Most oil characterisation procedures are time consuming, labour intensive and utilise only part of the acquired chemical information. Oil spill fingerprinting with multivariate data processing represents a fast and objective evaluation procedure, where the entire chromatographic profile is used. Methods for oil classification should be robust towards changes imposed on the spill fingerprint by short-term weathering, i.e. dissolution and evaporation processes in the hours following a spill. We propose a methodology for the classification of petroleum products. The method consists of: chemical analysis; data clean-up by baseline removal, retention time alignment and normalisation; recognition of oil type by classification followed by initial source characterisation. A classification model based on principal components and quadratic discrimination robust towards the effect of short-term weathering was established. The method was tested successfully on real spill and source samples.
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