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Many contaminated sites have mixed plumes or contaminants of concern from multiple potential sources. Examples of mixed plumes could include mixed free phase petroleum plumes (e.g. condensate) or polycyclic aromatic hydrocarbons (PAHs) from crude oil spills mixing with upstream or local anthropogenic sources (storm water runoff) of PAHs in sediments.
There are several advanced statistical techniques that can be used to determine the number and different sources of contaminant present on the site. In addition, these statistical tools can also apportion the amount of contaminants in each sample, thereby allowing liability to be distributed according the chemistry of the contaminants and those responsible for the release. Apportionment is important for litigious cases as it allows the calculation of who should pay for what portion of the cleanup.
Tools using positive matrix factorization (PMF) have been developed by US EPA but are no longer being supported are still publicly available to use. These techniques can be applied to many different chemical mixtures such as condensates or mixed petroleum hydrocarbon plumes. We have successfully applied the technique to PAHs from sediment data to allocate the source of the PAHs in the sediments to sources identified by the models. Unfortunately, these models are not definitive and provide multiple conclusions depending on their starting point which can make interpretation difficult and sometimes questionable, especially for litigation proceedings.
This presentation provides a summary of statistical tools used for chemical fingerprinting as well as the use of PMF and Bayesian modelling in order to provide some guidance on model usage for contaminant apportionment. The models need to be applied conservatively and require chemistry interpretation to elucidate what end members have been identified by the model and if those end members make sense. The models will be applied to a real case study scenarios to demonstrate their application.
Lawyers, regulators and environmental professionals involved in spill monitoring and liability determination will find this presentation educational in how these statistical models are able to determine sources and amounts of those sources of contaminants on site.