Multiscale spatial patterns of outdoor air pollution in California : drivers of variability and implications for exposure and environmental justice

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2021-04-06

Authors

Chambliss, Sarah Elisabeth

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Abstract

Exposure to air pollution causes diseases of the lungs, cardiovascular system, brain, and numerous other systems, and is a leading environmental health risk worldwide. The burden of air pollution exposure is not distributed evenly across the population of the United States, and often falls more heavily on low-income groups and people of color. An accurate understanding of how air pollution levels vary on multiple spatial scales is critical for shaping effective policies to improve air quality for the highest exposed communities. Pollutants with primary and secondary contributions like fine particulate matter (PM₂.₅) vary significantly within urban areas on length scales of 1 km but are influenced by emissions at scales of 100 km or more, while other pollutant categories exhibit strong near-source decay at length scales of 100 m. In this dissertation I apply two complementary approaches to assess multiscale spatial patterns for five health-relevant pollutants: PM₂.₅, black carbon (BC), ultrafine particles (UFP), nitrogen oxide (NO), and nitrogen dioxide (NO₂). Using a reduced-complexity chemical transport model I show that current emissions patterns lead to significant PM₂.₅ exposure disparity among racial-ethnic groups, income categories, and other socioeconomic groupings, driven by the systematically higher proximity to emissions from on-road mobile sources, industry, natural gas and petroleum development, and other major sources. To estimate exposure disparity for pollutants that vary at very fine spatial scales and follow difficult-to-model patterns driven by complex characteristics of the urban landscape (BC, UFP, NO, and NO₂), I use data collected via mobile monitoring to construct empirical air pollution maps for a variety of neighborhoods in the San Francisco Bay Area. These measurements show high exposure disparities both within and among racial-ethnic groups, with disparity in mean concentrations driven by differences in neighborhood background concentrations but higher within-group disparity driven by highly localized near-source gradients. I also assess sources of uncertainty in mobile monitoring-based mapping techniques. These complementary approaches provide a broad picture of causes of urban exposure disparity in California and can inform future mitigation measures.

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