Assessing the distribution of air pollution health risks within cities: a neighborhood-scale analysis leveraging high resolution datasets in the Bay Area, California.
Year: 2020
Type: conference-abstract
Abstract: Background: Air pollution-attributable disease burdens are typically reported at country, state, or county levels, masking potential smaller scale geographic heterogeneity driven by non-uniform pollution levels and disease rates. Estimating the variation in air pollution health impacts within cities is now possible with high resolution pollutant concentrations derived from satellite remote sensing, modeling, and mobile monitoring. Objectives: We quantify neighborhood-level variation in air pollution health risks, using highly spatially resolved pollutant and disease rate datasets available for the Bay Area, California. Methods: We estimate mortality and morbidity attributable to nitrogen dioxide (NO2), black carbon (BC), and fine particulate matter (PM2.5) in the Bay Area using epidemiologically derived health impact functions. We compare geographic distributions of pollution-attributable risk estimates using pollutant concentrations from different sources: (1) mobile monitoring of NO2 and BC, covering roadways over a one-year period; and (2) models predicting annual NO2, BC and PM2.5 concentrations from land use variables and satellite observations, with full spatial coverage. We also compare the application of county versus census block group (CBG) level disease rates. Results: Across Bay Area counties, estimated pollution-attributable mortality rates (attributable deaths per 100,000 people) ranged by a factor 15, 13 and 8 for NO2, BC and PM2.5 (NO2 range=40-570, median=219; BC range=3-40, median=13; PM2.5 range=60-470, median=305). Applying concentrations from mobile monitoring and land use regression datasets resulted in similar spatial patterns of estimated NO2-attributable mortality rates, though the mobile monitoring concentrations yielded more spatial heterogeneity. Using CBG disease rates revealed spatial heterogeneity in estimated NO2 and PM2.5-attributable mortality rates that is masked when using county-level disease rates. Discussion: Estimated air pollutant attributable health burdens vary considerably between neighborhoods in the Bay Area, driven by spatial heterogeneity in both concentrations and disease rates. Future research should test the generalizability of these findings for other cities.
Source: ISEE Conference Abstracts
Language: English
Subfield: Health, Toxicology and Mutagenesis
Field: Environmental Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W3166633296