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 (NO₂), fine particulate matter (PM_2.5), and ozone (O₃) across California for 2012-2019. Our findings revealed opposite spatial patterns of NO₂ and PM_2.5 to that of O₃. We also identified consistent, higher pollutant exposure for disadvantaged communities from 2012 to 2019, although the most disadvantaged communities saw the largest NO₂ and PM_2.5 reductions and the advantaged neighborhoods experienced greatest rising O₃ concentrations.

SUBMITTER: Su JG 

PROVIDER: S-EPMC11305374 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature