AAAR 37th Annual Conference October 14 - October 18, 2019 Oregon Convention Center Portland, Oregon, USA
Abstract View
Near-Source Spatial Extents and Socio-Economic Disparity in Urban Air Pollution Exposure
RISHABH SHAH, Ellis Shipley Robinson, Peishi Gu, Joshua Apte, Allen Robinson, Albert A. Presto, Carnegie Mellon University
Abstract Number: 322 Working Group: Aerosol Exposure
Abstract Primary carbonaceous aerosols (PCA) e.g., cooking organic aerosol (COA), hydrocarbon-like OA (HOA), and black carbon contribute ~ 50% mass of urban fine particulate matter, and have large spatial variabilities, exerting adverse health effects. Different intra-urban neighborhoods have different socio-economic features, and thus neighborhood-scale air quality impacts of restaurants and highways may result in certain socio-economic groups being exposed to higher pollutant concentrations. Our objective is to: a) characterize spatial extents to which urban sources influence PCA concentrations, and b) examine the socio-economic disparities in PCA exposure.
We use high- spatial-resolution data from mobile aerosol mass spectrometry measurements in Oakland CA and Pittsburgh PA. By binning our measurements into “distance-from-source” bins, and using a simple power law model, we are able to quantify distance-decay patterns of PCA e.g., decay of COA concentrations with distance from restaurants. We calculate characteristic length-scales of influence (df) of restaurants in Oakland and Pittsburgh to be ~ 150 and 450 m, respectively. The larger df in Pittsburgh is explained by its larger density of restaurants. Similarly, we calculate df for highways.
Socio-economic analyses of census tract data reveals minor disparities in exposure to highway emissions, but large disparities in exposure to COA concentrations near restaurants. In areas strongly influenced by cooking emissions (within df meters of restaurants), poverty is 1.2× higher, and household income is 0.7× lower relative to uninfluenced areas, suggesting that with poor people are far more likely to be exposed to near-source COA enhancements than prosperous people. Further, we find large racial-ethnic disparities in COA exposure: White (-1%), Black (2%), Hispanic (8%), Asian (12%), Other (5%). While we will perform additional analyses, preliminary results indicate that non-White population in both Oakland and Pittsburgh is exposed to higher-than-average COA concentrations, while White population is exposed to equal or below average COA levels.