot of coal,” and so on. Then it’s easy to think, “Well, therefore we just stop importing products from China.” But that does come with some implications for China, so the population and the growth in China is often dependent, or can be partly dependent, on the growth in trade and growth in exports. So if you just cut someone off and say, “We’re not importing your products anymore,” then there’s a whole group of people that will suffer loss of income, etc. etc. etc. That’ll have big equity implications. And it just comes back to things that are going on with the US and China and the trade war. Very many similar issues arise when you have a trade war and tariffs go up and you stop trading with another country, then there’s a whole lot of people that lose out because they can’t sell their products; they lose their jobs.

So if you take consumption based accounting too far and start to think, “Well, therefore we have to stop importing stuff and produce everything locally,” then that will have huge equity dimensions associated to it. There’s other issues as well, such as whether you could even produce stuff locally and if you did produce stuff locally, whether it would have lower emissions. And quite often by trading products, then the whole idea is that someone that could produce something more efficiently would produce it. So it’s not clear that you would reduce emissions that much, if at all, by not trading with other countries. Lots of complex questions get into policies that might be relevant to consumption-based emissions or carbon footprint emissions, particularly the equity one.

Ariel Conn: Are there other things that we can do to try to encourage producers to be more efficient? Aside from not buying from them.

Glen Peters: That’s essentially the process that’s been happening. So through climate negotiations and the Paris Agreement that’s trying essentially to get more and more countries on board, more countries involved in mitigation, and then countries have to put forward emission pledges. So therefore countries like China and India, South Africa, Brazil, etc. — they all have to put forward emission pledges and try and meet those pledges. So it’s sort of pushing the countries in the right direction. Completely inadequate in how fast it’s going, but within 30 years of climate negotiations, this is the only pathway that’s actually making some progress, which sort of indicates a lot of the challenges there.

There are other means that you could use. Some of these are directed maybe at the US. So the US has decided to pull out of the Paris Agreement. Then you could think countries could punish the US by putting trade sanctions on the US to try and encourage the US to get back into the Paris Agreement. Of course, as we see in the whole China-US thing now, these things just lead to retaliation. It may not be that effective overall. You can change your habits as an individual a little bit by where you purchase. Countries can implement policies which would encourage purchasing of cleaner products through, let’s say, procurements. You could do some things with trade policy, but then it’s a very risky territory to go, because countries may retaliate. And there’s big equity dimensions, which we often forget about.

Ariel Conn: Is there anything else equity related that you think is important to consider?

Glen Peters: Pretty much any climate policy does have equity dimensions, which is something that’s easy to forget. There’s been a lot of discussion and arguing about aviation, so Greta Thunberg traveling over to the US by boat instead of flying brought up a lot of discussions about aviation and so on, which is fair enough. But it’s also important to remember that there are huge inequities in a sector like aviation, just as there are in many other sectors. It’s generally the privileged that fly, but when you try and take away someone’s privilege, you may disadvantage other people. There may be some people that may need to fly for various personal reasons and so on, so even though aviation is a very high impact sector and has a very individual impact, there might be a whole range of equity reasons or issues that you need to be careful of when you’re pushing on that sector.

But the same applies to any sector: with transportation, electricity consumption, climate policies in general try to increase energy prices. Therefore you change your behavior and reduce your energy use. But this could all increase costs, which has a big impact on those with lower income. So there’s a whole range of issues that you need to take care of when you implement policies.

Ariel Conn: The one other thing that has often crossed my mind is I hear a lot about trying to reduce your consumption because the production of materials and goods has a lot of emissions. And I think that’s great and I’m trying to reduce my consumption, but I wonder if we’re all reducing our consumption, what impact does that have on the people whose jobs it is to produce? 

Glen Peters: This gets into a question of growth and whether the economy needs to grow and so on, which is a whole new discussion one could have. But also if you change your behavior so you’re producing less material products, you’re still going to spend your money.

Ariel Conn: True.

Glen Peters: So you might spend it on something else. So a lot of these issues are often distributional issues. If you take a US example with the coal miners, so a lot of coal power plants and therefore coal mines are being shut down because of solar wind and cheap gas. There might be enough jobs in the US, but those jobs may not be in the right place, so those people would technically have to move, but it’s where they’ve grown up or lived for 50 years. There’s quite often other issues that make it hard for people to be able to move or to change jobs. So even if the economy restructures so you consume less material stuff but produce more services, it involves a lot of disruption to existing jobs and so on, which is really hard for people that lose out. 

This is also true at the international level, climate policies will affect different countries differently. Middle Eastern oil countries will get a big hit, so they’re naturally going to be resistant to strong climate policies. So you really need to think about how can you get those countries on board so you’re not always fighting with them. Likewise, how do you get coal miners on board when they lose their jobs or when their industry is facing a dark future — how do you get them on board for strong climate policy. These are some of the more difficult questions getting into the politics of how you manage a transition.

Ariel Conn: Okay. I want to step back real quick to the carbon budget, where we started. You’ve been working on the carbon budget for quite a few years. In the time that you’ve been working on it, what have you seen change, if anything?

Glen Peters: When you look back, it’s not a surprise. It’s sort of hard to think what it was like 10 years ago. But certainly emissions have grown rapidly and continue to grow, so that’s maybe not a surprise, but it’s a sort of important aspect of the carbon budget. And a bit of a consequence there is that relative emissions from fossil fuels keeps growing in the carbon budget. We used to think that emissions from fossil fuels were the most certain part of the carbon budget, but now emissions from fossil fuels are so big that the actual uncertainty is quite important to things like the budget imbalance that we were talking about before.

The continued growth in fossil fuels is important. Maybe one component of the carbon budget that is continually uncertain is land use change. It’s very hard to estimate emissions from land use change, so you have to know what land use has changed from which type to which other type. If I go from crop lands to forest, it’s called aforestation, so I’m growing a new forest. Or if you go from forest, let’s say the Amazon, to pastures for cattle, or if you go to crops to grow soybean, there can be different carbon implications depending on those land use changes. And it also depends on the type of carbon that you’re cutting down or changing when you go from the land use change. So if you’re in the Amazon and creating more crop land by cutting down the forest, the implications would be different compared to if you were in Russia cutting down the forest and changing the land.

The relative carbon densities, as we would say, to go from one land use to another is quite important and we don’t have perfect data what’s going on in the soil. There’s a lot of carbon in the soil, a lot of uncertainty about what’s happening when we change from one land type to another. And actually, just tracking the areas can be quite hard to estimate, what area in this country has changed from forest to cropland or something like that. To make it even more complex, you can have multiple land use changes, so you could go from a forest to cropland and then that cropland may become a pasture, then that pasture is left and it becomes a forest again, and then someone cuts down the forest and converts it into cropland. So over a 10 or 20 year period, you could have all these factors happening, which is changing the carbon balance. It is really hard to estimate what’s going on with land use emissions, and this is the biggest uncertainty I think in the carbon budget, or one of the more important ones.

Ariel Conn: It seems like you hear a lot about the discussion between whether we should be having forests or crops and pastures and stuff like that, but I don’t really hear much about the impact of turning the land into a city or a town or something like that. Does that impact the land use debate?

Glen Peters: It does. The land uses involved are relatively small — the urban area, city area, compared to let’s say the forest area. So there’s that scale difference. And quite often, you may not get a city emerge in the middle of the forest. But the city might grow and it takes up the hinterland around it: so for example you have a town which becomes a bigger town, and so the farmland around that town is converted into housing, and then it grows bigger. And so you keep taking over the cropland and pasture land that was around the town, so the town expands. This will push agricultural production to other areas, which then might cause deforestation or other types of land use change. So there will be come direct link, in that expanding a city may impact on forests or woodland of different types. And there’s also an indirect effect, that even if you expand your city into cropland or pasture land, then you may cause some additional agricultural activity in another area, which might cause some deforestation. So, it’s a complex picture.

Ariel Conn: Okay. One last question for the carbon budget. As you said, you’ve been doing this for 10 or 15 years. Do you still think it’s a valuable calculation?

Glen Peters: It’s actually, I think, been a very useful thing to do for the carbon cycle community, and there’s several reasons for that. So when every year you come back and make sure that you’ve got balance and things are working and try and understand what’s happened in the last year, you’re sort of in a sense forced to learn about things that are happening. If you didn’t re-estimate the carbon budget every year — let’s say you only did it every five years — then many things would happen and you would maybe not follow up so closely the annual changes and what’s causing annual changes. So I think the fact that we do the carbon budget every year forces us to think about things like annual variability: we have to explain to people why the emissions go up or down this year; why did the atmospheric concentration of CO2 — so the amount of CO2 in the atmosphere — so why did that go up or down; how did it relate to natural variability, this El Nino I mentioned before. 

And also it gives a new opportunity every year to communicate what’s happening. So, one advantage of doing the carbon budget is we have a release every year; we can have a new story, a new narrative, a new way to engage with people focusing on what’s happened in the last year, which is much closer to home compared to what happened five years ago. I think it’s been a very useful tool to get the scientific community to work together, but also to communicate the science to a broader audience.

Ariel Conn: Okay. Another phrase that I’ve seen crop up in some of the papers of yours that I was looking at was greenhouse gas inventories. Could you explain what those are?

Glen Peters: Inventories are basically a report that certain countries — not all countries — certain countries have to do every year, more or less, to give statistics on their emissions. So before, I was talking about the territorial emissions, how much emissions have been released in different countries, in factories and so on and so forth. So every year the statistical offices or environmental agencies in those countries will compile the energy statistics and convert them into estimates of CO2. And so an emission inventory is basically a catalog or a database report of all the emissions that have happened in a country — usually by sector and type of activity, sometimes also by region. And so it’s essentially our latest estimate of emissions into the atmosphere.

I mentioned only some countries need to report this. So through the United Nations Framework Convention on Climate Change, countries have to report what their emissions are, but essentially it’s only developed countries have to regularly report what their emissions are and developing countries have less stringent reporting requirements. And this is a bit of a problem for people like me that are trying to estimate global emissions. We have quite good quality reports from one set of countries and then quite disparate information from another set of countries, so this is a sort of problematic issue when you’re trying to get climate action to happen. If someone’s not reporting something very well, then it’s quite hard to identify where they can reduce their emissions and to track whether they’re actually doing what they said they would do.

Ariel Conn: How do you deal with that?

Glen Peters: There’s some organizations that compile statistics at the international level. For example, International Energy Agency is maybe the best example; it compiles energy statistics for a whole range of countries — they essentially try and cover the world. They might have to make some estimates where there’s some missing data, and then you can make various assumptions and convert that data into emissions. And you can do a pretty good job there, but they’re in no way as detailed as, let’s say, a bottom up approach to it may be. If you think about the International Energy Agency, they’ll have a bunch of people working on emissions at the global level and energy statistics at the global level. But within a country, particularly if you go to a rich country, you’ve probably got even more people working just on that country.

So there’s a lot of knowledge within a country on what’s happening with energy and emissions in different sectors and obscure sub sectors, like what are the emissions in refrigeration and so on — there’ll be experts in countries on these sorts of things. And these statistics are compiled; you could say because it’s coming from the country, it could be biased, but there’s a review process which goes on. So people will pick up, “Well, you’ve been telling us some stories about the refrigeration. Could you please improve that estimate?” Or something like that. So, we have these global data sets that can give us a global picture, also every country at the global level. But the sort of national statistics gives a lot more information that allows us to verify things, to see whether something we saw in the international statistics made sense, and so on.

So it’s a very important way to get much more accurate information. We generally push the developing countries, to try and get them to also do national reports. So they have these inventory reports every year that we can go in and see what’s going on in China or India or South Africa or whatever that country may be. But of course, they find it’s a lot of work. They may not see it’s in their best interest to report detailed statistics, in case it means they may need to reduce their emissions. So it’s a constant struggle.

Ariel Conn: We’ve touched on this a little bit earlier, but could you also talk about the difference between measuring production versus consumption?

Glen Peters: Production is more or less synonymous with territorial emissions, so production emissions are the emissions that occur within the country. It’s a little bit different by territorial, but this gets into very obscure economic definitions related to companies that may be registered in one country but have activities in another country and so on. Whereas consumption emissions essentially are a carbon footprint, so a consumption emission will look at the emissions within the country; they will take out the emissions to produce products which are exported, but they will include the emissions in other countries to produce emissions from products which are imported. So it basically matches to a carbon footprint at the very aggregated national level. They sort of give different information. They allocate emissions a different way and give different information, and that’s why they’re both quite useful.

Ariel Conn: So a lot of what you’re talking about sounds complicated. I guess I’m curious: how much uncertainty is there in what you’re doing? How confident are you in a lot of the numbers that you work with and how much uncertainty are we dealing with?

Glen Peters: The uncertainty, it’s always a relative question. So when you go to a rich, well developed country, the uncertainty in these estimates of emissions may be let’s say a few percent. If you go to a developing country like China or India or something like that, you may get 10, 20% uncertainty. If you go to a least developed country, so very poor countries where they have very poor statistical infrastructure, the uncertainty may be even higher. But generally these countries don’t have much emissions overall, so their high relative uncertainty doesn’t really affect the global total that much. But there’s also this question then of how does uncertainty change? Is it so uncertain that we can’t tell if a country’s emissions are going up or down or anything like that?

And I think the uncertainty in both developed and developing countries is low enough that we have a good idea what emissions are doing in terms of trends — whether they’re going up or down or whatever. So there is uncertainty; it’d be much nicer if the uncertainty was lower. But I don’t think the uncertainty is problematic in the sense that it’s too large that we could avoid acting or something like that. So certainly the uncertainty is low enough that we can make good policy with the data.

Ariel Conn: And when you talk about, “We can figure out whether or not emissions are going up or down,” what is happening with emissions right now? Are they going up or down?

Glen Peters: They’re going up — although that needs a little bit of nuance, I suppose. Over the last decades, emissions have been going up one, two percent per year over a long term trend. We did have this little bit exciting period — 2014, ’15, ’16 — where emissions were more or less flat and everyone got very excited about that. But since then — 2016, ’17, ’18, probably this year — emissions are rising again. So the last 10 years emissions have gone up about one percent per year. Overall, emissions globally are going up. There was a slight slow down, but I think that was more of an aberration than anything else. And then when you go to the country level, the general rule of thumb is the developed countries’, the wealthier countries’ emissions are flat or going down; and in the developing countries, where they’re growing their economies, emissions are generally going up.

Ariel Conn: That was something that I thought I was picking up on in some of the stuff that I was looking at, which is it seems like growing an economy increases emissions just generally. Is that the case?

Glen Peters: It doesn’t have to be the case, but in the past that’s generally been the case. So when you grow your economy, you grow your energy consumption. You have some efficiency improvements, but generally the growth in the economy is faster. So energy use will generally go up, and when energy use is going up — if you’re producing energy with fossil fuels: coal, oil, or gas — then your emissions will go up. So broadly speaking, if the economy’s growing, it’s putting upward pressure on energy use and upward pressure on emissions. Countries where emissions have gone down — so US is an example, the EU is an example — they also have been able to slow or stop the growth in energy consumption. Their economies are growing slow enough so that the efficiency improvements are greater than the growth and energy consumption has gone down slightly.

And when your energy consumption is going down, then it’s easy to replace, let’s say, coal with renewables. You don’t have to expand your energy system. So instead when you put out solar or wind, that solar or wind can displace existing fossil power plants, like coal, instead of adding on top of a growing energy consumption. So there’s a general pattern that if you have got slow enough economic growth, you can slow down your growth in energy consumption, then you can get your emissions to go down. If you’re growing your economy fast, then your energy consumption is going up, and it’s very hard to build solar or wind fast enough to be able to produce energy for that growth. Overall, though, growing the economy puts upward pressure on emissions.

Ariel Conn: Part of the Paris Agreement relies on negative emissions. And I was hoping you could talk quickly about what that means and whether it seems feasible.

Glen Peters: Mainly we’ve been talking about historical emissions: so what’s happened in the past. But if we want to keep temperatures below, let’s say, two degrees or one and a half degrees or something like that, then we need to reduce our emissions quite dramatically. The emissions would need to go to zero. And emissions will actually need to go negative, so that means that we’ll have to take more carbon out of the atmosphere than we put in. So when you think about it in terms of the carbon cycle, we already put in carbon to the atmosphere and then take out some carbon naturally through forests and oceans. But most of these scenarios that are consistent with different temperature goals, like two degrees or one and a half degrees — you have to artificially take carbon out of the atmosphere. And this is what’s called negative emissions.

So you can do these negative emissions in different ways. You can grow a lot more forests. If you take cropland and turn it into a forest, then that will take up some carbon. You can use it with bio energy, where you burn the bio energy but then capture the carbon before it goes back into the atmosphere and then bury the carbon. This is called bio energy with carbon capture and storage, which is quite a weird technology in a sense. Or you can have direct air capture, which is basically a machine that sucks carbon straight out of the air. It takes a huge amount of energy, but you can suck carbon directly from the air.

A combination of these technologies — there are another few different types of technologies at the smaller scale — you’re able to take carbon out of the atmosphere in theory and help get stabilized temperatures at two degrees or something like that. So whether I think this is realistic, it’s important to point out a couple of things. So even if you want to reach some of these aggressive climate targets, you need to reduce your fossil emissions anyway. And then on top of that, you need to take some carbon out of the atmosphere, so you need some negative emissions. It’s a question of how much we can have and how much do we need. I have no doubt that we’ll have some negative emissions, but whether we can have a sufficient scale that it would be really meaningful at a global level, I think you could debate about.

There’s a whole range of issues related to using land for bio energy, or for forests even — then that’s going to put new water stress, new fertilizer stress, etc. It’s going to cause additional stresses on the land that you may not want; issues with food security, that’s a huge issue if you’re using cropland and pastures for forests or for bio energy. So there’s a whole range of issues that will make it hard to see those technologies come at scale. But according to most model runs, we need to figure out how to make this technology work. So we just basically have to find a way.

Ariel Conn: I mentioned not wanting to blame per se, but what countries right now are the biggest emitters?

Glen Peters: In a sense, that’s a data question, right? So who are the biggest emitters — it’s an obvious question. China is the biggest emitter, in aggregate terms: it’s about a quarter of global emissions. US and the EU — European Union — are both similar, around about 12 or so, 13%; don’t have these numbers on the top of my head. India is much smaller, it’s around the 5, 6% mark, from memory. So those four countries — region for Europe — they account for about 60% of global emissions. And then there’s another 100 or whatever, 150 countries, that are the rest; but even though those countries are smaller, they are all important. Everyone needs to reduce their emissions.

Just because a country’s big doesn’t mean that a country that’s small shouldn’t do anything. But also it’s important to point out that even though, let’s say, China and India are two of the biggest emitters, they also have very large populations. So if you look at it at a population-adjusted level, it’s quite different. The US and Australia will be two of the worst. Europe is, on a global average, not so bad. China actually has higher per capita emissions than the global average and than Europe, so China is certainly no saint when it comes to per capita emissions. But India does have quite a lot lower per capita emissions than many other countries. And it’s a growing economy; there’s a lot of people in poverty; they have made huge strides to get people out of poverty. But still, they need to grow their economy, give people the energy that they need to have a decent life. And so they’re going to have increased pressure on energy use, therefore emissions in the future.

So let’s say in Europe and in the US, we’ve reached a high standard of living where — a luxurious position where we can actually stabilize and even reduce our energy use. But that sort of has to happen at a faster speed to give more space to countries like China and India to develop. But also if they just develop on a high carbon pathway by using coal and so on, then all climate targets that we’ve ever dreamed of will just be blown out of the water. So China and India and other developing countries can’t repeat the mistakes that the rich worlds made in having a fossil fueled growth. They will need a solar and wind powered growth or different technologies. Otherwise we’ll certainly blow any climate budget that we might have.

Ariel Conn: I hear a lot about China’s coal use. How bad is it actually? And what are they doing that’s right? What are some of the steps they’re taking that we want to see more of? And same with India, I guess.

Glen Peters: China is, I think, more than half global coal use. The Chinese energy system is basically based on coal — very coal dependent country. And that’s fueled a lot of its growth. And a lot of the coal infrastructure in China is quite young, which is more of a problem. So the US has a very old infrastructure; it’s easy to retire old coal power plants. China already has an energy system very heavily dependent on coal. India is the same; they both have the same problem. So China is very dependent on coal, although China is taking a few steps. How many of these steps they would have taken anyway you could discuss, but let’s say China’s got a huge growth in solar and wind. A lot of the caustic lines in solar and wind around the world are because of the production capacity of China.

China’s made leaps and bounds in deploying solar and wind, but still their coal use is, let’s say, stable — maybe growing a little bit. But it’s not so related necessarily to the solar and wind. So China is certainly doing a lot on the solar and wind side, but it’s maybe not affecting energy use as much as some people would like to think. There’s a lot of local air pollution problems in China, and so there’s a lot of activity trying to shut down inefficient power plants or inefficient factories to reduce the air pollution, but this also has climate benefits. And China is generally trying to shift its economy to one that’s more based on services and less based on manufacturing products, which are then exported.

One big issue with China is they have a huge investment program, and when the economy’s quiet, they generally try to invest in new infrastructure. So people may have heard about all these, let’s say, ghost cities that they have in China, where they’ve built new cities but basically no people live in them. These are a way of sort of stimulating the economy, but it’s also very bad for emissions. So China is taking some very positive steps, but also there’s many of the old infrastructure that is continuing along. So China’s emissions growth has slowed down dramatically, but still it’s a question mark of whether it’s sort of peaked or whether it will keep rising slightly into the years ahead. China’s a very interesting place where there’s so many contradictions going on.

Whereas India is much more clear patterned. Their stage of development is a little bit behind China. They’re growing their economy more strongly. A lot of coal still going in, although it’s starting to slow down; a lot of renewables, particular solar, going in. Whether that’s fast enough to meet their incremental energy needs is a question, but certainly India’s making some progress in terms of deploying solar and wind; slowing down a little bit on the coal side, but emissions are still growing very strongly.

This is sort of a pretty common picture you have when you look at different countries. Their stage of development has a big role to play in what their emissions are, because you’re trying to put up your infrastructure, you’re trying to build power plants and roads and bridges and factories and schools and hospitals. And when you’re doing those things, then your emissions will go up.

Ariel Conn: What policies would you most like to see enacted to help address these problems?

Glen Peters: This is the most common question that I never have a good answer for. There’s the very standard answer that you can give, which is basically you need to have a price on carbon, policies to reduce carbon emissions. But it’s very easy to say that; it’s very cheap to say just have a carbon price and everything will be okay. In reality, there are political realities, there are social realities, there are elections. So it’s not very easy, necessarily, to put a price on carbon. So I’d just say, broadly speaking, you just need to roll out whatever policies you can find that you can get through your government or whatever that will help emissions go down, or encourage emission reductions in the future through investment in innovation and things like that.

You will find a patchwork, I think in any country, of different policies — based on what’s possible to achieve in different countries. So different sectors will have different policies. Europe is a classic example, where certain sectors are within the emissions trading system; certain other sectors are outside of that system, but then they have other policies which address them. Although not all sectors are treated equally in the sense that some sectors get less attention than others. So that’s certainly a problem. Yeah, there’s maybe no answer, but basically to implement whatever policies you can implement.

Ariel Conn: Maybe this is an equally hard question, I’m not sure. What actions do you think are most important for individuals to take?

Glen Peters: For individuals, it’s quite easy, in a sense, to a certain degree. Aviation is probably the number one. So if you go on a plane, that’s probably going to be the biggest part of your footprint. Maybe if you have one or two flights within your country, let’s say the US, in a year, then it might be similar to your driving emissions if you drive a car. But if you’re taking international flights, or if you fly more than once or twice a year, that will completely dominate your carbon footprint. So there’s a very big scope for individual behavior there. 

The next one on the list would be food: particularly red meat consumption has a huge footprint because of the methane emission when cows and sheep and so on basically burp. Just slight shifts in your diet can have a big impact. You don’t necessarily need to become a vegan or something like that, but slowly shifting your food patterns away from red meat to a more plant based diet, and also white meats instead of some red meats, and so on: that can make a big difference.

Driving a car is pretty important, sometimes underrated. Each individual car trip might be quite small, but you might take hundreds and hundreds of small car trips every year — so when you add them all together, it’s actually quite significant. So individuals have quite a bit of scope on things that they can do, but then they can only go a certain distance. So with the car transport and the aviation, if you don’t have alternatives — if you can’t take a bus or you can’t ride or it’s too far or a whole range of other reasons — then you may not have the capacity to be able to change your behavior. Also electricity, for example: if you don’t have your electricity system cleaning up over time, then that’s a little bit out of your hands, so there’s not awfully much you can do. So the individual behavior is somewhat also limited by government action as well. So I guess you could say individuals could then lobby governments to do better action. But clearly aviation, food, transport, particularly driving, etc. will be big items.

Ariel Conn: All right. And then looking at all these issues that we’re dealing with, what gives you hope?

Glen Peters: The hope is sort of abstract, but there’s pleasant surprises. We have had some pleasant surprises, let’s say with solar or batteries or things like that. But I think we need some pleasant surprises, so things that actually turn out better than we had hoped, or maybe behavioral change will become more accepted than we hoped, or maybe voters in different countries will change their habit and vote differently. It’s a little bit hard to sort of pinpoint exactly, but some things might happen that we didn’t expect to happen, and after that things might happen much more easily and faster. So I’m hoping for some pleasant surprises.

Ariel Conn: I think that’s everything on my end. Is there anything that you think is important that we didn’t get into?

Glen Peters: I think you’ve covered pretty much everything there is to do with emission statistics. Some are quite technical, but you’ve touched on just about everything, I think.

Ariel Conn: All right. Well, thank you so much.

Glen Peters: It was a pleasure, thank you.

Ariel Conn: So far on the Not Cool podcast, we’ve most talked about the impact of carbon, with only some mention of greenhouse gases more broadly. But for as large as the carbon impact is, it’s not the entire cause of climate change. On the next episode of Not Cool, we’ll be joined by Ilissa Ocko, a Sr. Climate Scientist for the Environmental Defense Fund, who focuses on many of those other gases and aerosols that end up in the atmosphere and impact our climate.

Ilissa Ocko: We know around 90% of the excess heat that has been trapped has gone into the oceans. And so then that warming that came from methane in the atmosphere is now in the ocean, where it can last a lot longer. So even though methane is a short-lived climate pollutant, it doesn’t have short-lived impacts.

Ariel Conn: As always, if you’ve been enjoying these episodes, please take a moment to like them, share them, and maybe even leave a good review. I hope you’ll join us for episode 19 with Ilissa.


Not Cool Ep 17: Tackling Machine Learning with Climate Change, part 2

It’s time to get creative in the fight against climate change, and machine learning can help us do that. Not Cool episode 17 continues our discussion of “Tackling Climate Change with Machine Learning,” a nearly 100 page report co-authored by 22 researchers from some of the world’s top AI institutes. Today, Ariel talks to Natasha Jaques and Tegan Maharaj, the respective authors of the report’s “Tools for Individuals” and “Tools for Society” chapters. Natasha and Tegan explain how machine learning can help individuals lower their carbon footprints and aid politicians in implementing better climate policies. They also discuss uncertainty in climate predictions, the relative price of green technology, and responsible machine learning development and use.

Topics discussed include:

  • Reinforcement learning
  • Individual carbon footprints
  • Privacy concerns
  • Residential electricity use
  • Asymmetrical uncertainty
  • Natural language processing and sentiment analysis
  • Multi-objective optimization and multi-criteria decision making
  • Hedonic pricing
  • Public goods problems
  • Evolutionary game theory
  • Carbon offsets
  • Nuclear energy
  • Interdisciplinary collaboration
  • Descriptive vs. prescriptive uses of ML

References discussed include:

The behaviors are just not on the same scale at all. The amount that you emit from taking a flight is just orders of magnitude more than almost anything else you’re doing in your life. Being able to actually track that and understand it could be very empowering for individuals to change their behavior in a meaningful way.

~ Natasha Jaques

Ariel Conn: Hi Everyone. Ariel Conn here with episode 17 of Not Cool, a climate podcast. Today, we’ll dive into Tackling Climate Change with Machine learning, Part 2. On our previous episode, we heard from four of the 22 authors of that paper, and today we’ll hear from two more. Tegan Maharaj and Natasha Jaques will talk about how machine learning can be used to help us improve our own carbon footprints, how it can be used to improve climate policy, and much more. 

Tegan’s most recent research aims to bring together the fields of deep learning and theoretical ecology. She has several active projects in ecosystem modeling with deep networks, including work collecting datasets, in multi-agent RL, counterfactual inference, and meta-learning. In January 2016 she began a PhD focused on deep learning research at Mila at the University of Montreal, and among other things, she recently co-organized a workshop at ICML call Climate Change: How can AI help? 

Natasha is finishing her PhD at MIT where she researches how to improve the social and emotional intelligence of AI and machine learning. She has interned at Google Brain, DeepMind, and was an OpenAI Scholars mentor. She received an honourable mention for best paper at ICML 2019, a best paper award at the NeurIPS ML for Healthcare workshop and was part of the team that received Best Demo at NeurIPS 2016.

Natasha and Tegan, thank you so much for joining us.

Natasha Jaques: No problem.

Ariel Conn: You’re both authors of this “using machine learning to tackle climate change” paper, which is a huge paper. We’ve interviewed some of the other authors as well. And I mean, my first question for both of you is just how did you get involved in working on this paper?

Natasha Jaques: Well, I’ve always been wanting to participate more in helping the climate in whatever ways that I can, because I do think we’re facing a global climate crisis, and hopefully my machine learning expertise could be useful for that. So this is my first foray into working in this area. I was recruited by the first author, David Rolnick. I was asked to work on my section because my work in the Media Lab relates a lot to interpersonal and social aspects of human communication.

Ariel Conn: All right. And Tegan?

Tegan Maharaj: I met David at a lunch at the NeurIPS Conference organized by David Rolnick and various people from MILA, where I am a PhD student. We started talking there and — with Priya Donti, one of the other main authors on this paper — me, David, and Priya sort of brainstormed some ideas both for a workshop and a paper; and it all happened. I think it was basically David’s brainchild and anybody he ran into who he thought could contribute well was brought on board.

Ariel Conn: Awesome. Before we get any farther, it’s probably fair to assume that most listeners understand what machine learning and reinforcement learning are, but if you could just quickly explain what those terms mean and how they’re different.

Natasha Jaques: Sure. Machine learning broadly tends to mean like the automatic recognition of patterns in data, so maybe discovering clusters of similar data or predicting trends given a bunch of past data. Reinforcement learning could be considered sort of a sub area of machine learning, but it really focuses on where you have an AI agent that’s trying to interact with the environment. The agent takes an action, and the environment gives back some type of reward. The agent is trying to optimize for that reward, but it’s not doing it greedily. It’s not just trying to say, “I want to get the maximum reward I can right now,” but it’s trying to do sort of long-term planning to achieve the most possible reward over the course of the future. So we think about it as sequential decision making. And that’s why it differs from just one step prediction that we see typically in the rest of machine learning.

Tegan Maharaj: I think Natasha pretty much covered it. The way that I usually describe machine learning, as opposed to any other computer algorithm that you would encounter: the fact that it’s learning means that rather than having hard-coded rules for how to behave — like when you click this button, the algorithm will do this thing — the algorithm is trained from lots of examples how to sort of behave in a certain way so it can recognize patterns that are sort of fuzzier than the rule based systems that people used before machine learning became very popular. And the reason that this is difficult and took a long time is a lot of data, a lot of examples are required to train these kinds of algorithm. Techniques for doing that well took a while to figure out.

Ariel Conn: Okay. I’m really excited to have both of you on because we’ve been doing this podcast for a few weeks now, and for the most part it’s talking about what climate change is and why it’s so bad, but we’re sort of limited in solutions. And so we do get into a lot of the solutions that are covered earlier in the paper, but one of the things that I really liked about your sections is that you look specifically at what people can be doing at an individual level and what we can be doing at a societal level. 

For listeners, Natasha was the author of the “Tools for Individuals” section; Tegan is the author of the “Tools for Society” section. So we’ll be asking them both questions about their sections but, as I’ve told them, hopefully they’ll also both be interjecting with their own thoughts, even if it wasn’t technically their name attached to the section. So Natasha, let’s start with you. Yours is tools for individuals. I really love the idea of using machine learning to calculate individual carbon footprints, which is one of the things that you talk about. Can you first explain some of the ways that that could be done?

Natasha Jaques: If a person is willing to give us some of their data, we can do simple things to extract information about their personal carbon footprint. For example, it could extract information about what flights you are taking from your email and automatically calculate the carbon footprint of that, or of the groceries that you’re buying. You can hook it up to your ride sharing apps; we can calculate the carbon footprint of the amount of Ubers that you’re taking; and then potentially present this to you in a way that makes it very easy for you to see, what are your most high emitting behaviors, and focus on the things that really matter if you want to reduce your carbon footprint.

What we learned from this is that the behaviors are just not on the same scale at all. The amount that you emit from taking a flight is just orders of magnitude more than almost anything else you’re doing in your life. Being able to actually track that and understand it could be very empowering for individuals to change their behavior in a meaningful way.

Ariel Conn: You talked about creating apps that can tap into my email and track emails I’m getting. In the paper, you also talk about ways that commercial systems could be implementing this. I was hoping you could talk a little bit about some of the tradeoffs between, say, me adding an app, or Uber or Delta or some other company tracking this — what are some of the tradeoffs between me having more control of it and a commercial system setting it up?

Natasha Jaques: That’s a great question. For the individual, obviously, if you want to give up some of your data, you have to give up some privacy. That’s a concern. We do have better and better machine learning algorithms that can work on device, so you actually may not have to worry about privacy as much; but privacy is a concern. But then with doing this from a big institution, like let’s say we wanted a grocery store that could print the carbon emissions of every item you buy on your bill: well, that takes a lot of buy in from the grocery store, and it’s not clear that they will be super motivated to do this. To the extent that those institutions aren’t willing to put those programs in place, it can be more individually empowered to build those on their own or buy into those.

Ariel Conn: I guess if we could get a combination of both, it seems like that would be ideal. Is that your take?

Natasha Jaques: I think so. I mean, the more information that’s available, the more it’s going to help the individual to make better decisions.

Ariel Conn: Are there examples of applications that have already been designed that we can start looking into, or is that something that you’re hoping to motivate ML researchers to create?

Natasha Jaques: People are already starting to work on this. There’s a few apps that are starting to come out that we reference in the paper; if you’re curious, you can go check them out. And so, it might be something that you could see on your phone within a few months.

Ariel Conn: Awesome. Moving on in your section, one of the things that I thought was interesting as well is that it turns out our homes account for 30% of global electricity consumption. To what extent did you look at this on a global scale where we can say homes account for 30%, versus, say, homes in the US?

Natasha Jaques: I do have the US figure for you if you’re curious.

Ariel Conn: Yes.

Natasha Jaques: I think residential electricity usage in the US is actually 21.8 — that’s a study from 2014 from the US government. I tended to try to look more at global figures, but I think you could find both in the paper if you were curious.

Ariel Conn: Were there countries in which homes do better or worse? I’m actually surprised that you’re saying that — if I’m understanding what you’re saying correctly — that homes in the US are below the 30%?

Natasha Jaques: It’s a complicated question because it depends on how much energy different industries in the rest of the country are using, so it’s going to vary widely.

Ariel Conn: Okay. We’ll move on from that. You also say that standby power consumption accounts for 8% of residential electricity demand, and if I did my math right, that means that the standby power that we’re using in our homes — so that’s the power that we’re not actually using; it sounds like that’s just stuff that’s plugged in. Is that correct?

Natasha Jaques: Right.

Ariel Conn: That actually is accounting for 2.5% of electricity consumption overall.

Natasha Jaques: It’s pretty surprising how much standby power can consume. There’s an interesting reference that shows that a laser printer that’s just plugged in, but sitting idle, is actually consuming 17 watts an hour, which is apparently the same consumption of a fridge freezer. So it’s just massive. If you actually look into this resource a little bit more, big screen TVs, flatscreen TVs, a lot of electronic devices, even random things like pottery wheels are incredibly power consumption heavy when they’re not in use.

There’s a lot of these devices that people may leave plugged in that they’re just not aware of at all how much energy they’re consuming. And similarly if you have a second fridge downstairs that you don’t really use very much, that can be very expensive in terms of power. A nice role we see for machine learning to play is doing this energy disaggregation and identifying which devices are consuming the most energy in your home and at what times, and making this information available to the consumer so they can make smarter choices about what they’re plugging in and when.

Ariel Conn: Wow. So even without machine learning, have you found that you’re unplugging things more?

Natasha Jaques: Well, I don’t have a laser printer at home, but if I did, I’d be unplugging it.

Ariel Conn: Right.

Natasha Jaques: Right. Yeah.

Ariel Conn: Okay. And then, so how do machine learning systems like that work?

Natasha Jaques: There are a couple of different really interesting options that you could do. One of the most promising solutions seems to be to plug in a device at the main electrical connection from your house to the rest of the grid. And then you can actually use that aggregated energy signal, in combination with more and more sophisticated machine learning techniques, to disaggregate that signal into a time series of which appliances are coming on at what time, and how much energy they’re consuming. And so by making that information available to the homeowner, they can make better decisions about this. And then you can even go one step farther, and you can start doing something really cool — which is, if your devices are outfitted with this capability, you can remotely turn them on and off at the appropriate times to minimize your power consumption.

Imagine that you want to be able to charge your electric vehicle at the right time so that you’re actually using sustainable energy. If your grid uses a lot of renewable energy, like solar and wind, often the grid still needs to have backup power that’s actually pretty carbon intensive. Maybe there’s like natural gas or coal backup power that needs to come on if it’s a cloudy day or there’s no wind. You can actually use machine learning to predict when the energy being supplied by the grid is the most green, and turn on your devices at that time. So that could really help reduce emissions.

Ariel Conn: These systems that you’re talking about would be connected to the individual home? Or would they also be connected to the power grids?

Natasha Jaques: Yeah. My part of the paper focused on devices in the individual home, but we cover optimizing power grids more broadly in different sections of the paper.

Ariel Conn: So what you’re talking about — again, it would be an instance where the data could still be kept private for the individual.

Natasha Jaques: Yes, exactly.

Tegan Maharaj: I think you don’t even have to have any climate-related motivation to want one of these things. You could just want to save money and this would still be a good thing to want in your home.

Natasha Jaques: That’s exactly right because it turns out that when the grid is the most green, the energy is also the cheapest. So it saves the consumer a lot of money to actually be more green.

Ariel Conn: Have you found that in general, does it tend to be cheaper? Or are you finding there’s sort of a balance, where some things are more expensive — to implement these systems, but in other areas you’re saving money?

Tegan Maharaj: I would say in the short term it’s often the case that greener or climate friendly solutions are harder to implement because they’re a change to the status quo, so that makes them a bit more expensive. But in the long term — even long term being like over a couple of years, and certainly in the long term over 50, a hundred years — virtually all of the climate and environmentally friendly solutions just make economic sense. They’re more efficient in terms of resources; they maintain our resources for a longer time so that future generations can use them better; and they let systems sort of be more efficient. It’s really a win-win if you look at it over a longer time horizon instead of being very myopic and only caring about your profits in the next quarter type of thing.

Natasha Jaques: Nice.

Ariel Conn: Yes, thank you. Continuing with the tools for individuals, one of the things that I’ve read about, unrelated to machine learning, is just that energy companies, often when they send out the electric bill, they will include how a household’s energy usage compares to their neighbors — and that often people will modify their usage as a result of what they’re seeing as this comparison to their neighbors. And it seems like in one of your sections, Natasha, that you’re talking about taking this a step further and targeting specific households with messages that are more directly applied to them in order to help them modify their energy usage. Is that correct, or can you explain how that works?

Natasha Jaques: Sure. The thing you mentioned about showing people what their neighbors are consuming, like, “Oh, it turns out you use 10% more energy than your neighbor,” is very effective. This was actually a startup called Opower that did that and showed how effective it was. That’s actually quite interesting. And it’s very cost effective to reduce energy consumption rather than try to produce new energy. So they basically did this in the cheapest possible way, even cheaper than building any new power plant, so that’s kind of cool.

But with respect to using machine learning to identify certain households that we talk about in the paper, what we’re trying to describe there is that it turns out people are very, very different in their willingness to pay for and be motivated by climate programs. In one study, it found that some consumers are willing to pay any price to reduce the emissions of their energy consumption — they’re very insensitive to cost; and yet there was another group that was willing to pay zero. So they care absolutely zero about the emissions of their energy consumption.

What machine learning can help us do is use clustering and demographic information to try to find those people that are actually motivated and care about these programs and try to provide them with resources that allow them to participate, rather than trying to waste time trying to recruit everyone into a program like that.

Ariel Conn: How would a machine learning system like that work? How would it identify the groups who are more likely to care about this?

Natasha Jaques: You can use information about a person’s household energy consumption, their location, size, their demographics — things like this.

Ariel Conn: Okay. And then I asked this with one of the earlier questions, but we’ve talked about a few more machine learning systems here: what already exists? What can people already start doing? And if machine learning systems don’t exist yet for some of these, what are the barriers to their creation?

Natasha Jaques: There’s definitely a long history of, for example, energy desegregation research, and the ability to identify which appliances are turned on from an energy signal. There’s also research papers on this stuff about identifying different households and modeling their behavior. A lot of these I don’t think have made it into products yet. We’re starting to see these apps that I mentioned come out, but what we really need — what’s a barrier, and the real motivation for doing this paper — is we just need more people to be working on this. We’re really hoping, through this paper, to motivate people to both provide data sets and motivate machine learning researchers to bring their expertise to these problems and develop better and better algorithms.

Ariel Conn: And then also, again, we touched on the issue of privacy a little bit with some of the individual questions I was asking — but more broadly, as you’re talking about applying machine learning systems to individuals and individual households, how can we be ensuring that people are able to maintain their privacy?

Natasha Jaques: A lot of the systems that I’ve been talking about, especially for like tracking your individual carbon footprint or optimizing the appliances in your house, are really up to the consumer to opt in. If they’re excited about this and they think that this would provide them some value, then they might be willing to provide their data. But it’s definitely not something that you would compel someone to give you their data. The nice thing is that machine learning techniques which allow an individual to maintain their privacy by keeping the data on the device are becoming more and more mature. Federated learning is something that a lot of people are working on, which allows you to just make predictions with the data never leaving the device.

Ariel Conn: And so, a last question that I had was based on me reading the paper as opposed to talking to you — and talking to you and getting some of these better explanations, I don’t think it applies as much, but I’m going to ask it anyway, just in case anyone else reads the paper and has a similar thought. And that was that some of these ideas actually seem a little bit based on sort of psychological manipulation, trying to convince people — using data about them, trying to convince them to make these different decisions about ideally improving how they’re making decisions about climate change. And to a certain extent, as someone who would like to be making better decisions for the climate, I would actually value this. But, I mean, psychological manipulation just sounds terrifying in general. So I was curious, how do you ensure that we’re creating machine learning systems that, I guess, just don’t have that creepy factor?

Natasha Jaques: I’m glad you asked that question because we absolutely are not proposing to do any sort of psychological manipulation whatsoever. That’s not on the table. We want to make sure that we’re proposing acceptable solutions to everyone that people aren’t going to find problematic in any way. We really want to make sure people have autonomy to make their own decisions. And actually what we’re trying to do here, really, is provide consumers with just better information so that they can make more informed decisions, and it can empower them to feel like they have the ability to reduce their behaviors, if they want to, in the most effective way.

So we’re about solutions like using machine learning to better visualize data, because climate change is a very complex topic, and it may be hard to understand all the different sources of information. We’re talking about machine learning that can predict flood risks in various areas, that people could use this when they’re buying a home. And then of course, all the systems we just talked about that help you understand your personal carbon footprint or help you optimize the energy use in your home; so, serving the needs of consumers, as well as helping them to be more informed.

Ariel Conn: Excellent. The final followup question that I have is, you use the example of a grocery store could print out the carbon footprint of whatever I just purchased so that I can have a better idea of the impact of the food that I’m eating. One of the things that I’ve found is that it’s just so incredibly complicated to try to figure out what the impact, the carbon impact, of all these different decisions I’m making is. Do you think that the suggestions that you’re making here can ultimately help us track all of these different super complicated systems? Is that how this can be used?

Natasha Jaques: Well, it is really complicated, and I think it can be very overwhelming. We really see these systems as a way to simplify that for an individual so they can understand what of their behaviors actually really matters, and what are just a tiny, tiny fraction of the emissions of a different behavior. So if you think about optimizing some of your groceries: now, beef consumption we know is actually a pretty significant part of your carbon impact, but some of your groceries may be a pittance compared to taking a flight. 

There can be kind of an identity politics around climate change that there doesn’t have to be. We shouldn’t make it that if you have to care about the climate, you have to be extremely strict with yourself on every front, and you can’t ever use a plastic bag or you’re not a true climate believer. Having something like that could be even deterring individuals from feeling motivated and encouraged to change the parts of their behavior that do matter. Distinguishing meaningful factors for reducing emissions could be really important.

Ariel Conn: I think that’s really valuable. I definitely see this idea of, if you aren’t perfect, you’re being a hypocrite and why even bother?

Natasha Jaques: Yeah, and that’s just harmful. That’s not helpful at all.

Ariel Conn: No.

Tegan Maharaj: To that point, what you were saying about it being so complicated to predict one number for the carbon emissions of this banana, or something like that?

Natasha Jaques: Yes.

Tegan Maharaj: I think an important part of scientific communication is communicating uncertainty about where numbers come from. Something like a plus or minus five or whatever on the number that you give could also be very helpful. But I think with the knowledge we have about global supply systems and about the climate at this point, we can offer numbers that are much better than nothing. We are not going to be totally off base in the numbers that we’re estimating. There’s uncertainty, but there is also good information out there that I think should be provided to people.

Ariel Conn: Yeah. I think that’s actually been another really interesting problem with the climate change debate, for lack of a better word, is this idea that it seems like a lot of people who don’t understand how science works are looking for certainty. And that’s just not something that can be — it doesn’t exist. Even things we’re very certain on still have some level of uncertainty.

Tegan Maharaj: Right. There’s this difference between, “I’m not sure whether this is going to happen,” versus, “I’m not sure if this is going to happen at all,” kind of thing. We can be very certain that something bad is going to happen. Maybe we don’t know if it’s going to be 10 millimeters of rain, or 13, or 14, or 25, but there’s a difference between not being able to forecast the exact weather in a certain place on a certain day, and not knowing if the weather on average is going to be snow versus sun for that day.

And the uncertainty — when we say uncertainty in English, that means, “I don’t know, I have no idea.” But that’s not what it means in science. It means, “We don’t know the exact number,” and those things are very different.

Ariel Conn: I think that’s a really important point. I’m glad you brought that up because it’s definitely something that I see in the discussion around climate change, is that people don’t understand how scientists use uncertainty.

Tegan Maharaj: Another thing that people mention a lot is that most of the uncertainty in climate models is not symmetric. Let’s say we’re estimating that global temperatures are going to rise by 1.5 degrees celsius. The uncertainty around that number is on the upper end, not on the lower end. So, there’s this skew toward, “Okay, we’re not sure. It could be way, way, way, way, way worse.” We’re not sure, but definitely it’s going to be pretty bad. And it’s not like we’re sure it’s going to be 1.5 exactly, but we are sure it’s going to be something. There’s no chance that everything just stays the same.

Ariel Conn: And there’s no chance that it decreases?

Tegan Maharaj: No.

Ariel Conn: Okay. Tegan, I think this is a good time to transition into the questions about your section. So moving from this idea of how we can help individuals to also recognizing that there’s only so much that individuals can do, and society as a whole — and especially politicians and policymakers — need to start also taking action.

My first question for you is, in the very first part of your section you talk about tools that can be used to help understand how the public would respond to different policies. Could you explain what that would look like, and some examples of how machine learning could be used for that?

Tegan Maharaj: Sure, yeah. I think machine learning is already being used by a lot of social science, and political science, and certainly economics researchers. And in the context of understanding public response to policies, I think most of the work that’s done is more retrospective. It’s not in planning an actual policy rollout in the government or a political party that they’re using much machine learning to see how the public will respond. It’s more like, this type of policy — for instance, pricing carbon emissions and taxing people based on them, or something like that — has been tried in these different scenarios; how can we analyze the results of those different roll-outs and see how we can do better? 

And if those results are analyzed quantitatively — maybe with machine learning, maybe with descriptive statistics — and then considered holistically with other factors: like how constituents of an area — what they care about, what the concerns of local businesses are, et cetera, et cetera, et cetera. So machine learning is just one part of policy analysis, but it is an increasingly important part, I think, as more data becomes available.

And some of the concrete things that I think policy analysts are using more and more are things like scraping social media or the internet for a lot of text data, where people are talking about a certain topic, and then using natural language processing techniques like sentiment analysis, which predicts what people maybe liked or disliked, or whether they feel generally positive or generally negative toward something; or maybe it’s not a number, maybe it’s categories like they support or don’t support a certain type of legislation. So using this kind of natural language processing approach, policy analysts or social scientists can analyze huge volumes of data that wouldn’t be possible with a person going through all of these tweets. And that kind of information can really help social scientists understand how people view something, and aggregate their preferences in a way that is more data-based than having small focus groups can achieve.

Ariel Conn: Okay. And so to clarify, it sounds like so far these systems have been used to help understand responses to something that has already occurred. One, is that correct? And then two, moving forward, would you also then expect to see policymakers applying this information they’ve already gathered towards developing new policies? Or do you think it’s mostly useful for better understanding and responding to public opinion?

Tegan Maharaj: I think it is already used for at least informing people’s opinion about what to do next, like for a policymaker to look at aggregated data about what policies have been effective or not effective in the past. Of course, it’s information for them, it’s going to inform their decisions about future policies. But I don’t know of any current machine learning techniques that are used to explicitly optimize a policy for deployment in the government.

The thing that’s difficult there is that you have to represent the space of possible policies in something that a computer can understand. You have to be able to write it down mathematically or in a programming language. And necessarily when you do that, you miss things. So people do this and then they look at how, for instance, in multi-agent RL, different agents would interact, and giving different policies in that environment, how that would affect the different agents in an environment.

People also use multi-objective optimization to try to optimize for different objectives like reducing climate emissions while also optimizing profits and maximizing maybe the amount of fresh air, or something, other things that stakeholders care about. But I don’t think we’re at the point where we want to just blindly apply a machine learning system to this because in writing down formally these descriptions of systems to be optimized, I’m repeating myself, but we necessarily miss things. You have to consider them in their environment with a lot of factors that can’t easily be encoded in math or in a programming language. Really, machine learning is just a tool. It’s a tool that policymakers can use, and it’s only one aspect of what they do.

Ariel Conn: Regarding it being a tool that policymakers can use, to what extent is that actually the case, versus do policymakers need to be working with other researchers who specialize in machine learning? Are we developing systems that a policymaker can then take and apply to scrape social media themselves? Or do they need help?

Tegan Maharaj: I would say there are a lot of systems at this point that can be applied or deployed by somebody who doesn’t have a lot of machine learning expertise. But both for people who have a decent degree of machine learning expertise and total non-experts, I think — like any tool – machine learning can be used improperly. People who use it have a responsibility to understand at least a bit how it works so that they make sure it is not doing things like amplifying biases that exist in the data in a way that is dangerous for stakeholders, or targets minorities, or something like that; or giving an algorithm more a sway in a decision-making process, when there may be considerations that the algorithm can’t make because those things were not encoded in the environment, or in the structure of what it was optimizing.

So, I think there’s a responsibility for anybody deploying a machine learning algorithm to understand the tool. But on the other side, there’s also a responsibility for machine learning researchers to make this kind of information available, and to make their tools easier to use, less dangerous, more interpretable, so that they can be used for good, for the useful purposes that they can be deployed for.

Ariel Conn: So, one of the things that you wrote about that I was really intrigued by is this idea of helping decision-makers and policymakers design market prices that are associated with social good. And I was hoping you could just explain how that would work?

Tegan Maharaj: Yeah. So, machine learning algorithms are really good at optimizing something, which means taking some number and finding a solution in the space of possible solutions that makes that number as high as possible — like playing a game, or something, and maximizing your score. So if we can set some kind of number like minimize emissions — we want missions to be zero, or some low number — then a machine learning algorithm can optimize, for instance, a stock portfolio for achieving that number. Or in complicated decisions like deciding where to put a hydro dam, or some other social infrastructure project that needs to be done, a machine learning algorithm can help weigh all of the different factors, like how much energy will be produced over the long term? What is the availability of the raw materials for the energy source? How much will it cost to construct? How long will it take to construct? How will local environments and ecosystems be affected? How will local people and businesses be affected? How the economy would be affected?

There are lots of factors that have to be weighed here. And when we can write those down, a machine learning algorithm can optimize those to find a good balance between all of the different objectives. So the thing that machine learning can help with here especially is when we don’t know exactly what the number is, but we know that that number is affected by a bunch of different criteria like the ones that I just mentioned. So the machine learning algorithm can both come up with the number, and then also come up with the way to balance across the criteria to best achieve an objective.

Ariel Conn: And are there examples of this being implemented already, or is it still something that’s in the test stages?

Tegan Maharaj: The fields of multi-criteria decision making, multi-objective optimization, have been using machine learning optimization techniques for decades, really. Usually they’re at the scale of something like an individual factory, where the operation of the factory, or maybe the relationship between multiple factories — like shipping lanes and things like that — that network or system can be easily represented in a computer. And the amounts of, for instance, raw materials and energy that are shipped between the factories, or between parts of the individual factory, can be quantified and measured. And then, all of these things can be analyzed by a machine learning algorithm to optimize a factory, or something like shipping routes. So the whole field of operations research has been doing this for a long time and they have really well-developed optimization methods for doing this kind of thing.

The thing that I would love to see be developed in the near future is using machine learning, maybe something like meta learning or transfer learning, to be able to coordinate the activities of many of these systems at a much larger scale than one factory, or something with 10 or 12 components to it. The techniques for doing that kind of decision making and optimization are much more difficult because there are many more factors to consider. And many of the methods that are developed are developed around finding exact solutions or computing things exactly, and that’s something that just doesn’t scale very well.

And the newer machine learning methods that we have — which learn from examples, rather than from solving exact mathematical formulas — might be able to help a lot with scaling this to huge numbers of factories in a graph, or pieces of a factory, or very large systems like the operations of a country, so that we could apply the same kind of techniques and reasoning to analyze much larger systems.

Ariel Conn: Okay. So something else that you mention in your section is hedonic pricing. Can you explain what that is, and talk about how machine learning can be applied to this?

Tegan Maharaj: Yeah. Hedonic pricing is basically the practice or idea of inferring value of something based on people’s, for instance, purchasing decisions, or how people behave in a market, rather than when you don’t know the value of it explicitly. This has been used a lot to guess how people value homes for housing prices and for other goods that it’s hard to quantify a value for. It can be used for non-tangible goods like carbon prices, carbon emissions, to understand how people value that.

The thing that makes it different from just market pricing is inferring the value on multiple criteria, and that is an ideal place to apply machine learning. This is not something that has been done, but speculatively people could employ hedonic techniques to estimate how much people value bad things instead of goods — so, people call these “bads”; like air pollution, or the stress of worrying if their home will be affected by a climate disaster, or things that are very intangible like this — and assign a price to those things.

Ariel Conn: So would that be similar to or different from a carbon tax?

Tegan Maharaj: It would be one methodology or one way to come up with the value for a carbon tax.

Ariel Conn: Okay. And then how would machine learning be used for that?

Tegan Maharaj: A carbon tax is maybe less applicable for hedonic pricing because emissions can usually be quantified, so it’s not like you have to infer the quantities or the value of those emissions. They have a relatively logical quantity. But if you wanted to incorporate aspects, like I mentioned, of the stress of worrying about climate change in the future, or the value of your grandchildren having butterflies, and fresh air, and things like that — those kinds of things, you could survey people, maybe, and get them to rank how much they care about these things.

Anything that can allow you to quantify how much people care about things, you can then aggregate that information from many people and try to estimate numbers that correspond to these kinds of intangible things. And you can make this a multi-step process where you then show those numbers to people to ask if that makes sense compared to the value of some other thing.

Some of this turns me off a little bit. I think a lot of this type of thing is, we’re trying to assign value to things that are essentially priceless, and it feels wrong in some way. But the thing is, if you don’t do this kind of thing — if you don’t assign a market value to intangible things that we care about, like nature and health — then they get overlooked by our economic system. So we really need to do this sometimes in order to make sure that these things are valued as much as we value them.

Ariel Conn: And so, in your section as well you do talk a lot about multi-criteria decision making and multi-objective optimization. If you could just again sort of explain what those are and how they could be applied to climate change?

Tegan Maharaj: Yeah. Multi-criteria decision making is basically what it sounds like, making a decision when you have to weigh multiple criteria. An example that I use often is something like having to decide on a new hydro dam or source of energy. There are a lot of different criteria to weigh economically with the local stakeholders, the environment, the amount of energy produced, et cetera, to weigh in that decision. And one way people might solve a multi-criteria decision making problem is via multi-objective optimization, a family of computational techniques for solving multi-criteria decision making problems when you can write down the multiple criteria as different objectives that you want to achieve — which is not always the case. But when you can, machine learning techniques become very useful and applicable.

Ariel Conn: All right. You also list quite a few examples where machine learning researchers either have worked with climate experts or can work with climate experts to tackle specific problems. So maybe you could pick one or two examples of these that you found most interesting, maybe most helpful, and talk about what’s been done.

Tegan Maharaj: Off the top of my head, one of my favorite papers was the paper that received the Best Paper Award at our workshop at ICML. It was about detecting anthropogenic cloud disturbances using machine learning, specifically using convolutional neural networks of the same kind that are applied to recognizing whether an image contains dogs or cats, or things like that.

The reason I really like this paper is that they framed the problem in a unique way. This wasn’t a problem that was on my radar anyway, but they thought, clouds look different — there was a climate scientist on this, it’s not just like they had this thought randomly — but that different clouds look different depending on whether they’re produced by natural processes, or anthropogenic sources like factories or ships going across the ocean. And what they were doing was using convolutional neural networks, computer vision, to look at images of clouds and see whether those clouds were produced anthropogenically or by natural processes. And this let them track ships and pollution across the oceans much more accurately than any measurements that we have, because a big part of the problem for a lot of things related to climate is that we just don’t have ways to measure what is being done. So if we can do it by computer vision on satellite imagery, to be able to find where the biggest sources of pollution and anthropogenic disturbance of the atmosphere are, that’s a big win in my mind.

Ariel Conn: If I’m understanding this right, you’re saying we can use satellite data to actually quantify how much is being emitted from these different sources?

Tegan Maharaj: For instance, yeah. Or at least, maybe not the exact — future progress in this line of work would be to identify what exact chemicals are in the cloud based on the formation of the cloud, which is maybe possible to do and is really cool. But what they were doing is just trying to tell whether it was anthropogenic or natural — which, if you look at a cloud, you’re like, “Oh yeah, that is clearly coming out of the smokestacks there,” and jet trails or contrails look really straight; they look very different from clouds. And it turns out, kind of unsurprisingly, that you can train machine learning algorithms to recognize the same type of thing, and this allows us to track anthropogenic cloud disturbances across the ocean that we just couldn’t do before.

Ariel Conn: Oh, that’s really interesting. Okay. Were there other examples that you wanted to mention?

Tegan Maharaj: It’s not a specific paper, but I’m really interested in a line of work that is being done at the intersection of game theory and mechanism design and multi-agent RL in trying to solve cooperative problems, public goods problems, using machine learning techniques like multi-agent RL. So what public good problems are, is things like tragedy of the commons, where there’s some area of common grass where all the sheep can graze, and if there are no rules about how to use it, the incentive of every farmer around there is just to use it until it’s gone for their own sheep. But then there is no more grass for anybody to use. So in the long term it’s bad for them. I would state public goods problems generally as short-term incentives for behavior not being aligned with long-term incentives for the good of the group.

Natasha Jaques: So this is something that I’ve actually been working on recently. We coded up some toy versions of those types of problems — so a tragedy of the commons problem and a public goods problem — so they’re available for multi-agent reinforcement learning researchers to work on.

Tegan Maharaj: I think this area of research is super cool. I’m doing some current work on modeling this kind of problem in ecosystems. Ecosystem modeling uses techniques a little bit similar to multi-agent RL, but usually involving slightly different models for how agents and the environment interact with each other — and particularly there’s usually not this environment that is kind of all powerful and tells the agent what to do; the environment is modeled as something more like another agent. And I’m hopeful that we can do interesting things to solve this kind of public goods problem.

Another interesting area that I hope machine learning researchers get more into is evolutionary game theory, which is basically game theory where you’re considering how your actions or the actions of other people affect not just yourself, not optimizing your own utility exclusively, but considering the evolution of the group as a whole. This kind of game theory or incentive structure really impacts human decision making. So just if we want to understand human decision making better, it is useful — but also it helps us make better decisions in public goods problems.

Natasha Jaques: There’s been some interesting research on this out of DeepMind. So there’s a nice paper recently that basically gave agents an inequity aversion motivation. So an RL agent doesn’t want to have its rewards differ too much from the rewards of any other agent, or else it will get “guilty” or “envious.” And they show that actually if agents have this motivation, then they can better solve these public goods and tragedy of the commons problems. So if you feel guilty if you harvest up all of the resources in the environment too quickly, then it preserves the environment better.

Tegan Maharaj: There’s a lot of biological research suggesting that social species depend on — it’s often called local enforcement, or individuals either guilting each other into doing something better or rewarding each other for doing things that benefit the whole population. So I think it’s really cool to see computational techniques doing this kind of thing.

Ariel Conn: I want to come back to the technical requirements for some of these systems and what policy makers need to be able to do themselves, versus whether we just need to get more machine learning researchers involved in policy. And to a certain extent, honestly, it sounds like we need to get more machine learning researchers involved in policy. And I was curious what your take on that is.

Tegan Maharaj: I would say that as individuals in society, we need to be more involved in the decision making of our society. I think people in general today are very disillusioned with political systems, and I include myself there, but that doesn’t take away the need for the policies that we make on a social scale to reflect the priorities and needs of everyone. And everyone has some responsibility, I think, to make that kind of knowledge known, to refine their preferences, to help aggregate them between groups of people. And it’s a difficult process. We haven’t figured out how to do it completely. We need to try new things. We need to make our political systems better and more representative. And machine learning researchers aren’t an exception to that, especially now that we are developing tools that are impacting this kind of system and also developing tools that could make those systems better.

In a way I think yes, machine learning researchers need to be involved more in policy. I think everybody does, and I think if you’re a machine learning researcher interested in this kind of thing, you’re in a really great position to help develop better tools that can foster collaboration between policymakers and machine learning researchers, make sure that the tools that machine learning researchers are making are used responsibly and effectively so that things get better for everyone.

Ariel Conn: I think that’s a really important point: the idea that this isn’t just about getting machine learning researchers involved, that all of us need to be more involved. And I think that nicely transitions to the question that I have for both of you now, and that is: how have your own habits changed as a result of working on this paper — either in terms of trying to be more involved in policy, or trying to get more involved in developing systems that people can use, or even non machine learning solutions? What, if anything, are you doing differently?

Natasha Jaques: Because I was researching this section on your individual carbon behaviors, I looked into exactly how much my different behaviors cost in terms of emissions, and I found that my flying and beef eating are definitely just dominating that. So what I’ve started doing is actually purchasing carbon offsets to offset my flights and any beef that I eat. And actually you can offset the rest of your emissions for almost nothing once you do that.

I was also looking into the viability of carbon offsets, and it turns out that they are still really impactful, because there’s still a lot of low hanging fruit around the world we can do to lower emissions — like for example, just funding people to buy cleaner cookstoves or funding the development of cleaner power plants. So I’ve been purchasing carbon offsets, and I actually started instituting a program in our media lab department here at MIT to offset flights for work-related air travel. So the media lab has agreed to start a pilot program to offset students’ and researchers’ flights.

Ariel Conn: That’s excellent. That’s been something that — it’s certainly my biggest carbon footprint, is the flying that I do. And I try to offset what I’m doing, but it seems like if someone is flying for their organization, it seems nice for the organization to be contributing to the solution, I guess.

Natasha Jaques: I think it is really good for an institution to do that, because for a lot of us, traveling is part of our job. For those of us who are doing research, meeting at conferences is a really important part of your career. It’s very hard to just give that up. So I think offsets are a really promising way to focus on this, because, I mean, they’re not perfect and there is some controversy around offsets, but looking into them further you can see that there’s just a lot of climate infrastructure that could be funded still, and actually have long-term impact. So I do think carbon offsets are something to look into. And if you’re interested, you can go to to check out that program. We’re hoping it’s going to spur other departments to adopt something similar.

Tegan Maharaj: Similarly to Natasha’s lab — this wasn’t my initiative, it was more I participated with Alex and Yoshua, the head of our lab — MILA is looking into something like this. And ICLR, the International Conference on Learning Representations — the conference is going to offset all of the costs of travel for everyone going to the conference. And I think it’s also a great initiative for conferences. So that’s not about me.

I’ve been working somewhat in this area for a while, so I think a lot of the changes I’ve made have been over the past, I don’t know, decade or something. I’m vegetarian, I bike everywhere, I try not to fly. But the things that have changed most are probably my research focus and my ability to supervise and collaborate with people who are wanting to work on projects related to climate change. This project gave a lot of visibility to applying machine learning to climate change, and I get a wonderful number of people contacting me to ask, like, “Hey, I’m interested in doing this. How can I help? What can I do?” And I get to talk to people every day about cool projects that they could do that have a climate impact.

One of the things that I’ve gotten most, I guess, from the paper is concrete resources for assessing what are going to be the most productive or efficient uses of my time, or somebody else’s time, in applying ML to climate change. Because there’s no way that I as a machine learning researcher can become an expert in all of these areas, so it was fantastic that we have all of these excellent researchers from many different fields contributing to the paper. Having that information, and also these contacts in other fields that I can refer people to, has been hugely helpful.

Ariel Conn: So have you both generally found that you are getting a good response to this paper?

Tegan Maharaj: Yeah, it’s really funny. A lot of the response that I’ve gotten is like, “I saw the title and I thought you machine learning researchers were being obnoxious again thinking you could save the day. But then I read the paper and I realized you didn’t mean that. I think the paper is actually really good.” So it’s like a one-two punch kind of feedback. 

But I think it’s really good that people are actually reading it, because I do think that our message is really not that machine learning is a magical wand that we are trying to wave and save the world. It’s really not that. Machine learning is not a magical solution; it is not going to solve all of the problems. But every little bit helps, and everything that we can do as machine learning researchers can be applicable to problems of climate change. You can have a great career in machine learning and work on really interesting problems that push the edges of our knowledge and understanding — and help the climate. That’s the kind of message that we want to get out there.

Natasha Jaques: I think people have been generally really enthusiastic about the paper and I find that really encouraging, but what’s even more exciting for me than just the paper is the workshops that Tegan and David and a lot of people have been continuing to organize, and the participation I’m seeing in those workshops. So there’s actually concrete evidence of researchers that have machine learning knowledge taking that and applying it to these problems. That’s been really encouraging.

Ariel Conn: And overall, do you both feel hopeful that we’ll be able to address climate change in a timely enough fashion?

Tegan Maharaj: My basic answer to this is yes and also that I’m not really sure there’s this timely enough fashion. There isn’t some magical day in the future, past which the world will explode, and if we just finish it as the clock counts down to the end of the movie, then we’ll all be fine. It’s a continuum. Every day that we don’t take action to make things better, it gets worse. There’s less and less chance that the environment, long term, will be stable enough to support biodiversity, to have populations on coastlines, to have as much fresh air and stable weather as we do. And every day that we take action and do something about the problem, there’s more chance that all of that good stuff is going to happen.

I think this all or nothing thinking can make us really discouraged and less likely to take concrete action, and I think everybody should feel encouraged and empowered. Every little bit makes a difference. Every step that we take takes us closer to a better place. And I am hopeful that all of these steps are going to add up so that the world keeps being a cool, awesome place full of air that we can breathe and interesting, awesome, weird animals and plants and stuff.

Natasha Jaques: Yeah, I agree with what Tegan said exactly. So, there isn’t an “in time.” We’ve already done a lot of damage to the environment, to coral reefs. We’ve killed 3 billion birds in North America in the last 50 years. Animal populations have declined by 60% on average. So that’s really scary. But I also see continued accelerating technological progress that could be used to help these problems, and I do think that we’re pretty smart and we’re pretty innovative so we could address a lot of these issues. But the problem is that if there aren’t incentives to do so, then I’m not sure that we’ll address them effectively.

One of my favorite examples is the issue of Freon gas and the ozone layer, right? It was fairly economically viable to replace Freon gas and still get cooling systems, and because there was regulations put in place, we made that transition fairly quickly and the hole in the ozone layer is now starting to shrink. But if we don’t have the incentives in place, then I’m not sure how we’ll engineer massive social change. So it is a political problem as well. We have to get people motivated and we have to get large institutions to change.

Tegan Maharaj: On that topic, one of the most surprising things that I took out of the things that I learned at our last workshop was a result from Drawdown, which shows that some of the biggest factors increasing greenhouse gases in the environment are old refrigerators and air conditioning units. So one of the most impactful things you can do as a homeowner, as an individual, is to make sure that your old refrigerator or AC unit is recycled and disposed of responsibly, so that it doesn’t just end up in a landfill leaking those gases that destroy the ozone layer and increase global warming.

Ariel Conn: As you guys were working on this, were there other things that surprised you?

Natasha Jaques: So one thing that surprised me in reading — I don’t know if you’ve seen this book from MIT Press called What We Know About Climate Change. It’s really good. And that book makes a really strong case for nuclear energy; basically saying that we are overly scared of nuclear energy and with the latest technology, it’s actually incredibly clean. It’s a solution we sort of already have that we could be putting in place. And so, I think it surprised me how much certain climate experts are really in favor of nuclear energy, and how unwilling some politicians are to talk about it.

Tegan Maharaj: It was surprising to me to learn how much policy analysts and people in social sciences, economics, and policy are using a lot of machine learning and empirical methods — maybe under different names and maybe without making the connection to the machine learning community. So I think there’s really a lot of — we’re a broken record saying this — but a lot of collaboration that can happen, a lot of really productive work that could come out of that kind of collaboration.

Ariel Conn: Excellent. And then are there any final thoughts that you want to leave with listeners? Anything that you think we should have gotten into that we didn’t, or that you think is really interesting for people to know or understand?

Tegan Maharaj: The main high-level ways I see ML can help with problems of climate change, or just can be applied in general, are like two families of stuff. There’s descriptive stuff, where machine learning can help analyze large volumes of data, make visualizations or analysis of large amounts of data that can help people make decisions; and then there’s also prescriptive stuff, where the machine learning algorithm can help decide what to do, make decisions, or predict what is going to happen as a result of complicated processes that are happening in the climate.

Natasha Jaques: I think the only thing I would like to reemphasize is that for individuals who don’t have that much information on climate change and sustainability, I think not to be intimidated and to just try to do what they can, and there’ll be more tools in the future.

Tegan Maharaj: I think it’s really important for machine learning researchers, and people in general, to know that our society is kind of a work in progress. The way we make decisions and the things that we’re doing in the world are things that we can have a huge impact on, that we can change; we can make them better. And you can apply your skills to doing that, and it’s not that hard. Maybe you need to learn about some stuff and collaborate with some people and think of a new problem setting where you can apply machine learning. But we’re researchers, and that’s the kind of cool stuff that I like doing, anyway.

So I think the potential for new problems, new interesting applications of machine learning — that’s all really exciting, and it’s really great that we can make a difference in something that is very important to me. Having a better world for everybody. It’s cliche, but that’s what I want and I think we can do it.

Ariel Conn: Excellent. Also, the points that you’ve both made earlier about every little bit helps, I think that’s especially important as well.

Well, thank you both so much.

Natasha Jaques: Yeah, thank you.

Tegan Maharaj: Thanks for having us on.

Ariel Conn: I hope you’ve enjoyed these episodes about how we can use machine learning to tackle climate change. On the next episode, we’ll be joined by Glen Peters who is a Research Director at the CICERO Center for International Climate Research in Oslo. Most of his research is on past, current, and future trends in energy consumption and greenhouse gas emissions.

Glen Peters: Emissions have grown rapidly, and continue to grow, and a bit of a consequence there is the relative emissions from fossil fuels keeps growing in the carbon budget. We used to think that emissions from fossil fuels were the most certain part of the carbon budget, but now that emissions are so big, the actual uncertainty is quite important.

Ariel Conn: You can catch Glen next week as he joins us for episode 18 of Not Cool, a Climate Podcast. And as always, if you’ve been enjoying these episodes, please take a moment to like them, share them and maybe even leave a good review.


Not Cool Ep 16: Tackling Climate Change with Machine Learning, part 1

How can artificial intelligence, and specifically machine learning, be used to combat climate change? In an ambitious recent report, machine learning researchers provided a detailed overview of the ways that their work can be applied to both climate mitigation and adaptation efforts. The massive collaboration, titled “Tackling Climate Change with Machine Learning,” involved 22 authors from 16 of the world’s top AI institutions.  On Not Cool episodes 16 and 17, Ariel speaks directly to some of these researchers about their specific contributions, as well as the paper’s significance more widely. Today, she’s joined by lead author David Rolnick; Priya Donti, author of the electricity systems chapter; Lynn Kaack, author of the transportation chapter and co-author of the buildings and cities chapter; and Kelly Kochanski, author of the climate prediction chapter. David, Priya, Lynn, and Kelly discuss the origins of the paper, the solutions it proposes, the importance of this kind of interdisciplinary work, and more.

Topics discussed include:

  • Translating data to action
  • Electricity systems
  • Transportation
  • Buildings and cities
  • Climate prediction
  • Adaptation
  • Demand response
  • Climate informatics
  • Accelerated science
  • Climate finance
  • Responses to paper
  • Next steps
  • Challenges

References discussed include:

The paper is divided into three groupings: climate mitigation, adaptation, and then the third overarching grouping is tools for action — where we see machine learning providing tools for individuals or society to have an impact on climate change solutions.

~ David Rolnick

Ariel Conn: Hi everyone, I’m Ariel Conn, your host for Not Cool: a climate podcast. And I’m excited to announce that we have a special two-part episode this week. Earlier this summer a very large paper came out called, Tackling Climate Change with Machine Learning. This paper was written by 22 authors from 16 of the world’s leading AI institutions in academia and industry. On today’s episode, which happens to be #16 of the Not Cool series, we’ll be chatting with four of the authors. We’ll talk about why machine learning can be such a valuable tool in the fight to keep global temperatures below 1.5C, as well as how machine learning can be used to help improve our electric systems, our transportation systems, our buildings and infrastructure, plus some of the challenges still to be addressed when applying ML to climate change solutions, and so much more. Then on Thursday, we’ll talk with two more of the authors about how machine learning can be used by individuals to improve their own carbon footprints and by societies to implement better climate policies. But for now, I’m going to break with tradition and let my four guests introduce themselves today. David, do you want to take it away?

David Rolnick: Thank you so much Ariel. It’s a pleasure to be here. I’m David Rolnick. I’m a postdoctoral fellow with the University of Pennsylvania. I’m a mathematician and I work on the mathematical foundations of machine learning and AI. And I also obviously work on machine learning and climate change.

Priya Donti: Hi, my name is Priya Donti. I’m a PhD student in computer science and public policy at Carnegie Mellon university and I work on the intersection of electricity systems and machine learning. Specifically, how can we reduce greenhouse gas emissions from the electricity system — for instance, by helping integrate more solar power, wind power, and other low carbon electricity sources.

Lynn Kaack: Hi, my name is Lynn Kaack and I’m a postdoctoral researcher in the energy politics group at ETH Zurich. My work is centered at the intersection of climate change policy and machine learning, and I’m focusing a little more on the climate change policy side. So for example, I use machine learning to help understand how we can reduce greenhouse gas emissions from transportation. I’m also analyzing how renewable energy technologies get developed and how we can apply policies to promote that. I’m also using machine learning for that.

Kelly Kochanski: I’m Kelly Kochanski and I’m a PhD student at the University of Colorado, Boulder where I work on snow science and polar science. Recently I’ve been working on finding ways to integrate machine learning into climate models. 

Ariel Conn: All right. Thank you all so much for joining us today. Let’s just start by talking about maybe some of the really broad, basic background of the paper, as in: what brought you all together to work on this?

David Rolnick: So for a long time, researchers and practitioners across many different fields have wondered how we can use our skills to tackle problems relevant to society — and in particular, one of the greatest problems that society has ever faced, namely climate change. Over the past few years, this has become particularly urgent. This particular project started really with conversations I was having with Yoshua Bengio and others at this Institute in Montreal, Mila, where many of us were trying to identify how we can use machine learning to tackle problems posed by climate change.

Simultaneously, many other people around the world are having similar conversations. The project got started because I felt that perhaps some of these conversations could themselves be a vehicle for impact, by enabling many people with very powerful skills across the field of machine learning to use those skills and leverage them to impact problems relevant to climate change. So the project has really involved a lot of people coming together, not just from the machine learning field, but also many other fields relevant to this interdisciplinary work — because to have an impact on problems related to climate change, one really needs a lot of expertise coming in from many different areas, as you can see from the authors which we gathered to work on this paper.

Ariel Conn: How did you all find each other?

Priya Donti: So how I first heard about this project is at the NeurIPS Machine Learning Conference, David organized a lunch for climate change and machine learning, during which a lot of different people were asked to speak about their existing work in bridging these two areas. David invited me to speak, and that sparked a lot of really interesting conversations, and it seemed like there was so much passion around this project. Importantly, there was a lot of conversation about what we could do moving forward beyond that lunch, beyond a couple of presentations. How could we really put something together that would inspire broader action from the machine learning community? Later on, when David was thinking about this paper and talking about this paper, yeah, he approached me and my interest had really been sparked by that lunch.

David Rolnick: The goal of bringing together this diverse set of authors was really to cover a wide range of needed expertise. Because I realized that I certainly did not have anywhere near the field-specific expertise to cover the individual areas into which we’d have to delve, in order to assess what kinds of problems and solutions were relevant in applying machine learning to climate change. I think everyone on that author list brings their own special expertise which is necessary for tackling one facet of this problem.

Ariel Conn: Why did you focus specifically on machine learning?

David Rolnick: I don’t feel that machine learning is the only tool for which such a paper should be written, or for which such an investigation should be made. It was a community that I and other authors are part of, and it is a very powerful, broadly applicable tool as a vehicle for enabling and accelerating progress. But it’s far from the only such tool.

Lynn Kaack: Maybe I can also add with a perspective coming from the climate policy side. During my PhD, I felt that there was a gap because more and more big data sources were coming online and we were not addressing or taking this data into account. I personally got into machine learning and statistics on the side of my PhD, initially for fun actually. I realized that combining machine learning with these domain expertise techniques that we developed to mitigate climate change was actually a really fruitful approach.

Kelly Kochanski: I think that one of the advantages, one of the really satisfying things about working on climate and earth science, is that you get to work on problems that have a really wide global scope and interest. But one of the challenges is trying to figure out a way to translate that interest into actual impact, on rapid time scales, that can actually improve people’s lives as climate change happens to us. And so for me, one of the ways that I’d like to try to increase the impact, or the time to impact, of the work that’s going on in my field is to bring in new computational techniques and to help people in my field work together with larger communities and start spreading our impact further in a relatively short period of time.

So this was a way for me to work on something that had a lot of that energy and had new tools that might allow us to make improvements to what we’re doing within the next few years, while we can start impacting infrastructure and policy decisions with better climate knowledge.

Priya Donti: Yeah, and I would say more broadly, climate change is a problem that affects everybody. We will need people of all expertise, stakeholders of many sorts, to come in and contribute to the issue. We felt that, as part of the machine learning community, we had something to say about how machine learning specifically could contribute. In particular, as Lynn mentioned, there are lots of areas where there’s a lot of data and there isn’t necessarily a lot of guidance about how we can take that data and translate it to action.

Machine learning is a particularly well suited tool for doing that. But again, machine learning doesn’t exist in a vacuum: It has to be applied alongside stakeholders and alongside collaborators who understand the climate change domains that we’re talking about in the paper a lot better than we might. So machine learning is one piece of a much larger effort.

Kelly Kochanski: One of the challenges of working on this is that a lot of the tools that we can make have a pretty distant impact in time. We can build better predictions of how the climate is going to change, but putting new science into these predictions can take several years; and then those predictions aren’t impactful until they’ve been acted on by individuals, governments, and people making, say, infrastructure decisions influenced by climate. So for me, one of the advantages of moving into machine learning is that it allows us to bring in new tools and to connect with really energetic technical communities, and start finding ways to make predictions on a more rapid scale — or make new kinds of predictions that get information out to more people faster, and let them make effective decisions.

David Rolnick: I second everything that Kelly just said, and I would add to that — but from the machine learning point of view — there are so many people desperate to do good, and use their skills for the good of society, who don’t know how best to do that. Enabling them to connect with problems and people who can channel those skills to the maximum possible effect is really what we’re trying to enable here.

Ariel Conn: So I think that’s a really nice transition to the next question that I had for you, and that’s getting a little bit more into the specifics with the paper. At the start of the paper, you have a very nice table that lists the climate change solution domains and the areas of machine learning that you see relevant to each. I was hoping you could talk a little bit about how you narrowed down all of the options to the list in this table.

David Rolnick: Sure. So some of the machine learning domains which we listed in that table we picked based upon major areas in which people had expertise; also, major areas which we see as up and coming and in need of further development within the field of machine learning. So for example, some of the areas we highlighted — computer vision, natural language processing, reinforcement learning — are areas of major research and entire sub fields of their own. Others are up and coming, and identified by many within the machine learning community as areas where great progress is being made or has the potential to be made.

For example, interpretable machine learning, or transfer learning, and few-shot learning. These are areas where we actually see the climate change applications we identify as being potentially very valuable in guiding and giving rise to improved machine learning from a research and an engineering perspective.

Lynn Kaack: We picked the climate change domains based on how this problem is usually split up in the literature. We added some sections that are typically not caught like that, so for example the tools for individuals, tools for society,  which we thought were overarching themes that ML could help with, which we wanted to identify separately.

David Rolnick: Overall, the paper is divided into three large groupings. The first of those groupings is climate mitigation. That refers to reducing greenhouse gas emissions. The second overall grouping is adaptation, so helping society respond to those changes that are inevitable or are happening now. Then the third overarching grouping, which is perhaps less conventional, is tools for action — where we see machine learning having an impact, for example, in providing tools for individuals or society to have an impact on climate change solutions less directly.

Ariel Conn: All right. So I’d like to start digging in a little bit more with this paper. You mentioned the first section is mitigation. Within that, obviously, our electric systems are some of the largest causes of greenhouse gases. So Priya, did you want to start off by just explaining a little bit about the work you did on the section about electric systems?

Priya Donti: Absolutely. So electricity systems and machine learning — this intersection is something that is really fascinating to me, in particular because electricity systems touch a lot of our lives. They shape the way we work, we live, we commute — and at the same time electricity is very invisible, and the situation for electricity systems is very different depending on where in the world you are. A lot of people in the world don’t have access to electricity at all. And so when you have a system that is so globally ranging and is also a huge contributor to greenhouse gas emissions — electricity supply and production contributes about a quarter of global greenhouse gas emissions — how do you even start to tackle this problem? 

So there are three ways in which it’s generally envisioned that we would reduce greenhouse gas emissions from electricity systems. The first is moving away from greenhouse gas emitting fossil fuels — so these are things like coal power or natural gas — and move towards low carbon electricity sources — like solar power, wind power, nuclear, geothermal, hydro — and run our system based on these low carbon sources rather than greenhouse gas producing sources.

The second method is, the transition to low carbon electricity sources isn’t going to happen over night. So in the meantime we have to do something to reduce the greenhouse gas emissions from the system as it currently stands. Another method that we can think about machine learning being applied to is how, in fact, do we reduce greenhouse gas emissions from fossil fuels today. Then a third kind of overarching theme is, while we think about transitioning to low carbon sources or we think about reducing greenhouse gas emissions from our current system, we want to make sure that we think about these solutions in a global manner.

So not only in places where we have a lot of data, for example in the United States, but also in places where we may not have as much data, but that may be equally important from a climate change mitigation perspective. So machine learning can contribute to all of these strategies: to the transition to low carbon sources, to reducing emissions from our current system, and to the global implementation of these through a variety of applications. This was something I was really excited to see as I was putting the section together.

There are applications ranging from forecasting solar and wind power, to detecting methane leaks on the electricity system, to helping accelerate the search for solar fuels or to accelerate discovery in nuclear fusion, and then to also generate data in settings where we may not have a lot of traditional data streams. We may not, for example, have information about how much power each solar plant is producing in a given time, but where we may have something like satellite data that allows us to gain insights into what’s going on in a particular system. So there are really a lot of different ways that machine learning can contribute to reducing greenhouse gas emissions in electricity systems.

Ariel Conn: So one of the things that I didn’t really mention at the start, but it might be useful to bring up here, is there’s three categories that you’ve all applied to some of these machine learning solutions. One is high leverage — something that you think will be especially effective. Long-term are solutions that you expect will primarily be impactful after 2040. High risk solutions are solutions that could be really helpful, but there’s also some unknowns about potential side effects or other ways that they could be risky. A lot of the questions that I plan to focus on through the rest of this focus more on the high leverage.

So I don’t know if you guys want to jump in on that breakdown real quick, but I was hoping to also switch to some of the sections that you found more high leverage within the electric systems work that you did.

David Rolnick: Sure. I’d be happy to briefly discuss the breakdown here. I think long-term speaks for itself. Those are the solutions which are going to have their maximal impact many years down the road, but are still extremely important. High leverage we see as those problems that have both high impact in either reducing greenhouse gas emissions or helping society adapt, but also have key elements which would strongly benefit from machine learning: so those high impact pathways forward where machine learning has very high leverage.

The third flag which we introduce is high risk, and that can refer to several kinds of risks. First, there are some solutions for which the technology is really not yet certain. For example, nuclear fusion would be a game changing technology, but has not yet been proven to be successful at any kind of scale. Second, there’s sometimes uncertainty as to the impact on greenhouse gas emissions. In many situations the systems involved are very complex, so it’s not certain that any particular action would have an out-sized impact on climate mitigation, reducing emissions, though it might.

Then the third kind of risk is if there are potentially unwanted side effects, what might be called negative externalities — so solutions that help from this perspective of climate change but may have other negative impacts in other ways. So for example, biofuels may be an essential component of a future climate change solution where it is necessary in many cases to have liquid fuels on which vehicles can run. 

Lynn Kaack: To grow bio crops, you have large land use changes, and of course they use water, and there’s the fear that they would take away from growing food on fields. So we have all these unintended side effects with technologies and it’s important to take those into account.

Ariel Conn: All right, excellent. Thank you. So Priya, why don’t we go back to you? Let’s start with the high leverage sections in the electric systems section. One of the ones that I noted was the generation and demand forecasting. Can you talk a little bit about that and why that’s important and what it means?

Priya Donti: Sure. So before talking specifically about generation and demand forecasting, let me step back and give a little bit of context. Electricity systems are a really delicate balancing act in some sense. There is electricity supply, so the production of electricity that is feeding into the electric grid; and then people are consuming electricity, so pulling electricity out of the grid. The power going into the grid has to equal the power coming out of the grid at every single moment. This is complicated by a couple of factors. On the electricity generation side, if we’re looking at sources like solar power or wind power — whose production is dictated by the weather — we don’t know exactly what the weather is going to look like ahead of time. So there’s a little bit of uncertainty about how much solar power or how much wind power will be produced ahead of time. 

If you have controllable electricity generators like coal, natural gas or nuclear, these are electricity generators that we can turn on and off explicitly, but these are still governed by some physical constraints. There’s only so fast that you can turn one of these electricity generators on, or so fast that they can change how much power they produce. So you have some uncertainty or some delay — both in terms of variable electricity sources like solar and wind; and controllable electricity sources like coal, natural gas, and nuclear.

Then on the demand side, you don’t always know exactly how much electricity somebody is going to use, because humans have free will: I can decide to turn on my electric kettle right now if I want to, or I don’t have to. So now we have this complex balance between supply and demand, where supply is potentially unknown ahead of time, and demand is also potentially unknown ahead of time. So this is where the machine learning solution can help. Generation and demand forecasting is an application machine learning can contribute to by looking at historical weather data; by looking at information about previous demand, about previous electricity generation from wind and solar sources; by looking at is it a holiday today, and even using video data, video of clouds going over a particular solar panel or satellite data. 

Machine learning can combine all of these different data streams and use them to produce forecasts of what we think solar power production or electricity demand will look like, maybe later today, or a few days from now, or a few years from now, even, if you combine it with physical models. There’s some interesting technical challenges that come up here. So for example, weather is governed by physics. So is there a way to incorporate information about physics into machine learning models to enable them to make better forecasts?

There’s also this question of, if you create a machine learning forecast — let’s say I say my demand is going to be a certain amount tomorrow — how certain am I about that forecast? Can I give some probability estimate or some error bars on that forecast, or can I maybe explain why exactly I think that’s going to be the case, so that a human electricity system operator can look at the forecast and sort of verify whether what it’s saying is reasonable or not? So this is an application where generation and demand forecasting can contribute to how electricity system operators manage their electricity system, and both make them more comfortable introducing more low carbon electricity sources and also can help even today reduce the amount that they rely on fossil fuel generators to maybe buffer some of the uncertainty in supply and demand in the future.

Ariel Conn: So do you envision us being able to use machine learning to help with the transition from some of our current systems to some of the low carbon electricity sources?

Priya Donti: Yes. So in order to transition from our current system to low carbon electricity sources, one of the things we definitely need to get a handle on is how much solar power we think will be produced in the future, how much wind power will be produced in the future. Because we need this information to decide how exactly to balance our electricity system to make sure that it continues to provide electricity without, for example, collapsing or having some kind of fault. There’s a lot of data that’s coming into the system here — grid sensors, weather data, etc. — and making sense of this data can be very difficult for an electricity system operator.

So machine learning techniques can help here by basically giving some data-driven insights to electricity system operators, and as a result, enabling them to manage the electricity system. So I’ve been talking about forecasting and variable electricity sources, but I mentioned earlier that controllable electricity sources are ones that we can turn on and off as we would like, though they are subject to some physical constraints. This is why nuclear fusion is also discussed as an interesting solution, and one that machine learning people like to contribute to. Because nuclear fusion — basically I would call it mankind’s quest to recreate the sun here on earth — basically takes hydrogen atoms, superheats them, and reacts them together in order to produce energy just like you would do on the surface of the sun.

You can control how much electricity comes out of a nuclear fusion reactor at any given time. And machine learning can help innovate and create these kinds of new electricity sources by helping more efficiently run experiments, or by making sure that when an experiment is run that you can do something like detect whether plasma — superheated hydrogen — is going to hit the site of a reactor, and therefore damage it. So in solutions like this, in solutions like accelerated science where machine learning can help speed up the search for new clean energy materials like solar fuels, I think there are lots of different ways that machine learning can help us transition into a low carbon system.

David Rolnick: I know I found it really surprising just how important forecasting is, both on the demand side and on the production side. It’s really counterintuitive, perhaps, that not just having not enough solar power is a problem, but also having too much. So understanding exactly how to make supply and demand be equal, and route power appropriately in a grid, is just so important.

Ariel Conn: When you say that too much is a problem, do you just mean that we can’t store it, or is there some other issue with having too much solar?

Priya Donti: You can put batteries, for example, or other storage devices on an electricity system — but generally speaking, you don’t have as much storage as you do capability to produce solar power. So if all of my solar panels started producing at 100% and I wasn’t anticipating that, I might not be able to store all of that electricity immediately. In part this is because actually electricity storage can be expensive. Then also, even if you do want to store electricity from a solar panel, you need to know when exactly you want to charge your battery. And knowing that also requires some understanding of when exactly you will have solar power production.

Ariel Conn: So the examples that you used for how machine learning can be applied with nuclear fusion and new materials are both listed as high risk, I assume because we just don’t know if we can develop the technology. One, if that’s incorrect, let me know. But then two, I was also curious if you could give some more examples of more certainty, where we can see machine learning being applied that would be high impact.

Priya Donti: So in this case, the reason we listed accelerated material science as high risk is, exactly, because these are technologies in development, and we don’t necessarily know if or when they will pan out. So we do think these are very impactful applications for people to work on, which is why we also list them as high impact. But they are definitely, in our perception, a longer term scientific endeavor — as opposed to something that can be implemented today. So generation and demand forecasting, which we’ve talked about, is one application machine learning that can be implemented today and on today’s systems with electricity system operators.

Another one is the detection of methane leaks. So methane is a really potent greenhouse gas. It’s 30 times more efficient than carbon dioxide at capturing heat, so really potent greenhouse gas. And methane is actually the main component in natural gas — one of the fuels I mentioned earlier that is used today to produce electricity. Methane is transported to natural gas plants via pipelines or through compressor stations, and can leak out of these pipelines, out of these compressor stations in the process.

The issue with that is we don’t necessarily know exactly when or where these links are occurring and we also don’t necessarily know how big of an issue this is, so how much methane is leaking. The estimates vary quite broadly. Machine learning can help provide some insight here by taking information from sensors that may be on pipelines; by taking satellite data and particularly hyperspectral satellite data — so satellite data that looks at different radiative bands as opposed to just light. So you can take sensor data and hyperspectral satellite data and combine all this information to both detect where methane leaks may be occurring already, but also potentially predict where methane leak may occur so that the problem can be fixed ahead of time and a methane leak never occurs.

Ariel Conn: Excellent.

David Rolnick: I’d love to stress that really every one of our recommendations has been very carefully thought through. Even those which we don’t flag as especially high leverage are still high leverage. We expect and hope that people will be working to implement all of our recommendations, because really all of them are useful and all of them are necessary.

Lynn Kaack: One thing to add there too is that there are a lot of applications that have really high impact, but  just don’t benefit from machine learning as much.

David Rolnick: For example, we didn’t talk very much about diminishing the effect of hydrofluorocarbons, HFCs, but that’s hugely impactful. It’s just not something where it’s very clear how the applications of machine learning could be involved.

Ariel Conn: Okay, good. I think that’s a really good point to make. Were there any other applications within the electric systems section that you think are important or helpful to mention?

Priya Donti: So as I mentioned earlier, electricity systems are everywhere. They’re a global phenomenon, a global issue. So it’s really important that we as machine learning researchers, and also the climate community, think about how we can mitigate greenhouse gas emissions in various global contexts. And so one thing I’d like the machine learning community to keep in mind is that, as we innovate on electricity systems, we don’t just want to focus on settings where we have a lot of data. We want to make sure that we’re thinking about electricity systems everywhere, including systems that don’t have a lot of data. One thing machine learning can potentially have a lot of leverage in doing is in producing new insights from non-traditional data streams.

For instance, we can use satellite data to detect which power plants are producing greenhouse gas emissions at a given time. Or there was one paper that used cell tower data in order to understand how much electricity people were using at a given time. So somehow leveraging these nontraditional data streams can help us innovate on electricity systems everywhere.

Ariel Conn: All right. Thank you so much. Lynn let’s switch gears over to you — we’re sort of going in order for the paper, and transportation was the next big section, which you wrote. So I was hoping you could just start by giving a quick overview of some of the work you did and what your findings were.

Lynn Kaack: Transportation is actually a sector that’s really important to look at if you want to reduce greenhouse gas emissions. It’s responsible for 14% of total greenhouse gas emissions in the world, and in the US for example, it’s about as much as those greenhouse gas emissions from electricity generation. When we look at transport, we should not only look at passenger transport, but also at add freight transport, which refers to goods being transported. Those actually account for about half of the greenhouse gas emissions from transportation. And machine learning has a number of different ways that it can help research on passenger and freight transportation. It can, for example, improve vehicle engineering — so make that more efficient. It can enable intelligent infrastructure. And it can also provide policy relevant information.

Ariel Conn: So there were a couple of things that you found high leverage, and hopefully we’ll get into that. But one of the things that I found interesting was that autonomous vehicles and shared mobility are obviously things that could help with climate change, but they were also listed as high risk because they could potentially increase emissions. So I was hoping you could talk a little bit about what you found for both of those areas.

Lynn Kaack: Sure. The energy impact of those two technologies are still unknown because they are not deployed yet to that scale that we can have this data. And there are several factors that play a role. So I’m going to dive into both of these and illustrate two factors that might be reducing the greenhouse gas emissions or increasing the greenhouse gas emissions for both of these technologies. 

So autonomous vehicles crucially rely on AI, and they could be good for the climate if they enable cars to drive in a more efficient way, which is also sometimes referred to as eco driving. But on the other side they might lower the barrier to using your own vehicle instead of public transportation, which actually might increase the amount of trips that people take in their own vehicle, and which also increases the greenhouse gas emissions from those vehicles. When it comes to shared mobility, this is a topic that encompasses everything from electric scooters to a group of neighbors sharing a truck. But we probably should talk about ride hailing services such as Uber and Lyft, because to date those are the most impactful applications. Perhaps a toy example here is best to illustrate why the energy impact of these technologies is still unclear.

So for example, if you want to visit a friend, you might drive there with your own car, so you drive there and back directly with your car. But instead if you use such a ride hailing service, it will come from somewhere, pick you up, drop you off, and go somewhere else to pick up a new person. So the journey that the vehicle has moved can easily be much longer than the journey you would have taken with your own car. If you’re using a normal combustion engine car, this probably increases the greenhouse gas emissions that come from that trip. But there is the possibility that these services enable a faster transition to electric vehicles, and they might also enable pooling many people in one vehicle.

Those factors would have a much better climate impact. So there’s really the need for these industries to prioritize lowering greenhouse gas emissions, and I think there could be quite some potential to contribute to that.

Ariel Conn: So in the example of autonomous vehicles, that’s still in the future. Shared mobility, we’re seeing that now in terms of the ride sharing. What are some of the things that we can do right now to reduce greenhouse gas emissions from transportation, and how does machine learning play a role in that?

Lynn Kaack: Most greenhouse gas emissions actually come from trucking. Trucks are really hard to electrify with batteries, because those need to be very big to transport all that heavy freight. But this might not always be that way. So we hope that battery development is leading us to having lighter, cheaper, and more powerful batteries, and machine learning can be used for battery development. 

There’s another technology that’s actually relying on autonomous vehicle technology and information communication technologies, which is called platooning. And this is an idea that you could allow trucks to drive really close to one another and that has actually less air resistance and can lead to a better fuel economy. But this technology is still kind of out in the future. 

One thing we can do right now is to incentivize that more freight travels on rail instead of on trucks. Typically what happens here is that you bring the freight, probably packaged in a shipping container, to the train; and then it travels for long distances on a train; and then gets picked up again by another truck to its final destination. This is referred to as intermodal, and making intermodal faster and more reliable with machine learning could actually have quite some leverage. So for example, we can use machine learning to predict demand, predict when the vehicles are likely to arrive, try to prevent failures by predictive maintenance. We can also use it in information communication technologies too — for example, truck containers.

Ariel Conn: How much of what you’re suggesting right now can be implemented either now or in the very near future?

Lynn Kaack: So people are actually beginning to implement these technologies already. This is still in the beginning, but the industry is definitely really looking at machine learning. It’s really important here to optimize for greenhouse gas emissions instead of for costs. Because of course the industry will optimize for costs, but we need ways to also look at the energy side of this equation.

Ariel Conn: Do you see ways in which machine learning can be used to help these industries optimize for both cost and decreased emissions?

Lynn Kaack: Sure. I mean, there are win-win situations, of course. If you have predictive maintenance, you actually make rail cheaper and this is great for everybody. So it depends on the application. Sometimes the incentives are aligned, sometimes they’re not.

Ariel Conn: So let’s switch to another section. You marked modeling demand as high leverage, and I was hoping you could explain what that means and why it could be so effective.

Lynn Kaack: Many countries actually know much less about their transportation systems than you would expect, but of course this information is needed to make transport systems more efficient and also to plan new low carbon infrastructure. Machine learning can help to both make sense of data that is already collected, and it’s also really great at forecasting. It can actually be used to help modeling efforts, and it can also help to infer primary data from your sources; for example, it can use satellite images to estimate how much traffic is going on.

David Rolnick: I think this is a great example of something we’ve seen many times in the paper: that sometimes the most impactful applications are really not sexy, but are fundamental to how stuff actually gets done in the world.

Ariel Conn: Let’s come back to that, because I think that’s a really important point. Lynn, I want to keep talking about transportation for another couple of minutes. Closing in on my final questions for transportation is just how machine learning can be used to improve things like electric vehicles.

Lynn Kaack: Electric vehicles are actually one of the main solutions for reducing greenhouse gas emissions from passenger transportation. There are actually a lot of things we still need to figure out about electric vehicles: how to make them better; understand how people use them and what that means for the existing infrastructure. This is especially the case since more and more electric vehicles are going to be used, and they might for example, be all charged at the same time. So understanding the time and place where they are charged both influences where we would place new charging stations, but also how to manage the grid. This ties in a little bit with Priya’s section. So we want to enable information to do better forecasting and know when vehicles are charged. 

For example, it’s expected that everybody comes home from work around the same time and then plugs in their vehicle, which might actually lead to a large spike in electricity consumption. Machine learning is really great at making sense of large data, and it could help to extract such behavioral patterns. But it’s also central to algorithms that help manage the way many vehicles can be charged without risking congestion, and also to manage better these large peaks and electricity demand by distributing them better over time.

Machine learning can also be used to improve electric vehicle technology — in particular, battery technology. Machine learning is currently used for predicting the battery state, the degradation, and the remaining lifetime, for example.

Ariel Conn: You also mentioned some other low carbon options that machine learning can be used for, like bike sharing and electric scooter services. Can you talk a little bit more about that as well?

Lynn Kaack: So bike sharing and electric scooter services are great examples of how fast new mobility solutions can be implemented. But they also show that there’s some need to regulate those new services to make things work. There is, for example, something that’s called the bike sharing rebalancing problem, and it refers to the fact that all the bikes in the end of the day, for example, end up at the same spot — and some other bike stations or areas where you usually would expect them are empty. So machine learning or AI applications can help to predict these things happening better and help to rebalance those stations.

Ariel Conn: Excellent. I’m going to keep going with you for just a few more minutes because you also worked on the buildings and cities section, which was a very interesting section as well. So can you talk a little bit about the current impact that buildings and city infrastructure has on greenhouse gas emissions and how machine learning can address that or help address that?

Lynn Kaack: Sure. Buildings is actually really important end-use sector because about a quarter of energy related emissions are from energy that’s consumed in buildings: so for example to heat or cool them, or to cook, or to power our laptops. Buildings are not only personal homes, but they also include office buildings, stores, and even industrial buildings. And we can use machine learning to reduce the energy that’s consumed in buildings in two main ways. The first one is to manage the energy use and to also reduce it with intelligent control systems, which is sometimes referred to as smart home, for example.

The other way is to use machine learning to help design better policies, where policy makers need to rely on great data for example, and machine learning can provide this type of information.

Ariel Conn: You described buildings as offering some of the lowest hanging fruit to reduce emissions. Can you explain that?

Lynn Kaack: This is based on the fact that it is possible to reduce the energy consumption from buildings with existing technological solutions by quite a bit. So some people estimate there’s up to 90% less energy used in those buildings. A lot of these solutions actually pay for themselves in a really short time. So the problem here is usually on the behavioral side, not on the technological side.

Ariel Conn: Can you give some more specific examples about how machine learning can help improve building efficiency? And can you talk a little bit about the extent to which we can actually turn current buildings into smart buildings? What can we do now or in the very near future?

Lynn Kaack: Machine learning as a part of intelligent control technologies can help reduce greenhouse gas emissions in two different ways. It can reduce the energy that’s consumed in a building by helping to forecast and control, for example, how heating and cooling is adjusted according to the user preferences. It can also detect the occupancy in a building with sensors and turn, for example, heating and cooling off if it’s not needed. Intelligent systems, for example, can decide to also ramp up cooling if it has learned that a family is likely to come home soon.

So these are all applications that could fall under the umbrella of smart home. And I think it’s fairly possible to retrofit current existing buildings with smart technologies, because those are based on appliances, so they don’t depend as much on the actual building. Of course, they work much better if the building is well insulated, for example, so they cannot be viewed in isolation. 

Another application of these systems is by helping with integrating renewables into the electric grid. For example, many office buildings actually have cool storage for their AC, which can be imagined, and is almost exactly a large block of ice. That block of ice can be seen as a form of energy storage, where one can decide at what point in time one wants to freeze more water. So one would likely do that when it’s beneficial for the grid. Today, this is often done manually by the grid operator calling a large consumer — for example, like a university campus — to stop those cooling operations when they’re undesirable and to previously generate a lot amount of ice in order to have that ready.

So, for example in Germany now, there are certain times where there’s so much electricity generated from renewables that actually exceeds the demand; and we would want in such moments to have this type of technology ready to be able to use that electricity beneficially, and then reuse it later for cooling buildings again. AI based algorithms can actually take the role of the operator, and instead of calling up somebody, they would give a signal, and they would optimize the way that it’s previously frozen and then use it on later.

Priya Donti: I would say that this application area of demand response is one that recurs in a couple of areas of the paper — where basically in commercial buildings, or when you have industrial equipment using electricity from the electricity system, we want to make sure that as much as possible it is using electricity when we have low carbon sources producing power. This concept of demand response, as Lynn says, is often done today by an electricity system operator literally picking up the phone and calling a building operator to say, “Please do this or please do that.” This is a great application where automation and machine learning can really help make this transaction more efficient.

Ariel Conn: Do you see an application like this then also being able to be applied to maybe smaller buildings that don’t necessarily have a maintenance operator, or do you see that as not an issue?

Lynn Kaack: So that’s definitely the idea, and it has been done, and it is currently also being done. Residential hot water storage can be used for the same purpose. So it’s definitely the idea to do that in people’s homes as well.

Ariel Conn: Is there anything else that you think was really important from the buildings and cities section that’s useful for either ML researchers or maybe policy makers to know about?

Lynn Kaack: Yes. There’s this whole side of urban planning and also policies that help to reduce the energy that’s consumed in a city. Policy makers are passing laws to make buildings more efficient, and they need to know a lot about the buildings in the city to understand how effective a policy is and how it could affect also certain populations in the city. One thing to notice here is that buildings are very heterogeneous — so they have different sizes, age, users, usage, ownership, etc. Machine learning can help to understand both energy consumption patterns if there is data available — it can help, for example, to cluster consumers into different groups that help policymakers understand how to shape a policy. 

But often there’s also very little data about the energy consumption in the city, and machine learning plays an important role for generating useful data. You can learn energy consumption for a whole city from all kinds of data points. People have used the sizes of houses, property class — all data they could basically find predictive for the energy consumption. And machine learning can even help to generate some of this more primary data; for example, how large buildings are from satellite images. This is really important because this kind of data is not available for many regions in the world.

Many of the mega cities in emerging economies are lying in very hot regions, so as people earn a better living, they will probably want air conditioning, for example. Designing low carbon systems for air conditioning is very desirable and will be very relevant in the near future.

Ariel Conn: Excellent. Thank you. Kelly, let’s switch over to you now. You worked on the climate prediction section within the larger adaptation section. Can you talk a bit about some of the work you did in your findings, regarding climate prediction and machine learning?

Kelly Kochanski: Sure. When I wrote the climate prediction section, I was looking for applications that would give us more accurate, more usable predictions for how climate and weather are going to evolve over the next few decades. Most of this is centered around climate models. Climate models are tools that make predictions, usually on the scales of years to decades, about how the climate is going to shift. And for the last maybe 20 years now, they’ve been the best tool that we have for predicting what the magnitude of climate change is going to be — and increasingly, as we’ve developed these models and improved their resolution — for figuring out more specific trends, like rates of change of temperature and precipitation in different regions around the globe, that we can use for planning and for figuring out what kinds of changes different agricultural regions and countries and cities will have to respond to.

So when I was writing this section, I found a whole host of really exciting opportunities to use machine learning to improve the accuracy and capability of existing climate models; and also to make some new structural changes, like new models that learn rapidly from data in real time and quickly incorporate new observations from satellites, or that make hyperlocal predictions to allow individuals or businesses to figure out the future of a specific building, for example, that they might want to buy or live in. So I think there’s a really wide range of applications that machine learning can be used for in this space.

Ariel Conn: One of the sections was titled “Uniting data, machine learning, and climate science.” And it seems like this is one of the most obvious applications of machine learning, since it’s taking the data that we have and applying it to climate science. I was wondering if you could talk about some of the work that’s already being done to unite these three things, and how much more we could be doing.

Kelly Kochanski: Sure. First off, I think it may be obvious to say that we have data; and we do have data — we have petabytes of data from satellites these days and that we should use that to make better predictions. But it’s not actually obvious or easy to find ways to integrate that into climate models. So when we look at long-term climate predictions, there’s a fundamental and irremediable data problem that we have, which is that the earth generates about one year’s worth of data per year exactly. No matter how well we observe that and how much data we generate, we can’t get more than that.

And we can’t make the few years of observations that we have stretch out to give us predictions to, say, years like 2050 or 2100. So most of the highest impact solutions that I’ve identified have involved using that data and putting it into the framework of existing models, which usually rely less on data and much more on physical laws — like energy conservation and thermodynamics — that we trust will hold constant and allow us to make more reliable predictions.

So one of the examples that I’m most excited about right now has to do with clouds. Clouds are actually one of the biggest sources of uncertainty in climate models. You can visualize this to some extent from the ground. So for example, I live in Colorado. Most of the time it’s very sunny, and that means that when a cloud comes through, it blocks the sunlight and it makes the ground cooler. But in winter, we get the opposite effect: if it’s cloudy overnight, the cloud acts like a little bit of a blanket, and it traps in some of the warmth from the city in the ground, and it makes that winter night a little bit warmer.

And we see these kinds of effects happen on a global scale all the way around the world, with some clouds cooling the earth and some clouds warming the earth and blanketing it. And it turns out that the differences between the two have to do with a lot of micro cloud physics, and tiny particulates in the air, and subtleties of location and temperature and thermodynamics that are really hard to model on a global scale. But we can model them on a small scale. So some of the most exciting research on this at the moment has to do with taking really small, high resolution, expensive models of clouds — sometimes even single clouds — and training machine learning models to replicate the results of those expensive models in a relatively cheap way that we can then put into big global climate models to make our predictions better.

This is a technique that’s called emulation, or sometimes surrogate modeling, where we train a machine learning model to act like a physics-based one. It’s being used in an increasing number of areas in climate science, and I believe that there are still many more where it could have a great impact, where it hasn’t yet been explored.

Lynn Kaack: This is, for example, also used for emulating physical models of buildings. And it has applications throughout the whole domain, which is something that we identified with this paper as well.

Priya Donti: Yeah, and it also comes up in electricity systems: this question of essentially how do we take a very large complex physical model for which we can write down all the physics that we want, but as a result it takes a really long time to simulate this on a computer — how do we take that really complex model and simplify all or parts of it using machine learning and other data-driven approaches that are trained maybe on inputs and outputs of that model?

David Rolnick: Just to feature another section written by Anna Waldman-Brown on industry: there is a notion of a digital twin of some industrial systems where you can run experiments or otherwise improve your understanding of the system by having a digital version of that system, which is simulated using machine learning.

Ariel Conn: I guess the implication in your paper then is one, it can obviously be used in more places; and two, would it be fair to say that it would be helpful to have machine learning researchers who can help optimize the systems that are already being used?

Kelly Kochanski: So I think of this as a small piece of a larger trend, which is that machine learning is going to give us a lot more options for many of the decisions that we as scientific modelers make when we’re building predictive models. So in this case, the decision is whether to use an expensive model that simulates physics that we know, we understand, we trust pretty well, and use that to get something that’s cheaper to run, but possibly harder to interpret. Although, interpretable ML is going to change this I think. 

There are a number of other areas where these kinds of transitions are likely to take place. For example, machine learning is also changing the way that people predict which codes are going to have bugs, or handle other technical challenges — like how to represent continuous ocean and cloud movement on a grid of discretely measured computational points. In all of these areas, they’re still under development. A lot of these are whole subject areas that have only started to come up in the last couple of years. And they’re going to need a lot more research by machine learning specialists, as well as a lot of testing in different application domains, before we can figure out where these techniques work and where they don’t. I think once we’ve pinned that down, it’s going to leave us with a lot of areas of scientific simulation that are suddenly much more tractable than they were before.

Ariel Conn: One of the examples that you give in this section is how machine learning can help with forecasting extreme events. Can you talk a little bit about that as well?

Kelly Kochanski: Extreme event forecasting is actually something that the machine learning community has picked up a lot on recently. So for example, the 2019 Gordon Bell Prize just went to a project which visualized extreme weather events and weather fronts in very large climate datasets. There are a lot of things people are doing — for example, taking weather datasets or climate model output and looking for hurricanes, or looking for extreme patterns of heat and cold, and using those to gather statistics either for the past or for the future; showing how often different types of extreme events come up in different places.

I think that this work is going to produce results that will be quite useful for people like urban planners and city governments as they try to figure out what types of storms, droughts, and so on, their cities are going to need to respond to in future years. Right now I think a lot of the challenges in this area involve the integration between the machine learning groups and between both scientists and city planners, in order to take the new machine learning solutions that are being developed and make them work within tools that can actually be used either by scientists to make more precise predictions or by the people on the ground who need to respond to them.

Ariel Conn: What are some of the technical challenges that machine learning researchers face working specifically with the climate data?

Kelly Kochanski: Climate data has a lot of messy characteristics that don’t tend to come up in benchmark machine learning data sets. One of the classic ones with extreme events is that the data sets are extremely skewed by their nature. Extreme events are very rare, and it’s hard to find a labeled training data set for a machine learning technique that includes a significant enough number of those to do good training on. Another problem that we have in earth science is that a lot of what we know about the earth is learned from inference across a lot of different physical processes and solutions that we put together in order to form a coherent picture of what the earth and its climate had looked like.

For example, if we want to figure out what past weather looked like over the last 50 years, we might be able to look at weather stations, which have used increasingly good sensor technologies as they’ve evolved and have been distributed in an increasingly large number of countries and places. We have to figure out how to integrate the data using all of those different sensors and observational locations in order to build up a record that’s long enough, 50 to 70 years, to be anything close to comparable to the distance into the future that we want to predict.

And so it’s really important to have tools that can pull data from multiple sources with different natures and different quality levels and put it all together to form that one cohesive whole before we can make predictions. As a related point, one thing that a number of people in the earth science community have thought about is building benchmark data sets for machine learning people to work on that have characteristics that are more common of the kinds of data that we deal with in earth sciences, to try to make it easier for machine learning researchers to develop tools that earth scientists can use.

Ariel Conn: Can you explain what you mean when you say benchmark?

Kelly Kochanski: So some areas of machine learning research — for example, image recognition — have involved a lot of development around specific datasets that a lot of people train on. There’s one in computer vision called ImageNet. And the advantages of these datasets is that people can look at them with many different machine learning techniques, and they can test optimizations, and they can quickly compare their code and their methods to other people’s code and methods to figure out what works well for tackling different problems.

One problem that a number of people in the earth science community have raised is that, since these data sets that are already in use don’t resemble our data that much, we might be able to create similar benchmark datasets that have some of the characteristics that are really important to us. If machine learning researchers develop algorithms for these specific data sets, we will begin to solve problems that are really important for earth science and create tools that can be used by a lot of climate researchers. One of the challenges that I’ve seen a lot in areas like hurricane tracking is that the standards for successful models within the machine learning community don’t always line up exactly with what’s being used by city planners or by other climate scientists.

For example, if you’re trying to make quantitative, useful predictions, it’s very important to have a well constrained uncertainty so that you don’t know just, for example, how many hurricanes you expect to have in a certain location, but whether that prediction is really good and precise or whether you might get two or three times that many. Within the climate science community, I think a large fraction of the effort that goes into modeling actually goes into modeling variability and uncertainty and accuracy and things like that. And I think the machine learning community is still working on establishing those standards.

And I think that it’s really easy for people to get excited about a model that looks like it’s working, and then really that’s only the beginning of the work — and you need to do a lot of digging in deeper to figure out the constraints on that model, and the bounds, and when it works and when it doesn’t, and when you can best trust it and make use of it.

Ariel Conn: It seems like addressing that type of problem would require exactly the type of collaboration that we’re seeing with this paper that you all worked on. One, is that the case? Two, are there other things that machine learning researchers and climate scientists can be doing to come together more to create better data sets?

Kelly Kochanski: I think a lot of people on both sides of this community have realized that this is a really fruitful area of research. Just in the last few years, there’s been a lot of interest by the machine learning community in climate science; and likewise within the climate science community, the interest is just growing really rapidly right now. At the big climate science conferences, we’ve gone from having a small number of abstracts discussing machine learning to having more than 10 sessions specifically dedicated to machine learning coming up at the next big Geophysics Conference later this year.

So the interest is really booming and a lot of people want to find ways to leverage this. And I think that they’re on track to converge and start forming these collaborations. So what we’re trying to do, really, is not push something that people don’t want to do, but to make something that people are already interested in happen a little bit faster and easier.

Ariel Conn: Were there other sections within this chapter that you think are important to mention that we didn’t get into yet?

Kelly Kochanski: I focused a lot so far on talking about the ways that machine learning can work within scientific models and with scientific datasets, but there’s also been a lot of work more directly with data. There’s been a lot of work to track land use cover patterns, which also comes up in another section of our paper, or crop types or reforestation from images and satellites and other remote sensing data that we have of the planet. It’s a more straightforward area. It looks more like traditional computing vision problems, but I believe that it’s also very promising and is also making a lot of changes in the way that we look at and measure the world.

Ariel Conn: I think that’s a really nice way to transition back to looking at the rest of the paper as a whole. We’ve gone through the sections that each of you worked on more individually, but obviously it’s a big paper. It covers a lot of topics. One of the things that David mentioned earlier that I think is really important is some of the most effective things that were discussed throughout the paper are not necessarily the — in quotes, I say they’re not necessarily the most “sexy” of topics, but they could be really impactful. I was hoping maybe you could touch on a couple examples of some of the most high impact, high leverage ways in which machine learning could be applied to the climate problem.

David Rolnick: So I’d like to second what Kelly said earlier about different applications of remote sensing. I think it’s a really great area of application for machine learning, partly because there are so many application domains, but also because computer vision — which is one of the main machine learning technologies involved in remote sensing, i.e processing image data coming from satellites or from planes — computer vision is a very well developed area now in machine learning. And I think it has a lot to offer almost out of the box for many of these applications.

So of course new innovations in computer vision also have the potential to lead to new innovations in these solution domains. There are just so many applications of remote sensing that it’s hard to pick even just a few. But as examples: pinpointing exactly where solar panels and wind turbines are, as Priya has talked about — that’s really fundamental to understanding power generation and grids, especially in situations where we don’t have a lot of centralized data. 

But also many other applications: so tracking deforestation, for example. There are many places in the world where deforestation is illegal, but enforcement is very hard. Satellites can be used to generate imagery at fine resolution where we can pinpoint using computer vision exactly where deforestation is happening, and thereby give more tools to law enforcement in various places to enable deforestation to be counteracted. Likewise with simply monitoring the health of different ecosystems across the world: sometimes that can be done very effectively, at least as a first cut, using aerial imagery to work out like what species of trees are there or how healthy the forest is.

Another area that I think is often under-investigated is adaptation. This is a huge area encompassing all the various ways that we can help society to be resilient to the unavoidable consequences of climate change and the consequences that are happening already. There are many different ways that machine learning can help society be more resilient to the effects of climate change — starting out with designing and implementing better infrastructure, finding places where infrastructure like water mains might fail, and creating systems that are more robust to the kinds of effects which we see happening; creating flood maps for particular cities to indicate what aspects of the urban infrastructure we should be reinforcing; then also, in the moment when a crisis happens, being there on the ground to provide real-time tools for first responders and for people who are trying to make a difference. People have used natural language processing, for example, to analyze social media, to work out where help is needed in disasters. This sounds a little bit strange, but sometimes this is the way to comb through large amounts of data to find out where help is needed.

Priya Donti: And I think adaptation illustrates one of the key points of our paper, which is that machine learning doesn’t exist in a vacuum. In a lot of the examples that David just discussed, in adaptation, machine learning can help give data driven insights about, as he’s mentioned, infrastructure or about disaster relief. But fundamentally, somebody has to build the infrastructure. Some city government has to create a disaster relief plan based on data driven insights that are given to them. So really a lot of the solutions that we propose here are to be done in conjunction with stakeholders like city planners or researchers in other domains or policy makers — because really we will all need to come together to address the climate crisis.

Kelly Kochanski: One of the other areas where I’ve seen a lot of exciting possibilities with machine learning is also to do with making more specialized and targeted predictions for individual stakeholders to learn more about how the climate is going to affect their specific area and location. I think that as we develop those tools, that will help a lot with communicating to people who are making these decisions and showing the impacts to individuals who need to figure out how to organize their lives.

Ariel Conn: This is a nice transition to a question that I have for you — and that is, now that you’ve written this paper, what are the next steps?

David Rolnick: We see our role as facilitating the development of this intersection of fields. One of the key components of that is — as we all have touched on — facilitating collaboration, because collaboration is the most important part of this work, and in many ways the most challenging part. So we are working on various different collaboration tools that will help stakeholders to talk to one another and form teams to address the solutions which we have outlined in our paper.

Kelly Kochanski: I’d like to chime in on that on a more personal note, which is that working on this project has opened up a lot of collaboration opportunities for me and has really encouraged me to look more for high impact work that I can be doing, and work that’s connected really directly to tools that people use and are going to need in the next few years, and to work on developments that will really affect a lot of people on the ground.

Lynn Kaack: I think also it helps to illustrate maybe where I come from, because I started working on the climate change policy field, but then increasingly started to integrate machine learning into the research. And I felt always kind of isolated in my work, and since we wrote this paper I met so many people working in the space, and it feels really great to have sort of an academic home, as somebody put it. So that’s really something that we’re trying to provide here. Not only for academics of course, but for everybody working on this space.

David Rolnick: We’ve really had people coming out of the woodwork in all kinds of sectors, everything from academics to people in finance who really want to make a difference here and are eager to see that they have the ability to use their skills, and the areas in which they work, for good within the space of climate change.

Ariel Conn: So it sounds like you’ve mostly gotten a pretty positive response to the paper so far. Is that how you see it?

David Rolnick: We’ve received a hugely positive response.

Ariel Conn: Excellent. This question sort of touches on some of what you’re saying. To a certain extent, I’m guessing that machine learning hasn’t been applied more to address climate change issues because it’s been a fairly small field for quite a while, at least relatively speaking. So you haven’t had as many people with the skills to do so, and I’m guessing it probably costs money to bring them on, or it requires a lot of time and money for someone to learn. Is that the case? Is that what you’ve seen? If so, how do you envision getting more machine learning researchers partnering with climate scientists?

Kelly Kochanski: I think the machine learning research community in general has taken a lot of actions that actually make this easier. There’ve been a lot of things that have come out of it: like habitual sharing of code from landmark papers in machine learning is really fantastic from the point of view of climate scientists, because it means that we can implement a lot of exciting things and try them out with a relatively low barrier to entry. I’ll also say personally that what I’ve found is that as I’ve reached out to machine learning researchers about their work, and about techniques that I think it might be interesting to apply in climate and earth science contexts, a lot of people have been really thoughtful and helpful and interested in thinking about ways that they could, for example, adapt their work slightly to make it more applicable to climate problems.

David Rolnick: I’d also like to shout out to all the communities that have been thinking about aspects of this problem, in some cases for years. So, for example, climate informatics — which combines climate science with data, statistics, and machine learning — has been around for many years and has led to many deep insights in this conjunction in different fields. Likewise, computational sustainability has been a movement that for many years has encouraged insights across sustainability, broadly defined, and different aspects of machine learning and AI.

Ariel Conn: What are some of the technical challenges that you still see for machine learning in the climate area?

Priya Donti: One of the challenges that I definitely see in bridging machine learning and climate change is in getting people together in the same room who speak different languages or come from different cultures — both literally, because this is a multi-stakeholder, multi-country problem, but also in a technical sense. People who, for example, speak the language of electricity systems, versus speaking the language of machine learning. To give a personal example from machine learning and electricity systems, there is a little bit of a culture within machine learning where the inclination is to try new solutions, in some sense move fast, break things, and if it doesn’t work, just try again.

When you intersect that with electricity systems — which is a field in which we need to keep the electricity system running, because the implication of not doing that is the power going out — how do we bring together this culture of move fast versus be careful? It’s something that I think we will continue to grapple with as we get different kinds of stakeholders at the table.

Lynn Kaack: Another big challenge is that we need to get better at generalizing, especially since many of the solutions need to be able to be transferred between countries, which come with very different socioeconomic realities; also, different natural circumstances, and they might also change over time. So this is something that I see over and over again in different domains and different areas of mitigation and adaptation: that we need to be able to make models that work for different settings.

Kelly Kochanski: One thing that I’ve seen come up again and again as well is the need for machine learning solutions that work well with constraints. By constraints, I can mean anything from, in Priya’s examples of energy grid management, guaranteeing that no matter where you put your machine learning system, you’re not going to make the kind of mistake that makes the power go off; or in my area of climate research, we worry a lot about constraints like energy conservation, and not building machine learning models that violate the conservation of energy. 

These are both cases where we have these constraints. We want the machine learning model to satisfy these constraints, and we also want to be able to use the knowledge about the system that these constraints represent to make the machine learning model easier or faster or otherwise simpler and better to work with. Having tools to do that in any kind of general way that makes it easy to translate from our intuitive understanding of what we want from the system’s behavior to the machine learning model would be very helpful.

Ariel Conn: I want to turn back to the paper as a whole. I was hoping each of you could maybe mention one or two examples from the paper that we haven’t gotten into yet that really surprised you, or were exciting, that you think are important to mention.

Priya Donti: The industry section written by Anna Waldman-Brown has a lot of examples that I personally find very exciting. Some of these are optimizing supply chains; that is, the way we move goods and services from creation to retail, and how we can make these processes more efficient by, for example, forecasting how much demand that we might have for a specific retail product. Other applications in this section include reducing food waste, for example by using sensors in a bucket of food to figure out which produce is going to go bad and as a result you can remove it in order to then prevent the rest of the produce from going bad.

I think the industry section highlights a lot of interesting considerations when working in this space. Specifically, you can optimize a supply chain all you want; or you can, for example, shift electricity demand and industrial applications all you want. But fundamentally, industrial partners incentives have to be aligned here to actually reduce greenhouse gas emissions. So policies either have to come into play or there has to be some alignment between reducing greenhouse gas emissions and saving money or servicing the bottom line.

Another interesting application for me here in the industry section that also recurs throughout the paper is this application of accelerated science: so creating, for example, alternatives to cement that require fewer emissions to produce. This application also comes up in the carbon dioxide removal section; so, how can we create more efficient sorbents — essentially carbon sponges — that allow us to remove carbon dioxide from the atmosphere more efficiently? Then I previously gave the example of solar fuels in electricity systems. So this application of accelerated science is one that is cross cutting throughout the paper that I found particularly exciting.

Lynn Kaack: That’s also something that surprised me quite a bit. Another thing was precision agriculture. They use a lot of data and robotic applications to really precisely treat a field according to the needs — so in terms of water or fertilizer. This both helps mitigation and adaptation, and it’s actually already being deployed. It was something that I thought was very far out in the future — but through writing this paper, I’ve actually learned that this is a real application that might have a future.

David Rolnick: Another area that I’d like to call out is finance; the finance section of our paper was written by Sasha Luccioni. There are two aspects in which finance relates potentially to climate change and both of them have huge potential impacts in shaping forces within the system to help the overall climate crisis. So the first one is climate investment, involving finance identifying which companies, which investments are contributing positively or negatively to the climate crisis, and allowing investors the ability to choose based upon those factors.

That really has the potential to give boosts to sections of the economy that are working against the climate crisis; and also, to increase liquidity in potentially very small businesses that are having an out-sized impact in a positive way. Then the other aspect of climate finance that I want to stress is climate analytics, which looks at the potential for companies or entire industries as it relates to the climate impacts on those industries. So here, one looks at what the inevitable consequences of climate change are going to be, and then looks at how that will affect certain industries.

Accounting for that in the global financial system is really vital to making us as a society take these kinds of impacts seriously. Because sometimes when you don’t put a price on it, it’s very hard for society to move to take action.

Ariel Conn: All right. We’ve looked at a lot of specifics and some of the details of the paper. If we were to take a step back and sort of clarify a few key points that you really want people to walk away with, what would those be?

David Rolnick: Machine learning is a really powerful tool, and it can be applied to a very broad range of problems with climate impact, but it’s also not a silver bullet. It’s not magically going to solve the climate crisis. Also, in every way of applying machine learning to climate change, it’s really essential to involve both multiple fields and multiple different stakeholders, experts in various aspects of the problem, and also end users, who will be the ones interacting with whatever is deployed.

Priya Donti: From a machine learning perspective, there are many kinds of innovations that we need in this area in order to combat the climate crisis. So there are things that researchers can do to fundamentally advance machine learning while contributing to climate change. There are interesting engineering opportunities, business opportunities, opportunities for established businesses to apply machine learning to their practices to reduce greenhouse gas emissions. And of course, there are a lot of public sector applications here. So really the kinds of people who should be interested in whether machine learning maybe can help them address their piece of the climate crisis is a very broad group of people.

Lynn Kaack: Another point is that there are really many ways to have an impact. This goes both for mitigation, where there are just so many different sources of greenhouse gas emissions and many solutions to reduce those, but also for adapting to the risk of climate change. What we would like to take away from this paper is one should have an open mind going into this field and be ready to work on problems you haven’t thought of before. Even as David already put it before, those might be not as attractive at the first sight, but if you’re coming with an open mind, they might open up into very interesting problems.

David Rolnick: Listen to what the domain experts tell you. Listen to what the people who have thought about this for their whole careers tell you. Talk to people who have thought about these problems their entire lives. Whatever area of solution you’re thinking about, there is somebody who has spent a long time working out exactly what is needed there. If you can give it to them, that has huge potential for impact.

Kelly Kochanski: I’d like to follow up both of the previous points from Lynn and David by saying that one of the things that’s been most surprising and wonderful about this project is that’s given me a lot of hope for climate change. Being embedded in climate science — sometimes that can be very difficult, because we spend a lot of time measuring how things could go wrong. But working on this project has really put a lot of emphasis on solutions, on things that we can do, on the wide range of possible avenues that there are, and on the fact that all of these will have an impact. Even the small impacts will still make a difference, and we can be moving towards something that’s really positive and optimistic in this area.

And finally, that there are a lot of people who are thinking about this, and who really want to make a difference, and are working hard on finding new and better ways to do it that’ll make it easier for us to have a climate future that works.

Ariel Conn: That really was great. I want to open this up now to everyone else, too. How hopeful are you now that we can address climate change before it gets too bad, and did this paper impact you as it did Kelly?

Lynn Kaack: So on the one hand, I’m actually quite hopeful because I know that there are a lot of technologies that exist today that, if we would implement them, they would actually make the economy emit way less greenhouse gas emissions than we currently do. And there are also many people working on future technologies, and I really believe that we will have some solutions in the future that will enable us to go down to net zero carbon emissions. 

But on the other hand, I’m extremely worried about that the society will not build up enough pressure to implement them. So our economic and political systems have, to this point, not acted fast enough, and I would really like to stress that it’s important that people make their voices heard if they want to transition to a low carbon society. I think part of that is also legislation that can help to tackle climate change.

David Rolnick: I’m terrified. I’m terrified because technological solutions are only part of the ultimate solution. Through machine learning, through other technologies, you can make decisions easier for society to make — but ultimately society does have to make those decisions. But I’m not just terrified. Climate change is often thought of as an on-off switch — either we’re doomed or we’re saved — and it’s really not about that. There are so many ways in which we can avert some of the most serious consequences and pick how far along the path we want to travel. Focusing on that, rather than on solving climate change, for all that we’ve talked about solutions, is really maybe the best way forward.

So focusing on reducing greenhouse gas emissions, focusing on helping society do what it can to be resilient to what is inevitable, will really help us reach a place which is as good as possible. And that’s all that we can do.

Ariel Conn: What do you hope to see from people, both in response to this paper but also just more generally? We’ve been looking specifically at what climate scientists and machine learning researchers can do to try to address this problem. But as you’ve been looking at this, are there some big or little things that you’d like to see happen that any individual could start doing more of?

David Rolnick: We’re trying to build tools to enable action from individuals and from organizations. On our website,, you can read about some of the things that we’re doing, and even sign up for a mailing list where you can receive updates about the kinds of tools that we’re trying to bring out there to enable work. But I would second what people have already said from this group — that if you’re trying to be involved, learn about these issues, find people to talk to who are potential collaborators, listen to them, and then make sure that whatever you’re doing really gets out there in the world is deployed with impact. 

Kelly Kochanski: The other thing I’d like to add with that is that it really helps to take action now, and a lot of what I think is important about this work is the speed. The faster that we can create solutions that will lower greenhouse gas emissions by any fraction, the less total warming we’re going to see on earth, because the less total warming we’ll have put into the atmosphere. And so if the work that we’re doing takes people who have the energy and the drive to do something and gets them moving even a month earlier than they might have been going otherwise, then I think that’ll be a big success.

Priya Donti: One thing I’d like to add and to stress is that while our paper looks at how one particular kind of expertise — that is, expertise in machine learning — can be used in conjunction with climate change domain expertise to address the climate crisis, I think there are many other types of expertise that are needed. And so other fields would also, I think, benefit from examining how specifically they can contribute to the climate crisis, and to mobilize movements in their fields to do that.

Ariel Conn: All right, so I think this is really good. David, Priya, Lynn and Kelly, thank you so much for joining and talking about your paper today. It was a really great paper and it was really great talking with you.

David Rolnick: Absolutely. Thank you so much.

Priya Donti: Yeah, thanks so much for having us.

Lynn Kaack: Yeah, thank you.

Kelly Kochanski: Thank you for having us Ariel.

Ariel Conn: I really hope you enjoyed this episode, especially since we’re bringing you more machine learning and climate change in the next episode! In episode 17 of Not Cool: a climate podcast, we’ll hear more about how individuals and communities can use machine learning to improve carbon footprints and climate policies.

Tegan Maharaj: I would say in the short-term, it’s often the case that climate-friendly solutions are harder to implement, because they’re a change to the status quo, so that makes them a bit more expensive — but in the long-term, virtually all of the climate and environmentally friendly solutions just make economic sense.

Ariel Conn: Be sure to join us again on Thursday, and as always, if you’ve enjoyed this podcast, please take a moment to like it, share it, and maybe even leave a good review.


Not Cool Ep 15: Astrid Caldas on equitable climate adaptation

Despite the global scale of the climate crisis, its impacts will vary drastically at the local level. Not Cool Episode 15 looks at the unique struggles facing different communities — both human and non-human — and the importance of equity in climate adaptation. Ariel is joined by Astrid Caldas, a senior climate scientist at the Union of Concerned Scientists, to discuss the types of climate adaptation solutions we need and how we can implement them. She also talks about biodiversity loss, ecological grief, and psychological barriers to change.

Topics discussed include:

  • Climate justice and equity in climate adaptation
  • How adaptation differs for different communities
  • Local vs. larger scale solutions 
  • Potential adaptation measures and how to implement them
  • Active vs. passive information
  • Adaptation for non-human species
  • How changes in biodiversity will affect humans
  • Impact of climate change on indigenous and front line communities

References discussed include: 

What people fear the most is the change in their lives. So if we can do the needed changes to address climate change and adaptation without disrupting the routines of people, to a great extent, that makes it a little easier.

~ Astrid Caldas

Ariel Conn: Hi everyone, and welcome back to Not Cool, a climate podcast. I’m your host Ariel Conn. Today, on episode 15, we’ll be joined by Astrid Caldas, a researcher with the Union of Concerned Scientists, who will go into more detail about what’s involved in adapting to climate change, how the ability or inability to adapt will impact biodiversity, the threat of extinction for many species, the role of government in creating more equity in the solutions to climate adaptation, and much more.

Astrid is a senior climate scientist with the Climate & Energy program at the Union of Concerned Scientists. Her research focuses on climate change adaptation with practical policy implications for ecosystems, the economy, and society. She also works on policy related to climate change, natural resources management, conservation planning, socio-environmental synthesis, and climate communication.

Before joining UCS, Dr. Caldas was a Science & Technology Policy Fellow at the American Association for the Advancement of Science. She was a climate change and wildlife science fellow at the nonprofit conservation group Defenders of Wildlife. And she was a research scientist at the University of Maryland. Dr. Caldas has advised or consulted on projects with organizations including the Smithsonian Institution and the National Socio-Environmental Synthesis Center. She has a lifelong passion for butterflies and moths, which she has studied for many years.

So Astrid, thank you so much for joining us.

Astrid Caldas: You’re welcome. Thanks for having me.

Ariel Conn: I really want to talk about your ecology background. But before we get there, you focus a lot on climate adaptation.

Astrid Caldas: Correct.

Ariel Conn: And I was hoping you could just start by explaining what that means.

Astrid Caldas: Climate adaptation means being prepared to face the impact that climate change is going to bring to you as a person, to your community, your city, or your state, your country. There are different levels of being adapted. But basically, that’s what it means. Being prepared with all the information, with all the policies, with all the physical preparations and protections, depending on what the impact is.

Ariel Conn: How does adaptation differ between — we’ll start with just different communities. I mean obviously if you live in a desert, how you adapt is going to be different than if you live in a coastal region. So can you talk a little bit about some of the various issues that communities might need to be dealing with?

Astrid Caldas: Climate change impacts a lot of stuff, right? And what it doesn’t impact directly, it impacts indirectly. It can multiply a natural hazard; It can make something worse like hurricanes or extreme precipitation. There is not only the temperature increase, there are all these other impacts that are going to be affecting people.

So if you live in the coast, one of the main issues may be sea level rise or hurricanes, depending on where you are. If you live in the mountains, it may be snowfall. It may be too much snow or too little snow; It may be snow melting too early or too fast. If you live along the river, it may be flooding that is influenced by extreme precipitation that is influenced by climate change. If you are in an area that has wildfires, climate change has made wildfires burn hotter and for a longer period of time. So wildfire season has increased in extent and length.

So depending on where you are, you can already tell that adapting is going to be different. If you are on the coast, you’re going to need to either protect against the sea level rise — you’re either going to have to accommodate the water as it comes in, creating areas that can be inundated without damage — or you may have to move away from areas that actually flood so often that you will not be able to either protect or accommodate anymore.

On the other hand, if you are in an area that has wildfires, you have to work with local government and have local policies to try to minimize the risk for wildfires. And also build better — actually that’s in most areas — to build better, to rebuild better, to have better policies in place for buildings that is more safe and more resilient to the impacts of climate change.

Ariel Conn: So we can watch the news and see that we’re getting bigger hurricanes. We can see that regions are flooding. We can see that places are burning and on fire. But what are some of the things that either we need to do to adapt, or that could pose a problem, that you think aren’t getting as much attention right now, or that people aren’t as aware of?

Astrid Caldas: Adaptation is not an easy thing, right, because in many cases it will entail changing ways of life, and that is one of the biggest barriers. People don’t want to leave the coast, the beach house. People don’t want to leave the home in the woods in California that they wanted their whole life and it was so beautiful before the fire. They want to rebuild in the same place. Either the beach after a hurricane or in the forest after a wildfire. They want to rebuild. They want to go back to their normal lives and their routines. And that’s human. That’s just the human spirit. That’s just the human nature.

However, many times that’s not the best way to be resilient because, as a colleague of mine puts it, “If you are rebuilding from flood, you are susceptible to flood.” That’s just basic. If you are rebuilding from fire, you are in an area that is likely to be on fire. Even if a lot of stuff has burned before, climate change can make it worse: make the earth drier, make the plants drier, create more kindling, create more fuel for the fires.

So in a lot of instances there is this fine line between, I want to stay and do the same things the same way I have done my whole life, and this other side of this fine line that is, I need to change something because I don’t want my home to burn again, or I don’t want my house to flood again.

And then a lot of times people just prefer to put it out of their mind and hope that it doesn’t happen again. That’s not the way it works. We need policies and incentives in case of flooding along rivers. We need better flood maps and better insurance policies; better programs to protect people, better programs to protect people before the thing happens.

It is a very local thing and a very specific thing for each location. You see there are some places that whole communities want to move away because they just can’t live there in the way they used to live anymore. And when it gets to that point, that’s the hardest part.

Ariel Conn: You’re talking about the problem being local and the solution to this being local. And yet if we do have situations where an entire town has to move, that becomes a problem for a bigger region. How can policymakers deal with the fact that the regional area of the problem grows?

Astrid Caldas: The solutions have to be local in the sense that the community has to decide what they want to do. But they definitely need federal incentives. And they definitely need federal policies and federal protections. So that’s one of the things that is very important. And as you said, if it turns into a regional thing and whole areas are going to be facing the same problem, then we got to start being creative, bold, and innovative in the ways to deal with this impact of climate change.

And honestly, we will only know when they get to a point where those impacts cannot be dealt with anymore. But we are not at that point. And nevertheless we are not seeing things that could be done right now to avoid getting to that point.

Ariel Conn: Can you give some examples of things that you’d like to see happening?

Astrid Caldas: I would like to see better zoning along areas that flood — not only on the coast but along rivers and floodplains. I would like to see more money, more policies, for pre-disaster mitigation, as we call it, to have people better prepared for when a disaster comes in an area that’s prone to that disaster. I would like to see a better national flood insurance program everywhere, including coastal areas — not just in the floodplains.

There are several things, and I’m talking mostly about water because that’s one of the things that I work the most with. And I’ve gone out to the coast and talked with the communities there that are losing their livelihoods. And the communities are just dwindling. The people are leaving. The young people are gone. So there’s all the old people who live there who are just holding the fort and really not leaving until they can’t stay anymore, and they’re hoping that it’s not going to happen in their lifetime.

Ariel Conn: You’ve talked a little bit about incentives, but how do we get people to embrace massive changes to their lives?

Astrid Caldas: That’s a tough one. The main thing is to try to find a way for them to keep what’s important in their lives, but done in a better way. For instance, you want to keep driving your car: Drive a better car. You want to keep eating some food that you like to eat: Try to get it more local if possible. You want to keep using your makeup: Try to use a better makeup. Anything that’s part of your life that is important to you, if we can find a way to make that thing better with less impact to the environment, that is the way to go.

Because what people fear the most is the change in their lives, right, as you said. So if we can do the needed changes to address climate change and adaptation without disrupting the routines of people, to a great extent — there will be some disruption — but as long as there is not a complete change in life, that makes it a little easier.

Ariel Conn: So we often hear and talk about policy changes that need to happen, but a lot of what you’re talking about actually involves simply helping people be better informed about their choices. Do you feel that that information exists and people just have a hard time finding it, or do you think we need to do a better job making that information available so that they know what the better cars are, so they know what the better makeup choices are, so they know better clothing and consumer habits and things like that?

Astrid Caldas: I think both your options are true. The information is out there, but it is hard to find. So it’s what I call active information as opposed to passive information. To do a better job of telling people what can be done, we have to actively tell them and not to just put it on the website and expect them to go do a search and try to find it.

So for instance, one of the things that upsets me a lot is every single car manufacturer, pretty much, has an electric vehicle or a hybrid vehicle. However, you don’t see commercials for those on the TV. You only see commercials for the regular combustion engine cars because they make a lot of money. That’s the most sales that they have. But we need a sea of change. We need to have … Actually, I think I saw a BMW, or one other brand, have a commercial for an electric car recently. And I was like, “Whoa. This is different.” Because if you look, everybody has an electric car, or a hybrid. Why can they not advertise those cars?

These are the types of changes that we need. And just like the cars, there are many other things. We have here at UCS a book that was published back, I think, in 2012 or 13. The title was Cooler Smarter. And it is about what you can do in your daily life to reduce your carbon footprint. Because at the time, the calculation was, if every person in the United States reduced their carbon footprint by 20%, it would be the equivalent of closing half the coal fired power plants that exist in the United States and remove all those emissions from the atmosphere. I think the number is like 300 power plants — at the time there were 600, so closing down 300 power plants. Reducing your carbon footprint by only 20%, it’s still totally doable for most of us.

There are these types of information that they are not life changing in a way, but they can be life changing because they will change the future of your life. So I am all for active information: finding better ways of telling people what’s out there that can do the same things that they do, and the incentives to make these things not as expensive. Some electric vehicles are not very expensive at all, but some are very expensive. Solar panels, the price has gone down. Renewable energies, all of these things. You need incentives for people not to have to spend more to save the environment.

Ariel Conn: I am really interested in the example of advertising for cars because this is not something I’ve thought about. Is this the type of thing where we could establish incentives for companies to advertise their vehicles? Would that help?

Astrid Caldas: I don’t know if they could get incentives for car manufacturers to advertise their products, but certainly the more incentive to improve their electric vehicles and make them more affordable and just as good and reliable as the regular combustion engine cars — that’s something that definitely policies can do. And once that exists, I mean why stay with something that’s an older technology, that pollutes the environment, when you can have a much cleaner option that does exactly the same thing.

Ariel Conn: So as I mentioned at the very beginning, you have a background in ecology as well. And we’ve been talking about what climate adaptation means for people. But what does it mean for plants and animals and for biodiversity overall?

Astrid Caldas: That’s the very interesting part about climate change. People can adapt to using external devices and technologies; They can adapt by changing the technologies that they use. But plants and animals do not have that ability. They live as nature around them allows them to.

So evolutionarily, over millions of years, plants and animals have adapted to an environment. Well, with climate change, plants are fixed in one place. When they throw their seeds, and their seeds disperse, they are finding other areas that in the past were not appropriate for them to germinate and to grow, but now they are.

So there are these plants changing their range of occurrence and disappearing from some other areas where they can’t take the heat anymore, or there’s too much flood, or there is salt water intrusion. A lot of areas along the coast that used to be hunting grounds for lots of tribal communities are not there anymore. They can’t hunt in those areas anymore because the trees are dead, there’s no more grasslands or whatever.

So this is with the plants. And the animals also follow because nature is always interacting. A lot of the animals depend on animals or on plants, right? Depending on what they eat and their life cycle. So animals are also changing their range and changing their habits sometimes.

There are studies that show that some things that we thought could only happen in an evolutionary scale, which is over thousands of years or millions, actually starting to happen much faster with certain organisms. They are able to adapt in the evolutionary sense, which is different from adaptation that we use — technologies to adapt to climate change. They are able to change themselves to take better advantage of the new environment that they are living on.

On the other hand, lots of species are disappearing and are slated to disappear as temperature increases because a lot of the interactions that they depend on and a lot of the other things in nature that they depend on are either more sensitive or changing. Plants that this animal eats can not stay here anymore; It moves away. Well, that the animal doesn’t have that plant here. It either dies or it follows the plant. Well, if where the plant is is not an area that they can live well, they are not going to thrive there.

So all of these systems are getting disrupted, and we don’t know where they are going. Lots of studies are trying to determine the future of a certain species, certain groups of animals, certain groups of plants. There is that uncertain part, which is, what processes are going to be lost? What interactions are going to be lost? To model one species and temperature is one thing. To model all the things that it depends upon in the environment, nature, is a completely different thing and much more complex.

Ariel Conn: So I have a lot of questions. I guess I’m going to start with the easy one. Well, the easy one for me to ask; I don’t know that it’s easy to answer. Why should people care about either biodiversity loss or biodiversity migration? How does that impact people? Why should we be concerned about this happening?

Astrid Caldas: Well, first and foremost, we are part of nature. There’s a lot of services that nature provides us for free that we don’t realize, right? Filtering water, replenishing groundwater, providing food for a variety of small animals that we don’t use, but they are food for things that we harvest or that we fish. There’s this direct dependency on nature.

On the other hand, there is also the cultural value, and the beauty of nature; the fact that a lot of people like being in nature — they value it. It’s a part of their being. If you live in an area that has always had these beautiful tall oaks and the oaks are dying, it turns into a completely different thing. Some people take that very, very hard. And in fact, there is a new term called ecological grief, which is the mourning of ways of life that are no more. People would just get depressed. They don’t feel the same. And their livelihoods change.

With the Bay water and the Chesapeake getting warmer, the fisheries are changing. The fisherman are not harvesting the way they used to or what they used to. So there’s all these things that we really depend on nature, and we are a part of it in so many ways.

Everybody should care. I don’t think if you ask anybody, “Oh, if all these woods, and the beach is gone, and everything in the lake, would you care?” I don’t think anybody would say, “I don’t care. I have my house.” Right? It’s a lake. It’s a place where they fish. It’s a place where they run. A beautiful park, or to go to the beach. They hunt in the forest. So many ways that we appreciate and depend on nature. So yeah, now you’re depressed. Okay. I am too.

Ariel Conn: Yeah, you mentioned eco grief, and I’m like, yeah, I’ve got that.

Astrid Caldas: I think a lot of people who are really connected with nature feel that to one degree or another. And even people who don’t think about it, if they sit down and start looking around and thinking about it, they will get a level of it too.

Ariel Conn: I hope so. I very much hope so. So you mentioned that some species are actually finding ways to adapt quickly, whether that’s adapting to new situations or figuring out ways to move. But most of what we hear about is biodiversity loss — so, the idea that most species aren’t doing this. Are you finding that’s the case, that most species are not able to adapt? Or do you think we’re going to be surprised by how many species do manage to adapt?

Astrid Caldas: From the literature, I do believe that we are going to get a great loss if we don’t stop global warming and climate change. What exactly is going to be lost, and what can bounce back, and what can find other ways to survive, is really not known.

But I would say it’s pretty much certain that things that depend specifically on temperature for instance, like corals: there’s no way that they can live above a certain temperature. They just die. And the seas are getting warmer. They are absorbing most of the energy from the atmosphere that comes from global warming. It’s going to keep getting warmer if we don’t reduce the amount of emissions.

So there are things that are certain. And there are things that we expect that they will happen, but we may not know exactly how it would happen and to what degree. But biodiversity loss — it’s pretty much well established that it is going to happen to one degree or another.

Ariel Conn: If we’re using this example of an amphibian or a fish that’s in a stream that’s getting too warm, how do you address a problem like that? Do you have to capture the animals and try to move them someplace else to try to come up with ways to cool down the stream? What does the solution look like? Or do you just recognize that it’s a problem and try to then do more research?

Astrid Caldas: A little bit of everything that you said. There are species that have been moved to other areas to be protected. And this may have not been done because of climate change, but it has been done because of loss of habitat, or land use changes, or stuff like that. But yeah, it would need to be done because of climate change in the future.

So for instance, there is — I think a trout is a big problem because trout likes a certain temperature. And there are lots of species that are not doing really well because the creeks and the places where they occur naturally are getting warmer. A lot of these may be locally extinct, but they may be thriving elsewhere. So that’s where the research comes on. Where is it that it still occurs and is it thriving there, or is there a decline in the whole range of occurrence of this species?

There are lots of things that need to be done, including interventions in nature that are intended to protect. One of the things that they do is try to increase the vegetation along the edges, along the margins of the creeks and the rivers, to create more shade so that there is less direct sun and the water doesn’t get as warm. That’s one of the strategies that I have read about for instance. But if the ambient atmospheric temperature keeps going up — the water has a surface in contact with the air; and if the air is warm, it will warm up the water.

I just heard from a tribal policy expert, and he was telling me about shallow inundation. At UCS here we did a study that we call chronic inundation. The title of the report is When Rising Seas Hit Home. And in that report, we identify locations along the coast of the lower 48 that will be chronically inundated, which means inundated only by high tide at least 26 times per year — because of high tides alone, which are the highest tides twice a month, give or take.

So we identified the areas because we did the projections, and sea level rise, and the whole thing. But this tribal policy person told me, he said, “For the tribes, the shallow inundation, this water, the tide that comes and floods, even at the very low inundation level, like just a couple inches, it comes in and it floods the ground for part of the time. That water gets very hot in the sun. And that’s starting to change the system. That’s starting to change the species there. Starting to change the environment.”

And you know how tribal communities are so attuned to their environment. And they plan on them, and they have things planned according to their environment for thousands of years. So this is one of the impacts that people don’t think about. You see that’s happening. How are those changes going to affect not only the environment, but also the people who depend on that environment for their livelihoods and their culture?

Ariel Conn: I guess I want to ask you more generally about what else you do. So you work with the Union of Concerned Scientists, and you do a lot with climate adaptation and trying to get various groups and policy makers to take action. I was hoping you could talk just a little bit more about anything else that you’re working on that you think is important for people to understand?

Astrid Caldas: One of the things that I think is very important is to get to know the people who are suffering these impacts firsthand. A lot of times those are what we call “front line communities.” They are the ones that are hit first and hit worst by the impacts of climate change. And they have been hit in the past by pollution and, you know, gas plants, oil plants, refineries.

They are all in certain neighborhoods where these people who are mostly low income and minorities live. And it’s like, they are there, they cannot live, and people keep using their area to build more polluting stuff because it’s already there and the land is cheap. So there is this cycle that keeps repeating itself. So to get to know the people who are living in those areas, and seeing their problems, and try to bring that to the policy makers is a very important thing.

Recently, I’ve been doing some work on the eastern shore of Maryland in very old communities. Some of them are black communities. Some of them are white fisherman. They are losing a lot of land to sea level rise. The eastern shore of Maryland is second only to Louisiana in loss of land because of sea level rise. A lot of these people are losing their livelihoods, they’re losing their land; The sea level rise is eroding their land, and the water is getting closer to their house.

So one of the things that I do is go there and ask what they are seeing, and ask why they think they are seeing that, and what they would like to do about it. And with that knowledge, we can come in and tell them, “This is happening right now, but the future looks like A, B, or C. It may get worse here or better here and you have certain amount of time before this or that happens.” And that can be very helpful for them to start planning their lives.

One of the senators of Maryland went to meet with one of these communities on the eastern shore of Maryland. And later on, I was talking to the senator, and I mentioned that to him, and I said, “You know, the National Climate Assessment went to great lengths, in this version that just came out last year, to show the impacts on people, on communities, on livelihoods — put even a price on it, what the economic impacts will be of unchecked climate change.” And yet, people think that the National Climate Assessment is this document that is pure science out there. No. I told the senator, “Every single thing that you saw at that community meeting and that you heard from that community is described in the National Climate Assessment. Everything is there.”

So the National Climate Assessment is a huge resource to see what can happen. And it’s not policy prescriptive, but it tells you what would happen if climate change didn’t go unchecked. What could be better. What could be saved. What could be protected. It doesn’t tell you what policies are needed, but it is a great resource that is not being used as it should.

So one of the things that I tried to do was try to make these connections, particularly for these frontline communities. Climate justice, Environmental justice. Communities that are forgotten. After Hurricane Harvey, lots of people are still trying to get back their lives. Where’s the help? People who are more wealthy, they have insurance, they have everything, they have the means to rebuild. But the people who live day to day, they don’t have the resources. They lose their money because they are not working during the flood. So I tried to bring up the importance of equity in climate adaptation. That’s one of the big things that I do, also.

Ariel Conn: That one’s really interesting to me. I mean, we talked earlier about the idea of what happens if you have a community that does have to move. And part of what happens is the wealthier people of the community are more likely to be able to move. Whereas people who have less are going to find moving harder. Or making all of the other little changes — I mean, a lot of instances the more environmentally friendly options are more expensive. Buying local is usually more expensive than cheap canned food. How do we address that?

Astrid Caldas: That’s where we need the government. That’s where we need the incentives. I think that I mentioned before, to make these things that are better not be more expensive or more onerous on the people who need them most. So subsidies, different policies, protective policies, financial policies, all these things that would help a lot. If only people put their minds to it.

Ariel Conn: So we talked earlier about how it can be difficult to find information about the choices people can make. And you mentioned the National Climate Assessment being a good resource. But that’s probably more for policy makers; I’m guessing the average American probably isn’t going to just sit down and read that. Are there resources that you recommend people use to try to improve their decisions?

Astrid Caldas: Well, the National Climate Assessment is not that bad if you read just the summary. You don’t need to read the whatever, 500 pages. But there are lots of organizations that are dedicated to bringing the information. My organization is one of them. We have lots of good resources for the general public, giving information in a digestible way that relates to climate change.

We can talk about policies that would be good to have and things that communities can try to fight for and can start asking of their elected officials at all levels. So I would start of course with my own organization. You know, our website is full of resources. But there are lots of other good organizations out there. Universities have programs that are related to climate change — Yale has a good program, George Mason University has a good program — that have websites that talk about how people react to climate change science, why they react like that. It’s kind of interesting. People can look at that. They have bubbles and stuff, you know, and it’s kind of an easy read. But then you kind of, “Oh, I relate to this person here that has this type of reaction to climate change.” And then you can read why likely they have that reaction and what are the reasons. And it’s kind of interesting.

Ariel Conn: I think we’ve touched on most of what I was hoping to get into. Is there anything that you think we missed that you think is important for people to know?

Astrid Caldas: Well, there are lots of people — lots of information that people should know. I can talk for hours, but I think one thing that I’d like to mention — because I talk a lot, I go to lots of different audiences to talk about science, and climate science in particular. And one of the things that people ask me a lot is, “Why do you think a lot of people in the United States do not accept climate change?” They say “believe in climate change,” but I don’t use “believe” because climate change is not a belief. It’s a matter of science and data. But why they don’t accept.

And one of the things that I have been studying and reading a lot in the social sciences: the idea of confirmation bias. The person will seek information that confirms their preconceived views. You have that idea, and you try to avoid anything that disrupts that idea. So that only reinforces more and more your ideas.

So from the beginning, if your peer group — well, some of your peer group, or one of your social groups, or your church, or your whatever — everybody thinks that climate change is a bunch of baloney, you don’t want to be the one that’s going to say, “Actually it’s not a bunch of baloney. It’s actually true because the data.” They are going to look at you and not invite you to the parties anymore.

So if people want to belong, they want to belong, they want to be part of something. And that’s one of the things, that people tend to listen to news that confirm their views. And that’s for everybody. I do that too. On both sides we do it. I always like to mention that to people because it’s not that people are bad. It is people’s nature to try to belong to a group that they value. Core values are things that are more ingrained in us and things that go against our core values are things that we fight. Climate change, believing in it or accepting it, is not a core value. It can be changed, but the only way to change it is if we can make it appeal to one of our core values. Ethics, honesty. Yeah.

Ariel Conn: I find the psychological element to accepting and addressing climate change really interesting. Confirmation bias is a big problem. But I often wonder if some of it is also accepting climate change as real means that you do have to make these lifestyle changes that people don’t want to make. And it also implies that what we’ve been doing is wrong and bad. And I wonder if people have a hard time accepting that their previous actions, no matter how well intentioned, were bad.

Astrid Caldas: I’m sure this factors in in a good segment of the population. I’m sure this factors in. Yes.

Ariel Conn: Probably lots of psychological elements to this.

Astrid Caldas: It’s all interconnected, right?

Ariel Conn: Yeah. So my very final question for you then is, are you hopeful? Do you think we can address this?

Astrid Caldas: I am hopeful. I am hopeful that we can address this. We may not be able to address it the best we could and keep it at 1.5 warming as we would like to. I think there are ways of us keeping under two if there is global political will, and the technologies, and the innovations, and the policies, and the incentives. It is a huge undertaking, but I believe it can be done.

However, not all is lost, but a lot is lost already. We have a lot of stuff that we cannot avoid anymore. And that’s the part of the “climate despair” that we call here sometimes. How is the climate despair level today? Because sometimes some things happen, some news come out that it’s like, oh crap.

But yeah, I am hopeful. I’m not completely hopeless at all. I’ll keep fighting, and I think that the youth movement has huge legs. I mean, pressure from the people can lead the governments to do great things — has always been, historically. So if we realize how powerful we are in the change we can effect, it can happen. We can avoid the worst of it. Let’s put it that way.

Ariel Conn: All right. That’s a mostly optimistic note to end on.

Astrid Caldas: Yeah. I try always to lift up.

Ariel Conn: All right. Well, thank you so much.

Astrid Caldas: Oh, thank you. This is great. A great conversation.

Ariel Conn: On the next episode of Not Cool, a climate podcast, we’ll launch the first of two episodes in which we hear from many of the authors of this summer’s big paper, Tackling Climate Change with Machine Learning. 

David Rolnick: The project has really involved a lot of people coming together, not just from the machine learning field, but also many other fields relevant to this interdisciplinary work. Because to have an impact on problems related to climate change, one really needs a lot of expertise coming in from many different areas.

Ariel Conn: As always, if you’ve been enjoying these episodes, please take a moment to like them, share them, and maybe even leave a good review.


Not Cool Ep 14: Filippo Berardi on carbon finance and the economics of climate change

As the world nears the warming limit set forth by international agreement, carbon emissions have become a costly commodity. Not Cool episode 14 examines the rapidly expanding domain of carbon finance, along with the wider economic implications of the changing climate. Ariel is joined by Filippo Berardi, an environmental management and international development specialist at the Global Environment Facility (GEF). Filippo explains the international carbon market, the economic risks of not addressing climate change, and the benefits of a low carbon economy. He also discusses where international funds can best be invested, what it would cost to fully operationalize the Paris Climate Agreement, and how the fall of the Soviet Union impacted carbon finance at the international level.

Topics discussed include:

  • UNFCCC: funding, allocation of resources
  • Cap and trade system vs. carbon tax
  • Emission trading
  • Carbon offsets
  • Planetary carbon budget
  • Economic risks of not addressing climate change
  • Roles for public sector vs. private sector
  • What a low carbon economy would look like

References discussed include:

We are significantly underestimating the benefits of moving to a cleaner, more climate-smart economy. There are estimates out there that say that with bold climate action we could deliver up to 25 to 30 trillions in economic benefits through to 2030.

~ Filippo Berardi

Ariel Conn: Welcome to episode 14 of Not Cool, a climate podcast. I’m your host, Ariel Conn. Today, we’re going to be looking more at the economics of climate change. Filippo Berardi will be joining us to talk about some of the efforts by the United Nations to help developing countries tackle the problem. He’ll also go into more depth about the economics of addressing climate change, including a cap and trade on carbon, carbon offsets, the overall cost of climate change, and much more.

Filippo is an environmental management and international development specialist at the Global Environment Facility. He has over 12 years of experience managing programs relating to climate change, clean energy, carbon finance and sustainable use of natural capital for private sector and government clients. Prior to joining the GEF, he worked for the Inter-American Development Bank, where he focused on designing programs to support small and medium enterprises to reduce their emissions and their exposure to climate change. 

Filippo also worked in the United Kingdom, first as Project Manager with EcoSecurities — one of the world’s largest developers of carbon offsets under the UN’s Clean Developing Mechanism — and later at J.P. Morgan Investment Bank, where he focused on analysis and management of social and environmental risk. 

Filippo, thank you so much for joining us.

Filippo Berardi: Thank you for having me.

Ariel Conn: Before I get into a bunch of the questions that we have, I was hoping you could just really quickly explain what it is that you do.

Filippo Berardi: Sure, so I work for an organization called the Global Environment Facility. It’s a government-to-government institution that acts as the financial mechanism for a number of UN Conventions on environmental matters. Generally we refer to these as multilateral environmental agreements. One of them, and perhaps the most famous one, is the Climate Change Convention — that technically is called the United Nations Framework Convention on Climate Change or UNFCCC. GEF, the facility I work for, is also the financial mechanism for other conventions, including the biodiversity one, the Convention to Combat Desertification, and a bunch of other international agreements that relates to the environment — like the Minamata Convention that covers mercury, et cetera. So I coordinate here at the GEF the work as it relates to the UNFCCC, meaning that I have a team of people that manage some resources that are used by developing countries to meet their [climate mitigation] commitments under the UNFCCC.

So how do we get these resources? Well, when the Convention was created — this was 1992 — there was obviously this tension between developed countries and developing countries in terms of where the money would come from for a developing country to do the sort of actions that would allow them to meet their commitments under the Convention. And so developed countries then decided to put together what is the financial mechanism of the convention, where they put money in funding cycles of four years. So every four years the GEF gets, let’s say, replenished with donations from the developed countries and these resources are available for developing countries to do a bunch of things.

Ariel Conn: How much money do you usually get invested every four years?

Filippo Berardi: This has evolved a little bit, but generally it started around 3 billion; In the last funding cycle, which runs between 2018 and 2022 — which is the seventh replenishment period of the GEF — we had about 4.1 billion. It’s a sizeable amount, but it has to be sort of divided across the different, we call them, “focal areas,” and the different conventions that we act as financial mechanism for.

So at the end of the day, you say like for climate change it would be about 800 million to a billion. So when you compare that to, for example, the Paris Agreement level of ambition, which is about a hundred billion per year — this is like the minimum that would be required for the Paris Agreement to be fully operationalized. Then you see that there’s a huge mismatch between what’s needed and what’s on the table. So even though the number might be looking big, in fact it’s only a little fraction of what will be needed if we were to respect what science is telling us.

Ariel Conn: And so what kind of things are done with this money?

Filippo Berardi: Basically it is a pot of money that is replenished by donor countries, to be used by developing countries for them to meet obligations under the respective conventions.

When it comes to climate change, these obligations are both related to preparing reports and communications on where they stand in terms of adopting measures to mitigate or adapt to climate change, but also — and perhaps even more importantly — to implement projects that can produce these positive global environmental benefits, which in the area of climate change are generally measured in terms of emission reductions that are generated through these projects, or to the level of increased resilience and reduced vulnerability vis-a-vis those impacts that climate change is already producing in many of the developing countries that are clients for us. [The GEF Trust Fund does not support climate adaptation, and it only supports climate mitigation. Climate change adaptation is supported by the Special Climate Change Fund (SCCF) and the Least Developed Countries Fund (LDCF), both managed by the GEF.]

And perhaps in terms of how we do that, we invest in a number of areas like electric mobility, renewable energy systems. We support countries in stepping up their effort to increase the level of efficiency of the use of resources and energy. And generally we do this through supporting countries at a regulatory level — transforming, for example, policy and regulatory environment in a way that helps government put policies and regulations and institutions in place that will allow them to redirect investment flows and their regulatory attention to spending practices that deliver greater benefits for the global environment. And then on top of that, we also sort of provide that support for their own institutional capacity and decision-making processes to be adequate for the environmental challenges that we see.

So this is on the government side. We also obviously act a bit more downstream where the different stakeholders, including the private sector, including civil societies are. And in this case we fund innovative approaches and business models, and we support piloting and testing specific projects that include perhaps innovative technologies in a way that we can sort of create that demonstrational impact that can bring more actors in a specific sector that has potential to generate those environmental benefits that we all look to generate.

A big chunk of our work goes towards supporting governments, both on the regulatory set up, or how they establish their policies and their laws, but also on the other hand, in terms of their own internal institution, how they work and how they understand the problem to be and what sort of solutions can be given to ministries, to public agencies, to deal with these sort of environmental challenges related to climate change.

On the other side, we also fund a lot of projects, which are more concrete pieces that we do in developing countries, because we fundamentally exist to support developing countries with resources from developed countries. And some developing countries are also, more recently, stepping in and are also contributing to the trust fund; But generally the bulk of the resources comes from developed countries. And so projects in a developing country may include supporting the government or the different ministries in strengthening their capacity to understand climate risk, to deal with climate risk, to sort of implement policies and regulations that are conducive to transitioning to lower carbon economies and productive systems.

But we also use them to see the financial mechanisms to do pilot activities in a number of areas like renewable energy, land management, forestry, and transport. We basically put at the disposal of developing countries some amount of money that they can use, generally in conjunction with local organizations or international agencies like the UN bodies or the multilateral development banks, to test and pilot innovative approaches that can then be scaled at national level, and hopefully reach that impact in terms of emission reduction that the science is telling us that we really need to reach in the short term that we have available.

Ariel Conn: $4 billion does sound like a lot of money right up until you start listing all of these projects that you’re trying to help support. I’m curious: How are countries chosen to receive this assistance?

Filippo Berardi: Yeah, that’s a good question. Originally there was no way to allocate money in an upfront way. Originally the allocation was done on a first-come-first-serve basis. This created all sorts of problems in terms of participation to the GEF system. So more recently — I believe it is about eight years ago — we introduced a system that is called System for Transparent Upfront Allocation of Resources, which means that each country received upfront allocation at the beginning of the funding cycle of X amount of millions. [The effort to support country ownership started already under GEF-4 (2006-2010), with the adoption of the RAF — Resource Allocation Framework.] 

This amount is determined using an algorithm that takes into consideration aspects like the size of the country, the population, the GDP, the development path, the amount of natural resources that are available, and the potential for that country to generate what we call “global environmental benefits.” And this is, I think, an important point because as a global environment facility under the UN Conventions, our mandate is that of generating not local environmental benefits, but benefits that are felt at global level.

And this is particularly the case in terms of emission reductions. It doesn’t really matter where you emit a ton of carbon; The impact for the climate system will be the same. What we really focus on is emission reductions — at least in my shop, which is related to climate change. When it comes to biodiversity or land degradation, we also try and focus our strategies where we can maximize benefits that are then for the entire biosphere and not just for a specific country.

Ariel Conn: So how many countries do actually get assistance, then?

Filippo Berardi: All of the countries that are parties to the Convention that are developing parties, so I believe it’s around 160 nations. The bigger countries will get allocations that are significant for climate change. For example, we have about 80 million that we can spend in China — because of the size of the country of course, and the impact that they have in terms of emission.

But then if you look at smaller countries, then the allocation tends to be on the smaller side. So we really have to be quite careful in terms of how we use this money, and make sure that we can maximize the impact that we can generate. For example, in my opinion, it’s very important to pay attention to the policy and regulatory side. So, give the government those tools that they need to implement policies that then have a downstream and multiplier effect, in terms of all of the projects that will be done at a national level will have to comply with that specific policy. So even if you only have 1 million that you invested upstream in the regulatory cycle, then hopefully you can generate emissions that go way beyond what you could generate if you were to fund 1 million in a renewable energy technology project.

Ariel Conn: Can you explain what carbon finance is? 

Filippo Berardi: Sure. This is a question that I have close to my heart because this is where I did my undergraduate thesis, and then basically that’s where it all started for me in terms of my career path. 

Carbon finance is at the heart of the solution of the climate change problem. It basically refers to all of those investments in emission reduction projects that can generate emission reduction that can be standardized into some type of certificate or allowances that can be tradable on the carbon market. So it is a form of finance that, let’s say, is different from just climate finance, which is in general any investment that has a potential to reduce carbon emissions. Because in the carbon finance, what you’re trying to do is to have the potential to standardize a specific tradable unit that can be traded on one of the platforms that are generally referred to as carbon markets.

The first and perhaps most important carbon certification offsetting scheme was precisely that introduced by the Kyoto Protocol in 1997. The Kyoto Protocol is one of the implementing instruments of the UN Convention on Climate Change, and it was adopted in 1997 with a clear goal of assigning specific emission reduction binding targets for developed countries. Now developed countries had the choice of whether to reduce emission domestically or whether to help developing countries — reducing emissions in developing countries — and then claim some of the results of that action for their own national targets.

Ariel Conn: That’s actually really interesting. I didn’t realize that that was an option.

Filippo Berardi: From the diplomatic standpoint at the Convention, the idea was like, “We developed nations are going to accept some level of binding targets, but we also want to have some element of flexibility. We also need to have a flexible arrangement that allows us to be as economic and as efficient as possible in realizing those emission reductions.”

And the premise was always that emission reductions are costly. That is not always the case. There are many options for emission reduction that actually have a negative cost. Think about energy efficiency improvement: You are able to repay that investment typically in two to three years because you save on your electricity or on your energy bill.

But anyway, back then there was this idea that, “Yes, okay, I can commit to reduce X amount” — and, I mean, these amounts, frankly, they were quite modest. The overall level of ambition of the Kyoto Protocol was reducing emission by 5% compared to levels of 1990 by 2012. It was a very modest step, but a very important one: It was the first time that countries agreed on binding targets that have, or can have, significant consequences on their domestic economic policies.

Developed countries said, “Okay, I can do that, but I need to have some flexibility there.” What is this flexibility? This flexibility is what is called flexibility mechanism. And the most important of that is what then was called the Clean Development Mechanism, or the CDM. And the CDM was basically a system where a developed country can go in a developing country, help the developing country implement specific projects that reduce emissions while also fostering technology transfer, sustainable development, et cetera. And then these credits that are certified and issued by a UN body, the UN Convention Secretariat, are available for the developed country to use in meeting their own commitments.

And this is the start of carbon finance, because these credits then are assigned a price and then they are traded on a secondary market that is similar to the stock market. So they have a value. This value, however, is very dependent on demand — as any commodity, as any stock in the stock market, you only have the price because somebody wants to buy it.

And so what happened later on is that since the carbon market is a completely policy-made market, it only exists because countries decide that it is desirable to reduce emissions, and therefore the possibility to emit should be limited. And so if we think of the atmosphere as a limited capacity of absorption of greenhouse gases, then each little unit of this capacity of absorption is assigned a price.

This leads me to the concept of emission trading, because once you have established a modality to standardize practices and methodologies to reduce emissions in a way that you can count the environmental outcome and represent these environmental outcomes in the form of emission credits, tradable units, then the next step is creating a trading platform. And this was something quite revolutionary, and something that the European Union championed quite strongly.

Cap and trade is one of the modalities of emission trading. And the way it works is basically you have a geography — like for example, let’s think of the European Union — and you have an authority, the European Commission, that decide that as a continent we can only emit a hundred tons of carbon, right? This one hundred level is very important because it basically represents the level of ambition of the cap and trade system. You know, the way you set that maximum amount of tons that can be emitted has to have some level of relation with what science tells you. Somebody came up with the term “carbon budget,” or “planetary carbon budget,” which is very, very helpful because it sort of equates the family budget that we are all very used to with the earth carbon budget. So how much do we have left, and how much have we spent already? That is a very important element of any cap and trade system. So you have to decide how stringent you want to be, and then it’s a societal decision, and includes the dynamics of politics, of the economic systems, etc.

But basically, a cap and trade system sets a baseline. Let’s say our baseline is X emission corresponding to, I don’t know, the emissions that we have in 1990, for example, no? And then it distributes a number of permits, or allowances, to all of the different economic sectors that are covered by this cap and trade. So you could have just power generation; or you could have power generation and cement industry; or power generation, cement industry and transport. So there’s a level of ambition that is like how many productive emitting sectors are we going to put under this regulated cap and trade system? That’s the first decision that needs to be taken.

Then the second decision that needs to be taken is, what is this baseline here? For example, in the Kyoto Protocol, the reason why we were able to meet the level of ambition of the Kyoto Protocol — which I said it was quite low to start with, but anyway — it wasn’t because everybody made a lot of effort, but it was because we had a collapse of the economic system in eastern Europe and the ex-USSR. And so since the baseline year was 1990, a year where emissions were very high still because the, I think, Berlin wall is 1989 — so by then, in 1990, you still had all the industry in the Soviet Bloc going full steam. Then in the years thereafter, there was an economic slow down in the whole region, which resulted in a lot less emissions. Which resulted in a lot of the credits that they had weren’t really a result of a conscious policy effort, but was just the result of the collapse of the Soviet Union. And so what happened is they ended up having a lot of surplus credits, which were dubbed in the climate community as “hot air.” So this was just a little story to say the baseline year is very, very important.

And then you have the distribution methods. Once you’ve set the geography of the system, the baseline year, then you have the distribution system, which is like how are we going to give these credits? Are we going to auction them, which will be the most ambitious way of doing it, or are we just “grandfathering” them — we’re just going to give them for free to a bunch of industries that we know are already emitting. And this system, of course, is the most business friendly, and is based generally on how much you’ve emitted in the past. We’re going to give you 98% of what you emitted in the past worth of carbon credits; So basically you will reduce 2%. It’s a fascinating system and it’s the preferred system in many jurisdictions, now.

I believe World Bank studies have mapped about 45 or 50 different cap and trade systems across the globe. Some Chinese provinces have their own; China wasn’t able yet to come up with a federal system. The US, of course, we know only has fragmented markets. The EU remains the most important one. But it’s not the only way that you can implement to curb emissions.

Ariel Conn: So I want to sort of clarify where we are globally today with the cap and trade, then. You said that the EU does have more systems in place, is that right?

Filippo Berardi: Yeah, the EU was the first and the biggest one. It covered the largest amount of sectors. The policy has to decide which sectors are going to go in, and in some countries they only want to do power. In some countries they want to do fuel imports. In some other country they can do transport. You really have to decide how big is the scope of your system. But also you have to decide at what point you are going to require people to comply with the cap and trade regulations. Is it the power producers, the operator of the industrial facility, or the distributors of the fuel, or is it the general public? So you always have to strike a balance between what’s feasible to implement and what is most, let’s say, environmentally sound from a coverage system of the different economic sectors.

Ariel Conn: Okay.

Filippo Berardi: The EU is quite advanced in that they have a number of iterations of the cap and trade system. The US has the northeastern state RGGI Initiative; And California, obviously, is a very important market. There is South Korea. And China actually might be overall the biggest market, but it’s very fragmented. They have it implemented in a number of different provinces and I think they’re trying to come up with a system to link them up.

Ariel Conn: And so are we actually seeing reduction in emissions as a result of this?

Filippo Berardi: Yes. If you implement a system of that kind and you are rigorous about the way you allocate emission allowances, then you will see reductions. That’s happened in the EU. It’s happening in California. Whether that’s in line with what science tells us is needed — that’s a completely different question.

So there are reasons to be mildly optimistic. And you know, as I said before, it’s not the only system. One could just have a carbon tax, but then the word tax implies all level of emotions, immediately makes people turn their back to you when you mention it. But taxes are very efficient in terms of achieving a set environmental goal. What they’re not extremely efficient at, perhaps, is to do it in the most efficient way because then you have to come up with a price for that tax. So it could be a little bit too high; Then you will be taxing too much. It could be a little bit too low; Then it wouldn’t be an incentive good enough for people to change behaviors. There’s always been this debate between whether to go for a tax or whether to go for more like a cap and trade system. I don’t have a strong preference as long as something is done.

Ariel Conn: And how do carbon offsets fit into this?

Filippo Berardi: So carbon offsets is one of the elements that can, or may or may not fit in a cap and trade system. The most basic example — and perhaps this is helpful for everybody to understand what a carbon offset is — when you go and buy your flight somewhere at the end of that very long and annoying process, they will ask you if you want to buy offsets, right? Basically that means you pay a certain amount of dollars to, for example, plant trees in, I don’t know, Mexico. And you know that by planting trees you are absorbing a number of tons of carbon. And so basically you’re using those tons against the tons you know you are going to generate with your air miles. So that’s the basic concept of offset. You are reducing something somewhere else to make up for something that you cannot reduce here and now, which is your air flight.

The carbon offset is actually quite important because it links back to the description I gave earlier of the Clean Development Mechanism under the Kyoto Protocol. And this was something that the EU cap and trade system decided to allow for EU operators that found it more economical to go in a developing country to implement, let’s say, a renewable energy project there. This renewable energy project only happens because there are funding coming in the context of the Clean Development Mechanism. So you could argue that without the funding and without the support of the CDM, that project would not have taken place.

So it stems from that that you can claim those emissions within the EUETS — the cap and trade of the European Union — provided that this is an avenue that the policy of the EUETS allows. And this was in the first iteration of the EU cap and trade system: C redits from the Clean Development Mechanism were allowed, so you basically were using offsets from projects overseas to meet your power generation commitments under the EU cap and trade.

It works. It is a concept that helps in terms of identifying the lowest hanging fruit. And it sort of also relates to the fact that it doesn’t really matter where you are emitting the ton. What matters is that at the global scale, we only have a finite carbon budget and we have to be within it. So if you can implement a project in Argentina, rather than Botswana, that helps Argentina move towards a lower carbon transport — and this would not have happened without the support of the Clean Development Mechanism — then, fine, then you can claim some of those reductions and use them for your domestic commitments.

Ariel Conn: We’ve been talking a lot about the costs of trying to address climate change. Your background is a bit in social environmental risk management. I was curious if you could talk a little bit about what some of the economic risks are to not addressing climate change.

Filippo Berardi: Sure. I mean there are risks everywhere. This is something that has been, again, debated for a very long time. There was a ground-breaking report from Lord Nicholas Stern, the head of the London School of Economics now, but actually he runs the London School of Economics Center for Climate Change. And he in 2007 — so we’re talking about more than 10 years ago — came up with this groundbreaking report that was called The Economics of Climate Change, where he showed that the cost of inaction outweighed several times the cost of action now. So this is a concept that is quite difficult to absorb when we have the political cycle that is so quick. So, you know, we have four years and then we have new elections. So that doesn’t really align very well with what the climate change solutions need to be, because they need to be in the long-term.

But basically, economic consequences are going to be felt in pretty much any area of human life. Unpredictable weather patterns are going to generate billions in damages in terms of property, floods, storms, loss of jobs. Many parts of the planet are already experiencing increases in temperature that are not compatible anymore with the general agriculture activities. So you’re going to have problems in food security. You’re going to have problems in terms of water availability. And all of these problems are only going to exacerbate the larger scale global phenomenon of migrations that we are seeing from South America to North America, we are seeing from Sub-Saharan and Northern Africa. So it is undoubtable right now that the consequences of inaction are going to be very, very deep.

The Stern report was pointing at something like 1% of the global GDP would be the cost of doing something about climate change now — that would put us on track to meet the Convention’s objective — versus a cost 10%, which will be that of not doing anything. The problem is that these costs will come, and the bill will come, only decades from now. Although even this narrative is changing, and we’ve seen that the pace of climate change that we are observing, from a scientific standpoint, is much faster than what we thought it was going to be. So, July 2019 is the hottest month ever on record since when the record started. The eight most hot years are in the last 10 years. We really are seeing an acceleration and a chronic under estimation of the consequences, both physical consequences and economic consequences, on the economic world systems.

Ariel Conn: So, we’ve been talking a lot about what governments can and possibly should be doing. Especially in light of the fact that not all governments want to be taking action just yet, what would you like to see private organizations and companies doing?

Filippo Berardi: I’m a firm believer that there’s a responsibility that lies on the public side to create those broad guidelines for the private sector to operate within. And so, although there are plenty of very good examples of environmental champions in the private sector, I think we shouldn’t just rely on the good will of a number of good corporates, because we don’t have time, and this is just going to be a drop in the ocean.

So the most advanced private sector companies in terms of thinking about climate change and climate risk are starting to take action, not just because of philanthropic or corporate social responsibility reasons, but also because they see this as a necessity in terms of protecting their business model and in terms of protecting their assets. And this happened for those companies that rely heavily on the use of water resources, for example, that are seeing a decrease in these resources and are moving towards a more efficient use of these resources.

But also, slowly, we are seeing the financial sector taking more seriously into consideration climate risks when it comes to deciding where to allocate their financial assets. So asset managers, insurance companies, pension funds: These are the players that, I believe, should be at the forefront of climate action. Some of them are already doing it. There is a lot of push and a lot of movement in the climate community to make sure that these actors always sit at the table where decisions are taken. I’m convinced that this will be a key element to keep the balance in terms of the efficacy of climate action. And I am mildly optimistic that this scale is starting to tip, and financial markets are starting to realize that doing nothing and continuing to have a lot of assets invested, for example, in the fossil fuel industry is definitely not something that is going to be good for their portfolios going forward.

Ariel Conn: And so if we can get an ideal situation, what does a low carbon economy look like?

Filippo Berardi: Let me start by saying that we are significantly underestimating the benefits of moving to a cleaner, more climate-smart economy. And there are estimates out there that say that with bold climate action we could deliver up to 25 to 30 trillions in economic benefits through to 2030. So these are real benefits in terms of new jobs, in terms of economic savings, in terms of reduction of risks on financial markets, portfolio competitiveness, market opportunities — and of course, not to mention the well-being, health, and food security for millions, or billions, of people.

So how does a low carbon economy might look like? Well, first of all, it’s an economy that is a hundred percent run by renewable energy; Smart grids are able to fully integrate renewable energy with batteries to give some relief to the issue of intermittencies that, of course, is related to the fact that the sun and the wind are not always shining or blowing. Effective policies in this case are needed to incentivize private markets and private investments in low carbon innovation, among those we talked about carbon pricing, but also most importantly the removal of fossil fuel subsidies, which continue to be a large item of spending in the budget of many countries, which is completely counter intuitive. Like, why are we subsidizing something that is no longer desirable?

It goes with that, that on the other hand we should be incentivizing something that is desirable — like, for example, renewable energy. And you can do that in a number of ways, like filling tires, for example. Preferential dispatch to the grid of 100% clean electricity. In the urban environment, obviously cities are expected to have something like 80% of all the people living on the planet by 2050, so urban planning is going to be key. We need to increase the densification of cities. We need to develop mass transport infrastructure. So we need to redesign neighborhoods and entire parts of the cities so as to create cities and neighborhoods that are, on the one hand, more livable, and on the other hand, more sustainable from an environmental standpoint, and obviously much lower in carbon intensity.

It goes with that, there is an entire revolution in terms of transportation in the sense of electrification and electric mobility. Part of it is also due to the fact that more and more people are kind of shifting away from ownership models of cars. And we’ve seen that with Uber, with Lyft — especially young people don’t necessarily feel like they need to own a car. And so this, in the context of the general reduction in price of batteries, in my view is going to have a deep impact on transport sector, which is right now responsible for about a quarter of the emissions on the planet.

And then the other really big chunk of emission reduction has to come from the way we produce food. So, deep systemic changes and transformational changes have to happen in the food system. And this includes the way we use land: moving to climate smart agriculture; moving quickly to reverse the dramatic pace of deforestation. Deforestation accounts for another 20% of the global emissions. And countries like Brazil and Indonesia really need to step up their game. And there’s a lot to be done there. Moving away from extensive and unsustainable production of commodities such as palm oil, rice, soybeans. So everything that relates to food — the way we produce food, the way we transport, and we process food — accounts for something estimated at around 50% of global carbon emissions. So it is an area that we absolutely need to tackle.

And then finally, the last piece is the industry: the way we produce things that we use. Obviously in this case there’s a lot of need for increased efficiency in both the inputs — water, electricity, thermal energy — but also in terms of the materials. So, more technologically advanced materials are going to help moving towards what we all want to see, which is a circular economy where waste is minimized and the interaction between the different production chains are maximized — so that we can reuse, hopefully, the waste coming out of a certain product’s production and use it as an input for the next one.

All of this should happen in the next 10 years. Good luck with that. And on top of that, some sprinkle of a global functioning cap and trade and carbon pricing system.

Ariel Conn: All right, so it looks like we’re about out of time. Is there anything else that you wanted to add?

Filippo Berardi: I think we covered a lot of ground.

Ariel Conn: Let’s end with the question that I ask most people. And that is: what gives you hope?

Filippo Berardi: There’s a lot of reasons to be hopeful about the future. First of all, the human ingenuity is limitless. There’s an army of entrepreneurs and thinkers that are coming up with new business models to produce goods that are equivalents to what we have, but only use a tiny fraction of the earth’s capacity to absorb the results of the human action. So I think human ingenuity and entrepreneurship in its very essence is something that is definitely making me a bit more hopeful.

And then the second element that is on the newspapers and we’ve all heard about is the youth. I mean, the youth movement that Greta Thunberg is leading — you know, she’s been able to stir up a movement of schoolkids. Frankly, those are the people that tomorrow will be occupying a seat in parliament. And I hope that some of the narrative and some of the hopes that they have will then percolate in their adult lives. And even before that, I also hope that they will be able to influence their fathers and their mothers that are right now occupying the seats in the different parliaments in the capitals of the world, to make sure that, if the science is not enough to move their agendas, then perhaps their kids’ future will be. So that’s another element that I’ve seen growing recently, and it makes me quite hopeful. Maybe we can end on that note.

Ariel Conn: That sounds great. Thank you so much.

Filippo Berardi: Thank you. Thank you so much for having me.

Ariel Conn: On our next episode of Not Cool, a climate podcast, we’ll be joined by Astrid Caldas, who will talk more about her work on adaptation to climate change at the Union of Concerned Scientists.

Astrid Caldas: People can adapt to using external devices and technologies; They can adapt by changing the technologies that they use. But plants and animals do not have that ability. They live as nature around them allows them to.

Ariel Conn: As always, if you’ve been enjoying these episodes, please take a moment to like them, share them, and maybe even leave a good review.

Not Cool Ep 13: Val Kapos on ecosystem-based adaptation

What is ecosystem-based adaptation, and why should we be implementing it? The thirteenth episode of Not Cool explores how we can conserve, restore, and manage natural ecosystems in ways that also help us adapt to the impacts of climate change. Ariel is joined by Val Kapos, Head of the Climate Change and Biodiversity Programme at UN Environment’s World Conservation Monitoring Center, who explains the benefits of ecosystem-based adaptation along with some of the strategies for executing it. Val also describes how ecosystem-based adaption is being used today, why it’s an effective strategy for developed and developing nations alike, and what could motivate more communities to embrace it.

Topics discussed include:

  • Importance of biodiversity
  • Ecosystem-based vs. engineered approaches to adaptation
  • Potential downsides/risks of ecosystem-based adaptation
  • Linking ecosystem-based adaptation to other societal objectives
  • Obstacles to implementation
  • Private sector acceptance of ecosystem-based adaptation
  • National Determined Contributions
  • Importance of stakeholder involvement

References discussed include:

A lot of ecosystem-based interventions are lower cost. They tend not to be as expensive as building big things with metal and concrete. So if you’re thinking about coastal defense, for example, or flood control, it’s actually a lot cheaper to manage flood plain ecosystems to help absorb floods than it is to build massive engineered flood control mechanisms.

~ Val Kapos

Ariel Conn: Hi Everyone. Welcome to Episode 13 of Not Cool, a climate podcast. I’m your host, Ariel Conn. Today we’ll be hearing from Valerie Kapos about some of the things we can do to use natural ecosystems to both help bolster communities in preparation for climate change, but also how those same systems can help us mitigate the problem of global warming.

Val is Head of the Climate Change and Biodiversity Programme at the UNEP World Conservation Monitoring Centre. The programme addresses the interactions between climate change and biodiversity, including the impacts of climate change and climate-related policies on biodiversity and ecosystem services, and the contribution of ecosystems to climate change mitigation and to societal adaptation to climate change. Val’s role includes overseeing the work of the programme’s team, and working with governments, collaborators and funders to develop new projects that meet their needs.

Val holds a PhD in Tropical Forest Ecology from Washington University, Missouri. She spent 15 years researching in the Caribbean and Latin America. 

Val, thank you so much for joining us today.

Val Kapos: Thank you for having me.

Ariel Conn: So you work for the UNEP-WCMC. And before we get too far into this interview, I was hoping you could just talk a little bit about what that organization is and what your role is.

Val Kapos: Absolutely. That mouthful acronym, UNEP-WCMC, actually stands for the UN Environment Programme’s World Conservation Monitoring Centre. We’re a branch of the UN Environment Programme, UNEP, which is actually in Cambridge. And we have responsibility for helping UNEP to address those issues that relate to the natural environment and particularly to biological diversity.

We often describe ourselves as an organization that works at the science policy interface. So we generate, collate, analyze data and information to try to make it available in forms that support decision-making as it affects the management and the status and the future of nature and biological diversity.

Ariel Conn: I want to jump into this idea of biological diversity real quick because we’ve recently, in the last couple of months, seen a report come out showing that biodiversity was at incredible risk. And I was wondering if you could explain why biodiversity is so important.

Val Kapos: Because it’s essentially the fabric of our natural world on which we depend fundamentally. Lots of people would argue that biological diversity — the diversity of life on Earth at the level of species, ecosystems, and within species — has incredible intrinsic value, that just as a matter of principle, it should persist and we shouldn’t be damaging it. And I personally would agree with that.

But in addition to that, biological diversity provides a really strong underpinning for people and their livelihoods and wellbeing and actually quite a lot of the economic activity of the world as we know it today. It is also fantastically important in securing our resilience in a changing world; And biological diversity underpins the resilience of both nature and society as we confront climate change and other forms of environmental change. So that’s the short answer for why biological diversity is so important. One could go on at length.

Ariel Conn: So your focus, if I understand correctly, has been looking at biodiversity from an ecosystem perspective. Is that fair to say?

Val Kapos: I’m an ecologist, so I tend to think in terms of ecosystems, and I worked on systems ecology rather than ecology of individual species. But my current role is in coordinating UNEP-WCMC’s work on climate change and biodiversity. By that, we mean both the impacts of climate change on biodiversity and the impacts of climate-related policies on biodiversity, but also the role that biodiversity plays in underpinning our efforts, our societal efforts, to mitigate and adapt to climate change.

And all of that leads me to think especially in ecosystem terms, but also in species terms. Particularly when we’re talking about impacts, we often think more in terms of species; When we’re thinking about that role of nature in underpinning our wellbeing in the face of a changing climate, we often think more in terms of ecosystem function and ecosystem services.

Ariel Conn: I think that connects to work that I want to ask you about that you’ve been doing on ecosystem-based adaptation. If I was understanding it correctly, and I may not have been, it sounds like by rejuvenating our ecosystems, we can better adapt to climate change.

Val Kapos: Essentially, yes. So ecosystem-based adaptation is something actually that people have been doing for years, which is using biodiversity and ecosystem services to help them adapt to a changing environment — in this case, climate change. The important thing about ecosystem-based adaptation is that it’s not the only solution, obviously, to adapting to a changing climate. But we are increasingly recognizing the importance of ecosystems in supporting our own adaptation and resilience in the face of climate change as part of an overall strategy for adaptation.

So if we look at what’s coming towards us in terms of climate change, and we look at the hazards and challenges that we’re going to have to address in any given place or for any given population of people, our understanding is that ecosystems offer at least part of, and in some cases all of, the solution to being better able to withstand those pressures that are going to come from a changing climate.

Ariel Conn: I’d like to get into some examples so that people can ground themselves.

Val Kapos: Absolutely. It’s very easy to talk about this in broadly theoretical terms. A lot of ecosystem-based adaptation, and you mentioned this earlier, is focused on restoring ecosystems. So the things that most people may have heard about will have been in the context particularly of managing ecosystems on coasts to help protect us from rising sea levels and coastal storm surges. So that would be restoring or indeed managing, for example, mangroves and coral reefs, so that they provide coastal protection.

Salt marshes are another ecosystem that actually help significantly to dissipate the effects of storm-driven waves, for example, and therefore reduce coastal flooding. They can absorb quite a lot of the impact of storm surges. Restoring forests generally affects the hydrology, affects the way that changes in precipitation affect the landscape, and particularly managing or restoring forests on slopes also plays a significant role in both reducing flooding or reducing peak floods.

Water is better absorbed by forested landscapes than by, certainly, concrete and also other more disturbed landscapes and is therefore released more slowly, reducing flood impacts. Vegetation also, for example, helps to reduce the rates of sedimentation. We’ve always seen pictures of really bad gully erosion and runoff taking soil away.

Well, that soil ends up in hydroelectric dams and rivers and urban water sources. If we have an increase in intensity of precipitation — as we expect from climate change in a lot of parts of the world — those kinds of processes of flooding and sedimentation will become an increasing pressure. Managing ecosystems is actually one of the best ways to try to reduce the impacts of that intense precipitation.

Ariel Conn: In those examples that you just gave, I guess it wasn’t clear to me: Were those all examples of restoring an ecosystem, or is some of that making changes to the ecosystem to help it be more stable?

Val Kapos: Restoration and management. In some cases, it’s restoring where it’s been converted and it isn’t there anymore, or it’s been degraded by activities — ranging from logging to fire to agricultural incursion. But we also need to think about the way we manage nature, the way our actions affect the ability of natural systems to survive climate change themselves.

Perhaps to illustrate what I mean, you can think about sea level rise, and the fact that mangroves, which are forests that grow on the edge of marine systems and need a certain amount of salt water, can’t survive in the sea. They need to have their feet in salt water or mixed brackish water, which means that they need potentially to retreat from a rising sea level. Part of our management of mangroves needs to make sure that there is space for the system to expand landwards. And if a mangrove fringe is sitting in front of a massive pile of concrete or a hugely developed area and there is no space for landward migration, then the resilience of that mangrove itself is at risk.

When I talk about restoration and management, I’m talking about conserving and managing ecosystems as they are so that they’re in good condition and can deliver the services that we need; I am talking about restoring ecosystems that have been degraded so that they deliver the services that we need more effectively; And I’m talking about making sure that we’re doing an adequate job of conservation and management to ensure that those systems have their own resilience to climate change.

And that ranges from looking at the context and the systems-scale situation of the ecosystems that we’re most interested in: So, the mangrove landward migration example is one; Another is thinking about patches of, let’s say, forest that are potentially more vulnerable in a hotter, drier environment than if they are part of a continuous area of forest. So it covers the full range from conservation management to restoration to understanding the systems context of how these ecosystem sit and recognizing very firmly and thoroughly what it is that they deliver and offer.

Ariel Conn: I live in the Western US, and last summer in the US and many other countries, we saw horrible fires. Are there processes that we could be implementing that would help prevent or at least mitigate some of the fires, or is that separate?

Val Kapos: Well, I think it’s a little bit separate, only because the fires are affecting the ecosystems themselves. And I think fire is one of the things where it’s actually a little bit hard to think about how we come up with ecosystem-based interventions that reduce fire risk. And yet, we know which things we do to ecosystems that increase fire risk. And we know that, for example, in the tropics, we know that increased logging moist forests increases their susceptibility to fire. We know this. It’s very well documented that you open the canopy, the understory dries out. We know that there’s fire in the environment anyway from the way that people manage land and occasionally from naturally caused, lightning-generated fires. And we know that fire spreads much more easily in logged forest than in intact rainforest or moist forest.

In the more temperate contexts, similar things. It’s a little bit more contentious because, I mean, fire management is a hugely charged issue, and people talk about, for example, reducing fuel accumulation by taking dead wood out of forests — which is great for reducing fire risk, and it’s not so great for many of the species that persist in forests that depend on dead wood for their ecological niches.

So there are always tensions, but there are certainly things that we can do in the way that we manage ecosystems that reduce fire risk. Even in the context of a changing climate, on the whole, keeping forests and other ecosystems intact — just the presence of vegetation tends to keep the system moister. But there are certainly things we can do in the way we manage ecosystems that help to reduce fire risk.

Ariel Conn: Okay. So a lot of the work that I’ve read of yours, the focus seems to be applying eco-based adaptation to more impoverished locations. I was interested in knowing what the reason for that focus is.

Val Kapos: It’s a cocktail of reasons, and I don’t actually think that focus is entirely correct. And there’s actually quite a lot of evidence — and in fact, the US Army Corps of Engineers has produced a whole handbook on using ecosystem-based approaches for infrastructure, for example. So I don’t actually think ecosystem-based adaptation is only applicable in impoverished locations, but I think there’s some good reasons why it’s come up first and foremost for those locations, or why we see greater uptake.

One of them is that in impoverished locations, people tend to have a greater dependency on natural resources, a much closer relationship with the natural environment in the first place — which on the one hand increases their vulnerability to climate change, and on the other hand increases what they stand to gain from using ecosystem services, from having ecosystems managed in a way that delivers them more benefits in the context of climate change.

Val Kapos: The other reason we see it used in impoverished areas is, frankly, that a lot of ecosystem-based interventions are lower cost. They tend not to be as expensive as building big things with metal and concrete. So if you’re thinking about coastal defense, for example, or flood control, it’s actually a lot cheaper to manage flood plain ecosystems to help absorb floods than it is to build massive engineered flood control mechanisms. There’s also quite a lot of work on putting those two things together, so using ecosystem-based approaches to complement engineered approaches.

The other thing that’s really important is that when we use ecosystem-based approaches, for example, to manage flood, they often have multiple additional benefits. Using ecosystems to manage floods also often will deliver product that local people need, and this is particularly the case in the context of impoverished communities. Communities need firewood. They use forest species as what we sometimes call famine foods, so as backup foods: Even if they don’t use wild food in their day-to-day diet, it’s there as a buffer.

Forests or other ecosystems can be culturally really important. They can purify water as well as containing flooding. We often talk about ecosystem-based adaptation as delivering multiple benefits, and those multiple benefits on the whole are more immediately important to impoverished communities that depend very closely on natural resources. But those arguments stand across all economic ranges, I would argue.

Ariel Conn: Your description of the cost especially was really interesting. In the US, we’re struggling to get politicians and communities to both recognize the importance of taking action and then also just taking action. And I would think that if we can present cheaper ways of trying to, say, minimize the impact of sea level rise, that communities even in the US would appreciate that. And then also, additionally, things like — my understanding is using concrete is actually one of the most — I don’t know if it’s energy intensive?

Val Kapos: It has a big carbon footprint. It has a huge carbon footprint. So that certainly adds to the cost writ large — not just dollar cost, but environmental cost — of some of those engineered approaches. I think actually you raising the carbon cost of concrete flags one of the multiple benefits that I should have mentioned and didn’t, which is that most of the ways that we use ecosystems to help support adaptation also contribute significantly to climate change mitigation. They tend to take carbon out of the atmosphere.

So ecosystems, as you know, store carbon; Destroying ecosystems releases carbon; And restoring ecosystems locks up more carbon. Often when we use or manage ecosystems to provide adaptation benefits, they’re also simultaneously delivering mitigation benefits. Not necessarily huge ones; Sometimes big ones. But that link between adaptation and mitigation, when you’re talking about using ecosystem-based approaches, is really fundamental.

Ariel Conn: I have this question for you about how we can help communities embrace ecosystem-based adaptation. And when I wrote that, I was originally thinking of these more impoverished communities. But as we’re talking, I guess my question now is how can we get all communities to embrace this more, and is there any reason that we wouldn’t? Are there downsides?

Val Kapos: There’s not much in the way of downsides. There are some risks, because we don’t have as much evidence as we would like about the effectiveness of some ecosystem-based approaches for some levels of impact, and we know that, for example, restoring ecosystems can take time. So if you’re concerned about hurricane vulnerability this year, certain things that you might do to restore salt marshes along the Gulf Coast that you would hope would reduce storm surge — they’re not going to be finished this year, which is why I emphasized earlier the potential for combining approaches sometimes.

But I don’t think there is any reason why you wouldn’t want to see people assess ecosystem-based options any time they identify a need for climate change adaptation. And for me, that is one of the bits of holy grail that I’m chasing. Every time we identify an adaptation problem, we should be asking the question, “How much of this problem can we address by managing ecosystems,” because that ecosystem management brings so many additional benefits.

Now I think part of the way that we get communities to embrace this, it’s going to depend on the community. It’s partly making those multiple benefits clear. It’s making the linkages between that ecosystem management and a whole set of societal objectives, which might be clean water; It might be good mental health — there’s really good evidence that, in cities, access to green space improve people’s mental health.

There’s a whole set of societal objectives that ecosystem-based approaches can contribute to. Making that contribution clear and explicit for different audiences is a big part of getting wider acceptance. Similarly, there are some challenges around mobilizing the technical understanding into the right places. So on the one hand, it’s the communities and how interested are they — and in a city, you will always have groups which see the advantage of green spaces and other groups which think it’s a waste of space and we should be doing things that are somehow commercially more exciting.

There are always those things, but there is also a question of getting the ecological understanding into the hands of the planners and the engineers and the politicians and the finance sector and indeed the private sector. And we’re actually seeing increasing attention to ecosystem-based approaches in the private sector: increasing recognition that if you’re running a hydroelectric company and you’re actually worried about your water supply in the long term to keep those turbines running, at least part of your strategy needs to be about managing the vegetation in the catchment for the hydroelectric basin and that that will also reduce the sediment loads, which will, therefore, reduce the damage to your turbines. You’re beginning to see that whole chain become much more part of mainstream thinking in the sector.

Ariel Conn: So is it reasonable to say that one of the reasons we haven’t seen ecosystem-based adaptation more, at least in part — if not large part — is just due to lack of information about it?

Val Kapos: There’s a big awareness component. I’m not sure it’s information; It’s information in the right places. There are some challenges with scale. As you say, a lot of what we know about ecosystem-based adaptation comes from work with impoverished communities. It comes from relatively local scale work. And we have challenges, which I think are largely policy and finance challenges rather than necessarily practical challenges, around how we scale up those interventions.

And there’s been quite a lot of work done on, for example, managing coastal systems, and how and where and how connected your efforts on management need to be to deliver the scale of benefit that you need to make it an attractive option to, let’s say, a state government. I wouldn’t say it’s nascent. We actually have quite a lot of experience, but there are some outstanding questions around scaling, technical capacity in the right places and the right sorts of people. So some of it is awareness in the engineering community and actually trying to bring sets of expertise together to deliver the solutions that we need. But we do have quite a lot of experience that we can build on, and I’m hopeful that we’ll see that scaling start to happen.

Ariel Conn: Are you seeing signs that that is starting to happen?

Val Kapos: Yes. The thing I raised just now about the fact that companies are beginning to recognize the benefits that they get — now what we need is we need those companies to tell other companies. There’s a sharing of experience in practice within and between sectors and types of actor, and we are seeing signs that this is happening. Some of it is in the guise of companies wanting to say, “Look how green we are.” That’s fine. There’s nothing wrong with that.

If the end result is the same, if they’re managing ecosystems to make the ecosystems healthier, they’re getting a benefit from it and they’re getting green credentials. Great. I can’t see how that’s a loss. I mean, if they’re doing nasty things on the side and using this to distract attention from doing nasty things on the side, that’s arguably something to be concerned about, but actually this is what we want.

Companies, governments, I mean, you’re seeing it in the US and elsewhere. A lot of city governments get this, and they are taking action on climate because they’re sitting on these heat islands. And they get it both in terms of the urgency of action, and they get it in terms of the role of ecosystems or ecosystem components: tree planting, having green spaces and blue spaces in cities. They get that, and we’re seeing that not only increase in frequency, but we’re seeing it propagate.

There are networks of cities which talk to each other, and they’re sharing experience. So, we are seeing some propagation. There’s a long, long way to go, and there’s a long way to go before we get to that point of, “I have a climate problem. Let’s see whether I can use an ecosystem to fix it,” rather than, “I’ll just call in my engineers, and let’s see what we can build to fix it.”

But we’re heading slowly in that direction, and we’re seeing some progress all over the place, from those private sector companies to financial institutions to particularly local government. Civil society has always been active in this, NGOs have always been pushing this, but we’re now starting to see it extend beyond the tree-hugging community to the hardcore, practical, “How do I deal with climate issues?” And that’s what I think we’d like to see.

Ariel Conn: These ecosystem-based adaptation options also come up in the Paris Climate Agreement, if I understand that right?

Val Kapos: They do. There’s nothing binding. The Paris Agreement includes text that recognizes the importance of ecosystems for both mitigation and adaptation. It flags the importance of natural carbon sinks for storage, and indeed removal, of greenhouse gases. So that’s the mitigation piece. And it notes the importance of ensuring ecosystem integrity to help address and help people adapt to climate change.

That then translates into countries’ commitments under the Paris Agreement. So the big thing about the Paris Agreement is countries have to make commitments under it, to say what are they going to do to help achieve its objectives. And there have been any number of reviews of those commitments. And what we know from reviewing those commitments is nearly half of them say something about using ecosystems, conserving ecosystems, managing ecosystems in relation to their objectives on adaptation. They don’t necessarily say, “We’re going to do ecosystem-based adaptation,” with that label. But the importance of ecosystems in meeting the objectives of the Paris Agreement is very clearly signaled in about half of the nationally-determined contributions that have already been put forward.

As we speak, countries are working on updating and revising their nationally-determined contributions in preparation for next year when the Paris Agreement actually comes into force. And I suspect we will see an increasing attention to the role of ecosystems — particularly on the adaptation side, but also on the mitigation side. There’s already a very high incidence among developing countries. I think we’ll also see an increasing attention in developed countries who can afford to buy concrete but actually might choose not to.

Ariel Conn: So can you give some examples? I think we’ve touched on some of this a bit already with things like scalability, but what can countries do to help ensure that they’re implementing these efforts effectively?

Val Kapos: One really important thing is to take a systems view — to understand, at least at the landscape scale, how action in one place can affect what happens in another place. And this is actually where, very occasionally, some kinds of adaptation — including ecosystem-based adaptation — go wrong: because people don’t actually think about what’s happening downstream. They think about the community they’re trying to deal with here. It’s less likely to happen in ecosystem-based adaptation, but it still does happen, and you want — something you do to reduce flooding here can increase flooding further down. So taking that systems view is particularly important.

Understanding what climate impacts are anticipated is particularly important, so actually starting with a good understanding of both the expected impacts and the vulnerabilities and the risks that people are suffering in the context of those projected impacts; Understanding the role that ecosystem services can play in increasing resilience or reducing risk. So that’s all the background stuff.

Building on experience and good practice from other places: not doing this stuff in a vacuum, but recognizing that there is experience to draw on. But then when you’re actually implementing, engaging stakeholders so that you’re not just coming in from outside and saying, “This is what you need. Here. We suggest you do this.” But actually drawing on local knowledge, engaging stakeholders in the conversation — and those stakeholders range from the people on the ground right up to the people in the government — so that people build a vision of what it is that you’re trying to achieve and an understanding of how particular interventions — if you’re restoring some bit of high-altitude grassland, what difference does that make for water supply in the city? 

That’s a specific example, where restoring high-altitude grasslands makes a big difference to the quality and quantity of water that’s available for city intake. But there are the communities around the grasslands who use the grasslands for grazing livestock and therefore, will be affected by management approaches. If you do it right, you can do it so that you also increase their resilience.

So involving a full range of stakeholders and actually having a really good understanding of the potential impacts on each of those sets of stakeholders, and then drawing on their knowledge — they actually know how to manage those grasslands often. They don’t always do it, because it takes resources to do it differently. But they know a lot about those grasslands, and they know a lot about their own requirements, and they know a lot about how the systems work.

They are not always managing things in the best ways, but certainly listening and drawing on that knowledge and on their concerns is a really fundamentally important part of designing and implementing effective ecosystem-based adaptation. So systems view, taking account of multiple benefits, and also good climate projections and the impact those projected changes are likely to have on people, building on existing experience, and involving stakeholders. And I’m sure I’ve forgotten a couple, but those are things I would argue are really very important.

Ariel Conn: So I have two questions for you, really, that I want to end with. One is, what do you think we need to see from people to address climate change, from individuals and/or policymakers more broadly — or specifically, with respect to ecosystem-based adaptation? We’ll start there.

Val Kapos: Action. We do need to stop talking and start doing. I would like to see ecosystem-based adaptation integrated into the way people think about responding to climate pressures, climate risks. So I’ve said that at least three times, but I think it’s important that people start to consider what the natural world has to offer at the same time as they look for other options, and that we evaluate these options together; We look at complementarities.

I think also in the context — particularly, you raised policymakers: in addition to action and policy and spending money, it’s actually recognizing the links between our societal objectives. There are links between conserving biological diversity and addressing climate change and achieving the sustainable development goals. Those links are clear in the way the sustainable development goals are structured, but actually getting policymakers to recognize that and to look for those — I sometimes refer to synergies as the S word, because I’m kind of tired of hearing about synergies, but they really are there. 

Those links are there. There are links between biodiversity conservation and climate change. There are links between climate change mitigation and adaptation to climate change. So actually trying to take a more holistic view, so that you can choose options that deliver on those multiple agendas. And often, those options will involve conserving and managing the natural environment, and making use of it in ways that help us towards a whole series of objectives. So recognizing those linkages, I think, is really important — and then actually taking action.

Ariel Conn: I like that answer. I don’t think anyone else I’ve talked to yet has made that point, and I think that’s a really important point.

Val Kapos: The image that just flashed through my mind is not pulling the rug out from under our own feet by trashing the natural environment. There is a risk that as we degrade and fragment ecosystems, we actually make things very, very, very much worse — rather than building on what nature can give us to help us to survive what is undoubtedly a crisis.

Ariel Conn: Well, on that note, what makes you hopeful for the future?

Val Kapos: Well, what makes me hopeful is actually the rising groundswell of voices — not just me, or you and me, or me and my tree-hugging friends, but the world is beginning to recognize this is a crisis. We’re also seeing increasing recognition of those links and synergies. Not as much as I’d like; It’ll never be as much as I’d like. But it is beginning to come up increasingly how intertwined those agendas are.

And that gives me hope, because I do think that people will then start to see care for nature in terms of enlightened self-interest, as well as something that has an intrinsic value and motivation — which for many of us it does, but not for everyone. So as we start to see these linkages, as these linkages come up the international agenda, that does give me some optimism. So the increasing sense of urgency and the fact that we are seeing people increasingly recognize links between sets of societal objectives does give me some grounds for optimism. They just need to do more of it.

Ariel Conn: All right. Well, here’s hoping people will be doing more of it. That’s certainly my goal.

Val Kapos: Good.

Ariel Conn: Well, thank you so much.

Val Kapos: You’re very welcome.

Ariel Conn: On the next episode of Not Cool, a climate podcast, we’ll hear from Filippo Berardi of the Global Environment Facility about some of his work looking at carbon finance and the economics of climate change.

Filippo Berardi: You have to decide at what point you are going to require people to comply with the cap and trade regulations. Is it the power producers, the operator of the industrial facility, or the distributors of the fuel, or is it general public? So you always have to strike a balance between what’s feasible to implement and what is most environmentally sound from a coverage system of the different economic sectors.

Ariel Conn: As always, if you’ve enjoyed this show, please take a moment to like it, share it, and maybe even leave a good review.

Not Cool Ep 12: Kris Ebi on climate change, human health, and social stability

We know that climate change has serious implications for human health, including the spread of vector-borne disease and the global increase of malnutrition. What we don’t yet know is how expansive these health issues could become or how these problems will impact social stability. On episode 12 of Not Cool, Ariel is joined by Kris Ebi, professor at the University of Washington and founding director of its Center for Health and the Global Environment. Kris explains how increased CO2 affects crop quality, why malnutrition might alter patterns of human migration, and what we can do to reduce our vulnerability to these impacts. She also discusses changing weather patterns, the expanding geographic range of disease-carrying insects, and more.

Topics discussed include:

  • Human health and social stability
  • Climate related malnutrition
  • Knowns and unknowns
  • Extreme events and changing weather patterns
  • Vulnerability and exposure
  • Steps to reduce vulnerability
  • Vector-borne disease
  • Endemic vs. epidemic malaria
  • Effects of increased CO2 on crop quality
  • Actions individuals can take

References discussed include:

At the core vulnerability just means the possibility of being harmed. It is an issue with climate change, because of course we’re all exposed. We don’t have some group that’s not going to be exposed to climate change.

~ Kris Ebi

Ariel Conn: When talking about the threat of climate change, we often hear about how the poorest and most vulnerable communities will be hardest hit. Which is a problem we must address, but climate change will affect all of us. So what are some ways that you could be impacted? Hi everyone, I’m Ariel Conn and I’m back with episode 12 of Not Cool, a climate podcast. On this episode, I’ll be talking with Kristie Ebi about the toll climate change is expected to take on all populations. From higher risk of disease exposure to decreased nutrients in our food, all of us, no matter where we live, will experience the negative effects of climate change. 

Kris has been conducting research and practice on the health risks of climate variability and change for over twenty years. Her research focuses on the impacts of and adaptation to climate variability and change, including on extreme events, thermal stress, foodborne safety and security, and vectorborne diseases. She focuses on understanding sources of vulnerability, estimating current and future health risks of climate change, and designing adaptation policies and measures to reduce the risks of climate change in multi-stressor environments. She has supported multiple countries in assessing their vulnerability and implementing adaptation measures. She has edited four books on aspects of climate change and has more than 180 publications.

 Kris, thank you so much for joining us.

Kris Ebi: My pleasure.

Ariel Conn: So you fairly recently were an author on a paper called Climate Change, Human Health, and Social Stability: Addressing Interlinkages, and there’s a lot of really interesting content in the paper, but one of the things that I thought was most interesting, it sort of helped really hit home with me, is — maybe you’ll disagree with this — but just sort of how broad our unknowns are that we’re trying to plan for. For example, there’s a table in here where you talk about the social stability consequences of climate related malnutrition, and two of the questions that would be helpful to answer are, “Will malnutrition increase out migration, because people need better, healthier food? Or will it actually decrease out migration because people are basically too sick and too poor to be able to deal with trying to travel places?” And so I was hoping you could maybe start with: how much of an unknown do you think the future is, as we’re looking at how climate change will impact us?

Kris Ebi: That’s a really good question. There is, of course, lots of uncertainties about the future. We have uncertainties about the rate, for example, of climate change. The Intergovernmental Panel on Climate Change Special Report on Warming of 1.5 said that under current greenhouse gas emissions, the earth could warm an additional half degree over what it’s warmed already from preindustrial times. The earth has warmed one degree Celsius, and the projections for 1.5 degrees Celsius indicate that the global mean temperature could reach that sometime between 2030 and 2052. So we do have lots of uncertainty about how quickly the climate system is going to respond to the additional greenhouse gases that are put into the atmosphere. We also have lots of uncertainties about then what happens with human and natural systems. How are they going to respond to the additional warming? We have uncertainties around how extreme extreme events will become. We know, for example, that heat waves are increasing in frequency, intensity, and duration.

We don’t know exactly how fast; We do know we need to prepare. And the paper you referenced then pointed out there’s lots of uncertainties around the human health and wellbeing aspects of these questions. How well the human systems respond, what kinds of choices will our governments make, and will we be prepared to handle the changes that are coming our way? So on the one hand, we do have lots of uncertainties. On the other hand, we also have lots of knowns. The climate is changing. Extreme events, as I mentioned, are becoming more intense; We know that many, such as heat waves, are becoming more frequent, lasting longer. So we have lots of information to use to better understand what the future could look like and how to start changing our policies and our programs to take those uncertainties into account, to be better prepared no matter what the climate change result is, and to reinforce our development patterns so that we move more towards a sustainable development pathway than the pathway that we’re on now.

Ariel Conn: And so how do we get onto a different path, or what path should we be trying to get onto? How do we take what we know and address it?

Kris Ebi: The United Nations has an Agenda 2030 with sustainable development goals in multiple domains: human health, ecosystems, oceans, pollution. So that effort resulted in a series of goals and targets on moving to more sustainable pathways. How we can get there has been laid out by the United Nations and by other organizations as well, so we do have a sense of what it is we need to do. We do have a sense of the timing we have available to us to make the shifts that need to be made. And more importantly, when you look out at what’s going on around the world, you see enormous transition taking place now — that countries, communities, individuals are making changes to move towards a more sustainable pathway, and it’s helping facilitate those changes.

Helping people understand what kinds of changes, for example, at the individual level would be beneficial, to what kind of changes do you need at the community, the national, and the international level. So there’s less unknowns than people like to emphasize. We do have lots of information and we do have lots of change underway. It’s always good to remember that the future is not a total disconnect from today. There’s a continuum between today and the future, and the future is already started.

Ariel Conn: We’ll link to some of the information about the UN 2030 program. Does that lay out some of the different steps that we need to be taking at individual, versus community, versus national levels? Or are there places you recommend people go for more information?

Kris Ebi: To look internationally, I would recommend looking at Agenda 2030. It’s quite detailed. There are 17 sustainable development goals, and under that are almost 200 targets, and under each target is a way to try and achieve that target. One of the challenges with the sustainable development goals is they’re laid out individually: Here are the goals and the targets for health, and the ones for ecosystems, the ones for agriculture, the ones for water. The interconnections across those — the synergies and the trade offs — are not always articulated, so work does need to be done to make sure that actions taken in one sector will support actions taken in another sector so that we do ensure that as we move towards sustainable development, we reinforce across all the sectors the kinds of actions that need to be taken.

Ariel Conn: I want to step back to some of the risks that you’ve looked at. Your bio, I think, nicely sums up some of what I want to talk about. I’d like to start, I think, with just this definition of vulnerability. We hear a lot about places being more vulnerable than other sections of the world — countries, communities being more vulnerable than others — and I think there’s sort of a vague sense of what that means, but I wonder if there’s a more specific definition that’s associated with the term.

Kris Ebi: There are hundreds of definitions. And when you look across all these definitions, at the core vulnerability just means the possibility of being harmed: that either individuals are vulnerable because they’re more at risk for some adverse health outcome, a community is more vulnerable because of its location, or more vulnerable because most of the population is poor. There’s lots of different ways that you can measure vulnerability. It is an issue with climate change, because of course we’re all exposed. We don’t have some group that’s not going to be exposed to climate change. And in looking at how to allocate resources available for adaptation, for example, there is an effort to try and put those resources into places that have higher risks, where we’re deeply concerned.

I do a lot of work in the Pacific. Low-lying island states are very concerned about sea level rise, storm surge, and what that means. People who live in the middle of the US, where there’s been a series of droughts and floods, are much more concerned about droughts and floods, obviously, than sea level rise. And it points out a fundamental perspective when you start thinking about climate change — is that although all of us are exposed, that exposure is different from place to place. The climate is changing faster in some places than in others, and the risks you see in a particular location are different for those you see in another location. And so you need to take into account this local context to understand the challenges that we could be facing, the opportunities we have, the capacities that you have in those locations, and what can be done to ensure that we increase the resilience of the population so that as the climate continues to change, we don’t see adverse outcomes.

Ariel Conn: I wonder as well if — would it be fair to say that because of climate change, everyone then is becoming more vulnerable? I ask because I think there’s a sense, especially in the US, where, “Okay, yeah, it’ll be bad, but it won’t be as bad for us.” And I think that that can actually be a harmful attitude, because the fact that it won’t be bad for us: what we’re experiencing will still be very different than our lifestyles now, or could be, I guess. And so I wonder if we have the wrong reference points when we’re making that comparison.

Kris Ebi: All of us are exposed, and that will result in weather patterns in the future very different from the ones we experience now. The extent to which we’re vulnerable to those will depend on the choices made. For example, heat waves are increasing in frequency and intensity and duration, but if we have heat wave early warning systems; if people are aware of the risks of heat; if people know what kinds of actions to take; if communities develop good response systems, they put in centers where people can go and cool themselves down during the day when the temperatures are really high — there’s lots of actions that could be taken. So in the short term, as the temperatures continue to rise, we don’t have to see an increase in mortality in heatwaves. Those can be prevented. The question is whether we constrain our greenhouse gas emissions, because if we don’t, then later in the century we may reach the point where there could be places in the world that will be pretty difficult to live in because they’re going to be so hot.

Ariel Conn: So spinning off the heatwave example: I read, I think it was an interview with you at some point, where one of the points you made that I didn’t know — and I think this is an example of us not doing a good job of preparing and educating people — was just that as people age, they’re less likely to recognize that their body is overheating. I thought that was really interesting. It’s one of those little side effects that I just don’t even think about yet. 

And then I also want to have you talk a little bit about vector-borne diseases, or even just diseases in general, and the impact climate change could have on them. I’ve got an interview that you did quite a few years ago now at this point, where an example you give is there was an outbreak in Anchorage of a gastrointestinal disease carried by a pathogen that grows in oysters, but that pathogen requires certain water temperatures before it can replicate — and the temperature in Anchorage had finally gotten high enough for that pathogen to survive. In the interview, you say previously the closest known case was 600 miles south. So I was hoping you could talk a little bit more about some of the disease problems that we could face.

Kris Ebi: That is a good example that comes from a publication out of Alaska, from an outbreak of a disease that’s called Vibrio parahaemolyticus. It causes nasty gastrointestinal symptoms, and it did appear for the first time in Anchorage several years ago. Think particularly about the vector-borne diseases, and diseases are vector-borne because they’re carried by mosquitoes or ticks for example, and when you look at mosquitoes and ticks, their geographic range is in large part — not entirely, but in large part determined by the weather patterns. If it’s too cold for the mosquito, it won’t survive, although some mosquitoes can overwinter in sewer systems. And similarly with ticks: you only see them in certain places. So it makes sense that as the temperatures warm, they’re just going to continue to change their range, that they’re going to expand from where they are now into other habitat that’s equally as suitable.

This has been a concern with climate change and health from the beginning, of what could happen. One of the concerns, for example, is malaria. When malaria occurs regularly in a population, it’s called endemic. The mortality rate is fairly low: it’s a few percent, and it’s typically in children under the age of five. When you have malaria appear in a region where it doesn’t typically appear, you have epidemic malaria, and then the mortality rate can be over 10%. So you can have pretty high mortality and it’s across the entire age range. And where we see epidemic malaria now is along the edges of its current distribution.

There’s quite a large number of publications showing that with warmer temperatures, the mosquito is expected to expand its geographic range in some places. It may decrease its geographic range in other places that become too hot and dry, but in the new locations where it appears you could then have epidemic malaria — until malaria becomes well established and turns into something you see every year. Assuming you don’t have a vaccine or something that can prevent malaria, then the projections all show, along the edge of the distribution, you’re likely to see increased numbers in the cases of malaria. There’s also concern for diseases like dengue, Zika, chikungunya and other viral diseases in that case that are carried by mosquitoes. So it is a topic of concern and a topic where considerable research is being done.

Ariel Conn: So I think this sort of comes back to my question about regions that think they’re relatively safe possibly being a bit more vulnerable than they thought. I don’t know if some of the wealthier northern countries are still going to be safe from malaria or dengue, but how far are we looking at something like that spreading? Or does that become an unknown?

Kris Ebi: There is good understanding of the environmental determinants of these vectors, so you can model, “What if water temperatures are warmer? What if precipitation patterns change?” That doesn’t necessarily tell you where you might have disease transmission, because for example, the vector that carries the disease dengue, the mosquito, certainly in the US tends to be an ankle biter that bites in the morning and the evening. And those of us in the US typically live in houses with screen doors, and we don’t get many mosquitoes inside our house. So we could be protected from exposure to that mosquito, except of course when we go out and have picnics on the weekend and when we go out and do other things.

Ariel Conn: Yes. I still manage to get bitten by mosquitoes a lot.

Kris Ebi: Yes, we all do. And there is some interesting research: A couple of years ago, some colleagues at the National Center for Atmospheric Research looked at this particular mosquito and looked at its current geographic range in the United States. And we don’t have good surveillance in all of our states for this mosquito, so we don’t necessarily know exactly where it is, but using the environmental determinants, you can say right now you’d expect the mosquito to be in the Southeast and in Texas, for example. And then looking at climate change, saying, “Where could you see this mosquito towards the end of the century?” In, for example, 2080. And then you see quite a big spread of where you could see this mosquito well into the Midwest. And the authors then asked a second question of, “When would the summers be hot enough and long enough that if you introduced the virus into a mosquito, you could actually have the disease?”

The mosquito obtains a virus by biting a person who is infected. The virus then travels to the gut of the mosquito where it replicates, and the rate at which it replicates is temperature dependent. So if it’s too cold, it’ll take the virus longer to replicate than the mosquito will live. And so you need to look at, how hot and how long is that summer? Can you actually have replication? And then showed that the range of possible transmission of dengue would be bigger than it is today, but not as far as the model suggests we could see the mosquito. And again, the mosquitoes’ range, in this model, were projected to be into the Midwest. And in 2017, breeding colonies of this mosquito were found in Toronto, Toledo and Detroit: significantly under-projected where we’re likely to see this mosquito. And again, just because we have the mosquito doesn’t necessarily mean we’re going to have disease transmission, but this mosquito is totally adapted to human environments, and as I mentioned, can do things like overwinter in sewer systems. And so we’re seeing, when people look for it we’re seeing the mosquito in more places where we thought it was before, which then raises concern about, as summers get longer and hotter — which they are — that it becomes more likely we could see disease transmission of some of these diseases in the US.

Ariel Conn: Another paper that you were involved in that I think is really interesting and a little worrisome: that was a study that found that rice actually has fewer nutrients in it if it’s grown in an atmosphere with greater CO2, if I was reading that correctly. And possibly more than just rice — possibly other crops as well. I was hoping you could talk a little bit about that.

Kris Ebi: You’re absolutely right. When you look at plants — to really oversimplify, there’s two main ways that plants bring in carbon dioxide from the atmosphere. And most of the plants that we eat — not all of them, but most of them — have a particular mechanism. These are called C3 plants, and that’s rice, wheat, barley, potatoes, also includes grasses. And as the concentration of carbon dioxide increases in the atmosphere, the plants bring more carbon dioxide in because they need that to grow. And that’s why you read in the newspapers, for example, that CO2 is a plant food — it helps plants grow. The plants also become more efficient in how they use water, and so they absorb less micronutrients from the soil. There’s also changes in essentially the plant physiology. It’s also an oversimplification. You see in wheat, rice, and other kinds of C3 plants about a 10% reduction in protein, a 5% to 10% reduction in all the micronutrients, iron and zinc included.

As a reminder, there’s 821 million people in the world who are food insecure, and there’s two billion people who have micronutrient deficiencies. So micronutrient deficiencies is a much bigger problem. And in addition to the reduction in the micronutrients, the paper you reference, we show that there is a reduction in the B vitamins. For example, folic acid reduced about 30%, and when pregnant women don’t get enough folate, they can have babies with birth defects. So we’re looking at broad scale changes in the nutritional quality of much of our cereal crops. And that potentially could affect us; We estimated that in the major rice consuming countries with low GDP, we’re talking about 600 million people could be affected. Other studies have projected a couple hundred million people being affected, depending exactly on what they looked at. And it would affect not only us, but it also affects livestock that are fed on these kinds of crops.

So the quality of our food overall is likely to decrease as carbon dioxide concentrations increase. And this is an area of high concern, and an area where there’s quite a lot of research underway to better understand the magnitude of the challenge and the opportunities for trying to make a difference before all of our food quality goes down.

Ariel Conn: When you say a couple hundred million to 600 million people will be affected by this, is that in addition to the 800 million that you already referenced?

Kris Ebi: Yes. This is just specific to the changes in plants from CO2, and I will point out that different studies looked at different aspects. So some of the studies that project 200 million people could be affected are looking at specifically iron and zinc. They’re not looking at the B vitamins, they’re not looking at the change in protein or the change in the other micronutrients. There’s not yet been a comprehensive effort to say when you put all these changes together what that could mean, or to say what does it mean on top of what we’re seeing with climate change reducing crop yields in some locations.

Ariel Conn: Climate change reducing crop yields is a problem that I’d heard about. With respect to crops being affected by the increased CO2 in the air, would that be global or is that still a regional issue?

Kris Ebi: That’s global.

Ariel Conn: So everyone is going to see a decrease in nutrients?

Kris Ebi: Correct.

Ariel Conn: It’s just some people will be more negatively affected by that than others?

Kris Ebi: It depends on your overall diet.

Ariel Conn: Okay. So I guess the more diversity in your diet, the better?

Kris Ebi: That’s right, and that’s why in our paper we focused on the countries where you see the lowest GDP. When you look, for example, at Bangladesh today, even as they become wealthier, three of four calories comes from rice, and so the impact on those populations would be expected to be larger. China, of course, is making different choices as it develops in terms of the diversity of its diet, and more work does need to be done to look at how we can ensure that dietary diversity will supply the nutrition that we need for us to grow and be healthy.

Ariel Conn: Okay. This might be a little bit too speculative, but do you think we’ll get to the point where we need to supplement the food in some way, or do you think most of the world will still be able to get the nutrients they need?

Kris Ebi: Today much of our food is supplemented.

Ariel Conn: True.

Kris Ebi: That’s already happening, and if it was as effective as people would like it to be, we wouldn’t have two billion people who are micronutrient deficient. Even in the States, we have far too many women and teenage girls who have iron deficiency anemia. This affects every country.

Ariel Conn: So we don’t want to count, I guess, then, on being able to supplement.

Kris Ebi: Unless we find more clever ways to do it, where it’s more effective than it is today. It should be one of the options we have available to us, but there needs to be more work done to identify additional options, to make sure that the entire population has the nutrition that it needs. Often people don’t have broad dietary diversity because of economic forces: they’re too poor. We have food deserts in the United States where it’s difficult for people to buy a full range of foodstuffs even if they had the money to afford it. So we do have institutional and governance issues that need to be addressed as well.

Ariel Conn: I want to go back to some of what we were talking about earlier and just ask you — you’ve mentioned Agenda 2030, and there’s lots of solutions — can you specifically highlight some things that you think are most important for us, either at an individual level and/or a more government level to be doing?

Kris Ebi: There’s two key issues I would start with. Number one is increasing awareness — and your podcasts are going to help people become more aware of the risks — because there’s really very little people can do if they don’t understand what the risks could be. And the second: there is growing research showing that far too few Americans talk about climate change. We don’t talk about it with our friends and family, we don’t hear about it very much in school — that there is a real lack of discussion, and it would be quite helpful for people to, as I mentioned, increase their own awareness, but then start talking with those around them about their concerns, and better understanding how we can help facilitate the changes that need to be made. You mentioned early on that one of these is voting, and that certainly is critically important, and that’s for all levels: that’s for your city council and that’s for your state legislature. But that’s just one of many activities people can undertake.

Reducing your own greenhouse gas emissions saves you money, and helps reduce how much we put into the atmosphere; Increasing awareness of the risks, for example, of heat, is really important; Thinking about how you use water; We’ve got real issues with how much plastic we’re throwing into our oceans. There’s a broad range of activities people can undertake — collectively and individually — that can make a difference. In King County, where I live, where Seattle sits, every other year there’s an award from King County to NGOs that are doing work towards sustainability. There was an award ceremony in April, and it was just lovely to see the kinds of actions different NGOs are taking — cleaning up local rivers and working to help save our salmon. There’s lots that people can get engaged in that does make a difference and can give people a sense of purpose in making the changes happen.

Ariel Conn: I like the idea of the city or county recognizing groups that are making a good difference. It seems like that would be motivational.

Kris Ebi: I hope so, because there’s so many opportunities for people to engage.

Ariel Conn: My one final question is sort of what you’re hopeful for, but before we get to that, I was looking through a bunch of your papers, and I really wanted to get to a lot more of it, and I don’t think we’ve got time. So I’m just curious if there’s something that you’ve worked on that you think is really important that maybe people don’t seem to understand yet, or if there’s anything related to climate change that you think is really key that we haven’t gotten into.

Kris Ebi: One of the key messages from the Intergovernmental Panel on Climate Change Special Report On Warming of 1.5 degrees is that it is possible to keep warming to below 1.5 degrees. We have the technology, and it certainly is possible to do this. What it takes is an action, to make sure in fact that we do undertake the actions that are needed. Another critical message from the same report is every action matters. It’s not an either-or of individual or collective, do this or do that. It’s every action matters, and we can all make a difference in lots of ways. And the better we understand that, the easier it’ll be for all of us to collectively make the changes we want to see in society and to have a more resilient future.

Ariel Conn: Excellent. So, this may already have answered the question that I have for you to end with. Are you hopeful?

Kris Ebi: I’m a worried optimist. I teach at a university, and my classes grow every year. The energy and enthusiasm from students on this topic is absolutely amazing. The public awareness of this is increasing. Several years ago, the conversation we’re having now would never have happened. You’re seeing a very large increase in awareness, people wanting to take action, people looking for information. And that gives me hope that, yes, in fact we can implement the changes that we know need to be implemented in a timely way, and ensure that our future’s going to look more or less like today and not look fundamentally different.

Ariel Conn: Well, fingers crossed. I’ve definitely, just from reading the news and a couple of the interviews that I’ve done so far, I am very hopeful that it will be some of the younger generations that will preserve our — and more importantly their — futures. Yeah. Anyway, I appreciate hopeful messages. Anything else?

Kris Ebi: No.

Ariel Conn: All right. Well, thank you so much for joining us.

Kris Ebi: Thank you.

Ariel Conn: I hope you’ve enjoyed this episode of Not Cool, a climate podcast. On our next episode, we’ll be joined by Val Kapos, who is the head of the Climate Change and Biodiversity program at the United Nations World Conservation Monitoring Center.

Val Kapos: We do need to stop talking and start doing. I would like to see ecosystem-based adaptation integrated into the way people think about responding to climate pressures. I think it’s important that people start to consider what the natural world has to offer at the same time as they look for other options, and that we evaluate these options together. We look at complementarities.

Ariel Conn: As always, if you’ve been enjoying these episodes, please take a moment to like them, share them, and maybe even leave a good review.

Not Cool Ep 11: Jakob Zscheischler on climate-driven compound weather events

While a single extreme weather event can wreak considerable havoc, it’s becoming increasingly clear that such events often don’t occur in isolation. Not Cool Episode 11 focuses on compound weather events: what they are, why they’re dangerous, and how we’ve failed to prepare for them. Ariel is joined by Jakob Zscheischler, an Earth system scientist at the University of Bern, who discusses the feedback processes that drive compound events, the impacts they’re already having, and the reasons we’ve underestimated their gravity. He also explains how extreme events can reduce carbon uptake, how human impacts can amplify climate hazards, and why we need more interdisciplinary research.

Topics discussed include:

  • Carbon cycle
  • Climate-driven changes in vegetation
  • Land-atmosphere feedbacks
  • Extreme events
  • Compound events and why they’re under researched
  • Risk assessment
  • Spatially compounding impacts
  • Importance of working across disciplines
  • Important policy measures

References discussed include:

Climate change can change the individual variables contributing to the compound event or the dependence between them. And then there might be new types of compound events that haven’t been relevant in previous conditions.

~ Jakob Zscheischler

Ariel Conn: Hi everyone, and welcome to episode 11 of Not Cool, A climate podcast. In Episode 10 we heard from Stephanie Herring who spoke quite a bit about extreme weather events. Today we’ll hear from Jakob Zscheischler about what happens when those extreme weather events occur back to back or in conjunction with each other, and why we’re so unprepared when these types of compound extreme events do occur. 

Jakob is an Earth system scientist with a background in mathematics, biogeochemistry and climate science. He uses sophisticated statistical approaches to infer new insights from a variety of datasets, including remotely sensed data, station measurements, reanalysis data, and model output from climate, vegetation and other impact models. Currently his research focuses on better understanding compound events.

Jakob, thank you so much for joining us.

Jakob Zscheischler: Thank you for having me.

Ariel Conn: I want to go back to basics a little bit and start by asking you about some of the research you did during your PhD on the carbon cycle and how drought and heat impacts that. And I was hoping you could first start by reminding us of what the carbon cycle is and how that works.

Jakob Zscheischler: Yeah. Okay. So, I’ve worked a lot on the carbon cycle on land and basically the land biosphere takes up a lot of carbon every year and also releases carbon. So we have a cross carbon uptake of about 120 petagrams per year, and a similar amount gets released by respiration, by fires, by soil microbes — but there’s a carbon net sink of about maybe two to three petagrams at the moment, which means that the land biosphere sucks up carbon from the atmosphere and by this, slows down the increase in atmospheric CO2 concentration that we cause by emitting CO2 through fossil fuel emissions, for instance.

Jakob Zscheischler: So, currently about a fourth of our fossil fuel emissions are taken up by the land biosphere, but we don’t really know whether this will continue into the future and how much of this sink activity — whether this will increase or decrease, and the carbon cycle climate models that we use, they are quite uncertain on that. And the land biosphere or the terrestrial vegetation experiences a drought or a heat wave: Typically, the carbon uptake is reduced substantially and we might even lose carbon to the atmosphere.

So, during drought and heat events the sink activity is substantially reduced and if drought and heat events increase with future climate change, for instance, then this might also lead to a stronger reduction in this uptake activity of the biosphere.

Ariel Conn: If we’re experiencing global warming, can we assume that the earth will not be absorbing the carbon or is there still a chance that we could still be okay?

Jakob Zscheischler: There are different processes happening at the same time. On the one hand, with warmer temperatures, for instance in the higher latitudes, this is beneficial for forests. So, forests are expanding in the northern latitudes. We actually see a greening globally, even. So, there’s an increase in leaf area globally, but at the same time in some other areas, plants reach their limits; For instance, in the tropics, some plants might reach their temperature limits and then die due to drought or heat. 

And the uncertainties in the models come also because of what we call CO2 fertilization. So, with higher CO2 concentrations in the atmosphere, plants are more efficient. They lose less water while taking up the same amount of carbon and they can uptake more carbon. Therefore, they are less sensitive to droughts. So, it could be also that plants actually like a warmer and more CO2 rich climate much more and grow better, but the models that we currently have somewhat disagree which effect will dominate, and that’s where the uncertainties come from.

Ariel Conn: So, even if we do get a situation where we’re seeing plants liking the hotter weather, can we still expect to see shifts in what plants are growing in different areas — that idea that what humans are used to in their current location might still not be the same?

Jakob Zscheischler: The vegetation composition will change and is already changing in some areas. The question is how quickly plants can adapt to these changes. So for instance forests, and trees in general, are long lived species. So, if climate is changing more quickly than forests can adapt or new tree species can grow, then this might be really difficult for the plants and we might actually lose more carbon then in these situations. It’s a matter of how quickly climate change is happening, but also these things are difficult to model into the future. So, a lot of models have a dynamic vegetation that adapts to these new climate conditions, but of course it’s very challenging to model this correctly.

Ariel Conn: If I understood it correctly, some of your research has found that heat and drought are more likely to occur together, as opposed to maybe heat and more moisture in the air. Is that correct?

Jakob Zscheischler: Yeah. So I got into this topic by looking at situations where the terrestrial vegetation loses a lot of carbon and I tried to understand what are the climatic drivers behind these conditions, and it’s typically a combination of drought and heat. And so I looked into what this actually — the likelihood that drought and heat co-occur and in which places do they co-occur more frequently than in others. And typically, drought and heat conditions are strongly correlated in a lot of places, particularly in mid-latitude regions. For instance, in areas like central Europe, drought and heat are correlated because of land-atmosphere feedbacks. If you have a dry spring, for instance, and then we have an atmospheric blocking event, a high pressure system, then the soil gets heated up and there’s less evaporative cooling because the soil is already dry, which then leads to even higher temperatures and then even more evaporative demand. So, even more drying out the soil. So, there’s a feedback process and it creates these correlations between dry and hot conditions.

Ariel Conn: So, you sort of transitioned into looking at more extreme events, I think still connected to drought and heat. Can you talk about what extreme events look like? Or maybe define what an extreme event is.

Jakob Zscheischler: An extreme even, such as drought and heat or a heavy precipitation events, typically just events in the tail of the distribution. So if you look at the temperature distribution, a heat event is at the upper tail of this distribution. So we usually say above the 90th percentile, or a temperature that is higher than a certain threshold. Can do the same for dry conditions: We look at if the precipitation deficit is particularly large; or for storms, if wind speed is very large. 

So, for a long time, people have looked at these extremes individually. So, we have experts on heat waves, we have experts on droughts, experts on heavy precipitation events and storms; But for impacts — as I have just discussed for the carbon cycle, for instance, but also for agriculture, for instance — these combinations of extremes are particularly harmful. And if we estimate occurrence probabilities from only one type of extreme, from one hazard — let’s say only heat waves — and combine this with risk estimate from droughts, then we might underestimate the risk when the heatwave and the drought occur together if they are correlated.

Ariel Conn: Can you give a little bit more detail about what these compound events look like? I think one of your papers you give the example of what happened in Russia in 2010. Maybe you could describe that?

Jakob Zscheischler: Yeah. So, Russia is kind of a prime example for a compound event. So, we define compound events as a combination of climate drivers or hazards that contribute to societal or environmental risks. So for us, compound events are multiple things in the climate domain that contribute to risk. In the case of Russia, we had a precipitation deficit earlier in the year in 2010 — this happened in 2010 — and then we had a very persistent blocking event in western Russia, a very stable, high pressure system that stayed there for a long time. And that led to very high temperatures. In combination with the dry soils, the temperatures got higher and higher, and then this triggered wildfires in large parts of western Russia, destroyed large amounts of Russian crops, and created a lot of air pollution that then killed a lot of people.

So, overall, more than 50 thousand people died in this event — largely due to air pollution, but also heat stress. Another important impact was the agricultural loss: About 25 percent of Russian crops were destroyed, so that the Russian government actually imposed an export ban. All these different climatic hazards compounded each other and led to these immense impacts in different systems.

Ariel Conn: Why haven’t more people been looking at these as compound events? Is it just a case of we needed to understand the individual events better first? Is it not understanding the impact of the compound events?

Jakob Zscheischler: It’s a good question. I mean, I think in a case like the Russian event, there are a lot of studies that disentangle all these different aspects of the event, and people have looked at this and these different drivers in mind, but still people usually focus on either the drought or the heatwave. So, it’s often called the Russian heatwave even though it was a strong drought also, and we had all these fires, and so on. One reason for this separation of hazards is, I think, how people are working in their own discipline and are experts in their own fields. And the other aspect is that it’s also very challenging to study these compounding aspects. For instance, if you want to estimate the risk of these types of events, we somehow need a multi-varied model that incorporates these very unlikely conditions in different variables. It’s just statistically very challenging to model this and then to make projections into the future.

Ariel Conn: Maybe as we’re getting more data about these events, do you expect us to get better models? Is it not related to data? What helped to improve the models?

Jakob Zscheischler: So, one thing is data, and I think what helps here is really model ensembles for instance, which is getting more and more common so that people run the same model a lot of times. So, if the model is well representing these types of events, you can then harvest these large amounts of data and try to estimate risks. It’s very difficult to estimate future risks from single events, so we need a good understanding of how these events happened and we also need to know how well models actually model these type of events, which is a bit of an open question. We do a lot of model evaluation based on single variables like temperature and precipitation, but we don’t know very well how well the models represent relationships between the variables. So, if you want to estimate risk of compound drought and heat events, for instance, we need to make sure that our models represent well the current risk of compound drought and heat, so that they basically represent the frequency of current drought and heat events adequately.

Ariel Conn: So, you’ve mentioned risk a couple of times. What is the impact on our understanding of climate risks if we’re looking at individual events rather than these compound events?

Jakob Zscheischler: So, if we estimate risk from single events — let’s assume we have a one-in-a-ten-year heatwave and a one-in-a-ten-year drought. Then, if we estimate the risk independently and then estimate the risk of the compound charted heat event, we would say it’s a one-in-a-hundred-year event. But if they are now strongly correlated, this likelihood can increase substantially. So, this is what we have shown in the study in 2017: that if you actually consider these dependencies between temperature and precipitation, this likelihood can reduce to a one-in-twenty-year event. So, we might strongly underestimate risks if we ignore these dependencies. And this is very important for drought and heat events, but also in coastal areas for compound flooding events. For instance, when a storm surge happens together with a heavy precipitation event inland, and when these events are correlated as well, and we then estimate floods from these variables, then we might also underestimate flood risks if we ignore these dependencies.

Ariel Conn: Are we seeing that? Or is that something that we would see in the future?

Jakob Zscheischler: Depending on the location, these type of events are correlated. So, for instance, in the eastern US coast, storm surge and heavy precipitation extremes are strongly correlated much more than the west coast — this is related to certain weather conditions and storms. But what the future might do is change these correlations. So, there’s actually already evidence that these correlations have increased over the last 50 to 60 years, so that the risk of such a compound flooding event is already larger just due to the change in dependence. And climate change might also change all kinds of dependencies between these hazards, and this is a topic that we are working on.

Ariel Conn: So you gave the comparison of the east coast to the west coast in the US. Would we just expect the east coast to have greater correlation between extreme storms and storm surges or would we also expect to start seeing an increase in that correlation on the west coast as well — or anywhere else in the world for that matter?

Jakob Zscheischler: So, I’m referring here to one study that has looked at this in station data. I think they also found increases in correlation in the west coast, but I think it’s currently unclear what the drivers are. If you talk about coastal areas, in addition, you will have a sea level rise which is compounding this already compound floods. It’s kind of a third variable in addition to that, that’s making everything a little bit worse.

Ariel Conn: So, would it still be considered an unknown — the extent to which locations might be experiencing new events versus locations just experiencing more extreme versions of what they’ve already seen?

Jakob Zscheischler: So, they are two different things, right? So we have a dependence in current climate; It already leads to compound events independent of climate change. Now, climate change can change the individual variables contributing to the compound event or the dependence between them and then basically change the risk altogether. This is one thing — what we try to understand, how do these things change, in which areas for which type of events, or how do drought and heat dependencies change, how do precipitation, storm surge dependencies change. And then there might be new types of compound events that haven’t been relevant in previous climate conditions.

For instance, there was a study coming out this week that discussed the possibility of a tropical cyclone or a hurricane that hits some coastal area — and then subsequently, a deadly heatwave arrives a couple of days later. So the cyclone might destroy the infrastructure in the area and then during the heatwave, you might not be able to use air conditioning to mitigate the impacts. And these type of events will become more common in the warmer climate, because it’s warmer, so the likelihood of heatwaves increases basically everywhere even though the likelihood of tropical cyclones might not change.

Ariel Conn: Okay. This might be a really awkwardly worded question, so bear with me for a minute. Basically, I’m sitting here in Colorado where I think our high today is going to be in the low 80s — and that’s actually cooler than I’m used to for the middle of summer — while you are sitting in Europe in the midst of some of the hottest recorded temperatures ever. And I guess my question is, what sort of research would you like to see happening to better understand these types of dynamics and maybe to help those of us who are not in science understand what’s happening?

Jakob Zscheischler: So, I’ve talked so far about compound events where we have basically couple of hazards, two or more, in the same area, but you can also call a compound event an event where you have a spatially compounding impact. So, for instance, if you have climate extremes happening in a lot of areas that are agriculturally relevant, and that leads to a big impact on agricultural production globally, then what we would like to know then, of course, is: is this physically related? And this could be — so, the jet stream for instance: there’s a lot of work now on how the jet stream is changing, but also how certain configurations of the jet stream lead to certain droughts and heat waves along the same latitude in advance, for instance.

So last year, we had heat waves in a lot of areas in the northern hemisphere; We had floods; We had droughts in some areas. And there is some evidence that these events were all linked to a certain configuration of the jet stream. So, to better understand risk also, and the future of this, for instance, global crop failure, we need to understand whether these events are physically related and then we can also better project or predict them and predict the risk and mitigate the risk. 

To do this work or to better understand these events, we need to work together across disciplines. Climate modelers need to work together with impact modelers, or people who really understand what causes impacts need to work together with statisticians to think about which multivariate statistical methods we can use to study these events, and with dynamicists to really understand how these dynamics work. So we try to do this in a European network that I’m leading here, which is called Damocles. So in Damocles, we try to bring together climate modelers, impact modelers, statisticians, engineers, but also stakeholders.

The main goal is first of all to develop a community working on compound events, to raise awareness about compound events, to also educate a new generation of scientists to work on these topics; But more concretely, we try to get an idea of what are the different types of compound events that can actually occur — can we somehow classify these type of events? We are working together with stakeholders to try to understand what are the events that are particularly relevant for different types of stakeholders. We are trying to create a database on impact data to better link impacts with climate conditions — this is a big gap that we have.

We have a lot of climate data, but to understand what climate conditions lead to large impacts we need data on impacts, such as crop yields, health impacts, infrastructural impacts, and so on. And then, we also want to think about new statistical tools, how to study these type of events, and also better understand how current mechanistic and process based models simulate these type of events and how we can improve these models.

Ariel Conn: And you also recently hosted a workshop where you brought a bunch of people together, and I was hoping you could talk a little bit about some of the points that were discussed during the workshop, or any interesting outcomes.

Jakob Zscheischler: So, this workshop was hosted in Columbia University by Radley Horton and Collin Raymond. I was in the organizing team, or in the steering committee. And the topic of the workshop was correlated extremes. And it went a bit beyond the compound events, or it’s expanding on the compound events that I’ve been talking about, which were mostly climate related. So, we had about 150 people maybe, and we started with the physical climate and correlations in the climate space that lead to compound extremes, but then we also had people from impact sectors, for instance, talking about fire, talking about what causes migration of people, talking about agricultural impacts, and health impacts. Then, we tried to link these multivariate or compounding additions in climate space to these impacts and try to figure out where are the research gaps. And in particular, impacts can kind of amplify climate hazards: For instance, if you think about a managed water system, there’s a human component in there that can amplify or mitigate climate stressors, such as a drought — a meteorological drought — for instance.

Ariel Conn: What should people be doing more broadly, both in terms of what policies would you like to see enacted, what individual actions do you think people should be trying to take to try to help mitigate some of this?

Jakob Zscheischler: I think what governments should do as quickly as possible is to reduce carbon emissions in all sectors, phase out coal, and maybe one of the most effective tools for this would be to introduce a carbon tax. It’s now, again, being discussed also in Germany and in the European Union. I think on the individual level, maybe what could be done is really put pressure on the governments to really act and to elect people that are really progressive in acting against climate change.

Ariel Conn: Do you feel hopeful for the future? Do you think this is something that we can address?

Jakob Zscheischler: I’m still hopeful; I think otherwise I wouldn’t be working on the topic. But I think time is running out and it’s getting more and more scary when you see these type of temperatures that we’re experiencing: In the last days in Europe, we have had all time heat records in at least three European countries, and this is already the second heat wave this summer we had — the French heat record was broken a month ago. And we had the Paris Agreement, but since then there’s actually little has happened — at least in terms of actual carbon emission reductions, little has happened. I think with the movements on the street that are going on since months, also scientists are getting a bit more optimistic — or I’m personally getting a bit more optimistic again. But time is running out.

Ariel Conn: Is there anything else that you think is important for people to understand that we didn’t get into?

Jakob Zscheischler: You might underestimate the risk of compound events if you take risk from the individual drivers and then multiply them individually. This is important for coastal flood assessment, for instance; So, if you want to build a dam to protect against flooding, and you estimate such a dam based on a hundred year return period that you estimate from heavy precipitation inland, or that you estimate from coastal storm surge events, this hundred year return period — or this dam height — basically depends on this. So, if the heavy precipitation inland and the storm surge are correlated, then you might need to build a higher dam for a hundred year event: So, the likelihood of having that same flood height is actually much higher because these events occur together and they might lead to a much larger flood than if they happen individually.

Ariel Conn: Do you think that we’re sufficiently prepared for the risks?

Jakob Zscheischler: I think it depends a bit on the region, but I think in a lot of areas, risks are underestimated because we are ignoring compounding factors. We might not be aware of some of them. We might be aware of others, but we kind of ignore correlations. It sometimes might be difficult to even know whether these factors are correlated, but I think in general, for a lot of impacts, we might be underestimating risk because we are not aware of compounding drivers.

Ariel Conn: Okay. I think that’s probably pretty good. Thank you so much for joining us.

Jakob Zscheischler: Thank you for having me.

 Ariel Conn: On the next episode of Not Cool, a Climate Podcast, we’ll be joined by Kris Ebi, who has been studying the health impacts of climate change for the last twenty years.

Kris Ebi: The quality of our food is likely to decrease as carbon dioxide concentrations increase. And this is an area of high concern, and an area where there’s quite a lot of research underway to better understand the magnitude of the challenge and the opportunities for trying to make a difference before all of our food quality goes down.

Ariel Conn: I hope you’ll join us for this conversation with Kris, which will go live on Tuesday October 8. If you’ve been enjoying the Not Cool podcasts, please like them, share them, and leave us a good review. It’s a small effort on your part, with a big impact for us. And please join the climate conversation on Twitter using #NotCool and #ChangeForClimate.

Not Cool Ep 10: Stephanie Herring on extreme weather events and climate change attribution

One of the most obvious markers of climate change has been the increasing frequency and intensity of extreme weather events in recent years. On the tenth episode of Not Cool, Ariel takes a closer look at the research linking climate change and extreme events — and, in turn, linking extreme events and socioeconomic patterns. She’s joined by Stephanie Herring, a climate scientist at the National Oceanic and Atmospheric Administration whose work on extreme event attribution has landed her on Foreign Policy magazine’s list of Top 100 Global Thinkers. Stephanie discusses the changes she’s witnessed in the field of attribution research, the concerning trends that have begun to emerge, the importance of data in the decision-making process, and more.

Topics discussed include:

  • Extreme events & how they’re defined
  • Attribution research
  • Risk management
  • Selection bias in climate research
  • Insurance analysis
  • Compound events and impacts
  • Knowns and unknowns

References discussed include:

We’ve seen more people start to ask the question, “Is there a linkage between that impact of climate change and some kind of socioeconomic factor?” — building this bridge between the pure climate change science component and actually connecting that to, “Why does it matter to the world? Why does it matter to people and humans and our societies?”

~ Stephanie Herring

Ariel Conn: Hello, and welcome back to Not Cool, a climate podcast. I’m your host, Ariel Conn. Today, we’re starting something of a two-parter about the extreme events that we’re already starting to see as a result of climate change. We’ll talk today with Stephanie Herring, a scientist with NOAA, looking at extreme events a little more broadly, and then on Thursday, we’ll hear about compound extreme events from Jakob Zcheischler who’s at the University of Bern in Switzerland. I say this is something of a two-parter because both Stephanie and Jakob both go beyond just extreme events. Today, Stephanie will also talk about risk management, insurance analysis, selection bias in climate research and much more, all related to climate change, of course.

Stephanie is a scientist and senior advisor with National Oceanic and Atmospheric Administration’s (NOAA) Center for Weather and Climate in Boulder, Colorado, where she specializes in extreme weather and weather-related events and climate services. She is the lead editor of the annual Bulletin of the American Meteorological Society report, Explaining Extreme Events from a Climate Perspective, which is aimed at understanding the physical drivers behind extremes and how risk exposure to extremes events is changing over time.

Stephanie, thank you so much for joining.

Stephanie Herring: Thanks for having me.

Ariel Conn: The first question that I have for you before we get into your work is just: what is climate change? We hear a lot of terms thrown around: We hear climate change, global warming, ocean acidification. We know there’s problems related to plastics that are somehow connected to climate change but separate. So I was wondering if you could just real briefly explain what these different things are and how they’re connected.

Stephanie Herring: Sure. So global warming refers specifically to the fact that because human-caused activities can release greenhouse gases into the atmosphere, it has caused a long-term warming trend across the planet. And that long-term warming trend is what we call global warming.

Climate change is the consequences of that long-term global warming, and it has other impacts on the climate system. And that is what we refer to as anthropogenic climate change. So it’s beyond just the warming factor, but also changes in ocean temperature have been caused by that; Some of the work that I look at, changes in extreme events, and those would also be changes that would be a consequence of climate change.

Ariel Conn: Okay. So let’s go ahead and switch to the work that you do. How do you define an extreme event?

Stephanie Herring: That’s actually a very interesting question because there is no one definitive definition of an extreme event. If you ask the National Weather Service or the World Meteorological Organization — you know, these societies that think about these things — there’s no one definition. So there’s a meteorological extreme, which generally gets set to the extreme extremes, or the top one to three percent of what we would see in terms of being extreme.

But some people also draw that line, say, at the top 10%. So for me personally, the way I tend to look at extreme events is that they can either be extreme from a meteorological or climatological perspective, as in it was an extreme physical phenomenon, but also because of extreme impacts. And so even certainly within NOAA, I think we’ve cast that definition more broadly to not just be a meteorological extreme but potentially also having an extreme socioeconomic impact as well.

Ariel Conn: That’s really connected I think to the next question I have: that is, exactly how extreme does something have to be to be considered extreme? For example, the Midwest had a lot of rain this last spring, but it might not have been one specific event that dumped a lot of rain — it was over an extended period of time.

Stephanie Herring: Yeah, so any event has to be defined in some way by space and time, and you could have an extreme event be an extreme annual global average temperature. So you’re looking across the planet; You’re looking at the temperatures across the planet over the course of a whole year and finding the warmest year on record. That could be considered an extreme event.

Alternatively, it could be the amount of precipitation that fell within one hour over Houston during a hurricane. And so I think that when you use the term “event,” one of the things that we do in our field is we require people to be very specific about defining that event. What region are you talking about, and what’s the time period that you’re talking about? And if you don’t have those two things, then you don’t have an event definition. And people actually spend a lot of time thinking about what is the definition of their event that they are looking at from a research perspective?

Ariel Conn: So hurricanes seem like obvious extreme events if they’re severe enough. If you have a five-year drought, could that be considered an event?

Stephanie Herring: Yes.

Ariel Conn: Okay. So something else that I wanted to clear up before I start asking a little bit more details about your work: in some of the papers, I read about ocean heat events and terrestrial events and atmospheric events, and I was wondering if you could explain what the differences are between those — or how it’s connected.

Stephanie Herring: So again, this really goes back to the definition of the event you’re looking at. So not only is it in time and place, but what exactly are the physical phenomenon that you’re looking at? Is it temperature, and if so, are we talking about a temperature in the air over a city, or the temperature of an ocean and looking at sea surface temperature? So needing to very clearly define an event before you can then go forward and make a statement about what happened is incredibly important, and we do actually spend a lot of time thinking about that. 

Because it’ll be interesting: two people will come forward and say, “Oh, I looked at precipitation from Hurricane Harvey.” And you’ll see three different papers come out that looked at precipitation of Hurricane Harvey. And that’s the title of their papers. If you look at how they define the event, they all use slightly different time periods, so what day to what day; slightly different geographic regions, so someone might’ve looked at the whole region of the Gulf; somebody might’ve looked at just the region where it stalled. Both of those are legitimate papers about Hurricane Harvey, but they define the event from their research perspective in a very different way.

Ariel Conn: Does that make your job more complicated? How do you deal with that?

Stephanie Herring: It can make it more complicated in the sense that when you’re trying to compare two different results from two different papers that maybe seemingly looked at the same event, you need to actually make sure they did look at the same event, not just the name and what appeared in a headline, but from a scientific perspective, were they looking at the same thing? Were they actually asking the same questions?

It’s actually really helpful if multiple groups who are independent look at the same event and then we can see how their answers may differ or be the same. And if they don’t actually define the event the same way, they’re not technically looking at the same event. It can make things a little bit tricky, but it also makes it, I think, more interesting because then you can really see where different methodological approaches have different benefits in terms of the information that they’re able to provide.

Ariel Conn: More specifically to some of your work, you’ve been working on papers titled Explaining Extreme Events from a certain year from a Climate Perspective for a few years now. How long have you been doing that?

Stephanie Herring: Since 2011. BAMS Explaining Extremes 2011 was our first report.

Ariel Conn: Okay. What have you seen change over the years?

Stephanie Herring: I would say a couple things. One, potentially less interesting for the broader community but interesting to me, has been really the explosion in the number of people who have been able to engage in attribution work. And I think this is actually true across a lot of climate fields that rely a lot on modeling, is that the computational power, just the technology and the ability to run climate models and have access to all this different data information has really expanded. And so there’s been an incredible leveling of the playing field within the research community as to just who can and can’t do this work.

It used to be a much smaller group because you needed to be at a facility that had high-performance computing power, could run models, or had access to model data. And now you can be almost anywhere and do a lot of this research. And so previously, when we first started this, a lot of the research was simply coming out of either North America, Europe, Asia, Australia; And I’ve seen an increase in the number of papers coming from other nations, which I think is exciting, because there’s a lot of selection bias in terms of which events get researched or not.

The selection bias previously was scientists actually are people and tend to be interested in events that they may have had personal experience with, or maybe their country had personal experience with. So most people, for example, who looked at the recent European heat wave came from European labs. Not surprising. So it’s nice to see, as we see more researchers from different parts of the world getting into this field, we’re seeing more papers about events from different parts of the world, which personally is exciting.

The other piece of it is that we’ve seen more people start to ask the question not only of, “Can I do an attribution event analysis? Can I understand whether climate change played a role in this specific event,” but, “Is there a linkage between that impact of climate change and some kind of socioeconomic factor,” building this bridge between the pure climate change science component and actually connecting that to, “Why does it matter to the world? Why does it matter to people and humans and our societies?”

And so that field is loosely being called impact attribution, and we’re seeing more and more papers along those lines. And early on, there weren’t that many. So I think that’s also exciting to see how people are trying to connect climate change research to real-world issues and challenges people are facing. And the other piece I think that was just a couple of years ago was that basically the way climate change attribution science works is that, in general, the basic methodology is that you look at a world in a model where climate change has not occurred, so it’s a control planet.

We can’t replicate that without having a model, and we compare that to the world that we actually live in. And we can actually test, and we know what that world looks like because we have observations and we take records of our environment now. And so we can look at the two models and understand, “Okay, what was the risk of that event occurring in a world without climate change, and what’s the risk of that event occurring in a world with climate change?”

And the statistical approach is actually taken from the public health community. So an example that might make more intuitive sense is, say you’re looking at the risk of smoking and lung cancer. So you can take a group of people who haven’t smoked and a group of people who smoke and assess, “What’s the different risk of any individual in those two groups getting lung cancer?”

When you take that same statistical approach, actually, and apply it to our climate models — there’s obviously some nuance there, but in general, the principles apply. And what we’re seeing now is that we are finding more events that we simply cannot replicate in a world where human-caused climate change hasn’t happened. In particular, we’re seeing this for heat events now, which is that we knew the risk of heat events was increasing, and I think within the climate change attribution community, we knew that someday we would cross this threshold. I personally thought that was going to happen much later than it did. I wasn’t so much surprised at the result — we knew that was coming; I think we were a little surprised at how soon it showed up in the data.

Ariel Conn: So I’m a little bit torn because I wanted to follow up with this idea that we’re seeing events that couldn’t happen without climate change, but before I go there, I actually want to take a little bit of a step back and ask if you could explain what climate change attribution science is.

Stephanie Herring: Sure. Attribution is just the general process of trying to understand what the cause of something is. And in climate change attribution research, what we’re trying to do is understand what the causes were of a particular event. The question we go in asking is, “Did anthropogenic climate change impact the intensity, frequency, or geographic distribution of this event, however it’s defined?” There’s actually a lot of different levels of climate change attribution. Specifically, the work that I’m part of is looking at that from the perspective of extreme events. Is climate change playing a role in changing the intensity, frequency, or geographic distribution of extreme events?

Ariel Conn: Okay. The other question that I had sort of lumped with this is, how is that then applied to risk management?

Stephanie Herring: So I’m not personally in the risk management space. That being said, I think that where I see it having applications is that one of the things we’re trying to do is not come up with a binary answer of yes or no. That might be what you see in the paper, but that’s not the point of the research.

The point of the research is actually to quantify that change in risk. So what we’re trying to do is understand how much — not whether or not, not a yes or no — but how much can we quantify change in risk of a particular event type happening in a particular location? From that perspective, the other part of that is then again to look out into the future and say, “Okay, from pre-industrial climate to today, the risk has changed by X.” And using the same processes, we can then look out into the future and understand, “Here’s what we would expect in the future. This is the trend or the path that we’re on. This is how we would expect the risk to change going forward.”

And then I think that information would be used in the same way that lots of other weather and climate information is used, regardless of whether it’s linked to climate change or not. NOAA provides weather and climate data to all different kinds of sectors to help them understand what the state of the climate is so that they can use that in planning all different types of decisions.

So the energy sector is one example where NCEI — the part of NOAA that I work for, the National Centers for Environmental Information — held a stakeholder engagement workshop with the energy sector. And one of the big questions they had was, “Hey, we have all this infrastructure, and it’s sitting in a flood plain today. I need to rebuild it. I’d rather not rebuild it in a flood plain. Can you tell me where the flood plains are going to be, not only today — my infrastructure needs to last 50 to 70 years — so not only do I not want to build it in what’s not a flood plain today, I want to build it somewhere that’s not going to be a flood plain in 50 years. Where’s that spot?”

Ariel Conn: So you were mentioning earlier that one of the things that’s surprised you is that we’re seeing more of these extreme events sooner than you were expecting?

Stephanie Herring: We’re seeing a higher quantity of events that couldn’t have happened without climate change; I would say that what we’re also seeing over all these years is that the number of events that have some climate change signal to them seems to be increasing. I’ll give the huge caveat that the number of reports that are out there, it’s very difficult to do any kind of real statistical analysis because there’s a huge selection bias, like I said. We’re not randomly looking around the Earth and saying, “Okay, we’re going to randomly select extreme events from around the planet and then look at them.” Scientists pick which events are interesting to them and again, that generally selects for events that have happened in the developed world or have had a major socioeconomic impact. So, not random.

Ariel Conn: To me, it seems like every new report that’s made that gets public attention seems to be getting worse and worse. And so if that’s the case — and maybe it’s not, but if that is the case — what sort of impact does that have on the suggestions that you then give to people who want to make sure they’re not building in a flood plain?

Stephanie Herring: We provide the data and information, and I think that on the end of the decision maker, they are the ones who really decide ultimately how that data and information is going to get applied to their particular decision. I will back up one second though. When we talked about extreme events and whether there’s an extreme event, for the purposes of those extreme events that are being influenced by climate change — back to the public health analogy: Extreme events is sort of like the meteorological equivalent of cancer.

There’s a lot of different types of cancer out there, and different cancers mean different things and they’re treated in different ways. Extreme events are actually the same way. So we kind of bundle them together, but an extreme heat event is not the same thing as an extreme tornado, for instance. And scientifically, our ability to attribute climate change to how the risk profiles may have changed is also not the same.

We are very good and we have very high confidence in looking at extreme heat events. We have almost no confidence in looking at tornado events because we do not understand how climate change is really going to change tornado dynamics in the future; We also don’t have a very good observational record of tornadoes — and when I say good, I mean back, you know, 150 years. Really, the tornado record is robust, probably starting in the ’70s and ’80s, post-satellite, because before that, they would happen and maybe someone would write it down, but maybe not.

Tropical cyclones suffer from the same issue with the observational record, whereas with heat precept, we have excellent observational records that go back quite a long time. There’s all kinds of paleoclimatological records; There’s tree rings: We have very good information to understand how the global climate and global temperatures have changed over time. We don’t have that for a lot of other event types, and so the more confidence we have in the observational record and the better understanding we have of how climate change is going to impact an extreme event type, the more confidence we can have when we do an attribution analysis.

Ariel Conn: So as someone who is not studying climate change, I find myself and a lot of the people that I hang out with, talk to, et cetera — anytime anything weird happens, we’re like, “Oh, climate change.” And I’m guessing that’s probably not always the case.

Stephanie Herring: Here’s the thing. It may be the case, or it may not. We don’t know. I think it’s not so much that, “Is climate change impacting tornadoes?” Maybe, but I don’t have any evidence to show you that it is. So it’s not that it’s not; Just because scientists haven’t found it doesn’t mean it doesn’t exist, right? But we don’t have the body of knowledge and the body of research to be able to confidently back up that statement. So you and your friends at cocktail parties: you may be right, but I can’t prove it.

Ariel Conn: Okay. Okay.

Stephanie Herring: I do think there’s a distinction between the two, as to what we can confidently validate with our scientific methods and our research and our data and our models, and the fact that there may be impacts happening today, and we may not know about them until the future when our data and our models and our scientific methods and our toolkit gets more robust, and we’re able to look at tornadoes. I think someday we will be able to. It’s just not today.

Ariel Conn: So a personal one that I’m interested in: Colorado very recently recorded the largest hail it’s ever had. Is that one of those that’s, “We don’t know if it’s connected,” or do we know that it is connected?

Stephanie Herring: No. Hail is a tough one. We do not have the ability at this time to do a robust attribution analysis on any one event. We are starting to increase our understanding of what drives hail events and how those drivers might be impacted by climate change, which is step one. But we’re not at the point where you can confidently say, “Oh, well, let me take a look at that for you and get back to you in a week,” and say, “Yep, climate change played a role in that one,” or, “No, it didn’t.” We’re not there yet.

Ariel Conn: Okay. Your most recent extreme events paper, you quoted someone else’s piece later on, saying, “Small deviations from estimations of future costs have considerable financial consequences.” Is that something you can elaborate on?

Stephanie Herring: I think I was quoting Rebecca Owen at the time, and I actually just spoke at the Society of Actuaries Conference about this because from an actuarial perspective, simply repeating what she would probably say, the point she was trying to make in regards to public health is that when looking out into the future, you make these small estimations — and you can think of it like a pie — where, early on, a small 15-degree difference in something a couple years out: the deviation is very small from what you had predicted.

But once you get further and further out in time, that early minor error propagates. So 10 years out, 15 years out, now you’re talking about millions and billions of dollars in difference in what you estimated versus what an actual cost might be. So that was the point that she was making from a health care perspective.

Ariel Conn: That was cost of health care related to climate change then?

Stephanie Herring: Yeah. So she and I did some work trying to see if we could look at insurance claims and relate them to heat events — and there has been a lot of work done in this area to show that during specific heat events, different types of claims go up. And one of the big ones that get looked at are related to people who are diabetic, so a lot of kidney-related issues, because during heat stress events, it can cause challenges to people’s organs if you’re already compromised in that respect. Heatstroke is actually not that big of a deal because generally, the tail of a heatstroke event is relatively small.

But if you have someone who is normally on dialysis and you throw them off of their steady state, the tail of medical costs from that to recover can be six months, seven months, eight months. That’s one of the reasons that they are very interested in understanding: how do heat events and other types of extreme events drive insurance costs? What’s the tail? And not only after the event, what do those look like? And so we were trying to understand what kind of changes we expect to see in our insurance claims data.

Ariel Conn: Interesting. All right, so you say you’re not an actuary, but you did write an article in —

Stephanie Herring: Society of Actuaries.

Ariel Conn: Yes. And I read the article, and I had some questions for you from that. So how do we prepare and build resilience to these events and mitigate their impacts on people and property?

Stephanie Herring: Being very clear that I’m not speaking for NOAA or anything like that, I think that fundamentally — and this is why I am very passionate about the NOAA mission: I think that what we do is we provide that data and provide that scientific basis to make more informed or better informed decisions — I think that a huge part of this is making sure that data and that science has a seat at the decision-making table. There’s lots of different variables that go into any decision a community, a family, or a country is making. And the data and the information is one piece of that, but it’s an important piece. So personally, I feel like it behooves all of us if we not only continue to make sure that we are able to provide the best available data and information about what the world looks like today and what we think it’s going to look like in the future, but that, more broadly, we welcome that information into the decision-making process.

And I would say that for the vast majority of interactions that I’ve had with people in the decision-making space, there’s a huge appetite for this information, to understand, “What is my risk?” and whether that be for a personal decision or whether for a business trying to make economic decisions. I don’t presume to know all the different factors that need to go into any particular decision in any particular sector. But I do believe that any of those decisions will be more informed if they allow the science to have a seat at the decision-making table.

Ariel Conn: I think it was one of the papers that you were working on: I’ve seen lots and lots of graphs showing how hot everything is getting, and the temperature extremes are getting hotter and hotter. And yet, one of the things that struck me most was seeing a graph showing that we really hadn’t had any cold extremes lately. I was wondering if you could talk about what we’re seeing on that end.

Stephanie Herring: That’s a super, super interesting question from a science perspective. What we’ve seen is that — globally — is that there are almost no more regions across the planet that now experience cold extremes. I know you’re not going to be able to use this because it’s a picture, but this basically is a record to date. So you can imagine that — the first record is just the first record. The second one is either your new extreme heat or your new extreme cold. And then what you see starting in the 1920s is that, wow, extreme heat events seem to take over.

And then this is where we’re at today, which is that as a proportion of the surface of the Earth — if you take the Earth and chop it up into grid boxes and look at how many of these grid boxes experienced a cold extreme over the course of any year; This data I think is from a couple of years ago now, 2015. So this year, there was like literally one grid box over the entire planet that experienced a cold extreme, whereas in a stable climate, you would expect 50/50. That’s just not what we’re getting, and it hasn’t been that way for a long time.

So cold extremes are becoming rarer and rarer across the planet, which is what we would expect, but it’s been really interesting, in particular — I don’t know this data globally, but in North America what we’ve really seen is that average daytime temperatures are increasing. What we’re seeing increase faster is average nighttime temperatures. Where you would expect things cool off in the evening, what we’re seeing is that those average nighttime temperatures aren’t cooling off as much as they used to be. There’s definitely geographic variation. If you dive down to any particular location in the US, you will find exceptions to that, but overall, it’s become a trend.

Ariel Conn: When you’re talking about the nighttime temperatures not decreasing, is that because the earth itself is warming? Or is there something else happening?

Stephanie Herring: There’s not a definitive answer to that. There’s still a lot of discussion going on as to what’s driving that. Certainly, we expect there to be fewer cold extremes. We expect nighttime temperatures to rise. Why are they rising faster than daytime temperatures? There’s still scientific conversations around what the drivers are.

Ariel Conn: I have a couple examples here of maybe unexpected problems that occur because of, say, an extreme event — for example, when you have a drought. I think it’s pretty obvious that if there’s a drought, there’s less water for agriculture; That’s a problem. But apparently because there’s less stagnant water for mosquitoes to breed in, the chances increase that they’re going to end up around birds that have West Nile virus because they’re all hanging out at the same limited water supply. And thus, you can see an increase of West Nile virus. And I was wondering what sort of connections you’ve seen that have surprised you?

Stephanie Herring: The climate change and human health aspect is a big one, but would I consider that surprising? Not particularly.

Ariel Conn: Maybe it’s only surprising because I hadn’t thought about it yet.

Stephanie Herring: Well, one that I think was brought to my attention recently that I don’t think I had given consideration to in the past was the impact of compounding events. I was one of the co-authors for the US National Climate Assessment’s Climate Change and Human Health Report, and I coauthored the chapter on extreme events.

And one of the things that came out of that, that I had not given attention to until we brought in some people from the public health community, was actually the compounding cascading events. And that was one of the things they were interested in. They were like, “Yeah, we know it’s going to flood. We know it’s going to have all these different individual events. What happens when they happen back-to-back?” Because they said that’s really when things start to become catastrophic for them from an infrastructure perspective and a health perspective.

And that I thought was fascinating and is not an area that we understand well. If you’re seeing changes in frequency and intensity, are we seeing more, for example, extreme precipitation events or extreme storms followed by extreme heat? Because a lot of times during those extreme precipitation events or other type of extreme storms, they’re losing power. This was one of the examples that was brought up in our report, was power was lost and that in and of itself was bad. But it was a week later, they had a heat wave, and no one had access to air conditioning. This was in the South.

So when you have those kind of back-to-backs, how that’s really when all of a sudden the infrastructure that we rely on — everyone prepares for, “Oh, okay, a flood. Here’s what we’re going to do,” or, “Here’s a particular extreme event. Here’s our emergency plan.” But when those emergency plans are thrown off because another extreme event is following immediately on its heels, that hits this tipping point from an emergency planner perspective that I hadn’t been aware of. Again, one of those things where you’re like, “Yes, of course, that makes sense.”

But again, I define my little event and I look at that and I think about the impacts of that particular event without saying, “Oh, what if there’s another event right on the heels of that or overlapping with that? Then what happens?” And I think that’s an interesting perspective and again, the research I don’t think addresses that very well. So it’s kind of an unknown for us: How are cascading events changing?

Ariel Conn: I think that connects really nicely to the next question I have for you. We’ve been talking about this off and on, but if you were to, say, pick a couple questions that haven’t been answered yet that you really think would be helpful for us to figure out, what would those be? What are the unknowns that you really wish we knew?

Stephanie Herring: I don’t know if I’d want to answer any one particular question, but one of the things that I wish we had was the perfect observational record. I feel like that is foundational to answering so many other questions. Extreme events, by their very nature, are very rare. And so if you don’t have an observational record that can capture enough of them to actually look at, then it’s very difficult to approach this field of research and have a lot of confidence in your results because the events you’re looking at are so rare.

And this is why I think it’s so important to continue to invest in monitoring our Earth system and collecting all this data: is because without it, you can’t understand why perturbations occur. You can’t understand what effect the climate change is having on a variety of different factors. You might not even understand how the climate is changing. And so I wish that we had that, because then I could answer a ton of questions.

Ariel Conn: That’s fair.

Stephanie Herring: So I’m cheating a little bit.

Ariel Conn: No, that’s fair. I think that works. So, a sort of depressing question: We keep hearing about all the things — like, we need to cut global emissions; We need to make all these changes; It’s not happening fast enough. For the most part, we want to be optimistic. But what does happen if we don’t get global emissions cut in time?

Stephanie Herring: So I think part of the reason it’s important to address climate change is because we don’t fully know. We know some of the things that are invariably going to happen. Obviously, the continued rise in global average temperature, Arctic sea ice melt, species migration/ extinction. We know what things are dependent on the factors that we’re able to be aware of, and I think that there’s actually an interesting piece of this in the IPCC report on the 1.5 degrees. So, I think there’s a lot of great research in there about the things that we sort of know about, and the predictions that are in there; And I wouldn’t presume to know more than the authors of that report.

But for me personally, I think what’s a little bit scarier is what we don’t know. There’s so much that, in terms of our predictions from 30 or 40 years ago and looking at the world that we have today, and I think that we’ve seen some of those predictions overshot by reality, so not realizing how fast the planet was going to warm; how quickly we would see some of these changes in extreme events; this idea that climate change was something that was going to impact us in the future. The future is today. It’s happening now. And so what’s the full breadth of those impacts? How different will life be and how different will our world be? We don’t know fully.

We have a lot of research that’s happening and trying to get a handle on that. Like I said, the IPCC has done a good job on this, and I wouldn’t presume to know more than those authors, but I also think that there’s an X factor that I think is maybe even more daunting. I do think it’s important for people to individually remember that even though these seem like very big, daunting problems, I truly do believe that we all have part of the solution in our own hands. And that in terms of preparing for a lot of these changes and extremes that we’re expected to see — a lot of that preparedness, a lot of that resilience, again, people actually have a lot of power to prepare and adapt and make themselves and their communities and their homes and their country more resilient. And so I do think that it’s very actionable information; It doesn’t just need to be this exercise in scientific research — that it’s actually something that people can act on.

Ariel Conn: Okay. And so I think this is probably connected then: what gives you hope?

Stephanie Herring: I think that, in our country, there’s a growing, at least, acceptance of the fact that climate change is real; It is being caused by us. And I think that’s the first step to being able to then take action. I also do think that humans have proven to be, so far anyway, pretty amazing and ingenious in their creativity. And so I’m hopeful that there will be someone or some group or some entity that will find new and creative ways to look at this problem and how to solve it that we’re just not even thinking about today, that there’s other solutions out there that maybe next generation or new technology or new advancements will help us unlock.

Ariel Conn: All right. Well, I think that’s it for me. Is there anything else?

Stephanie Herring: That’s good. Thank you.

Ariel Conn: All right. Thank you.

On the next episode of Not Cool, a climate podcast, we’ll go deeper into the problem of extreme events with Jakob Zscheischler, who looks at what happens when these events occur right on top of each other.

Jakob Zscheischler: For a long time, people have looked at these extremes individually: We have experts on heat waves, experts on droughts. But for impacts, combinations of extremes are particularly harmful. And if we estimate occurrence probabilities from only one type of extreme, then we might underestimate the risk when the heatwave and the drought occur together.

Ariel Conn: If you enjoyed this episode of Not Cool, please take a moment to like it, share it, and leave a good review. And please join our climate conversation on twitter using #NotCool and #ChangeForClimate.

Not Cool Ep 9: Andrew Revkin on climate communication, vulnerability, and information gaps

In her speech at Monday’s UN Climate Action Summit, Greta Thunberg told a roomful of global leaders, “The world is waking up.” Yet the science, as she noted, has been clear for decades. Why has this awakening taken so long, and what can we do now to help it along? On Episode 9 of Not Cool, Ariel is joined by Andy Revkin, acclaimed environmental journalist and founding director of the new Initiative on Communication and Sustainability at Columbia University’s Earth Institute. Andy discusses the information gaps that have left us vulnerable, the difficult conversations we need to be having, and the strategies we should be using to effectively communicate climate science. He also talks about inertia, resilience, and creating a culture that cares about the future. 

Topics discussed include:

  • Inertia in the climate system 
  • The expanding bullseye of vulnerability
  • Managed retreat 
  • Information gaps
  • Climate science literacy levels 
  • Renewable energy in conservative states
  • Infrastructural inertia 
  • Climate science communication strategies
  • Increasing resilience
  • Balancing inconvenient realities with productive messaging 
  • Extreme events 

References discussed include:

Behind the headlines, behind the red/blue, there’s plenty of things to look at that are going in the right direction. And no scientist and no longtime climate journalist like me would say it’s enough; But it’s real. 

~ Andy Revkin

Ariel Conn: Hi everyone and welcome to the 9th episode of Not Cool, a climate podcast. As climate week continues at the United Nations and around the world, I’m thrilled to introduce my next guest, who was one of the earliest people to write about the threat of climate change.

Andrew Revkin is one of America’s most honored and experienced journalists focused on environmental and human sustainability, and he recently became the founding director of the new Initiative on Communication and Sustainability at Columbia University’s Earth Institute.

Prior to that, he spent a year as a strategic adviser at the National Geographic Society, supporting worldwide environmental journalism. He was the senior reporter for climate change at the nonprofit investigative newsroom ProPublica. And he spent 14 years at The New York Times.

He has written acclaimed books on humanity’s weather and climate learning journey, global warming, the changing Arctic and the assault on the Amazon rain forest. In spare moments, he is a performing songwriter.

Andy, thank you so much for joining us.

Andy Revkin: Oh, it’s great to be with you.

Ariel Conn: So you’ve been covering climate issues for quite a while, and I wanted to start with your take on how would you summarize what I think is actually a really big and difficult problem to summarize?

Andy Revkin: Well, I guess it’s been 30, gosh, I hate to say it, 33 years, I think now –– 34. My first climate story was about nuclear winter –– it was like the inverse of global warming –– it was 1984 or ’85, the idea that a nuclear war could throw so much crap into the atmosphere that it would chill the Earth, and we’d all suffer, and ecosystems as well. 1988 was global warming and I’ve been at it in different ways ever since. If you include blog posts and stories, it’s way over 3000, plus three books that touch on this, plus several book chapters on how to communicate about climate. 

I think the summary I would give right now is that there’s actually two enormous climate challenges. And they operate on very different time scales, and they give us a lot to work on that’s actually addressable right now, even though it feels so global and amorphous and monumental. And the two challenges are: we need to decarbonize our energy systems and our food systems –– you know, we need to stop what we’ve been doing unintentionally for 100 years, which is building this pulsive influence on the climate system through emissions of greenhouse gases. But we need to recognize that that won’t have any benefit for decades, none. The system is big and slow moving, and the climate system doesn’t magically notice; Even if Greta Thunberg and Al Gore became President and Vice President of the world starting tomorrow, the climate system might notice that –– assuming they had a global impact on policy –– sometime around 2060.

Ariel Conn: Oh, wow.

Andy Revkin: Yeah. No, inertia: there’s a great 40 second video I did with a couple of MIT wonks two years ago. I asked them, “What’s the thing about global warming that people, even people who are concerned about it, don’t understand? What’s the biggest thing they don’t understand?” John Riley at MIT said, “Inertia.” He basically repeated what I just said.

We’ve got to get busy decarbonizing because through our pulsive growth and development in rich and poor places, and population shifts into zones of danger, we are building what some geographers have called an expanding bullseye of vulnerability and exposure. What that means is the thing that’s changing way fastest that’s driving risk related to climate is where we’re living and how we’re living.

And that’s something you could do something about right away, locally: We can look at your zoning, we can look at building codes and wildfire zones. You can actually make communities fundamentally safer and more resilient to climate stress right now. Those are two very different frontiers. One has immediate impacts –– it’s still hard: Changing zoning and building codes takes time, too, and sustained engagement in your community. But it’s something you can do right now.

And then these more structural challenges. So you have an emissions free energy system, or even eventually something that sucks in more C02, some kind of agricultural or energy system or the like. That’s a great, important, vital thing to be doing now to reduce long term risk, but it doesn’t have any real-time benefits.

Just to make it clear, that means there’s lots to do. That means it’s not to be paralytic, it’s not monumental, and it’s something that everyone can do something about. At Columbia University, where I am now, we just had a big conference called Managed Retreat. What is that, and how does it work, and can we do it? We know one of the most powerful things about climate change that’s so powerfully established is that warmer climates on this planet come with much higher sea levels, period. No debate.

And that means we’re facing sea level rise for centuries to come. And the inertia factor I mentioned means there’s nothing we do with emissions of greenhouse gases that the oceans are going to notice for even more decades, because the oceans have even more momentum and you don’t just magically stop the sea level from rising. That means that communities have to get real with their exposure that’s been built over the last half century in so many places. In America, in China, in Vietnam: any place that’s coastal –– Tacloban in the Philippines, that horrible typhoon that hit in the run-up to the Paris Agreement.

Several thousand people were killed, but the thing that caused the high death toll –– this is an area of the Pacific that gets hammered by typhoons, including extraordinary ones; that one was at the top end of the scale –– but the thing that had changed in the last 40 years was Tacloban, the town: The population had grown four times over. Mostly poor people moving into a city without governance adequate to provide housing and areas that are safe, and so you get crowded, informal development on a floodplain along the coast, and along comes a typhoon, and you have a terrible event.

That’s the vulnerability that we’re building, and rich people are doing the same thing. It’s like the world’s poorest and richest people in cities are building this expanding bullseye. I made it into a hashtag, there’s a hashtag #expandingbullseye, that people can explore. And it’s over and over and over again. It’s even true in places where there’s no evidence that climate change is playing a role in some hazard. Simplest place to look for that is Tornado Alley, where the worst tornadoes, the ones that do the worst damage –– there’s literally no science saying that there’s been a significant change in tornado behavior, in the ones that kill people: F4, F5 tornadoes, for decades; in fact, there’s a slight downward trend. 

But what’s happened in towns like Moore, Oklahoma, which I wrote about a lot, where they had a devastating, high fatality tornado strike in 2013 I think it was: the population had quadrupled in the last half century. People there don’t have basements. There’s no code saying you have to have a basement; There’s no code saying you have to have a safe room. The vulnerability was being built at a high rate. We’re talking about rapid rise in risk through building vulnerable structures, and building a lot of them. That doesn’t have anything to do with climate change. So what does that say? It says if you’re not busy on the vulnerability reduction right now, then you’re just setting yourself up for huge hits in the future.

Ariel Conn: Does it seem possible to address the vulnerabilities in ways that don’t then contribute more to the carbon in the atmosphere? Because it seems like if we have to build new structures and safer zones, or if we have to move people, that that’s going to contribute. Or, are there other solutions?

Andy Revkin: The managed retreat I mentioned, related to sea level rise, is something that has to happen, period. Or it can be unmanaged retreat, that’s fine, too; That’s what we call refugees or climate migrants. There’s not a lot of refugees that you can link to climate change. There are people moving, absolutely, related to coastal vulnerability, flood zones. People move. The carbon impacts of that are pretty marginal because people are always moving, cities are always changing.

I don’t think there’s a way to think about that that doesn’t involve some emissions building houses somewhere else. But what can happen, and actually is happening in many places, is you can improve coastal resilience by planting mangroves, for example. Mangroves are like this win, win, win thing. They give you more surge vulnerability for sure, along the coast; They definitely sequester carbon –– in fact, I think there’s some evidence they do a better job of it than terrestrial force; And they’re a biological resource –– they’re a haven for biodiversity. So actually there’s another hashtag, #mangrovesmatter. You’ll see some really cool stuff about that, too. My students at Pace University, when I was there a number of years ago, we did a film on coral conservation and the Caribbean, and one of the lessons there is planting mangroves is also good for reefs, because the fish that tend the coral reefs, I think it’s something like half of the fish species on reefs start out in mangroves. Look for the win, win, win, win, win, win, wins, and that can make up for a little bit of a loss here and there by moving people in one direction or another.

Ariel Conn: Okay. You’ve just started at Columbia and they had an announcement about your new role, and one of the quotes was, “We want to tackle specific climate and sustainability challenges where the impediment to progress is an information gap, a paralyzed conversation, or a missing connection between disciplines or sectors of society.” I want to go into that quote a little bit and talk about what examples are of each of those things. What would you say are some examples of the information gap that we have to address?

Andy Revkin: The lack of information, you can see that everywhere around the world. The worst gaps are of course in developing countries, poor places, or communities here as well. You don’t have the internet, you don’t have access to information. Those are fundamental gaps that give outsized advantage to people who are wealthier and more linked in. But some specifics are, here in the Hudson River Valley where I live, through a lot of hard work and innovative policy and some technological advances, you can have your community become a wholesale buyer of renewable energy.

So you’re not individual homeowners anymore just paying a bill. This community choice aggregation option, CCA, is spreading pretty rapidly. But it could spread a lot quicker. People just don’t know how to do it. They don’t know, how do we make our town one of the ones that can be part of this process? If you’re not even aware that it’s an option, if you don’t have a local newspaper anymore that’s looking at things like energy choice, then you’re not going to have that information.

Those are the information gaps. And in India, there’s 120 million farming families in India –– that’s families, not individuals. And one of the great achievements in North American farming history was extension service: Cornell and other land grant colleges who provide advice to farmers. But how do you do that in India? How do you plant a more resilient crop?

There’s an organization called Digital Green that has built sort of a YouTube network where some facilitators go into villages, they talk with farmers who’ve taken on a better practice using water more carefully, or trying a new seed variety. And the farmers create these little videos in the dozens of local languages that you have around India, so that it’s a farmer telling another farmer, “You might want to try this.” That’s kind of the problem and the solution all in one. The problem is that there’s too many farmers. The solution is help create a network.

Broken conversations I see all the time. When I was doing my blog at Dot Earth, my New York Times blog which I started in 2007 while I was still a reporter there, half of the time I was mediating these brittle arguments between people who are, “Hell no fracking” and people like me who think you could have fracking happen in a responsible way, and natural gas is better than coal in many circumstances, and there’s a lot of it, and we need energy in the northeast to heat and cool our homes.

You can have legitimate debates about a lot of these things, but they end up getting stuck in these yes/no positions. And what I started doing was digging in more to this other big body of science, not just climate science and energy emissions science and the like, but social science. How do mediators do their job? What is a mediated conversation as opposed to a yelling debate on social media? There is a science to that. Some of it’s peer reviewed science, actually. At Columbia, there’s an initiative, there’s a guy who I just met at Columbia university, Peter Coleman, who runs what he calls the Difficult Conversations Laboratory. How many difficult conversations do you know of that happened in this arena? GMOs versus organic; what’s the role of nuclear power; no nukes, yes nukes. What I’m looking for is some nukes. That’s a hashtag, too: #somenukes. 

And then more fundamentally, the behavioral science that I started to learn way too late in my reporting journey: peer reviewed work also shows that science literacy is not an indicator of consensus. It’s not like if you made a large population literate in climate science –– that doesn’t automatically shift the argument towards solutions. In fact, there’s demonstrable work by this group at Yale –– they invented a name for the field, it’s cultural cognition, and there’s a website, –– they’ve shown that more literacy in science, you see it most frequently at the two ends of the dispute over climate change: So people who are most dismissive of the message about climate concern and the people who are most worried have similar levels of climate science literacy.

Ariel Conn: That’s interesting.

Andy Revkin: It’s more than interesting. As a journalist, when I started diving into that work around 2006 through 2009, it was kind of an existential thing. What do you look for as a journalist? You’re a reporter, writer, because you want to identify a problem and energize people towards solutions, whether it’s gun violence or climate change. And it turns out that on issues –– especially ones like climate change and gun violence that have become polarizing –– that more information doesn’t change anything. You look at that and you go, “Oh crap.” 

This issue with broken conversations to me is significantly about broken perceptions. Meaning, if you’re trying to change the world and decarbonize the energy system in service of creating a safer climate, and you go to Woodward County, Oklahoma, and you come in saying, “Hey, everybody here. You have to agree there’s a climate emergency or climate crisis so we can get busy solving global warming,” you’re actually making your job harder than you would be if you went in after getting more understanding of the people who live there. There was a great revelation of this in 2015 when John Sutter, a CNN reporter at the time, went to Woodward County, Oklahoma, as part of a big two degrees project he was doing around the world.

He went there because Yale University and partners had identified Woodward County, Oklahoma, as ground zero for climate disbelief. So he went there and he started interviewing people, and there’s a great summary of the interview, like a three minute video clip on YouTube. The Yale survey also showed that in Woodward County, Oklahoma, people actually are really supportive of renewable energy. Some other part of their brain, some other part of their soul, some other part of their heart likes to be independent, and have the capacity to generate their own energy rather than pay someone for it.

So he went in there –– and this is this weird phenomenon: he interviews a guy who’s got a pressed blue shirt and a nice conservative tie, and he says, “You know, God controls the environment,” and for me, as a progressive coastal person, listening to that, my hair’s starting to prickle. But then a minute later, he’s talking about energy; he says, “We have half of our roof covered with solar panels and we want to do the rest, and get off the grid entirely.”

And John Sutter visited him at his house and sure enough, he had more panels and he was going to do this. When I show this to audiences, I say, “Knowing what you know about this guy, would you run into that town going, ‘Climate emergency, climate emergency,’ expecting to build consensus, or would you go into that town saying, ‘Hey yeah, that’s cool. You’ve got solar panels. What’s up? Maybe we could talk about ways that more people could get that capacity.'”

The moral of the story is that telling your story is often a disservice to the bigger question –– that listening is job one, and then you can engage ideally over time and build a constructive conversation about renewable energy standards or the like, and certainly