Assessing the Distribution of Air Pollution Health Risks within Cities: A Neighborhood-Scale Analysis Leveraging High-Resolution Data Sets in the Bay Area, California

Southerland, V.A., S. Anenberg, M. Harris, J. Apte, P. Hystad, A. van Donkelaar, R.V. Martin, M. Beyers, and A. Roy (2021), Assessing the Distribution of Air Pollution Health Risks within Cities: A Neighborhood-Scale Analysis Leveraging High-Resolution Data Sets in the Bay Area, California, Research A Section 508-conformant HTML version of this article, doi:10.1289/EHP7679.
Abstract

Alameda County Public Health Department, Oakland, California, USA BACKGROUND: Air pollution-attributable disease burdens reported at global, country, state, or county levels mask potential smaller-scale geographic heterogeneity driven by variation in pollution levels and disease rates. Capturing within-city variation in air pollution health impacts is now possible with high-resolution pollutant concentrations. OBJECTIVES: We quantified neighborhood-level variation in air pollution health risks, comparing results from highly spatially resolved pollutant and disease rate data sets available for the Bay Area, California. METHODS: We estimated mortality and morbidity attributable to nitrogen dioxide (NO2 ), black carbon (BC), and fine particulate matter [PM ≤2:5 lm in aerodynamic diameter (PM2:5 )] using epidemiologically derived health impact functions. We compared geographic distributions of pollutionattributable risk estimates using concentrations from a) mobile monitoring of NO2 and BC; and b) models predicting annual NO2 , BC and PM2:5 concentrations from land-use variables and satellite observations. We also compared results using county vs. census block group (CBG) disease rates. RESULTS: Estimated pollution-attributable deaths per 100,000 people at the 100-m grid-cell level ranged across the Bay Area by a factor of 38, 4, and 5 for NO2 [mean = 30 (95% CI: 9, 50)], BC [mean = 2 (95% CI: 1, 2)], and PM2:5 , [mean = 49 (95% CI: 33, 64)]. Applying concentrations from mobile monitoring and land-use regression (LUR) models in Oakland neighborhoods yielded similar spatial patterns of estimated grid-cell–level NO2 -attributable mortality rates. Mobile monitoring concentrations captured more heterogeneity [mobile monitoring mean = 64 (95% CI: 19, 107) deaths per 100,000 people; LUR mean = 101 (95% CI: 30, 167)]. Using CBG-level disease rates instead of county-level disease rates resulted in 15% larger attributable mortality rates for both NO2 and PM2:5 , with more spatial heterogeneity at the grid-cell–level [NO2 CBG mean = 41 deaths per 100,000 people (95% CI: 12, 68); NO2 county mean = 38 (95% CI: 11, 64); PM2:5 CBG mean = 59 (95% CI: 40, 77); and PM2:5 county mean = 55 (95% CI: 37, 71)]. DISCUSSION: Air pollutant-attributable health burdens varied substantially between neighborhoods, driven by spatial variation in pollutant concentra-

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