title: Problems in the fingerprints based polycyclic aromatic hydrocarbons source apportionment analysis and a practical solution.
abstract: This work intended to explain the challenges of the fingerprints based source apportionment method for polycyclic aromatic hydrocarbons (PAH) in the aquatic environment, and to illustrate a practical and robust solution. The PAH data detected in the sediment cores from the Illinois River provide the basis of this study. Principal component analysis (PCA) separates PAH compounds into two groups reflecting their possible airborne transport patterns; but it is not able to suggest specific sources. Not all positive matrix factorization (PMF) determined sources are distinguishable due to the variability of source fingerprints. However, they constitute useful suggestions for inputs for a Bayesian chemical mass balance (CMB) analysis. The Bayesian CMB analysis takes into account the measurement errors as well as the variations of source fingerprints, and provides a credible source apportionment. Major PAH sources for Illinois River sediments are traffic (35%), coke oven (24%), coal combustion (18%), and wood combustion (14%).
authors.affiliation: Illinois Sustainable Technology Center, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA. Electronic address: yhzou2009@gmail.com.
authors.forename: Yonghong
authors.initials: Y
authors.lastname: Zou
authors.affiliation: Department of Geosciences, University of Wisconsin-Milwaukee, Milwaukee, WI 53211, USA.
authors.forename: Lixia
authors.initials: L
authors.lastname: Wang
authors.affiliation: Department of Civil and Environmental Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA.
authors.forename: Erik R
authors.initials: ER
authors.lastname: Christensen
mesh_terms: D001499:Bayes Theorem; D004784:Environmental Monitoring / Q000379:methods*; D019015:Geologic Sediments / Q000032:analysis* / Q000737:chemistry; D007087:Illinois; D008962:Models, Theoretical; D011084:Polycyclic Aromatic Hydrocarbons / Q000032:analysis*; D025341:Principal Component Analysis; D045483:Rivers / Q000737:chemistry; D014874:Water Pollutants, Chemical / Q000032:analysis*
chemical_list: D011084:Polycyclic Aromatic Hydrocarbons; D014874:Water Pollutants, Chemical
keywords: Bayesian; Fingerprints; Polycyclic aromatic hydrocarbons (PAHs); Positive matrix factorization (PMF); Principal component analysis (PCA); Source apportionment analysis