Open AccessSocio-economic disparities in exposure to urban restaurant emissions are larger than for traffic
Author(s) -
Rishabh U. Shah,
Elmer Robinson,
Peishi Gu,
Joshua S. Apte,
Julian Marshall,
Allen L. Robinson,
Albert A. Presto
Publication year - 2020
Publication title -
environmental research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.37
H-Index - 124
ISSN - 1748-9326
DOI - 10.1088/1748-9326/abbc92
Subject(s) - downtown , geography , poverty , ethnic group , census , socioeconomics , agricultural economics , environmental science , business , economic growth , demography , economics , political science , population , sociology , archaeology , law
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.