Assessment of oil contamination in the marine environment by pattern recognition analysis of paraffinic hydrocarbon content of mussels

Abstract

Data on the paraffinic hydrocarbon content of mussels ( Mytilus edulis and M. califomianus) were analyzed statistically in an attempt to assess oil contamination of several aquatic areas of the greater Puget Sound basin in the State of Washington. The mussels were collected quarterly over a period of two years from ten locations. Fundamental statistical treatment of the data did not reveal meaningful trends. Application of pattern recognition techniques to the hydrocarbon data set allowed the mussel samples to be successfully classified into groups, from areas near known sources of potential pollution or from areas remote from known pollution. Several samples however, could not be grouped consistently as either from contaminated or uncontaminated sites. In addition, the mussels from a particular area could be separated as to season of sampling. Seasonal variation in levels of individual paraffinic hydrocarbons were greater than annual changes. The n-C 16 hydrocarbon concentration was the most useful of the 34 features studied for establishing possible oil contamination of the areas. The n-C 16 hydrocarbon content was also used successfully to detect oil spills and to define uncontaminated locations in Puget Sound.