Socio-economic disparities in exposure to urban restaurant emissions are larger than for traffic

Bibliographic Data

ID15547867
AuthorsRishabh U Shah (0000-0002-4608-1972, Environmental Defense Fund), Ellis S Robinson (0000-0003-1695-6392, Johns Hopkins University), Peishi Gu (0000-0003-3519-7942, California Air Resources Board), Joshua S Apte (0000-0002-2796-3478, The University of Texas at Austin), Julian D Marshall (0000-0003-4087-1209, University of Washington), Allen L Robinson (0000-0002-1819-083X, Carnegie Mellon University), Albert A Presto (0000-0002-9156-1094, Carnegie Mellon University, corresponding author)
Year2020
Volume15
Issue11
Pages114039-114039
Publication date2020-09-29
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEnvironmental Research Letters (JOURNAL)
Journal identifiersISSN: 1748-9326 • E-ISSN: 1748-9326
PublisherIOP Publishing (PUBLISHER • GB)
DOI10.1088/1748-9326/abbc92
OpenAlexW3089425977
LanguageEN
Citations received5
References cited51

Restaurants and vehicles are important urban sources of particulate matter (PM). Due to the ubiquitous presence of these sources within cities, large variabilities in PM concentrations occur in source-rich environments (e.g. downtown), especially during times of peak activity such as meal times and rush hour. Due to intracity variations in factors such as racial-ethnic composition and economic status, we hypothesized that certain socio-economic groups living closer to sources are exposed to higher PM concentrations. To test this hypothesis, we coupled mobile PM measurements with census data in two midsize US cities: Oakland, CA, and Pittsburgh, PA. A novel aspect of our study is that our measurements are performed at a high (block-level) spatial resolution, which enables us to assess the direct relationship between PM concentrations and socio-economic metrics across different neighborhoods of these two cities. We find that restaurants cause long-term average PM enhancements of 0.1 to 0.3 μ g m −3 over length scales between 50 and 450 m. We also find that this PM pollution from restaurants is unevenly distributed amongst different socio-economic groups. On average, areas near restaurant emissions have about 1.5× people of color (African American, Hispanic, Asian, etc), 2.5× poverty, and 0.8× household income, compared to areas far from restaurant emissions. Our findings imply that there are socio-economic disparities in long-term exposure to PM emissions from restaurants. Further, these socio-economic groups also frequently experience acutely high levels of cooking PM (tens to hundreds of μ g m −3 in mass concentrations) and co-emitted pollutants. While there are large variations in socio-economic metrics with respect to restaurant proximity, we find that these metrics are spatially invariant with respect to highway proximity. Thus, any socio-economic disparities in exposure to highway emissions are, at most, mild, and certainly small compared to disparities in exposure to restaurant emissions

Agricultural economics · Business · Census · Downtown · Economic growth · Economics · Ethnic group · Geography · Political science · Population · Poverty · Socioeconomics · Sociology · Air Quality and Health Impacts · Environmental Science · Urban Transport and Accessibility · Vehicle emissions and performance · Demography

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