title: Source allocation by least-squares hydrocarbon fingerprint matching.
abstract: There has been much controversy regarding the origins of the natural polycyclic aromatic hydrocarbon (PAH) and chemical biomarker background in Prince William Sound (PWS), Alaska, site of the 1989 Exxon Valdez oil spill. Different authors have attributed the sources to various proportions of coal, natural seep oil, shales, and stream sediments. The different probable bioavailabilities of hydrocarbons from these various sources can affect environmental damage assessments from the spill. This study compares two different approaches to source apportionment with the same data (136 PAHs and biomarkers) and investigate whether increasing the number of coal source samples from one to six increases coal attributions. The constrained least-squares (CLS) source allocation method that fits concentrations meets geologic and chemical constraints better than partial least-squares (PLS) which predicts variance. The field data set was expanded to include coal samples reported by others, and CLS fits confirm earlier findings of low coal contributions to PWS.
authors.affiliation: W. A. Burns Consulting Services LLC, Houston, Texas, University of Wales-Bangor, Anglesey, UK USA. wburns@alum.mit.edu
authors.forename: William A
authors.initials: WA
authors.lastname: Burns
authors.forename: Stephen M
authors.initials: SM
authors.lastname: Mudge
authors.forename: A Edward
authors.initials: AE
authors.lastname: Bence
authors.forename: Paul D
authors.initials: PD
authors.lastname: Boehm
authors.forename: John S
authors.initials: JS
authors.lastname: Brown
authors.forename: David S
authors.initials: DS
authors.lastname: Page
authors.forename: Keith R
authors.initials: KR
authors.lastname: Parker
mesh_terms: D000413:Alaska; D001682:Biological Availability; D015415:Biomarkers; D002244:Carbon; D003031:Coal; D004784:Environmental Monitoring / Q000379:methods*; D006838:Hydrocarbons / Q000737:chemistry* / Q000493:pharmacokinetics; D016018:Least-Squares Analysis; D015233:Models, Statistical; D008962:Models, Theoretical; D011084:Polycyclic Aromatic Hydrocarbons / Q000032:analysis*; D014876:Water Pollution
chemical_list: D015415:Biomarkers; D003031:Coal; D006838:Hydrocarbons; D011084:Polycyclic Aromatic Hydrocarbons; D002244:Carbon