In this week’s episode, host Daniel Raimi talks with Ann Wolverton, a senior research economist at the US Environmental Protection Agency, about how the agency incorporates environmental justice in its rulemaking and its analysis of agency regulations. Wolverton discusses the history of accounting for environmental justice at federal agencies, how the availability and granularity of data affect this ability to evaluate environmental justice outcomes, and how formally considering environmental justice can inform federal regulations.
Listen to the Podcast
- Federal agencies have been evaluating environmental justice since 1994: “We in the federal government have had direction to evaluate environmental justice for a long time. There’s an executive order that was signed in 1994, Executive Order 12898, and it directs federal agencies to evaluate whether its policies, practices, and programs result in disproportionate impacts to specific populations that are defined on the basis of race, income, and ethnicity.” (7:18)
- Methods continue to evolve for evaluating environmental justice outcomes: “A lot of the previous environmental justice analyses … were only able to characterize what’s happening historically and/or currently. A common way of doing that is to think about locating the sources of emissions … Now, what we’re trying to do is ask whether we can do better, and, in part, it’s to have a more refined understanding of, Where does pollution that comes out of a plant’s smokestack, for example, go? And who’s actually being exposed to it? But also, how is a given regulatory option going to change that picture?” (11:49)
- Benefits to disadvantaged communities: “Now, we can ask the question of whether there are some regulatory options that might deliver greater benefits to specific communities, perhaps at the cost of what would’ve otherwise been a higher aggregate welfare—but still delivering benefits to everyone and just targeting these communities more effectively.” (22:52)
The Full Transcript
Daniel Raimi: Hello, and welcome to Resources Radio, a weekly podcast from Resources for the Future. I'm your host, Daniel Raimi. Today, we talk with Dr. Ann Wolverton, senior economist at the US Environmental Protection Agency (EPA).
Ann recently published a fascinating article on how economists can improve the way they account for environmental justice when carrying out analysis of rules and regulations. In today's conversation, I'll ask Ann to help us understand the role that economists play in evaluating rules of the EPA and what tools they're using to try to better account for environmental justice outcomes. We'll also talk about the important data gaps that make it challenging to do this work. Stay with us.
Ann Wolverton from EPA, welcome to Resources Radio. It's great to have you with us.
Ann Wolverton: Thank you for having me. I'm really excited to be here.
Daniel Raimi: We're excited to have you. And I learned just a moment ago that this is your first podcast, so welcome to the podcast.
Ann Wolverton: Thank you.
Daniel Raimi: We're going to talk today about a really fascinating recent paper that you've published, all about how EPA is incorporating environmental justice issues into its economic analyses. It's going to be a great conversation, but we always ask our guests how they got interested in working on environmental issues—whether you had a period of inspiration at a young age, or whether you got interested in this stuff later in life. What drew you into working on these topics?
Ann Wolverton: I had to think about this. I grew up in a really small town in Minnesota, and I spent most of my summers outside. My mom would kick my brother and me out and say, "Don't come back till lunch." We lived on a bluff above the Mississippi River, so we spent a lot of time wandering around in the woods, and we also spent a lot of time up north at our cabin, whether that's fishing or swimming or picking blueberries or whatever it was. I think my love of nature started from a really young age. And, in addition, my dad had a real skill for noticing things, details: if you went on a walk in the woods, he’d make it a very special experience, identifying tracks or specific trees or plants or just noticing the world around you.
Then, when I was in high school, we moved to Arizona, and that was a big change for me. I was really aware of the difference in landscape. This wide open space instead of being closed in by trees made me feel like I forgot to put something on in the morning. But it also was a change from a small town to a big city, and it, I think, made me aware of the fact that air quality and water quality are sometimes really at odds with economic growth, and it made it more explicit in a way that was maybe less evident in a small-town setting.
Then, how does economics come into all of that? I took an economics class in high school, and I did not love it, but I went to Arizona State University, and I had a professor who taught one of those really big, 500-person classes to undergraduates, and he had a real gift for showing how what I had previously thought of as a rather dry discipline could be applied to really interesting and difficult policy questions and provide a framework for thinking about trade-offs inherent in many of the choices that we make. I think that's what drew me in—those two pieces. Environmental economics allows me to think about nature and air and water quality and things that I really love, and economics makes it challenging and interesting and provides me with a systematic approach for trying to think through those things.
Daniel Raimi: That's so interesting how those two streams come together.
We're going to talk today about this recent article that's published in the Review of Environmental Economics and Policy. It's called “Environmental Justice Analysis for EPA Rulemakings: Opportunities and Challenges.” Before we start talking about the environmental justice, or EJ, aspects of this question, can you give us a little bit of background on what is the role that EPA economists play when rules are being developed within the agency?
Ann Wolverton: For each rulemaking that's promulgated by an agency, there's a rule-development process, and it's informed along the way by analysis. Analysis, in this context, often means quantifying, or trying to think through, what are the main costs of imposing a particular requirement—typically on firms—and then, What do we get out of it? What are the benefits of that action in terms of avoided health effects, for example, or improvements in the ecosystem? It’s something along those lines.
In addition to benefit-cost analysis, we also often are asked to help think through the economic impacts of a given policy on specific groups of people or specific entities. That might be small businesses that might be thinking about effects on employment. That might be whether we're imposing requirements on state or local governments, what's happening with electricity prices and effects on consumers—it can be a wide range of things. We have this toolbox to try to quantify and, when possible, monetize those effects. And really, what we're trying to do in many cases is think about whether a given policy is going to be delivering more in terms of benefits than costs, and then also thinking through, Are there trade-offs between some of the other goals of our policy, and/or unintended consequences that we haven't really carefully thought through that might imply a change in the regulatory design of the program itself?
Daniel Raimi: That's great background. Within that context, to what extent has EPA in the past sought to incorporate environmental justice considerations into that analytical process? In addition to that looking back question, the Biden administration has expanded this approach. Can you talk a little bit about how it's been done in the past and how it's changed in recent years?
Ann Wolverton: I'm going to mainly focus on the extent to which EPA has evaluated environmental justice as part of the rulemaking process as opposed to more broadly, because that's my area as this analytic piece. I do want to note, before we get too far into the discussion, that while I can describe the analytic practices at the agency to incorporate environmental justice, I'm not formally representing the agency's policies and views during the discussion.
To answer your question, we in the federal government have had direction to evaluate environmental justice for a long time. There's an executive order that was signed in 1994, Executive Order 12898, and it directs federal agencies to evaluate whether its policies, practices, and programs result in disproportionate impacts to specific populations that are defined on the basis of race, income, and ethnicity.
I can't go all the way back to 1994 to answer this question, but we did an exercise at EPA where we looked at the inventory of rules going back to 2012 to look at the extent to which we were examining potential environmental justice concerns. Under the Obama administration, about two-thirds of the economically significant rules—those are the big ones that actually require benefit-cost analysis and other regulatory analyses—included an environmental justice analysis. We also released a technical guidance document in 2016 at the very end of the Obama administration, and that sets out broad expectations and recommendations for how to conduct environmental justice analysis.
The reason I mention that is because we have analysts sprinkled all across the agency who are involved in doing support for rulemaking, and familiarity with the expectations that were set out in that guidance really ensured that environmental justice analysis continued to be conducted. If you look at the Trump administration, for example, we still see that about two-thirds of the really big rules were including an environmental justice analysis despite a pretty big change in policy priorities at the time.
Now, when we think about the Biden administration, there's been a real emphasis on the importance of environmental justice that, at least in my experience, is somewhat unprecedented, and it's been in a variety of ways. One piece I haven't mentioned is there's a component of environmental justice called “meaningful engagement”—this idea that you allow affected communities to have a voice in decisionmaking, and there's been a really proactive attempt to figure out how to operationalize that, both in terms of feedback that might inform the analysis, but also more broadly.
Then, in addition, we're trying to push the methods for analysis past just a characterization of preexisting concerns, or what's sometimes referred to as the baseline, to think about exposure and risk and really, Who's being affected and how? There's a new Executive Order, 14096, which was signed back in April of 2023, that expands the notion of environmental justice to a wider variety of population characteristics.
In addition to race, ethnicity, and income, it includes disability, for example, and it continues to call on agencies to assess the potential for disproportionate impacts, but it calls out the importance of thinking about climate change and the role of multiple stressors. It asks federal agencies to think about systemic barriers and historical inequities. It's really expanding the notion of what we might potentially take on in an environmental justice analysis.
We're trying to actively think through how to incorporate those aspects. It's definitely a work in progress. I will note that the technical guidance that I mentioned a few minutes ago is out for public comment right now, because we've decided to revise it to reflect some of the recent advances in the state of the science, as well as the availability of new data and methods.
Daniel Raimi: That's great and super interesting background and context there.
Let's get up to the present day, and you mentioned you're in the process of incorporating these issues into your analysis of rulemakings. Can you just put some more meat on those bones? What are some of the issues that you're wrestling with? What are some of the important decisions you need to make? And, maybe, if there's an example or two that comes to mind to help illustrate this, that would be really helpful for us, too. But I'd just love for you to talk a little bit about how you're seeking to make these changes.
Ann Wolverton: A lot of the previous environmental justice analyses—not all of them, certainly, but quite a few of them—were only able to characterize what's happening historically and/or currently. A common way of doing that is to think about locating the sources of emissions. It might be a collection of power plants, for example, and then we’d draw a buffer around those sources to say something about the people that live nearby. The reason we do that is because, often, we don't have a good notion of what's actually being emitted and then who's being exposed to what's being emitted. In lieu of that information, we're doing this drawing of buffers and saying, "Hey, this is what people who live within one mile or three miles of a plant look like, and this is similar to or different from people who live further away from that particular environmental hazard."
Do they look similar? Do they look different? Do we have people who are poor and have a particular demographic profile in terms of race and ethnicity living near the plant, when people further than three miles away look really, really different? Now, what we're trying to do is ask whether we can do better, and, in part, it's to have a more refined understanding of, Where does pollution that comes out of a plant's smokestack, for example, go? And who's actually being exposed to it? But also, how is a given regulatory option going to change that picture? In order to be able to say something about how a regulatory option will actually affect change, we need to have better data and a better sense of not just who's being affected but how they're being affected.
Daniel Raimi: That's really interesting. I wonder if it would surprise people to know that information is not always readily available for you and your colleagues when you're doing these types of analysis. There are, of course, academic papers that have models that seek to estimate things, and EPA has its own models that rely upon. I'm curious if you could talk a little bit more about that information gap and how it's getting filled in.
Ann Wolverton: One example where it's a relatively data-rich environment is when we think about policies to reduce particulate matter; for example, we have air quality monitors that tell us some information about where particulate matter is higher or lower. We can potentially leverage satellite data to fill in those gaps. We have really sophisticated models that can estimate concentrations of particulate matter based on where they travel and wind direction and other factors like that. That means that we can characterize what things might look like absent a change in policy, and then we can also simulate how that might change based on a reduction in particulate matter. That's not always the case for a lot of other pollutants, either because we don't have the underlying data to inform those, or we don't have sophisticated models to understand—even if we know what's being emitted—where it's going. Sometimes, we can piece those together.
One example I give in my article is for lead dust. We have a lead-dust hazard standard and then a set of practices to clear to a particular level. And there, we were able to use information on how much lead is showing up in blood-lead levels for children. That's reported in biomonitoring data that the US government collects. We know something about where people live based on the American Housing Survey and how old that housing is—the likelihood that it contains lead. We could combine the demographics and the housing information with the biomonitoring information and then look at who likely has elevated lead levels and then how that's going to potentially change as you clean up the lead dust from contamination. There, we're being innovative in terms of taking disparate pieces and putting them together to try to evaluate a context.
But there are lots of cases where we don't have a survey that the federal government produces, or we're not collecting information on emissions. And we're left with the proximity analysis with the drawing of buffers around sources that I mentioned before.
Daniel Raimi: That's really interesting, and it's so fascinating to hear about data limitations and analytical-tool limitations from within the government perspective. I think, sometimes, people might have an inaccurate view that the federal government knows everything, and they've got all the data, and big brother or big sister is crafting these rules, when in reality, at least for these particular topics, there are pretty substantial limitations that can make this work challenging.
One of the things that you talk about in your article that I think is really interesting and really important is the difference between thinking about marginal impacts from a rulemaking and cumulative impacts that communities might experience. Can you talk a little bit about the difference between those two things—marginal and cumulative impacts—and why thinking hard about cumulative impacts is a little bit of a change for economists when doing these types of analyses?
Ann Wolverton: Sure. Let me back up a little bit and talk about the way we conduct a benefit-cost analysis for a rule, because I think that's where this notion of a marginal or incremental effect comes from. The goal of a benefit-cost analysis is to evaluate how the costs of taking that action and the resulting benefits change overall or aggregate welfare. That's an incremental question. How does it change? Then, that's also the typical focus of a distributional analysis. How are those costs and benefits distributed across the population? Again, costs and benefits being the incremental or new piece.
It's not that the question isn't relevant when thinking about environmental justice, but I think we're taking a much wider lens in trying to characterize what's already happening in these communities and then how cumulative effects or multiple stressors might be playing a contributing role to those underlying disparities, and that's a really important piece of the puzzle. It's a recognition that some communities face a combination of stressors that could be multiple sources of pollution, but it could also be psychosocial stressors, lack of access to healthcare, lack of access to good nutrition, or stress related to living in a neighborhood with more crime.
Not all communities are starting from the same point, and ultimately that combination of stressors could mean not only that they're exposed to more pollution, but also that they have a greater response to a given level of pollution, because of this mix of things that are already happening in their lives. Focusing on cumulative effects means thinking about that broader context and thinking a bit more holistically.
A piece that we're still trying to figure out is also how to think about cumulative effects outside of the analysis of an individual regulation or policy, which is really what we've been talking about so far, and thinking holistically about a combination of policies and programs that might reduce the disparities. Because the reality is, sometimes, that when you think about multiple sources of pollution or stressors, and you have in front of you a specific regulation, that regulation might only deal with a specific piece of that problem and doesn't address all the other pieces. You need to think about it in combination with other potential actions.
Daniel Raimi: That makes lots of sense, and it's very reflective of I think what the environmental justice advocacy community has been arguing for quite some time. It's interesting to see it getting applied and really implemented in this context. Another thing that your article notes is that, even if an economic analysis of a given role making might find that particular rule yields positive net benefits to society—that is, the overall “goods” outweigh the overall “bads”—that there still could be concentrated damages for certain groups or communities that need a lot of attention.
I'm wondering if you can give us an example of a scenario like that and help us think through what EPA might do in that situation. Just be a little more colloquial, for example, if a certain regulation yielded positive net benefits for society, but large concentrated damages for one group or another group, could that be enough for EPA to scrap the rule entirely? That goes to the question of how does the benefit-cost analysis ultimately inform the decision of whether or not to finalize a rule in a certain form? Could you just talk about that a little bit? I know I've asked a lot. That's a big question, but I'd love for you to address it as best you can.
Ann Wolverton: The policy question I can't really answer, but I can speak to the role that analysis can play for a decisionmaker.
I think of the role of analysis … We've traditionally done a benefit-cost analysis, and that really elevates the economics in the decisionmakers’ discussion of how to balance statutory requirements, feasibility, institutional concerns, political issues—whatever they are—within that conversation. When we conduct environmental justice analysis, that allows us to make more explicit the trade-offs between aggregate welfare and the distributional implications of a specific approach.
Now, we can ask the question of whether there are some regulatory options that might deliver greater benefits to specific communities, perhaps at the cost of what would've otherwise been a higher aggregate welfare—but still delivering benefits to everyone and just targeting these communities more effectively. How those trade-offs get made is within the policy mix and the discretion of the administrator and other decisionmakers.
But I think the role of the analyst is to provide them with enough information that they can have that discussion and potentially make those trade-offs more evident. In terms of an example, one could think of something like a regulation where you need to set a national standard. You're setting some level of stringency, that might be a national ambient air-quality standard for particulate matter or ozone, or it could be a regulation to reduce the amount of specific hazardous air pollutant.
Really, what you have as a policy lever within the statute is the ability to ratchet up or down that stringency. But it could be that you have particular communities where there are much higher concentrations of a pollutant—that's really difficult to target with a national level standard. You could continue to ratchet down the stringency, but that might impose large costs on everybody else. How do you think about that? That also means that you have to recognize that sometimes the specific regulation or policy lever you have in front of you might not actually be the right tool to reduce those disparities. You might need to combine that national-level stringency with thinking about other programs or policies that will more directly target those more localized issues.
You can also think about if there are constraints on the regulatory design to think about what you might do with additional monitoring or information provision, or if there are requirements you can put in place for analysis or other types of tools that can be leveraged at key decision points. A lot of the federal regulations that we promulgate are then given to state and local jurisdictions to figure out how to implement. There might be ways to infuse the process down the road with thinking explicitly about distributional and/or environmental justice concerns that way.
Daniel Raimi: That's great. One last question, Ann, before we go to our Top of the Stack segment, which is that we've been talking about the role of economists in this conversation, but economists, of course, aren't the only ones that are involved in doing analysis and collecting data and helping to inform these decisionmaking processes. Can you just talk a little bit about how other scientists and other folks are working to develop data and tools to better these processes?
Ann Wolverton: Economists are definitely part of a broader team that includes risk assessors, specialists in geographic information systems or mapping tools, and other types of scientists. It's important to think about the role that these other specialists play, because environmental justice analysis actually occurs relatively late in the analytic process. If you want to generate inputs into the environmental justice analysis, you need to think about it at the earliest stages of the analytic process.
That often can mean thinking about it when you're conducting a risk assessment. A risk assessment would typically occur much earlier and might ask about whether there are potentially important exposure pathways to think about that might be unique to particular communities or particular groups.
An example: It's not really an environmental justice example per se, but with lead, a typical unique exposure pathway is that children crawl around on the ground and put things in their mouths. And if they're in a place where there's chipped paint on the windowsills or on the floor, they're going to naturally get that on their hands, put their hands in their mouth, or chew on the windowsill, and they're going to get a lot more lead that way.
You also want to think about questions like, How do impacts vary across a distribution of affected individuals? How might that vary with specific underlying conditions or population characteristics? For example, if you're thinking about air pollution, you might want to know whether certain populations have a higher incidence of asthma, because that could really complicate and elevate the response to particular types of pollution.
I think that's super important and also points to some additional potential data and modeling gaps that we might want to worry about that aren't really necessarily just specific to economists, but might also mean that you need better biomonitoring data or epidemiological studies that focus more on groups that are typically underrepresented in scientific studies, so that we can more fully delineate exposure and response across the full population.
Daniel Raimi: That makes a lot of sense, and it's really interesting to hear just a thumbnail sketch of how all of that is getting updated and incorporated into the rulemaking process. I just really appreciate your expertise on these topics and helping us understand how they're being implemented and evolving over time.
But we've come to the end of our time. I'd love to ask you now, Ann, to recommend something that you've read or watched or heard that you think is great. It doesn't really have to be related to the environment if you don't want it to be, but if it is related to the environment, all the better. Ann, what's at the top of your literal or your metaphorical reading stack?
Ann Wolverton: I was trying to think of something that would be relevant to this audience. A book that I read a few months ago is called Toms River. It's by Dan Fagin, and I thought it was a really fascinating, hard-to-put-down read. It's about a town in New Jersey that's basically had a host of rare cancers in the town, and they're trying to demonstrate the role that dumping, many years before, into the water had in terms of the cancers that now people are dying from in the town. It really demonstrates all the different steps and also the difficulty of actually demonstrating that. This particular town ended up with a really large settlement, but it took many, many, many, many years.
The other thing about the book that I think is really interesting is that it weaves the history of epidemiology into the story. It gives you this broader lens of thinking about where they first made the connection between being exposed to a particular environmental hazard and how it shows up in the body. Of course, the most obvious place was with workers, because they were working with toxic chemicals and dyes and other things and would end up with these really rare cancers. And it just walks through that demonstrating how we ended up with this whole new science that basically tries to connect the dots between contamination and human health. I thought it was a hard-to-put-down, investigative-reporting type of book that I really enjoyed.
Daniel Raimi: Very, very interesting. Great. We will have a link to that book and of course to your paper, Ann, in the show notes for the show so people can check them out.
One more time, we just want to say thank you to you, Ann Wolverton, from EPA, for coming onto the show and helping us get a better sense of how you and your colleagues are working to update the rulemaking process to incorporate environmental justice considerations. It's been really fascinating.
Ann Wolverton: Thank you. It was a lot of fun.
Daniel Raimi: You’ve been listening to Resources Radio, a podcast from Resources for the Future, or RFF. If you have a minute, we’d really appreciate you leaving us a rating or comment on your podcast platform of choice. Also, feel free to send us your suggestions for future episodes.
This podcast is made possible with the generous financial support of our listeners. You can help us continue producing these kinds of discussions on the topics that you care about by making a donation to Resources for the Future online at rff.org/donate.
RFF is an independent, nonprofit research institution in Washington, DC. Our mission is to improve our 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.