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Leveraging crowd-sourced environmental data to assess air pollution exposure disparity: A case of Los Angeles County by Tianjun Lu; Dulce A. Garcia; Armando Garcia; Yisi Liu is a Environmental Science article available to read on EtoBox.

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The COVID-19 pandemic has underscored the significance of air pollution exposure; however, its impacts on the exposure disparity between disadvantaged communities (DACs) and non-DACs remain understudied. We utilized crowd-sourced open data from the PurpleAir website, a widely used low-cost sensor network, and data from CalEnviroScreen 4.0, a tool for identifying disproportionate pollution burdens in California, US, to investigate air pollution exposure in Los Angeles County, CA. We compared particles with diameters smaller than 2.5 μm (PM 2.5 ) concentrations before and during the pandemic (March 2019 -March 2020 vs. March 2020 -March 2021) across eight regions, with a focus on DACs that often have high proportions of low-income and people of color residents. Some DACs experienced higher-than-average concentrations when lockdown measures were lifted, with a higher percentage of days exceeding the 35 μg/m 3 threshold compared to non-DACs. We confirmed persistent air pollution disparities between DACs and non-DACs, as indicated by both PurpleAir data and EPA regulatory monitors. We also found that the impact of traffic and land use factors on PM 2.5 concentrations became more consist

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Author

Tianjun Lu; Dulce A. Garcia; Armando Garcia; Yisi Liu

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Environmental Science (Physical Sciences)