American Association for Aerosol Research - Abstract Submission

AAAR 31st Annual Conference
October 8-12, 2012
Hyatt Regency Minneapolis
Minneapolis, Minnesota, USA

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Spatial Distribution of Black Carbon, Polycyclic Aromatic Hydrocarbons and Volatile Organic Compounds During the Wintertime in Greater Pittsburgh Area

YI TAN, Rawad Saleh, Eric Lipsky, Albert A. Presto, Neil Donahue, Allen Robinson, Carnegie Mellon University

     Abstract Number: 754
     Working Group: Urban Aerosols

Abstract
Pittsburgh’s air quality is affected by a complex combination of local industrial and commercial sources, motor vehicles, topography (e.g. river valleys) and regional transport. To better understand the temporal-spatial distribution of air pollution in Pittsburgh, we developed a mobile measurement platform to characterize a suite of air pollutants (black carbon, particle-bound polycyclic aromatic hydrocarbons, benzene, and toluene). During the 2011/2012 winter, 42 mobile sites were sampled in three different sessions (afternoons/evenings, mornings, and midnights): 38 sites were randomly sampled for one hour in each session and 4 sites were sampled multiple times only in the mornings. One fixed site was continuously monitored for 5 days. CMU campus was monitored for the rest of the time. Pollutant concentrations were influenced by the combination of meteorology, terrain (e.g. valleys), traffic (e.g. buses) and industrial sources. Meteorology conditions and point sources controlled background concentrations at sampling sites, while local traffic caused strong spikes. Highest concentrations were observed in the mornings due to the combination of meteorology and traffic. Measurements were compared with 2005 NATA predictions. Predicted concentrations were generally within a factor of 2 of measured values except for PAH. PAH concentrations near industrial facilities were significantly over-predicted by NATA, possibly caused by large changes in emissions. However, predictions (census tract level) did not capture the measured spatial variation of pollutants. Large spatial variations within census tracts potentially contributed to this discrepancy.