Past oil spills (Exxon Valdez, Selendang Ayu, and Deepwater Horizon) have taught us that oil spills will occur, that oil will linger (approaching 25 years with the Exxon Valdez spill), and that identification of the source oil will be complicated and controversial. Oil spills in the Arctic will be no different. An increasing number of vessel operations, discovery wells, and natural oil seeps ensure there will plenty of contaminated material to analyze, and source identification in those oil spills will likely be contested.
Auke Bay Laboratories Habitat and Marine Chemistry Program has made strides in the forensic chemistry of identifying hydrocarbon sources, and much of that progress depends on mathematical modeling. Chemistry provides the primary data; we now have five analytical “streams” that quantify 100 different hydrocarbons that include polynuclear aromatic hydrocarbons (PAH), alkane hydrocarbons, and biomarkers such as hopanes, terpanes, and steranes. Recent progress has been in the mathematical modeling that follows chemical analysis. Together these analytical and mathematical measures are required to separate multiple anthropomorphic and natural organic sources.
Principal components analysis (PCA) is a mathematical strategy proving useful in source identification. Applied to the 2004 Selendang Ayu spill in the Aleutian Islands, PCA of hopanes and steranes distinguished all known oil sources and provided evidence of the environmental stability of these compounds. For PAHs, and separately alkanes, PCA analysis provided evidence of weathering (thermodynamically controlled shifts in composition) and clearly distinguished oiled sediment from reference sediment.
A second mathematical approach proving useful is direct comparison of the composition of stable compounds (those highly resistant to degradation) from known sources to composition of unknown samples. For example, hopane composition can be quantitatively compared between known sources and field samples and has allowed definitive identification of hydrocarbon sources in sediment.
A third mathematical approach useful in understanding sample conditions is a pattern-recognition algorithm designed to distinguish petrogenic (oil) and pyrogenic (fire) sources. This model works despite weathering and has been used on samples from Exxon Valdez and Deepwater Horizon spills.
It is not enough to measure the quantities of hydrocarbons in environmental samples; their source must also be identified. Collectively, chemical analysis followed by the mathematical modeling allows us to identify the source that contributes hydrocarbons to an unknown sample. In the Arctic we have the luxury of collecting and archiving near-shore samples before development proceeds. In the future, these samples will allow us to place a numerical value on what is meant by the term “pristine” and point to the naturally-occurring sources of environmental hydrocarbons.
