(00:00:09) Ken Ono: Welcome to Hoos in STEM. I'm Ken Ono, your host and the STEM Advisor to the Provost and the Marvin Rosenblum Professor of Mathematics at UVA. Our goal is to evoke flights of imagination and wonder by showcasing the cornucopia of all that is STEM at UVA: the marvelous world of UVA science, technology, engineering, and mathematics. In our last episode, we had an incredible time chatting with the talented Jimmy Burns, Coleen Carrigan, and Liheng Cai. They're doing amazing work in the UVA School of Engineering and Applied Sciences, where their work spans what we do in engineering, from materials to the cultural and societal impacts of the need for diversity in engineering, and also in terms of materials that are used in space stations. It was really awesome. 

Now, the reason that we focused and featured three guests in our last episode is that they have just caught our eye as recipients of the PECASE award, the Presidential Early Career Award for Scientists and Engineers. This is the highest award that the federal government gives out to young scientists and engineers beginning their careers. So, to have three winners is really remarkable. Now, when we first started imagining that episode, we didn't know that UVA actually has a fourth PECASE winner. And it's a pleasure to have today our fourth winner, Sally Pusede, and she is an associate professor in the Department of Environmental Sciences. Now, it's appropriate for us to frankly separate these episodes because while environmental sciences and engineering, as close as they can be in some respects, are different disciplines. I'd like to point out that the University of Virginia is the first major university to have and understand the need for a department in environmental sciences so it's very appropriate that this success and this tradition of excellence continues with this award. So, I can't wait to dig in. Sally, congratulations. Welcome to Hoos in STEM.

(00:02:27) Sally Pusede: Thank you. It's really nice to be here.

(00:02:29) Ono: So, Sally, congratulations. Incredible award. How did it feel when you learned that you were winning a PECASE award, a prize from the president?

(00:02:39) Pusede: It was really exciting. It's always nice to be recognized for your work. It feels great. I also just really love the work.

(00:02:47) Ono: So your work in environmental sciences is really specialized. It's technical. As I understand it from the award abstract, that your work is based on satellite remote sensing and I want to dig in and ask about that. But before I go further, I do know and I'm aware that you do quite a bit of work beyond the satellite remote sensing so I want to make sure that we save time for that. But tell us, your award-winning work satellite remote sensing. What are you doing in the field?

(00:03:19) Pusede: Sure, well, so the work that we do has really advanced the application of satellite remote sensing of the atmosphere to describe, to understand, to inform, policy around neighborhood-level air quality issues. And so, what satellite remote sensing is we have instruments on satellites in space. They look down to the surface of the earth. They compare those observations to observations of the sun directly and from the differences in light that they measure, they can infer the concentration of a wide variety of different air pollutants in the atmosphere.

(00:03:54) Ono: So, what kind of instruments are we talking about?

(00:03:57) Pusede: I guess I would say that these instruments are space-based spectrometers. They sort of look at the sun, look back at the surface of the Earth. This is an application of, an exciting application of, Beer's Law, which many people learn about in introductory physics. 
(00:04:11) Ono: So, we're looking for differences in the wavelengths in light which I guess purely originate from the sun, but then when they reflect off the earth, the wavelengths are impacted by the pollutants in the air.

(00:04:26) Pusede: Correct.

(00:04:27) Ono: Yeah, so remind us, what is Beer's Law?

(00:04:30) Well, Beer's Law takes advantage of the difference between light coming in and a light measurement after it's passed through a medium, and you can have some knowledge of how far that light traveled, and to infer some information about what types of pollutants are in that path. I mean, this in its simplest case is what we're doing, it's very challenging because we're getting measurements through a very complex and dynamic atmosphere. There are clouds, there are other pollutants, the surface of the earth is variable so it is really challenging, but we can think about it that way.

(00:05:04) Ono: So, what kind of pollutants are you searching for? Which are the ones that that keep you up at night?

(00:05:10) Pusede: We look at a wide variety of pollutants. Our work for this award has really sort of started with a pollutant called nitrogen dioxide. Nitrogen dioxide is a combustion pollutant. So, it's going to come out of any source where you have high temperature combustion, a tailpipe of a vehicle, a smoke stack of a factory, a forest fire, really anything where we have something burning at a high temperature. And nitrogen dioxide is also really useful because we can see so many different anthropogenic sources or urban sources. We can learn something about those sources. And also, the other piece of nitrogen dioxide that makes it really useful, one, it has a very strong signal in the in the spectra that are measure measured from space, but two, nitrogen dioxide is very short-lived so it's emitted into the atmosphere…

(00:06:01) Ono: In bursts.

(00:06:02) Pusede: Yeah, so then it's going to actually, it goes on to form other molecules through chemistry and is lost quite rapidly. What that does is you get a pollution distribution that's very heterogeneous or very variable in space. So if you were, for example, you know, sort of at a freeway where you have a lot of traffic, you're going to have a lot of emissions of this pollutant, but even as you walk 100 meters, 200 meters, 500 meters downfield of that freeway, you're going to experience really different air pollution concentrations. And so, you might sort of, when you fly into a polluted city, you often see a brown cloud sitting over that city. That brown color comes from the presence of nitrogen dioxide. But what you also see is a kind of an even layer of pollution over that city. And that's quite different from the reality. In fact, the reality is that we get a lot of variability and pollution within that city as well.

(00:06:57) Ono: So in your work, do you focus on particular cities, particular neighborhoods, particular individual factories, or do you think more globally? What is your focus?

(00:07:08) Pusede: I'll just say really quickly that one of the benefits of satellites is that these satellite instruments, they're out in space. They're collecting measurements everywhere all the time and they're giving us pollution information where we don't have any surface measurements. And that's really important because it allows us to study problems where we don't have measurements. So, people use satellites for all sorts of things, looking at pollution globally, looking at forest fires. We've really focused on US cities, by and large, and that's because we're particularly interested in the application of using satellite measurements of air quality to study environmental justice issues, the kinds of environmental justice issues that we see in the United States. So, we have focused in specific cities and we've focused across all US cities. We've done both. That's one of the things that the satellite allows you to do: look in detail in one city but also look across major cities.

(00:08:05) Ono: Can you share one example of some of your findings with respect to a specific city?

(00:08:10) Pusede: Absolutely. I'll share one analysis that we did that was part of this award. We looked at 52 major cities across the United State and were very interested in the portion of neighborhood level NO2 inequalities in this case. And this is really the difference in pollution that people experience within cities. We're very focused on issues of environmental racism and environmental inequality, but attributing the portion of that inequality to diesel trucks. Diesel trucks are just 2-5% of all of the vehicles on the road, these really heavy duty diesel trucks. I'm thinking so, when you're on the freeway, and you see those really big trucks that are transporting goods. So, thinking about the portion of pollution coming from those trucks, they're 2-5% of vehicles on the road. In some cities, they contribute 30 to 50% of all the pollution in the air. So, we used, we took advantage of differences in trucking traffic that happen in US cities on weekends and weekdays. So those are trucks that transport goods commercially, so they're largely parked on the weekends. And so, there's this at there's this experiment that's happening in the atmosphere in the United States weekly. We call it the weekend-weekday experiment. But we see this substantial decrease in NO2 pollution associated with these trucks being parked on the weekends. So, we were able to apply this experiment to looking at neighborhood level NO2 inequalities and assign the portion of of NO2 disparities or air quality disparities that were coming from diesel trucks. And so, it turns out this was at the same time that the Biden administration was proposing its new clean trucks plan, and that was going to decrease NOx emissions from trucks by 60% by 2045. We saw weekday to weekend, a reduction of NOx emissions of 60%, so we were actually able to test the outcome of this proposed policy on inequality in US cities, and our paper was really widely cited in public comments and was able to influence the process in that way.

(00:10:15) Ono: Well, that's really great. So Sally, satellites are out in space. They're nowhere near the Earth's surface, and as you say, the satellite is collecting images. And the way the spectrometers work is that they collect information essentially by measuring wavelengths of light in a column of air. Talk about the size. Talk about the land area that that column of light covers.

(00:10:43) Pusede: Yeah, so I think the best way to think about this is if you think about it as a camera. The satellite's taking a picture of air pollution from space and that picture is pixelated, and those pictures at best have a spatial resolution of 3.5 x 5.5 km.

(00:10:59) Ono: Which is much larger than a neighborhood, much less 500m. So, you must have done something amazing.

(00:11:06) Pusede: So, we did a few things. The first thing that we did, and I would say that our primary accomplishment in this field, has really been to evaluate the extent to which we can resolve neighborhood level differences with these observations. And so, we did that through sort of a really detailed evaluation of the measurements themselves, thinking about what are actually are the gradients between neighborhoods, and to what extent is the variability that we see in that column. Right, the satellite is in space. It's measuring the full column to the surface, but we care about the air that people are breathing. So to what extent is that variable is that variability occurring at the surface? So, those two analytical challenges were what we faced in this kind of initial work and I did that with a former PhD student at the University of Virginia. Her name's Angelique Demetillo. You know, we were really, at that time, focused on issues of spatial resolution. Do we have enough spatial resolution? So, we thought that one of the ways that we could overcome the challenges of spatial resolution, the fact that we have these large pixels was to do a process called oversampling. Oversampling takes advantage of the fact that while the satellite is taking a picture of the surface, every day the location and size of those pixels changes, and so they overlap in in ways that allow us to extract more spatial resolution from them. If that pixel was the same size, same place every day, we couldn't do this. But they're moving around and they're changing size, so we took advantage of these oversampling techniques or super resolution.

(00:12:42) Ono: Are these images taken over a period of days or how does that work?

(00:12:46) Pusede: So, it leads us to a realm of of averaging data, temporal averaging. And that's useful, right? Because I said at the beginning, I was interested in sort of like the sort of daily average exposure to pollution that people have. But you have to include a high number of images, so you get a static map and you can create these maps under different conditions. You can look in the summer, in the winter, on the weekends, and on the weekdays. So, you can start to tease out some aspect of the temporal variability from that. But that was really where we started. And we showed through this work that in fact you really could see a very large portion of neighborhood level variability from space. You couldn't see everything. Certainly, we miss a lot, but because these observations fill such large gaps, they give us so much new information that we didn't have before.

(00:13:46) Ono: So, it's kind of like your satellite Roomba, the vacuum cleaner that just roams and over time will eventually cover space.

(00:13:53) Pusede: Yeah. So everyday though, you get an image that's comprehensive, right? Just like you would with a photograph. And so that kind of led us to the next step like, well, okay, we're averaging a lot of data. We're using these oversampling techniques. We're looking at neighborhood level variability. We don't see everything, but we have a really good idea of what we're missing. We have very detailed records of what we're missing. And we sort of thought, well, what happens if we don't do that? What happens if we start to look at these individual photographs, these daily scenes over cities? What do we lose? You know, going into it, I thought we were going to lose a lot. I didn't know that we were going to see that much. It turns out, actually, that you see almost more using these very coarse images. And this was work that we did in collaboration with Isabella Dresell. She was an undergraduate student here at the time. Amazing. She did amazing work sort of repeating what we had done, but instead of using these images that had undergone oversampling, she started using the individual daily scenes directly.

(00:14:54) Ono: And can you tell us a little bit more, or indicate what you mean by "we see more"?

(00:14:59) Pusede: We see more for two reasons. And so, one of the things that we learn is that well, you don't necessarily need to be able to resolve hundreds of meters because in cities, the structure of pollution sources aren't that you really have these isolated pollution sources, that in fact, in cities, you have regions of pollution. You know, freeways combine, they overlap, they get wider, and you might have places where you have industrial sources where you don't just have one factory, but you might have tens of factories. So instead, what we're resolving from space are these regions of pollution, and that lessens the requirement on spatial resolution for us because those steep gradients are going to add in ways that make them much, much bigger. The other piece of what Isabella was doing was she wasn't averaging out the high values. She wasn't averaging out the low values either, but it's really the high values that drive neighborhood level inequalities. And those high values are the values that are, you know, sort of located directly over the facility, especially when winds are calm, and so that that had a big effect on the data that and the analysis we were doing because we became much more sensitive to these temporal extremes which have a really, really big impact.

The important consequences of this is we moved away from these time-averaged images, which very much put us in conversation with policy makers and health scientists who looked at things like average exposures, and now put us in direct conversation with atmospheric chemists who think about the atmosphere as a dynamic changing place. And so, this allowed us to now start to, you know I'm an atmospheric chemist, and we start to think now about all of the temporally variable processes in the atmosphere and think about how the distribution of pollution affects that. And so, I'll give you one example. This is in Houston, Texas. We published a paper last summer that Isabella led, looking at a pollutant that people are very familiar with, called ozone. And ozone is high in the summer, it’s formed in the atmosphere through chemistry. A lot of work has gone on in the United States to regulate ozone. And so NO2, which is a pollutant I was mentioning earlier, is a precursor to that, and so we don't tend to see steep spatial gradients in ozone because it's formed in the atmosphere through chemistry, and chemistry takes time, so it tends to get evened out. But what we found in Houston was it wasn't just how much precursor there was. The distribution really affected it. So, environmental inequalities in the distribution of these precursors actually drove the chemistry, not just the amount. And so that was something that people hadn't really looked at before, but you know, we have the ability now to ask questions like that because we have daily varying information. Certainly, we lose something, because we've sacrificed a little bit of spatial information, but I would argue we gain a lot because we have all this temporal information.

(00:18:04) Ono: Oh, that's great. So, I probably should have led off with this. Although there have been satellites for many decades, going back to even the 60s, this work obviously is still fairly brand new, because you're talking about new collaborations with atmospheric chemists, and so on and so forth. So, your work, the impact in the field moving forward with the science... can you speak about how your work has tentacles and is literally changing the field as a science, and then I want to turn to some of the the social and ethical impacts.

(00:18:40) Pusede: Sure. People hadn't applied the observations in this way. They hadn't thought about evaluating them in this way. Now there's a collection of research groups who do work in this line, that we have, you know, sort of made possible through this foundational work on the data. I think you absolutely see the types of analyses that we were doing sort of become kind of standard ways for policy makers and activists and scientists to talk about the impact and the import of their work.

(00:19:15) Ono: So yeah, let's turn to that now. In addition to the science... some science is fundamental, right? You perform certain kinds of chemistry experiments, or experiments in high energy physics, or maybe research in pure mathematics, without having a clear set of applications in mind. But your work, I think, is very different. We hear it in your words. As I understand it, a large part of your work matters because you're making it matter straight away. I think you have a lab called the Repair Lab. Can you tell us about that?

(00:19:51) Pusede: Sure. So, the Repair Lab is an interdisciplinary environmental justice lab that I co-run with Professor Kimberly Fields, who's in the Carter Woodson Institute for African American and African Studies. She's a political scientist and she has expertise on state and local-level environmental justice policymaking. In the Repair Lab, what we've done is develop... we call it the practitioner-in-residence program. It's much like an artist-in-residence program but community members or organizers, leaders who have environmental justice concerns, do residencies in our program to develop policy solutions to those problems. So, in this case, we're really trying to work with people to develop policy solutions.

(00:20:35) Ono: So, for example, you spoke of ammonia pollution in the Carolinas, and you spoke about ozone in Houston. Are these scientific papers going to then be developed into this policy work or maybe that's already part of the goal?

(00:20:50) Pusede: So, in this case, the practitioner brings the problem to us. And so right now, we have just finished the residency of two practitioners from Hampton Roads area, so Newport News and Norfolk. Lathaniel Kirts and Malcolm Jones have been working with our organization for the past two years as practitioners to develop policy solutions to coal dust air pollution.

(00:21:13) Ono: So, that that comes as a surprise to me. So, when you speak of coal dust, I would have thought West Virginia, but you're saying there's coal dust pollution in Newport News. `

(00:21:21) Pusede: Yeah, so coal that's mined in West Virginia travels by train. It actually goes through Charlottesville and then it comes to the Port of Virginia, where it's exported. The state of Virginia exports more coal than any other state in the country, and so that coal sits before it's exported in Newport News. It sits in these large mounds or dunes, and in Lambert's Point in Norfolk it will stay on the trains, but in both places, it blows off those piles or those trains into the adjacent communities, which are historically and predominantly African American communities who've been complaining about coal dust for decades without intervention. And so, we've been really focused through this program on developing policy solutions. We haven't really, you know, it's hasn't been our focus to think about science through this. We're really focused on policy, but from this work, new science has been coming out of this work. So, there's a couple scientific things that we have, sort of scientific initiatives that we've launched because of you know, sort of realizing what doesn't exist and realizing the kinds of information that we need to have to be effective in pushing for new policies. And so, one example that kind of connects to sort of issues of analytical chemistry was that the Virginia Department of Environmental Quality sort of in response to community concerns, handed out these small low-cost air quality sensors to residents, to give them the opportunity to measure the amount of coal dust in the air. Well, this raised a lot of concerns to me because the sensors that they handed out actually do not measure large particles, which would be, for example, coal dust.

(00:23:110) Ono: What do they measure?

(00:23:11) Pusede: They measure small particles that say, for example, come out of a tailpipe, and then what they do is they have a series of mathematical equations and they estimate the amount of large particles. That works, maybe, for freeway pollution, it works for forest fires, but it's not going to work for coal dust. So, what it means is that they've handed out air quality sensors that explicitly do not measure coal dust. So, one of the things that we have now is a pretty large community monitoring program going on where we have sensors that really are sensitive to dust, and they sit next to these sensors that the DEQ handed out. And what we see are these really large dust events that come through and absolutely no... flat lines on the other. 
And then the other one was really kind of addressing this issue of well does, you know sort of what is the impact? Certainly, you can see coal dust on the homes but does the coal dust get inside the homes? You know when I say one thing... I will say like, when I hear the word dust, dust doesn't sound that bad. We all have dust in our homes, but we don't have dust like this. Coal is filled with heavy metals.

(00:24:16) Ono: It's carcinogenic, right?

(00:24:17) Pusede: Yes, absolutely, so it's not... dust is not dust everywhere, right, and it leaves these black residues and these black films. And so right now, what we're doing is working with residents, actually going into people's homes and swabbing for dust. We absolutely, you know, when you run the wipe along places where dust might accumulate, it will come back black. And we're working with Justin Richardson in the Department of Environmental Sciences, and he's measuring, quantifying, the amount of toxic metals in that dust. And that will actually allow us to say, without a doubt, that this is coal in this dust. So, science, you know we haven't set out to do scientific work.

(00:25:00) Ono: This is scientific justice in action.

(00:25:02) Pusede: Yeah, but we're seeing sort of opportunities where, like really, this information isn't in the literature. There's no evidence and so we have to create it.

(00:25:10) Ono: So, Sally, this is great, but as a theoretical mathematician, I don't think so much about whether my work might have a direct application, and what I find so exciting about your work is that it's crystal clear that this work matters. So, I'm compelled to ask, where does this work go from here? How do you go from having, I think you called it, a practitioner-in-residence who identifies a problem, and then you work together with them and conduct these studies. What's the ultimate goal, and where are you along that path?

(00:25:45) Pusede: Sure, so the ultimate goal is policy change that leads to pollution mitigation. Less pollution is the ultimate goal.

(00:25:53) Ono: And in this case, locally in say Newport News, right?

(00:25:56) Pusede: Right, so through the residency of the practitioners, we've looked at sort of the political landscape, identified possibilities, particularly at the local level, through working through city local city council. We're also in the process of collecting environmental and scientific data that will support the claims of residents that this dust impacts them.

(00:26:16) Ono: Who pays for that?

(00:26:17) Pusede: The practitioner-in-residence program was funded by the Karsh Institute for Democracy. The follow-on work, collecting the environmental data, collecting the dust swabs in people's homes, a lot of the community engagement work that we're doing, that's funded by the Robert Wood Johnson Foundation. And so, you know, we're in the process of collecting these observations, thinking really closely about exactly the types of measurements and environmental data that compel action. And we've met with community leaders, we've met with a lot of residents. We have two really big events this summer around Newport News. We actually also are really focused on telling the stories of people who live in Southeast community of Newport News talking about the organizing that has happened in Southeast Newport News and Norfolk. We released a podcast this summer where people tell their stories. It's called Crosswinds. It kind of surveys the issue but really sort of all of our focus has been on creating these measurements, understanding the politics around the issue to work for policy change at the local level.

(00:27:27) Ono: Great. So, this is a university. University of Virginia is a university. You've already spoken quite eloquently about some of your students and postdocs. So, that's great. What sort of message do you have for students who want to become part of the Repair Lab or do some of the science in in your lab?

(00:27:50) Pusede: They should email me.

(00:27:51) Ono: They should email you. Okay. Well, Sally, thank you for all that you do at the University of Virginia. And I'd like to begin to wrap up here. And there are two kinds of questions I ask of all of our guests. The first is tell us a little bit about your path. Did you know, for example, when you were in high school that I'm going to be an environmental scientist? I'm going to make the world a better place through my science and my partnerships with people who think deeply about policy. What's your story?

(00:28:20) Pusede: So, when I was in high school, I was very interested in social justice issues, but I was also very interested in art. I didn't think of myself as being interested in science in high school. I went to art school, went to the Pratt Institute, I majored in sculpture. So, I was very, very interested in art. But what happened was, I ended up getting a job in a chemistry lab at Pratt Institute, with a chemist. She was studying the degradation of the color blue in wall paintings in Italy, and she needed somebody to make her samples for her. So, she gave me a book written by Cennino Cennini in the 14th or 15th century and I followed the instructions for how to make the same types of fresco paintings that were made, that she was studying. She was particularly interested…

(00:29:16) Ono: I'm thinking Sistine Chapel blue.

(00:29:17) Pusede: Yes, very interested in the color blue. And blue was the rarest. The most valuable blue came from lapis lazuli, which was a precious stone and it was ground up and it was saved for very important, very expensive paintings. But there was also kind of a, you could create a blue with metal oxides, but that often degraded or vanished over time. And she was studying that. And so, I made these fresco painting samples for her. She was amazing. She taught me about the science. She did NMR analysis on it. She took me with her to the NMR room. So I became really interested in it. And I also, you know, was very interested in becoming... maybe doing art history and conservation. Wall paintings were something I really connected with, in part. I mean, this project was looking at Italian wall paintings, which were in churches, but fresco paintings were something that were in public spaces in the United States and Mexico, so very much a social aspect to them. And I was like well, maybe I'll be an art historian and do conservation, and to get into this program I was interested in, in art conservation, you had to take organic chemistry as a prerequisite.

(00:30:31) Ono: Oh wow.

(00:30:32) Pusede: So, I was like okay, well, I'll take organic chemistry. And I moved back to Denver, Colorado, which is where I grew up. And I enrolled in some science and some math classes, and I took organic chemistry. And it was, I will say, the most fun I have ever had in the classroom. I absolutely loved organic chemistry.

(00:30:52) Ono: Okay, Sally, that that wasn't my experience, but okay.

(00:30:55) Pusede: I know that's not, you know, not everybody says that, but I just I just loved it. And I kind of fell in love with chemistry. My organic chemistry professor, his name is Dr. Bob Damrauer, he's retired now. He was an amazing professor. He also had two sons. One son was a chemistry professor at the University of Colorado, and one was an artist living in Brooklyn. So maybe there was you know, some kind of, you know, I just really loved that experience. I found chemistry to be such a powerful tool for studying, you know, studying major problems, environmental problems. And then I ended up thinking, well, maybe I'd like to go to graduate school for chemistry. For a year, I worked, I thought maybe that was going to be renewable energy. I got a job at the National Renewable Energy Lab in Golden, Colorado. I worked in a lab studying something called photoelectrochemical water splitting, which is a way to generate hydrogen for hydrogen fuels. That work was great, but you know, it felt kind of far removed. I always kind of wanted to do something that was very applied. So then, when I went to UC Berkeley, I got a job in an atmospheric chemistry lab focused on air pollution.

(00:32:13) Ono: Thank you, Sally, for sharing kind of your remarkable story. I didn't know that earlier in life you wanted to be an artist. It's much more common, I think, for a scientist to be a son or a daughter of a scientist in the same field. So thank you very much for sharing that. So your work, which spans analytical chemistry, environmental science and social justice, really spans a lot of the university. Do you see your love of art as part of your work in in any other ways?

(00:32:46) Pusede: Sure. I have an exciting collaboration working with Erin Putalik in the School of Architecture, and what we're focused on is looking at how environmental risk is visualized, and how environmental risk is communicated through imagery. So really, the visuals of it, and you know, just thinking about the ways that we communicate through pictures about harm. We have a paper that's going to come out any day now in a design magazine, looking at the early history of air pollution and how visual and sensory those experiences were. Think of photographs of hazy scenes, and thinking about how sort of early in the emergence of environmental pollution or in environmental risk, the way we understood that was through these kinds of sensory experiences, our eyes, our bodies. For example, photography. So, Los Angeles is surrounded by mountains, and in many pictures, those mountains aren't visible.

(00:33:51) Ono: Oh, yeah. Just brown. In the 1970s, you only saw smog, but it was supposed to be, and correct me if I'm wrong, one of the major achievements in public policy, environmental public policy, that now you can occasionally see these mountains.

(00:34:07) Pusede: Right. And other types of embodied sensing might be, if we go back to eastern North Carolina, is the smells and the nausea for example, that comes along with being in these clouds of pollution that emanate from industrialized swine agriculture. Coal dust is a great example because coal dust is black and it settles onto white surfaces and you can see that that dust on surfaces.

(00:34:33) Ono: So, Sally, I'd like to end these conversations with a fun fact and maybe we've already done it, your love of art. Are there any generally unrelated to our conversation?

(00:34:43) Pusede: Well, I would say, you know, in addition to really loving art when I was in high school, I really loved punk rock music.

(00:34:50) Ono: Punk rock. So, I mean like the Clash or...?

(00:34:52) Pusede: Well, you know, I really loved sort of the local bands that played in Denver. And I think actually the values of punk culture, and collectivism, and do-it-yourself, these types of values sort of stick with me today.

(00:35:08) Ono: Thank you so much for joining us today. You are extraordinary and very interesting so it's been a pleasure to have this conversation. To say that you're fulfilling President Ryan's mission to be great and good in everything we do is pretty clear. You span the Grounds. Thank you very much for being a leader in that way and I hope some of our students reach out to you by email.

(00:35:33) Pusede: Well, thanks for having me.

(00:35:34) Ono: So, I'm Ken Ono, STEM Advisor to the Provost and the Marvin Rosenblum Professor of Mathematics, and you've been listening to Hoos in STEM. 

• University of Virginia Professor Wins Prestigious PECASE Award from the Biden Administration (College of Arts and Sciences, February 4, 2025)
• Pusede Lab
• Repair Lab
• Crosswinds Podcast