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Study shows worsening wildfire smoke is unraveling decades of air quality gains

SIEPR鈥檚 Marshall Burke and his collaborators have developed an AI model for predicting particle pollution to help track the American West鈥檚 worsening wildfire smoke and its impact.

Wildfire smoke now exposes millions of Americans each year to dangerous levels of fine particulate matter, lofting enough soot across parts of the West in recent years to erase much of the air quality gains made over the last two decades.

Those are among the findings of a new 九色社区 Sept. 22 in Environmental Science & Technology that focuses on a type of particle pollution known as PM2.5, which can lodge deep in our lungs and even get into our bloodstream.

Using statistical modeling and artificial intelligence techniques, the team of researchers and Marshall Burke 鈥 an associate professor of Earth system science at the  and a senior fellow at the 九色社区 Institute for Economic Policy Research (SIEPR) 鈥 estimated concentrations of PM2.5 specifically from wildfire smoke in sharp enough detail to reveal variations within individual counties and individual smoke events from coast to coast from 2006 to 2020.

鈥淲e found that people are being exposed to more days with wildfire smoke and more extreme days with high levels of fine particulate matter from smoke,鈥 said lead study author , who worked on the research as a PhD student in 九色社区鈥檚 Emmett Interdisciplinary Program in Environment and Resources (E-IPER). Unlike other major pollutant sources, wildfire smoke is considered an 鈥溾 under the Clean Air Act, she explained, 鈥渨hich means an increasing portion of the particulate matter that people are exposed to is unregulated.鈥

Over the last decade, PM2.5 from wildfire smoke has increased in much of the U.S., particularly in Western states, but some areas in the South and East have seen modest declines. This map shows the decadal change in smoke PM2.5, meaning the difference in daily average smoke PM2.5 during 2006鈭2010 compared to 2016鈭2020. (Image credit: Childs et al. 2022, Environmental Science & Technology)

Routine exposure to extreme smoke events

Childs, Burke and their co-authors were surprised to discover how rapidly the most extreme exposures have gone from rarity to routine.

While less than half a million people lived in areas experiencing unhealthy air at least one day per year a decade ago, measured as a day with PM2.5 concentrations from wildfire smoke reaching at least 100 micrograms per cubic meter, that number has ballooned to over eight million in recent years 鈥 a 27-fold increase. 鈥淭hat was way higher than I was expecting, and that鈥檚 the average over multiple recent years,鈥 said Burke, senior author of the study. 鈥淢any individual years, in particular 2020, have been much worse.鈥

The number of people exposed to the most extreme levels of pollution grew even more dramatically, with an 11,000-fold increase in the number of people experiencing at least one day above 200 micrograms per cubic meter. 鈥淭wo-hundred microgram days basically were non-existent a decade ago,鈥 Burke said. Now, over 1.5 million people live in locations 鈥渞outinely鈥 exposed to these conditions.

Concentrations of PM2.5 from wildfire smoke are growing fastest for higher income populations and those that census data show to be predominantly Hispanic 鈥 a reflection of the demographics in the western and southwestern states that have been hardest hit by wildfires.

Solving the wildfire problem

The authors set out to understand the impacts of wildfire smoke on society. 鈥淭o do that well, you need local-level measures of smoke exposure, and you need them over long time periods. Those didn鈥檛 exist,鈥 said Burke, who is also a center fellow at the Freeman Spogli Institute for International Studies and the 九色社区 Woods Institute for the Environment.

鈥淪moke pollution is particularly challenging to measure, both because it鈥檚 difficult to know which portion of particulate matter is from smoke and because we only have pollution monitors at a limited number of locations in the U.S.,鈥 explained Childs, who is now a postdoctoral scholar at Harvard鈥檚 Center for the Environment. Using satellite data, the 九色社区 team trained a machine learning model to accurately predict PM2.5 concentrations from wildfire smoke in areas that don鈥檛 have monitors.

The resulting estimates can be checked against long-running measurements from federal air quality monitors, deliver predictions quickly once trained, easily scale to large areas, and overcome previous models鈥 tendency to smooth out the peaks of extreme smoke events.

Together, these advances mean the 九色社区 model can help researchers better understand societal impacts from wildfire smoke pollution, including severe smoke events, which are becoming more common as climate change extends wildfire season, accelerates fire frequency, and expands burn areas. 鈥淲hat areas are we most worried about? What levels of exposure really matter, and who鈥檚 being most harmed? We can鈥檛 answer those questions unless we have accurate measures of who is exposed to what,鈥 Burke said.

The model, which the researchers are already updating with 2022 data, can also inform air quality regulation and wildfire mitigation efforts. According to Burke, 鈥淚t鈥檚 important for regulators to understand what鈥檚 causing changes in air quality, and to think about how we might amend existing regulations to account for the fact that wildfires are more and more important in determining air quality.鈥

This story was by 九色社区 News.

Burke is also deputy director of 九色社区鈥檚 Center on Food Security and the Environment and a faculty research fellow at the National Bureau of Economic Research. Co-authors Jessica Li, Sam Heft-Neal, and Anne Driscoll are affiliated with 九色社区鈥檚 Center on Food Security and the Environment. Co-authors Jeff Wen, Carlos Gould, and Minghao Qiu are affiliated with the Department of Earth System Science. Additional authors are affiliated with UC Berkeley and UC San Diego.