Communities of color are disproportionately exposed to long-term and short-term PM2.5 in metropolitan America

Timothy W Collins; Sara E Grineski; Yasamin Shaker; Casey J Mullen

doi:10.1016/j.envres.2022.114038

Communities of color are disproportionately exposed to long-term and short-term PM_2.5 in metropolitan America

Environ Res. 2022 Nov;214(Pt 4):114038. doi: 10.1016/j.envres.2022.114038. Epub 2022 Aug 10.

Authors

Timothy W Collins¹, Sara E Grineski², Yasamin Shaker², Casey J Mullen²

Affiliations

¹ Department of Geography, University of Utah; 260 Central Campus Dr., Rm. 4625, Salt Lake City, UT, 84112, USA; Center for Natural & Technological Hazards, University of Utah; 260 Central Campus Dr., Rm. 4625, Salt Lake City, UT, 84112, USA. Electronic address: tim.collins@geog.utah.edu.
² Center for Natural & Technological Hazards, University of Utah; 260 Central Campus Dr., Rm. 4625, Salt Lake City, UT, 84112, USA; Department of Sociology, University of Utah; 380 S 1530 E, Rm. 301, Salt Lake City, UT, 84112, USA.

PMID: 35961542
DOI: 10.1016/j.envres.2022.114038

Abstract

We conducted a novel investigation of neighborhood-level racial/ethnic exposure disparities employing measures aligned with long-term and short-term PM_2.5 air pollution benchmarks across metropolitan contexts of the contiguous United States, 2012-2016. We used multivariable generalized estimating equations (GEE) to quantify PM_2.5 exposure disparities based on the census tract composition of people of color (POC) and POC groups (Hispanic/Latina/x/o, Black, Asian). We examined eight census tract-level measures of longer-to-shorter term exposures derived from data on modeled daily ambient PM_2.5 concentrations. We found associations between increased POC composition and greater exposure to all PM_2.5 measures, with associations strengthening across measures of longer-to-shorter term exposures. In a GEE with a negative binomial distribution, a standard deviation increase in POC composition predicted a 0.6% increase (incidence rate ratio (IRR): 1.006, 95% confidence interval (CI): 1.005-1.008) in the number of days PM_2.5 concentrations were ≥5 μg/m³ (longest-term benchmark). In a GEE with an inverse Gaussian distribution, a standard deviation increase in POC composition predicted a 0.110 μg/m³ (1.0%) increase (B: 0.110, 95% CI: 0.076-0.143) in mean PM_2.5 concentration. In GEEs with a negative binomial distribution, the effect of a standard deviation increase in POC composition on exposure strengthened to 2.6% (IRR:1.026, 95% CI:1.017-1.035), 3.4% (IRR:1.034, 95% CI:1.022-1.047), 4.2% (IRR:1.042, 95% CI:1.025-1.058), 16.2% (IRR:1.162, 95% CI:1.117-1.210), 22.7% (IRR:1.227, 95% CI:1.137-1.325) and 28.3% (IRR:1.283, 95% CI:1.144-1.439) with respect to the number of days PM_2.5 concentrations were ≥10, 12, 15, 25, 35 and 55.5 μg/m³. POC group models indicated exposure disparities based on greater Hispanic/Latina/x/o, Asian, and Black composition. Evidence for stronger POC associations with shorter-term (higher concentration) PM_2.5 exceedances suggests that reducing PM_2.5 would attenuate racial/ethnic exposure disparities.

Keywords: Air quality; Environmental justice; PM(2.5) pollution; Race and ethnicity; Short-term exposure; United States.

MeSH terms

Air Pollutants* / analysis
Air Pollution* / analysis
Environmental Exposure / analysis
Humans
Particulate Matter / analysis
Racial Groups
United States

Substances

Air Pollutants
Particulate Matter