R8 AM Contamination Source Identification and Apportionment
Thursday, 17 November 2005: 8:00 AM - 11:40 AM in 331-332

(KAS-1118-433882) Molecular Marker Characterization and Source Partitioning of Processed Leaf Compost from the Northwest Region: An Environmental Forensics Approach.

KASSIM, Ph.D., T.¹, SIMONEIT, Ph.D., B.R.T.², ¹ Seattle University, Department of Civil and Environmental Engineering, P.O. Box 222000, Seattle, WA 98122-1090, USA² College of Oceanic and Atmospheric Sciences, Oregon State University, COAS Admin. Bldg. 104, Corvallis, OR 97331, USA

ABSTRACT- Composted deciduous leaves (CDLs) originating from various metropolitan cities in the Northwest region were collected and characterized in terms of their organic chemical contents, represented by their lipid molecular marker (MM) signatures. The distributions, chemical structures, and applicability of such lipid MMs in determining characteristic group(s) representative for CDL extracts are discussed in this paper using a multi-tracer environmental forensics MM approach. Several low molecular weight compounds were identified that represented a blend of diesel molecular markers. Traces of homologous long chain n-alkanes, CPI, unresolved complex mixture, and molecular markers such as pristane, phytane, tricyclic and tetracyclic terpanes, hopanes, steranes with a minor amounts of diasteranes were found to be the most suitable indicators to differentiate between petroleum hydrocarbon- from non petroleum hydrocarbon-containing CDL samples. On the other hand, high temperature thermogenic/pyrolytic derived compounds were indicated by a specific group of polycyclic aromatic hydrocarbons (PAHs). This group, ranging from phenanthrene to dibenzo(ae)pyrene with different alkyl-substituted PAH series, is considered to be combustion products from fossil fuel. Different terrestrial (i.e., natural) molecular markers were also characterized in all CDL samples, such as cholestane, stigmasterane, stigmast-4-en-3-one, stigmastan-3-one, stigmatan-7-one, cholesterol, and alpha and beta amyrane. Statistical analyses (extended Q-mode factor analysis and linear programming technique) were performed in order to examine the variations in the multi-tracer MM data set, group the data into specific groups, and find statistically significant associations (end members) in the data set to help assess and identify the different chemical sources and original compositions representing the Northwest CDL extracts.

Key words: leaf compost, molecular markers, forensic analysis, source partitioning