GSTDTAP  > 资源环境科学
DOI10.1289/EHP7679
Assessing the Distribution of Air Pollution Health Risks within Cities: A Neighborhood-Scale Analysis Leveraging High-Resolution Data Sets in the Bay Area, California
Veronica A. Southerland; Susan C. Anenberg; Maria Harris; Joshua Apte; Perry Hystad; Aaron van Donkelaar; Randall V. Martin; Matt Beyers; Ananya Roy
2021-03-31
发表期刊Environmental Health Perspectives
出版年2021
英文摘要

Abstract

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 2.5μm in aerodynamic diameter (PM2.5)] using epidemiologically derived health impact functions. We compared geographic distributions of pollution-attributable 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); NO2county mean=38 (95% CI: 11, 64); PM2.5CBG mean=59 (95% CI: 40, 77); and PM2.5county mean=55 (95% CI: 37, 71)].

Discussion:

Air pollutant-attributable health burdens varied substantially between neighborhoods, driven by spatial variation in pollutant concentrations and disease rates. https://doi.org/10.1289/EHP7679

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文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/320899
专题资源环境科学
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Veronica A. Southerland,Susan C. Anenberg,Maria Harris,et al. Assessing the Distribution of Air Pollution Health Risks within Cities: A Neighborhood-Scale Analysis Leveraging High-Resolution Data Sets in the Bay Area, California[J]. Environmental Health Perspectives,2021.
APA Veronica A. Southerland.,Susan C. Anenberg.,Maria Harris.,Joshua Apte.,Perry Hystad.,...&Ananya 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.Environmental Health Perspectives.
MLA Veronica A. Southerland,et al."Assessing the Distribution of Air Pollution Health Risks within Cities: A Neighborhood-Scale Analysis Leveraging High-Resolution Data Sets in the Bay Area, California".Environmental Health Perspectives (2021).
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