Examining air pollution exposure dynamics in disadvantaged communities through high-resolution mapping | Science Advances
High-resolution air pollution models reveal exposure disparities between advantaged and disadvantaged communities.
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.