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Airborne exposures to polycyclic aromatic hydrocarbons (PAHs) are associated with adverse health outcomes. Because personal air measurements of PAHs are labor intensive and costly, spatial PAH exposure models are useful for epidemiological studies. However, few studies provide adequate spatial coverage to reflect intra-urban variability of ambient PAHs. In this study, we collected 39–40 weekly gas-phase PAH samples in southern California twice in summer and twice in winter, 2009, in order to characterize PAH source contributions and develop spatial models that can estimate gas-phase PAH concentrations at a high resolution. A spatial mixed regression model was constructed, including such variables as roadway, traffic, land-use, vegetation index, commercial cooking facilities, meteorology, and population density. Cross validation of the model resulted in an R2 of 0.66 for summer and 0.77 for winter. Results showed higher total PAH concentrations in winter. Pyrogenic sources, such as fossil fuels and diesel exhaust, were the most dominant contributors to total PAHs. PAH sources varied by season, with a higher fossil fuel and wood burning contribution in winter. Spatial autocorrelation accounted for a substantial amount of the variance in total PAH concentrations for both winter (56%) and summer (19%). In summer, other key variables explaining the variance included meteorological factors (9%), population density (15%), and roadway length (21%). In winter, the variance was also explained by traffic density (16%). In this study, source characterization confirmed the dominance of traffic and other fossil fuel sources to total measured gas-phase PAH concentrations while a spatial exposure model identified key predictors of PAH concentrations. Gas-phase PAH source characterization and exposure estimation is of high utility to epidemiologist and policy makers interested in understanding the health impacts of gas-phase PAHs and strategies to reduce emissions.

We describe spatial and temporal patterns of seven chemical elements commonly observed in fine particulate matter (PM) and thought to be linked to roadway emissions that were measured at residential locations in New York City (NYC). These elements, that is, Si, Al, Ti, Fe, Ba, Br, and black carbon (BC), were found to have significant spatial and temporal variability at our 10 residential PM(2.5) sampling locations. We also describe pilot study data of near-roadway samples of both PM(10-2.5) and PM(2.5) chemical elements of roadway emissions. PM(2.5) element concentrations collected on the George Washington Bridge (GWB) connecting NYC and New Jersey were higher that similar elemental concentration measured at residential locations. Coarse-particle elements (within PM(10-2.5)) on the GWB were 10-100 times higher in concentration than their PM(2.5) counterparts. Roadway elements were well correlated with one another in both the PM(2.5) and PM(10-2.5) fractions, suggesting common sources. The same elements in the PM(2.5) collected at residential locations were less correlated, suggesting either different sources or different processing mechanisms for each element. Despite the fact that these elements are only a fraction of total PM(2.5) or PM(10-2.5) mass, the results have important implications for near-roadway exposures where elements with known causal links to health effects are shown to be at elevated concentrations in both the PM(2.5) and PM(10-2.5) size ranges.