The 天美影视传媒 is proud to announce that 56 faculty and researchers who completed their work while at UW have been named on the list from Clarivate.

The annual list identifies researchers who demonstrated significant influence in their chosen field or fields through the publication of multiple highly cited papers during the last decade. Their names are drawn from the publications that rank in the top 1% by citations for field and publication year in the .

Highly Cited Researchers demonstrate significant and broad influence in their fields of research. The total list includes 7,131 awards from more than 1,300 institutions in 60 countries and regions. This small fraction of the global researcher population contributes disproportionately to extending the frontiers of knowledge and contributing to innovations that make the world healthier, more sustainable and which drive societal impact, according to Clarivate.

The that determines the 鈥渨ho鈥檚 who鈥� of influential researchers is drawn from data and analysis performed by bibliometric experts and data scientists at the Institute for Scientific Information at Clarivate.

The list below includes faculty and researchers whose primary affiliation is with the UW, Fred Hutch Cancer Center, and the Institute for Health Metrics and Evaluation.

Please note: Some of the people on the list are no longer with the UW and their current affiliation is noted. This list reflects initial data from Clarivate and may be updated.

Ivan Anishchenko (Vilya)

David Baker

William A. Banks

Gregory N. Bratman

Steven L. Brunton

Guozhong Cao

Ting Cao

Lauren Carter (Gates Medical Research Institute)

Helen Chu

David H. Cobden

Katharine H. D. Crawford

Riza M. Daza

Frank DiMaio

Kristie L. Ebi

Evan E. Eichler

Emmanuela Gakidou

David Ginger

Raphael Gottardo (CHUV)

Alexander L. Greninger

Simon I. Hay

Andrew Hill (Infinimmune)

Eric Huang

Michael C. Jensen (BrainChild)

Neil P.听 King

C. Dirk Keene

J. Nathan Kutz

Eric H. Larson

Aaron Lyon

Michael J. MacCoss

Brendan MacLean

C. M. Marcus

Julian D. Marshall

Ali Mokdad

Thomas J. Montine (Stanford)

Mohsen Naghavi

Marian L. Neuhouser

Julian D. Olden

Robert W. Palmatier

David Pigott

Hannah A. Pliner (Bristol Myers Squibb)

Ganesh Raghu

Stanley Riddell

Andrea Schietinger (Memorial Sloan Kettering Cancer Center)

Jay Shendure

M. Alejandra Tortorici

Troy R. Torgerson (Allen Institute)

Cole Trapnell

Katherine R. Tuttle

David Veesler

Theo Vos

Alexandra C. Walls (BioNTech SE)

Bryan J. Weiner

Di Xiao

Jie Xiao

Xiaodong Xu

Jihui Yang

While air quality has improved dramatically over the past 50 years thanks in part to the , people of color at every income level in the United States are still exposed to higher-than-average levels of air pollution.

A team led by researchers at the 天美影视传媒 wanted to know if the Clean Air Act is capable of reducing these disparities or if a new approach would be needed. The team compared two approaches that mirror main aspects of the Clean Air Act and a third approach that is not commonly used to see if it would be better at addressing disparities across the contiguous U.S. The researchers used national emissions data to model each strategy: targeting specific emissions sources across the U.S., requiring regions to adhere to specific concentration standards or reducing emissions in specific communities.

While the first two approaches 鈥� based on the Clean Air Act 鈥� didn’t get rid of disparities, the community-specific approach eliminated pollution disparities and reduced pollution exposure overall.

The team Oct. 24 in the Proceedings of the National Academy of Sciences.

“In earlier research, we wanted to know which pollution sources were responsible for these disparities, but we found that nearly all sources lead to unequal exposures. So we thought, what’s it going to take? Here, we tried three approaches to see which would be the best for addressing these disparities,” said senior author , a UW professor of civil and environmental engineering. “The two approaches that mirror aspects of the Clean Air Act were pretty weak at addressing disparities. The third approach, targeting emissions in specific locations, is not commonly done, but is something overburdened communities have been asking for for years.”

Fine particulate matter pollution, or PM2.5, is less than 2.5 micrometers in diameter 鈥� about 3% of the diameter of a human hair. PM2.5 comes from vehicle exhaust; fertilizer and other agricultural emissions; electricity generation from fossil fuels; forest fires; and burning of fuels such as wood, oil, diesel, gasoline and coal. These tiny particles can lead to heart attacks, strokes, lung cancer and other diseases, and are

The researchers tested the three potential strategies using , which Marshall and other co-authors developed. InMAP models the chemistry and physics of PM2.5, including how it is formed in the atmosphere, how it dissipates and how wind patterns move it from one location to another. The team modeled these approaches with national because it was the most recent data set available at the time of this study.

The researchers looked at how efficiently and effectively each approach reduced average pollution exposure for all people and how well it eliminated the disparities for people of color.

While the emission source and concentration standards approaches were successful in reducing overall exposure across the country, these methods failed to address pollution disparities.

“Our optimization models what happens if we maximize the reductions in disparities. If an approach cannot address disparities even when optimized to do so, then any real-world implementation of the approach will also not address disparities,” said lead author , a doctoral student in civil and environmental engineering. “But we saw that even with less than 1% of emission reductions targeting specific locations, the pollution disparities that have persisted for decades were reduced to zero.”

Implementing this location-specific approach would require additional work to identify which locations would be the best to target and working with the communities there to identify how to reduce emissions, the team said.

“Current regulations have improved average air pollution levels, but they have not addressed structural inequalities and often have ignored the voices and lived experiences of people in overburdened communities, including their requests to focus greater attention on sources impacting their communities,” Marshall said. “These findings reflect historical experiences. Because of redlining and other racist urban planning from many decades ago, many pollution sources are more likely to be located in Black and brown communities. If we wish to address current inequalities, we need an approach that reflects and acknowledges this historical context.”

Additional co-authors are and , both at the University of California, Berkeley; at the University of Minnesota; at the University of California, Los Angeles; at Carnegie Mellon University; and at the University of Illinois Urbana-Champaign. This research was funded by the U.S. Environmental Protection Agency.

For more information, contact Marshall at jdmarsh@uw.edu, Wang at ywang02@uw.edu, Ivey at iveyc@berkeley.edu and Patterson at reganfp@ucla.edu. Note Marshall is currently in Spain and is nine hours ahead of Pacific Time. The other co-authors are all on Pacific Time.

The authors suggest that reporters reach out to environmental justice organizations and frontline communities as a way to include in stories the voices of people most impacted by air pollution. Possible additional contacts could include members of the and the EPA’s .

Grant number: R835873

Despite dramatic improvements in air quality over the past 50 years, people of color at every income level in the United States are exposed to higher-than-average levels of air pollution. While this disparity has been widely studied, the links between today鈥檚 air pollution disparities and historic patterns of racially segregated planning are still being uncovered.

Now a new study from a team of researchers at UC Berkeley and the 天美影视传媒 has found that housing discrimination practices dating from the 1930s still drive air pollution disparities in hundreds of American cities today. In this study 鈥� the first to do a national-level analysis of modern urban air pollution and historical redlining 鈥� the team examined more than 200 cities and found a strong correlation between present-day air pollution levels and historical patterns of redlining.

The researchers March 9 in Environmental Science & Technology Letters.

“Racism from the 1930s, and racist actions by people who are no longer alive, are still influencing inequality in air pollution exposure today,” said co-author , a UW professor of civil and environmental engineering. “The problems underlying environmental inequality by race are larger than any one city or political administration. We need solutions that match the scale of the problem.”

The term “” describes a widespread federally backed discriminatory mortgage appraisal practice in the 1930s. This process color-coded city areas red if they included high concentrations of Black, Asian, immigrant or working-class residents, deeming these areas hazardous and excessively risky for investment. Redlining blocked access to favorable lending and other services. Historically redlined areas have been cumulatively affected by a low prevalence of home ownership, uneven economic development, displacement of residents, community disintegration and lack of access to education and economic opportunities.

A redlining map of Seattle. Click on a neighborhood or a grade for more details. Credit:

听The researchers compared year-2010 levels of two regulated air pollutants 鈥� nitrogen dioxide (NO₂; a short-lived gas emitted by traffic, industry and other sources), and fine particulate matter (PM_2.5; longer-lived, tiny particles found in dust, soot, smoke and other emissions or formed in the atmosphere) 鈥� to redlining maps in 202 U.S. cities.

In these cities, redlined areas consistently had higher levels of pollution today than听 areas that received favorable treatment. In fact, air pollution disparities associated with redlining status听 were even larger than those associated with race and ethnicity.

The study highlights the “distinct inequities that affect people in all neighborhoods, regardless of redlining grade,” said lead author , a doctoral student in civil and environmental engineering at UC Berkeley. “It also emphasized the importance of identifying and improving conditions in those neighborhoods which have been systematically isolated from financial investment through practices like redlining while being subjected to increased environmental exposures for decades.”

The long-lasting implications of historical segregation on present-day disparities are striking, according to the researchers.

The team also found racial disparities within redlined neighborhoods, suggesting that housing discrimination is one of many factors propelling environmental racism. In other words, white people who happen to live in redlined neighborhoods still have lower air pollution exposure than people of color in the same community. That trend held across non-redlined and redlined neighborhoods alike, the researchers said.

“This study underscores how the past is still very much present when it comes to air pollution disparities,” said senior author , assistant professor in the Department of Civil & Environmental Engineering and the School of Public Health at UC Berkeley. “Redlining is a good predictor of air pollution disparities but it’s only one of the things that drive the racial and ethnic disparities in air pollution. It’s not the only source of disparity that we need to be worried about.”

The research goes “a long way toward highlighting the lasting consequences of structural racism on community health,” said co-author , a professor of Public Health and Environmental Science, Policy and Management at UC Berkeley and co-author of the study. “These results can point the way toward targeted approaches for regulating emission sources and reducing exposures, as well as longer-term strategies to address discriminatory land-use decision-making that adversely impacts communities of color.鈥�

This publication was developed as part of the Center for Air, Climate, and Energy Solutions (), which is funded by the U.S. Environmental Protection Agency (R835873).

For more information, contact Marshall at jdmarsh@uw.edu and Apte at jsapte@berkeley.edu.

Adapted from from UC Berkeley.

Air pollution is linked to multiple health conditions, including heart disease, cancer and cognitive decline. These effects vary depending on the source of air pollution. And not everyone is equally exposed to poor air quality.

天美影视传媒 researchers investigated disparities in exposure to six major air pollutants in 1990, 2000 and 2010 by comparing models of air pollution levels to census data 鈥� including where people live, their racial/ethnic background and their income status.

The team showed that while overall pollutant concentrations have decreased since 1990, people of color are still more likely to be exposed to all six pollutants than white people, regardless of income level, across the continental United States.

The researchers Dec. 15 in Environmental Health Perspectives.

“This is the first time anyone has looked comprehensively at all these main pollutants and watched how they vary over time and space,” said senior author , UW professor of civil and environmental engineering. “This paper is a chance to recognize that, while every community is unique, there are some factors that play out over and over again consistently across our country. If we go state by state, there’s no place where there are no environmental justice concerns.”

Previously the researchers showed that Americans of color were exposed to higher concentrations of (NO2), an outdoor pollutant from cars and trucks, in two census years: 2000 and 2010.

Now the team has expanded that research to look at five additional pollutants that are harmful to our health: (CO), (O3), (SO2) and 鈥� both larger particles, such as dust or pollen (PM10), and smaller particles, such as molecules from vehicle exhaust (PM2.5). For all pollutants except for PM2.5, the researchers also expanded the census years studied to include 1990, in which the Clean Air Act .

“There have been so many improvements,” said lead author , UW doctoral student in civil and environmental engineering. “But we still see these disparities persist, even after two decades.”

To get air pollution data for each year, the researchers used models that incorporate pollution estimates from multiple sources, including data from satellites and Environmental Protection Agency monitoring stations. These levels were then mapped onto census demographic groups 鈥� including four race/ethnicity categories (Black, Asian, Hispanic and white) and income 鈥� to determine estimated exposure to each pollutant for each group across states in the contiguous U.S. and Washington, D.C.

For each location, the team calculated both absolute and relative disparities. For absolute disparities, the researchers subtracted pollution exposures for each group from the average exposure for the state. The team determined relative disparities by dividing the absolute disparity by the average exposure across the country.

Grant number: R835873

With the coronavirus still a concern this fall, a UW class that normally is about air pollution and emissions has pivoted to focus on another airborne health hazard 鈥� coronavirus aerosols.

Air pollution expert听, a UW professor of civil and environmental engineering, is leading his class in building and testing low-cost, DIY air purifiers. The MERV filters used in their design can remove common pollutants from the air, plus virus particles 鈥� and can be used to reduce the risk of COVID-19 transmission.听

These types of homemade air purifiers have already been successful at removing particles found in wildfire smoke from the air.听

As part of the class project, the students are designing various configurations of the purifiers and testing how effective they are. Initially, the students built a “one fan, one filter” device. Then they built larger devices with two to five filters in triangular or three-dimensional box shapes. Students will be testing their听devices to see whether having the fan push or pull air through the filter is better, how noisy the purifiers are and how effective they are at removing particles from the air.听

For more information about the class and project, contact Marshall at jdmarsh@uw.edu.听For video, contact Kiyomi Taguchi at ktaguchi@uw.edu or 206-685-2716.

A new study from researchers at multiple universities, including the 天美影视传媒, models peoples鈥� exposure to air pollution 鈥� based on race/ethnicity and income level 鈥� and shows that exposure disparities among people of color and white people are driven by nearly all, rather than only a few, emission source types. The researchers April 28 in Science Advances.

“We find that nearly all emission sectors cause disproportionate exposures for people of color on average,” said co-author , a UW professor of civil and environmental engineering. “The inequities we report are a result of systemic racism: Over time, people of color and pollution have been pushed together, not just in a few cases but for nearly all types of emissions.”

The team used an air quality model to analyze Environmental Protection Agency data for more than 5,000 emission source types, including industry, agriculture, coal electric utilities, many types of vehicles and equipment, construction and other miscellaneous small emissions sources. Each source type studied contributes to fine particle air pollution, defined as particles being 2.5 micrometers or less in diameter, the study reports.

To identify patterns of air pollution exposure associated with race/ethnicity and income, the researchers combined the spatial air pollution patterns predicted in their air quality model with residential population counts from the U.S. Census Bureau.

For the 2014 U.S. total population average, fine particulate air pollution exposures from the majority of source types are higher than average for people of color and lower than average for white people. The results indicate that white people are exposed to lower-than-average concentrations from emissions source types that, when combined, cause 60% of their total exposure, the study reports.

Conversely, people of color experience greater-than-average exposures from source types that, when combined, cause 75% of their total exposure. This disparity exists at the country, state and city level and for people within all income levels.

“Community organizations have been experiencing and advocating against environmental injustice for decades,” said corresponding author , a University of Illinois Urbana Champaign civil and environmental engineering professor. “Our study contributes to an already extensive body of evidence with the new finding that there is no single air pollution source, or a small number of sources, that account for this disparity. Instead, the disparity is caused by almost all of the sources.”

The researchers found that air pollution disparities arise from a more systemic set of causes than previously understood.

“We were struck by how these systemic disparities exist for people of color not only in certain neighborhoods but at every spatial scale in the U.S.,” said co-author , a professor of civil and environmental engineering at the University of California, Berkeley. “The problem exists within urban and rural areas, many distinct U.S. regions, and for people living within almost all American cities.”

The study results come with caveats, the researchers said. For example, this study focuses on outdoor air pollution concentrations in places where people reside and does not account for variability in mobility, access to health care, and baseline mortality and morbidity rates, among other factors.

“This new study adds context to our previous work, which showed that a disproportionate consumption of goods and services 鈥� which is an underlying cause of pollution 鈥� compounds the exposure of people of color to air pollution,” said co-author , a professor of bioproducts and biosystems engineering at the University of Minnesota.

The researchers hope these findings will highlight potential opportunities for addressing this persistent environmental inequity.

“Some assume that when there is a systematic racial-ethnic disparity, such as the one we see here, that the underlying cause is a difference in income,鈥� Tessum said. 鈥淏ecause the data shows that the disparity cross-cuts all income levels, our study reinforces previous findings that race, rather than income, is what truly drives air pollution-exposure disparities.鈥�

, a research and policy analyst at the Clean Energy Transition Institute who completed this research at the 天美影视传媒, and at the University of Texas, Austin also contributed to this research. The EPA provided financial support for this study through the Center for Air, Climate, and Energy Solutions (CACES).

For more information, contact Marshall at jdmarsh@uw.edu, Tessum at ctessum@illinois.edu, Apte at apte@berkeley.edu and Hill at hill0408@umn.edu.

Adapted from by the University of Illinois Urbana Champaign.

Starting in mid-March, many states issued stay-at-home orders or encouraged people to work from home to try to curb the spread of COVID-19. In cities nationwide, .

But did fewer cars on the road lead to cleaner air? Not necessarily, according to a new study led by 天美影视传媒 researchers.

Using air quality data from U.S. Environmental Protection Agency monitors across the U.S., the research team looked for changes in two common pollutants: , and called PM2.5. Compared to the past 10 years, neither pollutant has been consistently lower than expected levels since stay-at-home orders began. But the team found that another pollutant that mainly comes from car exhaust, NO2, was at much lower levels in three cities 鈥� Seattle, Los Angeles and New York 鈥� (30% lower on average) after stay-at-home orders were implemented.

Update Jan. 27, 2021:听The paper was originally posted on the preprint server , but it has now been peer reviewed. It published online Jan. 2 in .听This release has been edited to reflect that change.

“It’s difficult to determine whether the air really is cleaner now because, in general, there is a lot of variability in weather and emissions patterns,” said senior author , a UW professor of civil and environmental engineering. “You can’t look solely at concentrations today and compare them to the same day a month or a year ago.”

Because pollutant concentrations vary over time and across regions, the researchers developed a method to determine whether pollutant levels in any given week were notably different from normal.

“Let’s say you’re measuring height and you want to know if a difference of 2 inches is a big deal. Well, it depends on how much variability there is,” Marshall said. “If you measured the height of people in a city and then you have someone who’s 2 inches taller than the average height, you’d probably say they’re still about average because people’s height varies by feet. But if you found an NBA hoop rim that was 2 inches different from the average, that’s a big deal. Rim height is so precisely controlled.”

The team’s “robust differences” metric compares a pollutant’s median concentration during a week in 2020 to its median concentration in the same time period over the past 10 years. The metric also adjusts for whether a region has been getting cleaner or dirtier over the past 10 years, a lot like adjusting prices for inflation. This calculation yields a score where negative numbers indicate that a region was cleaner than expected for that week, and positive numbers indicate that a region was dirtier than expected.

The researchers attempted to calculate the robust differences score for the nearly 1,000 PM2.5 and the more than 1,170 ozone monitors across the U.S. But the team excluded monitors that had less than three years of data or were missing data from at least two of the last three years. West Virginia didn’t have any PM2.5 monitors that qualified, and Rhode Island, South Carolina and Hawaii didn’t have ozone monitors that qualified. For all other states, the team used individual monitor data to calculate state-level scores.

鈥�

California was the first state to issue a stay-at-home order, on March 19. That week, average PM2.5 levels across the country were slightly (5%) higher than expected. Since then, PM2.5 levels have continued to be similar to expected values, as of June 17, when this story was initially published. Editor’s note: The maps and graphs in this story will continue to be updated. See them for current information.

PM2.5 levels in individual states also fluctuated over time, which is normal depending on what’s happening with emissions and weather patterns, the researchers said. But in general, the team didn’t see any trends of states being consistently cleaner or dirtier over time.

“Everyone was saying that pollution had to be lower after the stay-at-home orders went into effect,” said lead author , a UW doctoral student in civil and environmental engineering. “But that’s not what we saw across the U.S. It was very surprising.”

鈥�

While the researchers analyzed all states that had enough data, this article highlights three states with stay-at-home orders and large metropolitan areas: Washington, California and New York. As of June 17, Washington had higher PM2.5 levels than normal the week before its stay-at-home order went into effect, and the levels have bounced around since then. Meanwhile, California had lower PM2.5 levels than normal before its stay-at-home order, and that has gradually increased. New York only had a few counties reporting data, but in those counties, PM2.5 levels remained relatively consistent over the course of 2020.

鈥�

Across the country, ozone levels dropped below expected values before stay-at-home orders were issued and have increased since then, reaching expected values by early May. As of June 17, when this story was initially published, ozone levels continued to be similar to expected values. Ozone levels often change over time, the researchers said, depending on what’s happening with emissions and the weather.

鈥�

Similar to the PM2.5 data, ozone levels varied by state. For example, New York’s ozone levels were similar to the national trend. California had lower ozone levels before the stay-at-home order and those levels gradually increased to higher than expected before dropping again the week of May 13. Washington only had one county reporting ozone data 鈥� King County 鈥� and its ozone levels were within the expected range when the stay-at-home order went into effect. Since then, the levels have fluctuated between lower and higher than expected.

While the team didn’t see any consistent drop in ozone and PM2.5 levels, the researchers wondered if , a pollutant that’s more closely linked to car exhaust, would be affected by fewer people on the road. The EPA has not posted NO2 levels for 2020 yet, so the team used data for Seattle, Los Angeles and New York City from .

NO2 levels for all three cities were lower than expected the week of all three states’ stay-at-home orders, with Seattle 46% lower, Los Angeles 56% lower and New York City 46% lower. These levels generally have remained below normal values, as of June 17. These findings are consistent with , the researchers said.

“Everybody thinks that because so many people are not driving the air is really clean, but it really depends on what type of pollution you’re talking about,” Bekbulat said. “Cars are the main contributor to NO2 levels, which are down, so there’s something to people’s intuition. But we’re still using electricity, and that power plant is generating emissions. When it’s cold, people still burn fires, and that generates emissions. Meteorology plays a role, too: Stagnant air tends to be dirtier. There are all kinds of things happening that could explain why we think we’re all shutting down, but pollution levels don’t show that.”

Other co-authors on this paper are 鈥� at the University of Texas at Austin, and at the University of Minnesota, and at Carnegie Mellon University. This publication was developed as part of the , which was supported under an Assistance Agreement awarded by the U.S. Environmental Protection Agency.

For more information, contact Marshall at jdmarsh@uw.edu and Bekbulat at bujinb@uw.edu.

Grant number: R835873. This research has not been formally reviewed by EPA. The views expressed in this document are solely those of the authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication.

A UW study abroad program empowers students from all disciplines to apply their skills to real-life problems 鈥� such as food insecurity, water scarcity, and a lack of adequate housing and education. At the end of the program the students create videos to share their projects.

Participants in the , which is offered through the Department of Civil & Environmental Engineering and UW Study Abroad, spend winter quarter in India鈥檚 third-largest city, Bengaluru, which was previously known as Bangalore. After three weeks of classes and field trips that help students develop their problem-solving skills, participants spend seven weeks working with local organizations that are already addressing challenges in the area.

This year, the program’s third year, boasted the biggest class so far: 27 undergraduate and graduate students from a variety of units across campus, including public health, human centered design and engineering, and civil and environmental engineering. Students worked in seven groups to tackle challenges in the area. The program was cut short by a few days this year because of the coronavirus pandemic.

Some of this year’s projects include:

Connecting people to sanitary public restrooms

Connecting migrant workers to potential employers

Developing a method to clean up “black spots,” or regions of the city where people have dumped trash

Developing a card game to educate young drivers before they get on the roads

To see videos for all of the projects, visit the program’s .

This program received support through the Global Innovation Fund.

For more information about the program, contact Julian Marshall at jdmarsh@uw.edu.

Air pollution doesn’t just come from cars on the road, generating electricity from fossil fuels also releases fine particulate matter into the air.

In general, fine particulate matter can lead to heart attacks, strokes, lung cancer and other diseases, and is responsible for more than 100,000 deaths each year in the United States.

Now 天美影视传媒 researchers have found that air pollution from electricity generation emissions in 2014 led to about 16,000 premature deaths in the continental U.S. In many states, the majority of the health impacts came from emissions originating in other states. The team also found that exposures were higher for black and white non-Latino Americans than for other groups, and that this disparity held even after accounting for differences in income.

The researchers Nov. 20 in the journal Environmental Science & Technology.

“Our data show that even if states take measures to change their own electricity production methods, what happens across state lines could dramatically affect their population,” said senior author , a UW professor of civil and environmental engineering.

The team first examined how emissions from electricity generation plants could move across the continental U.S.

“We looked at emissions from different types of power plants 鈥� including coal, natural gas, diesel and oil power plants 鈥� and modeled how the pollutants would travel based on things like wind patterns or rain. We also consider how emissions can react in the atmosphere to form fine particle air pollution,” said lead author , a UW civil and environmental engineering doctoral student. “That gave us a map of pollution concentrations across the country. Then we overlaid that map with data from the census to get an estimate of where people live and how this pollution results in health impacts.”

Then, using mortality data from the National Center for Health Statistics, the team estimated premature deaths due to electricity generation emissions. In 2014, there were about 16,000 premature deaths. The researchers estimate that 91% of premature deaths were the result of emissions from coal-fired power plants. The number of deaths in each state varied, with Pennsylvania having the highest number 鈥� about 2,000 鈥� and Montana and Idaho having the lowest number, with fewer than 10 deaths each.

Emissions from electricity generation don’t stop at state lines 鈥� many states “imported” or “exported” pollution. In 36 states, more than half of premature deaths were the result of emissions from other states.

Overall, the team found that emissions affected black Americans the most, leading to about seven premature deaths per 100,000 people in that group. White non-Latino Americans were the second most affected group with about six premature deaths per 100,000 people. Other groups averaged about four premature deaths per 100,000 people.

“A lot of people may expect that the disparity we see for race or ethnicity comes from an underlying difference in income. But that’s not what we see,” said co-author , a research scientist in the UW’s civil and environmental engineering department. “We find that differences by race or ethnicity tend to be larger than differences by income group.”

While the researchers found that overall, lower-income households experienced more exposure to emissions, the disparities they saw between race groups still held when they accounted for income.

The amount of power plant pollution that people breathe can vary by where they live. These disparities may be influenced by societal trends. For example, where people live often reflects segregation or other conditions from decades earlier.

These trends don’t always hold when looking at individual areas. For example, exposures for Native Americans are lower than other groups overall, but in Kansas and Oklahoma, this group is the most exposed. The state with the largest disparities by race is Kentucky, where black people are the most exposed.

“We’ve seen in our previous research that our society is more segregated by race than by income, and now it’s showing up again with air pollution from electricity generation emissions,” Marshall said. “These results can help local, state or national governments make more informed decisions that will improve everyone’s air quality and quality of life.”

, a professor of energy resources engineering at Stanford University, is also a co-author on this paper. This publication was developed as part of the , which was supported under an Assistance Agreement awarded by the U.S. Environmental Protection Agency.

For more information, contact Marshall at jdmarsh@uw.edu, Thind at thind@uw.edu or Tessum at ctessum@illinois.edu.

Grant number: R835873. This research has not been formally reviewed by EPA. The views expressed in this document are solely those of authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication.

Poor air quality is the largest environmental health risk in the United States. Fine particulate matter pollution is responsible for more than 100,000 deaths each year from heart attacks, strokes, lung cancer and other diseases.

But not everyone is equally exposed to poor air quality, nor are all people equally responsible for generating it.

Black and Hispanic Americans bear a disproportionate burden from air pollution generated mainly by non-Hispanic white Americans, according to new research from a team led by the 天美影视传媒 and the University of Minnesota. The finding, which quantifies for the first time the racial gap between who generates air pollution and who breathes it, was in the Proceedings of the National Academy of Sciences.

“Similar to previous studies, we show that racial-ethnic minorities are exposed to more pollution on average than non-Hispanic whites,” said first author , a research scientist in the UW’s civil and environmental engineering department and a recent University of Minnesota graduate. “What is new is that we find that those differences do not occur because minorities on average cause more pollution than whites 鈥� in fact, the opposite is true.”

The team compared what people spend their money on 鈥� such as buying groceries or gas or getting clothes dry-cleaned 鈥� to the pollution these activities generate. Then the researchers overlaid these results on a map of where people live to see if there was the difference between the pollution that specific racial-ethnic groups generate and what they experience.

“Someone had to make the pen you bought at the store,” said co-author , a UW professor of civil and environmental engineering. “We wanted to look at where the pollution associated with making that pen is located. Is it close to where people live? And who lives there?”

The team found that on average, non-Hispanic white Americans spend more money on pollution-intensive goods and services, which means they generate more pollution than other groups. But white Americans also experience a “pollution advantage” in that they are exposed to approximately 17 percent less pollution than they generate.

At the same time, black and Hispanic populations bear a “pollution burden.” On average, black Americans experience about 56 percent more pollution than they generate. For Hispanics, it is slightly higher: 63 percent.

These disparities may be influenced by longstanding societal trends, such as income inequality. Also, racial patterns in where people live often reflect segregation or other conditions from decades earlier. Black and Hispanic Americans are more likely to live in locations with higher concentrations of pollution compared to white Americans, which means they have increased average daily exposure to it.

In general, the U.S. has made strides to reduce air pollution across the country: Average exposure to particulate pollution declined approximately 50 percent between 2003 and 2015. But pollution inequity remained high over that same period.

鈥淥ur work is at the intersection of many important and timely topics such as race, inequality, affluence, environmental justice and environmental regulation,鈥� said corresponding author , an associate professor of bioproducts and biosystems engineering at the University of Minnesota.

The team hopes this pollution-inequity metric can provide a simple and intuitive way for policymakers and the public to see the disparity between the pollution that population groups generate and the pollution to which they are exposed.

鈥淭he approach we establish in this study could be extended to other pollutants, locations and groupings of people,鈥� Marshall said. 鈥淲hen it comes to determining who causes air pollution 鈥� and who breathes that pollution 鈥� this research is just the beginning.鈥�

The other co-authors on this paper are Joshua Apte at the University of Texas at Austin; Andrew Goodkind at the University of New Mexico; Nicholas Muller at Carnegie Mellon University; Kimberley Mullins at Lumina Decision Systems; David Paolella at the 天美影视传媒, and Stephen Polasky, Nathaniel Springer and Sumil Thakrar at the University of Minnesota. This research was funded by the U.S. Environmental Protection Agency, the U.S. Department of Energy, the U.S. Department of Agriculture and the University of Minnesota Institute on the Environment.

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For more information, contact Tessum at ctessum@uw.edu, Marshall at jdmarsh@uw.edu, or Hill at hill0408@umn.edu.

Adapted from by the University of Minnesota.