Sensing Pollution with Satellites, with Alan Krupnick and Daniel Sullivan

References and recommendations

• Using Satellite Data to Fill the Gaps in the US Air Pollution Monitoring Network by Daniel Sullivan and Alan Krupnick

Full Transcript

Daniel Raimi: Hello and welcome to Resources Radio, a weekly podcast from Resources for the Future. I'm your host, Daniel Raimi. This week, we talk with Alan Krupnick (a senior fellow) and Daniel Sullivan (a fellow) at RFF. I'll talk to Alan and Dan about their recent study using satellite data to better measure air pollution in the United States. I'll ask them about what their new study finds, what the implications are for public health, and how policymakers might respond. Stay with us.

Okay, Dan Sullivan and Alan Krupnick—my friends and colleagues, thank you so much for joining us today on Resources Radio.

Alan Krupnick: Happy to be here.

Daniel Raimi: Great. So, today we're going to talk a little bit about a recent paper that you two coauthored. It's an RFF working paper published in September 2018 called, "Using Satellite Data to Fill the Gaps in the US Air Pollution Monitoring Network." We're going to get into that in just a minute—but, first, so listeners know where you're coming from, can you each tell us just briefly how you got interested in energy and the environment in the first place?

Alan Krupnick : Well, of course, I'm pretty old at this point. So, I got into it when I was in graduate school at the University of Maryland and the environmental economics revolution was just beginning. And this seemed like a great area for me, thinking about pollution and its effect on health and the environment. It was really the early days of the environmental movement and the early days of economists working in the environment. So, I've been interested in it for almost 40 years now.

Daniel Sullivan: So, I actually have a similar story, where I was in grad school at Harvard, and I was actually doing more urban labor economics. I came across some interesting problems of, you know, using house values to measure how people value clean air and other environmental amenities—and I just kind of went down a rabbit hole of a lot of interesting topics and questions of how do we measure air pollution? What are the particular spatial data problems inherent to this field? And, actually, that has led right to this research we're going to talk about today.

Daniel Raimi: That's great. So, let's get into it. The paper that we're going to talk about uses satellite data, (as the title tells us) and it's part of something called the VALUABLES Consortium. Can you tell us briefly about the VALUABLES Consortium and how this paper and the techniques you're using sort of fit into that network?

Alan Krupnick: NASA(the National Aeronautics and Space Administration), was interested in showing the world really how valuable its research is and its satellites are. So, we have a big project with NASA to work with scientists at NASA to help them show how valuable the information is that they generate through satellites and other programs. Our project fits right into that because we're using NASA satellites to do this work.

Daniel Raimi: The value of information problem is really tricky because it's—how does access to this information change policymakers? How they approach problems, the decisions they make, the options they face? You know, what's the value of improving the resolution of surface temperature from 10 meters to 5 meters? That's a tricky question and so that's why they've brought us on board, to try to put some structure to that question.

Daniel Raimi: So, this kind of research can help policymakers decide how much is it worth investing in certain new satellite technologies, or how much should we spend to improve our existing capabilities measuring the potential benefits that we could experience on Earth from those investments. Is that right?

Daniel Sullivan: Exactly. So, you know, launching a new satellite that's measuring something we haven't measured before—it's going to have a huge benefit, launching a whole new satellite with a new instrument to slightly improve something we already have. We can put numbers on that and it may pass cost–benefit.

Daniel Raimi: Right. Okay. Yeah, that makes sense. So, a couple of terms that are crucial for the paper that I want us to define so that we all know what we're talking about—so, national ambient air quality standards. We'll probably call those NAAQS as we go through our conversation. Can you [...] either of you guys just tell us, you know, what are NAAQS? How do they fit into the Clean Air Act and how are they measured in different parts of the United States?

Alan Krupnick: Sure. So, the Clean Air Act mandates that the US EPA [Environmental Protection Agency] set ambient air quality standards for a variety of pollutants. One of them is fine particles with a diameter of 2.5 microns or less.

Daniel Sullivan: Right. And that's the “PM 2.5” that we'll be referring to.

Alan Krupnick: Yeah, that's PM 2.5. And then those standards are supposed to be protective of health with a margin of safety. So, this has been going on since the Clean Air Act was passed in around 1970. The standards are revised periodically—all the health literature is closely looked at and then there's a decision made by the administrator at EPA on what the new standards should be (and that's subject to public comment, and so on, the way any regulation is). So, these concentrations of PM 2.5 are measured throughout the country according to a set of rules and they're measured by ground-based monitors. And there's a set of rules about where, in general, those monitors should be located. The states are supposed to follow those rules and put monitors in where they think there are problems like high air pollution levels. And then that data is processed and if an area is found to have concentrations that exceed the standard, then that area is designated as being in “nonattainment”—as violating. The term of art is “not-attainment,” [as] in nonattainment of the ambient air quality standard for that particular pollutant.

And if their concentrations are below that standard, then they're termed as being “in attainment” of the National Ambient Air Quality Standard. Then if you're in [...] I guess there's one more piece. If you're in nonattainment of the standard, then you're subject to regulations and requirements that you get into attainment with a standard over a period of time. So, you have pollution control requirements to try to get you into attainment.

Daniel Raimi: Right, so we have these monitors around the country, they're measuring various things in the air. PM 2.5 is what will be focused on in our conversation today (even though, there are monitors for other pollutants as well). Just really quickly—what are some of the main sources of PM 2.5? And what are some of the health impacts that it has at various concentrations?

Alan Krupnick: So, PM 2.5 is primarily what's called a “secondary” pollutant. There is some direct pollution from PM 2.5, let's say from diesel engines in cars, or motors in the industry, and so on. These are very fine particulates that are emitted directly into the air. But most PM 2.5 is a combination of nitrogen dioxide or nitrogen oxides and sulfur oxides in combination with, actually, ammonia that's in the air. And so these react to create a weak sulfuric acid and a weak nitric acid and those are called aerosols, and they're in the air. When those aerosols are breathed in, they affect health, they affect the functioning of the lungs. And statistical analyses that relate the concentrations of PM 2.5 in the air with the health of the population experiencing those levels of PM 2.5 show that there are pretty significant effects of PM 2.5 on health—and, in fact, high concentrations of PM 2.5 can lead to premature death. This is the biggest, most worrisome effect of PM 2.5, obviously, and that's why we focused on this pollutant.

Daniel Sullivan: Yeah, and I want to reiterate that we're still even finding out more and more direct health effects from PM 2.5. So, there's recent research out of Arizona State University that finds, pretty convincingly, that a significant portion of Alzheimer's and dementia cases in the United States are explained by PM 2.5. And the biological mechanism through which that happens is [...] so, 2.5 microns is really, really small. It's much smaller than the width of a human hair. And when you breathe this stuff in through your nose, it actually travels through the olfactory nerve in your nose straight into your brain and gets lodged there. So, this is an organic material, think of it as just gunk. And then your immune system tries to attack it because it's this foreign substance in your brain and it ends up creating lesions in your brain because your immune system attacks the stuff, can't kill it. It just keeps throwing, you know, white blood cells and whatever at it—and those have been found in Alzheimer's patients in post-mortems. You go into these lesions that have been (for a long time) associated with Alzheimer's, get in the middle of these lesions—and you find PM 2.5.

Alan: So, scary stuff.

Daniel Sullivan: Yeah it's really, really big stuff. And the premature death is mostly caused by, well, one the Alzheimer's dementia. But when this stuff gets into your lungs, it's like you're walking on a treadmill all day uphill. It makes it harder to breathe—it puts stress on your system both the day that you experience it and potentially several days afterwards. Those are the direct health effects.

Daniel Raimi: So, as Alan said, serious stuff—to be sure. Despite the seriousness of this pollutant, when reading the first part of your paper, one of the points you make is that the monitoring networks that we have for measuring the concentrations of PM 2.5 are not comprehensive (is maybe a charitable way to put it). One data point that stuck out to me in the paper is that in 2015, 79 percent of counties in the United States did not have a monitor for PM 2.5. Can you talk a little bit about the gaps in our current monitoring protocols and how these new satellite data improve upon that?

Daniel Sullivan: The main thing with the monitors is they're just really expensive, these regulatory-grade monitors. You can't just use any off-the-shelf, you know, $100 monitor and expect it to withstand scrutiny in courts. These regulations can negatively impact businesses and so you can't, in a sense, frivolously harm businesses by using inaccurate instruments. To withstand that scrutiny, you have to have really quality monitors. Now, those become really expensive and that, I think, is the primary reason why we don't have more monitors. The other reason is that it's actually a big political question about where you put monitors and how many, because these monitors can make life difficult for local politicians, for local regulators, and for the profits of local businesses. So, this has actually been in the news for a while now—there's an ozone monitor in Sheboygan, Wisconsin, that is perennially [...] [that] puts it [the region] into nonattainment. And not the scientific community or the regulators, but the state legislature has been pushing for a long time to try to shut this ozone monitor down and thereby make it easier for them to become in attainment.

Alan Krupnick: It's a really hard problem. If you don't have something like satellite data, how do you know where to put the monitors in the first place? So, you know, you look around your city and you think about, “Well, where might be” [...] (if you're doing your job)—“where might be the highest pollution levels? And, well, let's put a monitor there.” But you don't actually know. And, as Daniel suggested, it's subject to political pressure and even potentially manipulation. So what this research really does is kind of blows the lid off of that by using the satellite data to show where the hotspots actually are, and compares that to where the ground-based monitors are.

Daniel Raimi: Let's talk about that. What did you find when you compared the satellite data with the ground-based data? Where were some of those hotspots? And, yeah—just talk about geographically and maybe demographically as well—where did you find some of the biggest differences?

Daniel Sullivan: So, what we do is we take the satellite data, and what it tells us is for every square kilometer in the United States, what's the annual concentration and then we overlay that with population data from the census. And then we ask, are there any counties—so, the county is usually the unit of jurisdiction used to determine compliance or noncompliance. Are there any counties that contain areas that—if there was a monitor there, it would be flagged as nonattainment? And we looked at both counties that have no monitors and counties that did have monitors. And what we found was there are 24 million people that are classified officially as attaining the NAAQS (so, not violating the Clean Air Act)—but they were, in fact, contained areas that exceeded the NAAQS. Now, roughly half of those were in counties that didn't have monitors at all. So, there was just [...] we didn't know what was going on there, as far as the regulators were concerned. The other half, about 12 million, were in areas that contain monitors, and what we found is that the monitors were placed kind of on the outskirts or kind of the edge of the hot zone—and so they were very close to the limit, but they weren't actually over the limit.

And if you had moved those monitors slightly, you know, more downtown basically, they would have picked it up. And so this is mostly in the Midwest. This is Chicago; Indianapolis; Cincinnati; Louisville, Kentucky; some in Houston, and Texas [...] a couple of border cities in Texas. We have maps in the paper, and we have a list of all the counties as well. I think it's 56 counties and 11 states.

Daniel Raimi: Yeah. So for those of you following along at home, keeping score—in the back of the paper, if you look at Figures 4 through 6, you can see some of these results and the counties that are affected in a pretty [...] really stark, compelling way. All right. So, we know some of these areas are classified as being in attainment when they probably should not. You guys did some calculations about the number of people that were affected and also the value of the health damages that we could expect for these people that are affected. Can you talk a little bit about that?

Daniel Sullivan: So, when a county gets classified as nonattainment, they have to implement a number of measures to get themselves back in attainment. And you see the air quality in those areas improve. So, what we did is we took the actual nonattainment counties and looked at how their pollution improved over the [...] following couple of years. And then we asked, what if these misclassified counties had also gotten that additional improvement in air quality? Right? And so then we took that difference, applied it to the number of people that would have been affected, used kind of standard numbers from prior research that say “This is how all-cause mortality in an area is impacted by PM 2.5”—and then got the answer that, across the country, over the two years following the classification, approximately 5,500 people died that probably wouldn't have if they had had that improved air quality.

Daniel Raimi: So, if the counties that have high concentrations of PM 2.5, if they had taken the types of measures that counties that were recognized as being in nonattainment—if those places had taken those measures, we could have seen a reduction in premature mortality of, you know, more than 5,000.

And then we apply the value of statistical life measures to those deaths.

Daniel Sullivan: It's like you have two drivers, or two sets of cars—one set put on their seat belt, and we see how much better off they fared. And then we posit: What if these other people had put on their seat belts as well? How many more people would have survived? And then [...] so, again, so in government accounting and policy accounting, we use this measure called the “value of statistical life” that basically equates, like, how much does this impact the society? How much value does removing someone from society take from everyone else? And that value is approximately $9 million per life. It is the value of a statistical life. And so, putting all that together, this misclassification costs society, the American people, about $50 billion.

Daniel Raimi: Okay. And for those of you who aren't familiar with the value of statistical life (or VSL) literature, there's a deep and fascinating literature about how that number is calculated. So, you know, that's a fun research topic to explore if you're not familiar with it. So, last question on this paper: What are some of the policy implications of what you found? How does the availability of these data affect the potential for either the federal government or state governments to adjust how it measures compliance? And have you spoken with any policymakers about that? Or do you think there's interest out there in using these types of data to create new metrics and measure things in new ways?

Alan Krupnick: So, actually, to take your last question first, we have given presentations to people at the Environmental Protection Agency and at state agencies who are responsible for monitoring air pollution. This is a pretty new type of information and so it's going to take some time for the use of satellite data to kind of sink in—to, basically, almost 50 years now of using ground-based monitors to regulate air pollution in this country. So, we're not going to see overnight penetration of these ideas into regulatory behavior. But some people maybe listening to this podcast would say, "Well, let's throw out all those monitors on the ground and just use satellites because it can't be manipulated and it gives you data all the time and so we should do that." And our paper and in our discussion with policymakers, we do not push that idea. And the reason is that the ground-based monitors are quite accurate for what they're trying to do and the satellite data has holes in it because of, you know, cloudy days or rainy weather. The reflectivity of the land is different in different places; it needs to be accounted for. The way you calibrate the conversion of aerosol optical depth to PM 2.5 is problematic depending on the area that you're trying to calibrate for—you have to make sure these match up correctly.

So, what our primary recommendation is, is that satellite data be used to supplement ground-based monitoring—and in a particular way. So, you take the satellite data, you look at where the hotspots might be, and then if you don't have a monitor there, you put one there and then see what happens. And that seems like a relatively low-cost strategy. You could actually move a monitor from one place where the satellite data say is not a problem and put it in another place where it is. So, that would be very low cost as opposed to adding additional monitors. That's our basic policy thrust.

Daniel Raimi: Yeah, that makes sense. And it's fascinating that some people might see these new types of data as a panacea to the problem of measuring pollution. But what you're saying is that it can be, maybe, a leading indicator of something that's happening—and then you need additional tools to kind of “ground truth” what the satellites are telling us.

Alan Krupnick: That's a very good phrase—ground truthing.

Daniel Raimi: All right. Well, I turned a phrase, happy about that. So, this is fascinating stuff. Thank you guys for joining us and telling us about this work. We're going to close out the show the same way that we always close out Resources Radio, which is asking our guests what's on the top of their reading stack. What have you read, or maybe listened to in a podcast, or seen in a video recently that you think listeners of this podcast might be interested to know about? And this could be a journal article, it could be a new story, it could be something happening in the policy world—or anything else related to energy and environmental topics. So, Dan or Alan, what's on the top of your stack?

Daniel Sullivan: One thing that's really interested me is[...] so we just had the election not too long ago and there are a number of climate and energy things on ballots in various states. And one thing that really interests me is the clean energy propositions in Nevada and Arizona. The main components of both of those measures were to require state utilities to produce at least 50 percent of their electricity from renewable sources by 2030 (and there are some other details to each of the propositions as well). The measure in Nevada passed and the measure in Arizona didn't. And without getting into the “whys” or whatever, that's just going to be really interesting to watch going forward—how much the doom and gloom prophesied by utility companies of "Oh, we're not going to be able to do that"—how much of that comes to pass and how easy that adjustment really is. I think it's going to be a great incubator for looking at these things going forward, and maybe encouraging other states to adopt similar measures or dissuading other states from making the same mistakes.

Daniel Raimi: Yeah, lots of fascinating results from the recent midterms. So, Alan, what's at the top of your stack?

Alan Krupnick: Well, I have this huge stack—the Trump administration keeps adding layers to my stack every day. But one of the things that I think is very important in that stack is the idea of capturing CO2 [carbon dioxide] coming out of smokestacks and coming out of industrial processes, and even coming directly out of the air—and storing that permanently in the ground or in products. So, this is all called by the name “carbon capture utilization and storage” (or CCUS). And this is gaining currency very rapidly because it's not actually anathema to the Trump administration, because they're interested in making coal generation more viable in a climate-constrained world. And the way to do that is by having carbon captured coming off of the smokestacks of electricity generation units and putting it into the ground or into products. So, what we're starting to see is an explosion of interest in pursuing CCUS in a variety of places. I just got back from a meeting in Houston where we were talking about Houston's industrial emissions of CO2, which are very large because there's so much refinery and petrochemical operations down there.

So, we're finding interest in these technologies and in policies that can incentivize reducing CO2. Like in the new federal tax bill, there's a regulation called 45Q that gives incentives for projects to do just that. [...] A big, big increase in interest—so, I think your listeners should be on the lookout for new technologies and new ideas and new activities going on that will try to reduce our carbon footprint.

Daniel Raimi: Yeah, that's fascinating. You know, to point people to a couple of resources, there was a recent National Academy of Sciences report on this topic. There's also some pretty major initiatives at universities and think tanks around the country looking at CCUS (or sometimes people call it carbon dioxide removal, or CDR). So, absolutely, we'll be checking that out. Looks like Alan's got smokestacks on the top of his reading stacks. Thanks again, Alan and Dan, for joining us, telling us about your recent research and giving our listeners something else to look into. We really appreciate it.

Daniel Sullivan: Great. Our pleasure.

Daniel Raimi: Thank you so much for joining us on Resources Radio. We'd love to hear what you think, so please rate us on iTunes or leave us a review—it helps us spread the word. Also, feel free to send us your suggestions for future episodes. Resources Radio is a podcast from Resources for the Future. 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. Learn more about us at rff.org. The views expressed on this podcast are solely those of the participants. They do not necessarily represent the views of Resources for the Future, which does not take institutional positions on public policies. Resources Radio is produced by Kate Petersen, with music by Daniel Raimi. Join us next week for another episode.