AAAR 34th Annual Conference
October 12 - October 16, 2015
Hyatt Regency
Minneapolis, Minnesota, USA
Abstract View
Spatial Patterns and Environmental Justice of Traffic Related Pollutants in Pittsburgh, PA
Yi Tan, Timothy Dallmann, Allen Robinson, ALBERT A. PRESTO, Carnegie Mellon University
Abstract Number: 57 Working Group: Aerosol Exposure
Abstract Our mobile monitoring campaign in Pittsburgh, PA showed substantial spatial variability of traffic related pollutants. The highly time resolved data indicated that pollutant plumes from high emitting vehicles (HEVs) contributed a disproportionately large fraction of the on-road exposures of particle-bound polycyclic aromatic hydrocarbons (PB-PAH) and black carbon (BC). Pollutant concentrations measured at the 42 mobile monitoring sites were the sum of the contribution of HEVs and the non-plume background. In this study, we aimed to develop novel statistical models to understand spatial patterns and environmental justice of PB-PAH and BC. The model consist of a plume layer that described the near road decay of emissions from high emitting vehicles using kernel interpolation, and a background layer that predicted the spatial pattern of the non-plume background using land use regression (LUR). The performance of models was examined using measurements from 36 hold-out validation sites which covered the outer suburbs of Pittsburgh. We employed pollutant concentrations at each house and its fair market value (FMV) to understand environmental justice in residential outdoor exposure. The two-layer model described 76% of PB-PAH variation and 61% of BC variation. The plume layer performed well at validation sites, but the background layer showed little transferability due to the large difference in land use between the city and outer suburbs. On average, HEVs contributed at least 32% of residential outdoor PB-PAH and 14% of BC. Pollutant concentrations at houses with FMV lower than $20k were slightly higher (7% for PB-PAH and 10% for BC) than houses with FMV in the top 10th percentile. The inequality was not driven by emissions from HEVs. The two-layer model developed in this work better predicted pollutant spatial patterns than traditional models. The model indicated that controlling emissions from HEVs could considerably reduce residential outdoor exposure to PB-PAH and BC.