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Source identification of PM2.5 in an arid Northwest U.S. City by positive matrix factorization
Authors:Eugene Kim  Timothy V Larson  Philip K Hopke  Chris Slaughter  Lianne E Sheppard  Candis Claiborn
Abstract:Spokane, WA is prone to frequent particulate pollution episodes due to dust storms, biomass burning, and periods of stagnant meteorological conditions. Spokane is the location of a long-term study examining the association between health effects and chemical or physical constituents of particulate pollution. Positive matrix factorization (PMF) was used to deduce the sources of PM2.5 (particulate matter ≤2.5 μm in aerodynamic diameter) at a residential site in Spokane from 1995 through 1997. A total of 16 elements in 945 daily PM2.5 samples were measured. The PMF results indicated that seven sources independently contribute to the observed PM2.5 mass: vegetative burning (44%), sulfate aerosol (19%), motor vehicle (11%), nitrate aerosol (9%), airborne soil (9%), chlorine-rich source (6%) and metal processing (3%). Conditional probability functions were computed using surface wind data and the PMF deduced mass contributions from each source and were used to identify local point sources. Concurrently measured carbon monoxide and nitrogen oxides were correlated with the PM2.5 from both motor vehicles and vegetative burning.
Keywords:Source apportionment  Receptor modeling  Positive matrix factorization  PM2  5  Conditional probability function
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