Examining air pollution exposure dynamics in disadvantaged communities through high-resolution mapping

Abstract

This study bridges gaps in air pollution research by examining exposure dynamics in disadvantaged communities. Using cutting-edge machine learning and massive data processing, we produced high-resolution (100 meters) daily air pollution maps for nitrogen dioxide (NO 2 ), fine particulate matter (PM 2.5 ), and ozone (O 3 ) across California for 2012–2019. Our findings revealed opposite spatial patterns of NO 2 and PM 2.5 to that of O 3 . We also identified consistent, higher pollutant exposure for disadvantaged communities from 2012 to 2019, although the most disadvantaged communities saw the largest NO 2 and PM 2.5 reductions and the advantaged neighborhoods experienced greatest rising O 3 concentrations. Further, day-to-day exposure variations decreased for NO 2 and O 3 . The disparity in NO 2 exposure decreased, while it persisted for O 3 . In addition, PM 2.5 showed increased day-to-day variations across all communities due to the increase in wildfire frequency and intensity, particularly affecting advantaged suburban and rural communities.