Abstract
The source of crude oils and petroleum products released into navigable waterways and shipping lanes is not always known. Thus, the defensible identification of spilled crude oils and petroleum products and their correlation to suspected sources is a critical part of many oil spill assessments. Quantitative “fingerprinting” analysis, when evaluated using straightforward statistical and numerical analyses, provides a defensible means to differentiate among qualitatively similar oils and provides the best assessment of the source(s) for spilled oils. Polycyclic aromatic hydrocarbon (PAH) and petroleum biomarker concentration data are a particularly useful quantitative measure that can benefit most oil spill investigations. In this paper the strategy and methodology for correlation analysis that relies upon quantitative gas chromatography/mass spectrometry operated in the selected ion monitoring mode (GC/MS-SIM) is demonstrated in a case study involving 66 candidate sources for a heavy fuel oil spill of unknown origin. The strategy includes identification of 19 chemical indices (out of 45 evaluated) based upon PAH's and biomarkers that were (1) independent of weathering; and (2) precisely measured, both of which are determined by statistical analysis of the data. The 19 chemical indices meeting these criteria are subsequently analysed using principal component analysis (PCA), which helps to determine defensibly the “prime suspects” for the oil spill under investigation. The strategy and methodology described, which combines statistical and numerical analysis of quantitative chemical data, can be adapted and applied to other environmental forensic investigations with the objective of correlating any form of contamination to its suspected sources.
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