PARENT SESSION
PW16 - Atmopheric Fate Processes
Wednesday, 20 November 2002
8:00 AM to 6:30 PM
Exhibit Hall
(P901) Source apportionment of polycyclic aromatic hydrocarbons and trace metals in New Jersey air.
Gigliotti, Cari*,1, Offenberg, John1, Lee, Jong Hoon1, Reinfelder, John1, Turpin, Barbara1, Eisenreich, Steven1,2, 1 Rutgers University, New Brunswick, NJ, USA2 Joint Research Center: Institute for Environment and Sustainability, Ispra, Varese, Italy
ABSTRACT- To effectively begin the process of controlling emissions of hazardous air pollutants, the first step must be to identify those sources contributing to the burden in the atmosphere. A least-squares statistical technique called Positive Matrix Factorization (PMF) has been employed to identify the dominant sources of polycyclic aromatic hydrocarbon (PAH) emissions in New Jersey. There exist numerous strengths associated with PMF over more commonly applied source apportionment techniques, such as Principal Components Analysis coupled with Multiple Linear Regression (PCA-MLR). PMF takes into account the uncertainties associated with individual data points. The non-negativity constraint inherent in PMF is more appropriate for handling data in units of concentration, than are PCA-based models that produce meaningless negative factors. PMF can handle missing values, values below detection limits, and large "outlier" values that often occur in environmental data, all of which can diminish the statistical power of PCA-MLR. The concentration data is derived from the New Jersey Atmospheric Deposition Network (NJADN) that has established a comprehensive database for concentrations of hazardous air pollutants including PAHs, PCBs, trace metals, and organochlorine pesticides at multiple sites around the state of New Jersey. Because PAH species are not unique tracers of specific combustion-related sources, trace metals have been incorporated into the model to aid in source identification of motor vehicles, natural gas and oil, resuspended soil/road dust, coal, and wood.
Key words: PAHs, source apportionment, Positive Matrix Factorization, trace metals