Smoke from wildfires is a growing health risk across the US. Understanding the spatial and temporal patterns of such exposure and its population health impacts requires separating smoke-driven pollutants from non-smoke pollutants and a long time series to quantify patterns and measure health impacts. We develop a parsimonious and accurate machine learning model of daily wildfire-driven PM 2.5 concentrations using a combination of ground, satellite, and reanalysis data sources that are easy to update. We apply our model across the contiguous US from 2006 to 2020, generating daily estimates of smoke PM 2.5 over a 10 km-by-10 km grid and use these data to characterize levels and trends in smoke PM 2.5 . Smoke contributions to daily PM 2.5 concentrations have increased by up to 5 μg/m 3 in the Western US over the last decade, reversing decades of policy-driven improvements in overall air quality, with concentrations growing fastest for higher income populations and predominantly Hispanic populations. The number of people in locations with at least 1 day of smoke PM 2.5 above 100 μg/m 3 per year has increased 27-fold over the last decade, including nearly 25 million people in 2020 alone. Our data set can bolster efforts to comprehensively understand the drivers and societal impacts of trends and extremes in wildfire smoke.

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Wildfires have increased in frequency and severity over the past two decades, threatening to undo substantial air quality improvements. We investigate the effect of wildfire smoke exposure on learning outcomes across the US using standardized test scores from 2009-2016 for nearly 11,700 school districts and satellite-derived estimates of daily smoke exposure. Relative to a school year with no smoke, average cumulative smoke-attributable PM 2.5 exposure during the school year (∼35 µg/m 3 ) reduces test scores by ∼ 0.15% of a standard deviation. These impacts are more pronounced among younger students and are observed across differing levels of economic disadvantage and racial-ethnic composition. Additionally, we project that smoke PM 2.5 exposure in 2016 reduced discounted future earnings by nearly $1.7 billion ($111 per student). Roughly 80% of these costs are borne by disadvantaged districts. Our findings quantify a previously unaccounted for social cost of wildfire that is likely to worsen under a warming climate.

The impacts of environmental change on human outcomes often depend on local exposures and behavioral responses that are challenging to observe with traditional administrative or sensor data. We show how data from private pollution sensors, cell phones, social media posts, and internet search activity yield new insights on exposures and behavioral responses during large wildfire smoke events across the US, a rapidly-growing environmental stressor. Health-protective behavior, mobility, and sentiment all respond to increasing ambient wildfire smoke concentrations, but responses differ by income. Indoor pollution monitors provide starkly different estimates of likely personal exposure during smoke events than would be inferred from traditional ambient outdoor sensors, with similar outdoor pollution levels generating >20x differences in average indoor PM2.5 concentrations. Our results suggest that the current policy reliance on self protection to mitigate health risks in the face of rising smoke exposure will result in modest and unequal benefits.

Wildfires and associated smoke exposure have increased in frequency and severity over the past two decades, threatening to undo decades of air quality improvements. Our understanding of the impacts of these growing exposures on a range of societal outcomes remains incomplete. Building on emerging evidence that environmental exposures can negatively affect cognition, we investigate the effect of wildfire smoke exposure on learning outcomes across the US. We combine standardized test score data from 2009-2016 for nearly 11,700 public school districts across 6 grades with satellite-derived estimates of daily smoke exposure. We estimate that relative to a school year with no smoke, average cumulative daily smoke-attributable PM2.5 exposure during the school year (~35 ug/m^3) reduces both English language arts and math scores by ~0.16% of a standard deviation. These impacts are more pronounced among younger primary school students and are apparent across communities with differing levels of economic disadvantage and racial-ethnic composition. Using previous estimates of the relationship between test score performance and future earnings, we estimate that smoke PM2.5 exposure in 2016 reduced discounted future earnings by $117 per student, resulting in cumulative future earning losses of nearly $1.9 billion across the US. Roughly 80% of these costs are borne by disadvantaged districts. Our findings quantify a previously unaccounted for social cost of wildfire that is likely to worsen under a warming climate.