In this week’s episode, host Daniel Raimi talks with Lara Aleluia Reis, a scientist at our sister institution, the RFF-CMCC European Institute on Economics and the Environment. Reis and her coauthors have recently released a new study in Lancet Planetary Health about the connection between air pollution and climate change. The study explores how policymakers can most effectively accomplish two important goals at the same time: reducing air pollution, which contributes to millions of deaths per year, and achieving our long-term objectives in mitigating climate change.
Listen to the Podcast
- Health impacts of air pollution: “What we find is that we could save, by 2050, around 1.6 million people just by incorporating air pollution impacts into the decision. This is about three times more than simply the co-benefits of air pollution.” ―(11:50)
- Reducing air pollution benefits regions differently: “All the regions benefit—both in terms of avoided air pollution (absolute numbers) and in terms of economic benefits. All regions improve their welfare when we include the air pollution impact into the decision. This is robust across all the policies we’ve seen … But when it comes to the economic value—so, when we look not only at the absolute number of avoided premature mortality, but also at the value that we give to improved health—there’s another region that pops out, which is the region of the Middle East and North Africa … if we take into account air pollution damages, the Middle East and North Africa should for sure be pushing for these kinds of policies.” ―(14:00)
- Focus on technologies that maximize co-benefits: “We should be implementing the best available technologies and practices to reduce air pollution. We’ve seen from the results of this paper that this can avoid a lot of economic impacts and a lot of mortality. The other thing is that I think there’s a policy message here: policymakers should be targeting technologies that maximize co-benefits.” —(20:25)
Top of the Stack
- “Internalising Health-Economic Impacts of Air Pollution into Climate Policy: a Global Modelling Study” by Lara Aleluia, Laurent Drouet, and Massimo Tavoni
- The Invisible Killer: The Rising Global Threat of Air Pollution—and How We Can Fight Back by Gary Fuller
- PurpleAir, a personal monitor for real-time air quality assessments
The Full Transcript
Daniel Raimi: Hello, and welcome to Resources Radio, a weekly podcast from Resources for the Future (RFF). I'm your host, Daniel Raimi. Today, we talk with Dr. Lara Aleluia Reis, scientist at RFF’s sister institution, the European Institute on Economics and the Environment. Lara and two coauthors have just released a new study in Lancet Planetary Health on the connection between air pollution and climate change. Specifically, the study shows how policymakers can most effectively accomplish two goals at the same time: reducing the air pollution that contributes to millions of deaths per year, and achieving our long-term goals on climate change. It's a fascinating piece of work, so stay with us.
Okay, Lara Aleluia Reis from CMCC, EIEE, RFF, our sister organization based in Milan, Italy. Thank you so much for joining us today on Resources Radio.
Lara Aleluia Reis: Thanks for the invitation. I'm happy to be here.
Daniel Raimi: We're happy to have you. And Lara, we're going to talk about a new study that you have co-authored with a couple of colleagues, Laurent Drouet and Massimo Tavoni, whose names I have probably mispronounced horribly, and for which I apologize. The new study is called, “Internalising Health-Economic Impacts of Air Pollution into Climate Policy: a Global Modelling Study,” and it's out in the journal Lancet Planetary Health. We're going to dig into that paper today, but we always start by asking our guests how they got interested in working in environmental issues, either as a kid or later in life. So, what drew you into this field?
Lara Aleluia Reis: I think I've been always interested in environmental issues, ever since I remember, basically. I think family probably plays a role in there, but I was also at school during the '90s, when all these problems started. There were people talking about the ozone layer and global warming. And I was actually in the nature club at the school. We were out saving nests of birds. And so it was always some, I don't know, for me, environmental heroes were always the coolest, and for me it was always something that was out there. So, when I decided to join the environmental engineering course in the new University of Lisbon, there was a branch on urban planning and I thought, "That's what I'm going to do, because I get to be a little bit outdoors, and it's going to be fun. And it's creative, and it has to do with the environment."
But when the time came that I had that course, I actually hated it. It was all about legislation—you can't do this, and you can't build here, and you have to do that. And so I really hated it, but at the time, I was having this other course on environmental statistics, and a lot of it was data applied to air pollution. I really liked it, and I thought, "Okay, that's what I'm going to do." I had it all figured out by then. I thought, “I still get to be outdoors. I'm going to send out balloons in the atmosphere and get to read vertical profiles, and this is going to be fun.” Well, that didn't work out either.
I started being more and more interested in modeling—so much for the outdoors spending time. And now I just spend all my time behind the computer, doing environmental research. But I actually don't regret it. I like it a lot.
Daniel Raimi: That's great. Well, at least maybe you can take your laptop outside sometimes and work outdoors.
Lara Aleluia Reis: Exactly.
Daniel Raimi: As I mentioned at the outset, you and two coauthors are out with this new study. It's focused on air pollution and climate change, and it's a really fascinating and complex piece of work. We've talked a lot on the show about climate change and air pollution, including recently with another excellent Portuguese researcher Inês Azevedo. But can you tell us how this new analysis differs from some others? Particularly ones that focus on climate change and which typically consider air pollution mitigation as what's called a “co-benefit” to climate. How does this analysis differ from many of those previous pieces?
Lara Aleluia Reis: You're right. Most of the studies out there, they look at climate policy and then kind of, as a post-processing step, a step afterwards, they assess the co-benefits. Actually, not just about air pollution—many other types of co-benefits. There's many great studies out there.
But in this case, what we do is, instead of assessing the co-benefits, we integrate the air pollution impacts into the decision. In a way, if you like, instead of assessing co-benefits, we are optimizing co-benefits. What happens is that when you integrate the air pollution damages into your decision, you have to achieve the climate goals at the same time as you're trying to avoid these damages. So, the policymaker will choose technologies that have synergies between these two goals. So, in a way, the co-benefits are optimized, if you will.
So, let's think for example about the case of biomass. If you think only from a perspective of climate change, biomass is a very helpful and viable technology, but it may create air pollution damages. What we are trying to do here is to take both into account and counterbalance all these trade-offs between both objectives. When you do that, by incorporating this in the decision, the policymaker will have all this information, and you'll be able to act on it.
The other thing that is innovative in this study—at least at the global scale, not at the local scale, which has been done, but at a global scale including climate change—is that we include in the study the opportunity for the policymaker to use end-of-pipe measures. End-of-pipe measures are, say, technology that is put in the end of the production line that only prevents pollution—say, gas and particulate matter (PM)—to go out into the atmosphere.
So, it's not changing fuels, it's not changing technologies, it's not doing anything for climate change, but it's indeed avoiding the impacts of air pollution. So, it's called end of pipe. It's something that you put at the end, and these technologies are much cheaper than changing the energy structure of the system. So, in this study, the policymaker will try to maximize the welfare of its region at the same time that he's balancing these two objectives and has these two possibilities when it comes to air pollution mitigation.
Daniel Raimi: That's great—a really interesting way to approach the problem and really centering this issue of air pollution right alongside the climate change problem.
The methods that you carry out with the authors in the study are complex, and they're multi-layered. We don't have time to get into all of them, of course, but can you sketch out for us a brief overview of how you methodologically carried out the analysis?
Lara Aleluia Reis: Let me try: We have three models here. One, we have a main model, which is the model where all the decisions are made. The policymaker, as I said, is trying to maximize the welfare of his region. And in this model, there's a representation of the energy systems—energy and production and industrial activities: they emit. They emit air pollutants and greenhouse gases. So, what we do is we add a little model—an air pollution model that takes these emissions and calculates concentrations. From the concentrations, we can calculate mortality due to air pollution. And then these mortality numbers are given an economic value that is then given back to the main model—the model where the decisions are made. So now, the policymaker knows that polluting will cost him lives that have an economic value. So, we will be forced to act on it.
So, as I said, he can act on it by changing the energy system, which are generally more costly measures, or by introducing end-of-pipe controls. The other thing we do is to add yet another little model—these are all reduced models—that calculates climate. And this takes into account not only the greenhouse gases, but also the air-pollutant gases, and it calculates temperature at the end of the century. So, when I have a climate target—a temperature climate target—I need to take into account also the aerosols, because aerosols also account for radiative forcing. So, in order to have all that incorporated, we include these two other models that kind of speak to the policymaker the model that makes the decision. And so the policymaker will have all this information, both on climate and air pollution, and he will be able to maximize his welfare based on all this information while achieving the climate goals.
Daniel Raimi: Right, that makes sense. And just one follow-up question on the health analysis: You include mortality effects, which are deaths, essentially. Do you also include morbidity, which is things like illness and people missing work and things like that?
Lara Aleluia Reis: Yes, that's a good question. In this study, we don't. The way we account for that is that we do a lot of sensitivity on the way we value health, improved health, and the way we estimate this value of health. So, directly, we don't have this, but our sensitivity kind of accounts for the variations that morbidity and productivity loss could make to the decision.
Daniel Raimi: Right; great. Okay, thank you for that.
So, let's get into some of the high-level results now. And of course, I'd encourage people who really want to dig into the methods to read the paper, which again is called, “Internalising Health-Economic Impacts of Air Pollution into Climate Policy: a Global Modelling Study,” and we'll have a link to it in the show notes. So, what are some of the emissions scenarios that you modeled, and what are some of the key results under those different scenarios?
Lara Aleluia Reis: We did a lot of investment in the number of scenarios we modeled in this paper. The reason for this is that we have two goals, and they are influenced by many, many aspects. Of course, we cannot control a new sensitivity on all the aspects, but we wanted to include the main drivers.
We have five baselines. These are called the socioeconomic shared pathways, the SSPs, and these are baselines that differ in their socioeconomic drivers, such as population and GDP. Most importantly for this study, they assume different baselines on air pollution emissions. So, we will see for each SSP a different baseline of pollution. That's why it is important for us to kind of spam all these possible futures of baseline air pollution, so that we know that our results are robust across all these assumptions.
On top of that, we study two climate targets: So, a global average increase of 1.2 degrees by the end of the century. And the well-below-two-degrees here in the study modeled by the 1.5-degree temperature targets.
On top of that, we model a delayed-action scenario. So, what happens if we delay climate policy a little bit—like, by 10 years or 20 years—what happens, and what is the value of including the air pollution impacts in the decision when we delay the climate action? And we also model a lot of ways in which we could value the improved air pollution—ways in which one region values their own health improvements.
What we find is that we could save, by 2050, around 1.6 million people just by incorporating air pollution impacts into the decision. This is about three times more than simply the co-benefits of air pollution.
And this is robust across all our end-of-line baseline assumptions. We find also when we look at our delayed-action scenario, if we delay climate policy, that it is really important to include air pollution impacts into the decision. Because if we are not decarbonizing already in the first decade, then there's really a lot of lives that could be avoided. And then it becomes really important to include health, as I’ve mentioned, in the decision. There's a lot of debate in the literature on how we should include and value improved health. We did a lot of sensitivity on this value; it indeed changes the global avoided mortality, but we find that the sensitivity of changing this value on how we value life is less important than, for example, the variation that we found in changing socioeconomic parameters such as GDP, or even what we assume as already deployed air pollution controls.
Daniel Raimi: That's really interesting. And for those who are following along at home with the paper, Figure 2 has some really nice illustrations of those ranges that you're talking about, based on the different sensitivities.
And just one clarifying question: You said 1.6 million deaths by 2050, I think. Is that an annual figure, 1.6 million per year?
Lara Aleluia Reis: Yes. In that year or around that year, we find that estimation, yes.
Daniel Raimi: Right, great. So can you talk now a little bit about the geographic distribution of the benefits—these air quality benefits—how they're distributed around the world, which regions benefit the most, which benefit the least? And how does that look on the map?
Lara Aleluia Reis: Thank you for that question. Actually, first of all, all the regions benefit—both in terms of avoided air pollution (absolute numbers) as well as in terms of economic benefits. All regions improve their welfare when we include the air pollution impact into the decision. This is robust across all the policies we've seen. We have regions in terms of absolute numbers—such as China and the reforming economies in India that see most of them—big numbers in terms of avoided air pollution.
But when it comes to the economic value—so, when we look not only at the absolute number of avoided premature mortality, but also at the value that we give to improved health—there's another region that pops out, which is the region of the Middle East and North Africa. And this region typically objects to, or has many—say, puts many barriers to climate policy. But what we find here is that this region actually has a lot of interest in reducing, in engaging in this type of climate [decisionmaking]. So, if we take into account air pollution damages, the Middle East and North Africa should for sure be pushing for these kinds of policies.
Daniel Raimi: Wow, that's really interesting. And a couple just quick follow-up questions: The first, you said reforming economies, I think, earlier. Are those like former SSR [Soviet Socialist Republic] nations?
Lara Aleluia Reis: Exactly.
Daniel Raimi: Yeah, I imagine that's a term that's maybe used widely in Europe, but not so often here in the United States.
And then, maybe digging a little bit more deeply into the North Africa and Middle East region: Can you talk a little bit about what the drivers of those health damages would be? I know they use a lot of oil and petroleum products for power generation in that part of the world. Is that one of the major drivers of air pollution?
Lara Aleluia Reis: Yes, for sure. I didn't look specifically at what technology switches were happening there, but that's for sure a region where there's a lot of extraction of oil. And because of their VSL value—that is the “value of a statistical life”—the value that you give to improved health due to air pollution is not very small. Just by acting and saving a few lives, they would see a lot of economic benefits.
Daniel Raimi: I see. That's interesting because it's a relatively high-income region—at least for some of those nations.
Lara Aleluia Reis: Yes, medium region.
Daniel Raimi: Right, great. So, let's ask sort of a policy question now, which is: Sometimes, when decisionmakers are trying to solve one problem, they might accidentally exacerbate another. This is the law of unintended consequences. So, I'm wondering how that applies to this analysis. If we optimize for air pollution, does that mean we're sort of losing benefits related to climate change mitigation, or does it go the other way? So, are there trade-offs here that we need to be thinking about?
Lara Aleluia Reis: Yes; indeed there are. I mean, it's known in the literature there are aerosols with reflecting properties. They cool the Earth. Particulate matter, which is an air pollutant, PM—they are aerosols. When you are tackling the air pollution problem, you provoke a little bit of warming. That means in order to reach that temperature target, you have to decarbonize a little bit more. But our methodology, as I explained before, takes into account this feedback by our climate model. So, even by taking [feedback] into account, our results show that you should act on air pollution. What I'm trying to say here is that by no means air pollution jeopardizes the fight of climate change. What we find is actually the reverse: it's like even despite this trade-off, we should still be tackling air pollution at the same time that we are achieving the climate targets.
On another note, what we also find is that most of these end-of-pipe technologies that I explained—these are technologies that are used to remove air pollution, but do not remove greenhouse gases—they are deployed at the beginning of the century. When the transition is still ongoing, there's not yet a lot of the carbonization done. So, in order to help the air, we could deploy this technology. And these are in the early years of the century.
Because air pollutants are short lived, these reductions that we see at the beginning of the century won't affect the temperature much in 2100, when our climate targets are. So, our framework takes into account this intertemporal interaction and allows for saving a lot of lives now at the beginning of the century, which won't jeopardize so much the climate target at the end of the century, because these are short-lived gases. And this is something that we find that is also important. So, indeed, there is a little bit of extra effort on decarbonization, but this won't by any means jeopardize the fight against climate change. This impact is little.
Daniel Raimi: That's really interesting. And, just so I have a little bit of intuition about these end-of-pipe technologies, would one example be like scrubbers on a coal-fired power plant that reduce air pollutants, but don't necessarily reduce greenhouse gases?
Lara Aleluia Reis: Exactly. Scrubbers, electrostatic precipitators, filters—all these types of technologies that are easier and cheaper, generally speaking, to deploy. They won't switch any fuel. They won't switch to less-carbon-intensive technologies. But they will help us prevent the impacts of air pollution.
Daniel Raimi: Right, great. And these are technologies that are largely deployed in the United States and many parts of Europe, but less so around the world. Is that right?
Lara Aleluia Reis: Exactly. That's exactly the case.
Daniel Raimi: So this next question is a really hard one, because there's so much variation in policies around the world, both with regard to climate change and with regard to air pollution. And there's so much variation in the fuel mix, as we've been talking about. So, I recognize that this is a tough question to ask, but when you step back and think broadly about this paper and what it might tell us, what are some of the key lessons for policymakers that you think emerge?
Lara Aleluia Reis: Yeah, that's indeed a tough question. But I think what comes up right away is that we should be deploying this end-of-pipe technology, and we should be deploying it all over the world as fast as we can. We should be implementing the best available technologies and practices to reduce air pollution.
We've seen from the results of this paper that this can avoid a lot of economic impacts and a lot of mortality. The other thing is that I think there's a policy message here: policymakers should be targeting technologies that maximize co-benefits. If we think back on the example I gave about biomass, if we only look at one objective, we might be creating other problems. Here, again, I think this paper emphasizes the role of maximizing co-benefits in choosing technologies that actually have co-benefits.
The other thing I think is quite clear from this paper—and I hope it'll stick out in the policymaking—is that, generally, we should be integrating how the health dimension in the policy design proves to be important. And I think, if anything, this pandemic has shown us that this is so much the case.
Then, of course, there's many, many things that could be done that we do not tackle in our paper. Even easy things, like improving air-quality information and awareness, where this will help people not to mitigate so much, but actually to avoid exposure, which will ultimately avoid death and productivity loss, and all these kinds of things, among many other things that could be done.
Daniel Raimi: Yeah, that's really interesting. What are some of the mechanisms you have in mind for sharing better information about air quality? Here in the United States, we have air-quality alerts that are sometimes issued by governments. We actually did an episode recently with a researcher named Eric Zou, who found that local governments sometimes strategically report air quality for complicated policy reasons. But I'm just curious what you had in mind for some mechanisms that can inform the public about air pollution risk?
Lara Aleluia Reis: That's a good question. I'm not an expert, but I think citizen science has a role here. We see, all over the world, big projects and efforts by using these low-cost sensors that everybody would carry around or have in their home to measure air pollution themselves. And this, for me, plays a big role. It has a big role in putting out some of the problems that might be there in reporting—also because the instruments that I use for official reporting are very expensive. They cost a lot of money. They need to be constantly calibrated and so on. So, it's kind of impossible to have a wide network and agreed-upon data on this. Satellites have helped a lot. And I think the citizen science on monitoring devices and low-cost sensors could really help with this and are a big, big step into lowering exposure to air pollution.
Daniel Raimi: Yeah, that's a great idea. And it makes me think of this network that I'm a part of. I have one of these sensors at my house—the PurpleAir network. If people are curious, check out purpleair.com, and you can see particulate matter exposure not just in the United States, but also in Canada and in Europe. There's a pretty extensive network of these sensors all around.
One more question, Lara, before we go to our Top of the Stack segment—and this is a wonky one, so hoping you can maybe get into some weeds here. Can you tell us a little bit more about how you estimate the health impacts in the analysis? So, can you take us under the hood a little bit and help us understand how climate change might either directly or indirectly affect people's health with regard to heat exposure and cold exposure? And then, how does air pollution affect people's health in your model—either directly or indirectly?
Lara Aleluia Reis: All right. Just to clarify, I don't directly calculate climate damages in this study. By achieving the temperature targets, we assume we are doing that already in order to avoid major damages. So, damages will still exist, but we do this to avoid major damages. And then, of course, climate policies will have a role in the damages here, as well, because as you're investing in decarbonizing your economy, you're also using cleaner technology. And while you are using cleaner technology, you need less extra end-of-pipe, and you have less costs from air pollution damages. So, the policy maker will say, "Okay, I'm decarbonizing. But I'm achieving this goal, but I'm also contributing to the other goal, and this is an important thing." The way we specifically model, or take into account the economic impacts of air pollution, is through something called a VSL—the value of a statistical life, which is a value that gives us an idea of how we value improved air pollution.
So, we have to meet the energy demand of this region. There are these economic and industrial and energy activities that emit both greenhouse gases and air pollutants. Emissions are then used to calculate concentrations. Concentrations are then mapped out—mapped with population—because if you have high concentrations where no people live, you won't have an impact. So, it is important to map both together to get exposure. From exposure, we have an impact function that gives us how many people died due to this exposure. And then this number of people—the premature modality—is given an economic value that goes into the model. So the decisionmaker will know, "Okay, it costs me," and will try to avoid these damages. This is how the damages are calculated.
Of course, it can then invest in end-of-pipe, which won't help this other objective, but it can also invest in accelerating the decarbonization, which will help both objectives.
I have to say here, also, that the VSL—the value of a statistical life—is extrapolated across the world. We don't assume that every region values improved health due to improved air pollution the same way. And this is actually, for me, a very good point of future research: How do we know this? How do we know, and how do we extrapolate these values? How do we know how each region currently values the improvements in health, but also will value in the future these improvements? So, for me, this extrapolation both in time and space of this value of a statistical life is a very important topic. We did sensitivity on that. Our results seem to show that, at the global level, it doesn't change much—but at regional level, I'm sure this will change a lot.
Daniel Raimi: Yeah, that's such an interesting topic. And it gets so deep, morally, really quickly—right?
Lara Aleluia Reis: Exactly.
Daniel Raimi: When we think about the value of a statistical life being different in one country relative to another, that's totally something we should explore on the show. And I'd love to have you back to talk about that in the future, if you're up for it.
Lara Aleluia Reis: We'll have a paper on that.
Daniel Raimi: Oh, cool.
Lara Aleluia Reis: Very soon. Let's hope.
Daniel Raimi: Yeah, fingers crossed.
Well, Lara Aleluia Reis, thank you again so much for coming onto the show and telling us about this really fascinating work. It's interesting to learn about.
And now let's ask you the last question that we ask all of our guests, which is to recommend something that you've read or watched or heard. It can be related to the environment, or even just tangentially related to the environment, that you think is really great. So, Lara, what's at the top of your literal or metaphorical reading stack?
Lara Aleluia Reis: I would recommend the book called The Invisible Killer. It's by Gary Fuller, and it's about air pollution, and it's about the history of air pollution. And for us, now, it's so direct that smoke is bad and that it provokes premature death. But at the time, it was really—I mean, in order to arrive here, it took a lot of time and a lot of effort. And the author kind of guides us through this process of recognizing that air pollution is a problem and that affects our lives. And so, there's a little bit of history of air pollution there. I think it's a very easy book to read. I would advise that—The Invisible Killer.
Daniel Raimi: Great, that sounds fascinating. Thank you for the recommendation. I’ve got to check that out. Well, one more time, Lara Aleluia Reis, thank you so much for joining us today on Resources Radio. We really appreciate it.
Lara Aleluia Reis: Thank you.
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RFF is an independent nonprofit research institution in Washington, DC. Our mission is to improve environmental energy and natural resource decisions through impartial economic research and policy engagement. The views expressed on this podcast are solely those of the podcast guests, and may differ from those of RFF experts, its officers or its directors. RFF does not take positions on specific legislative proposals. Resources Radio is produced by Elizabeth Wason with music by me, Daniel Raimi. Join us next week for another episode.