The comparison of two heavy fuel oils in composition and weathering pattern, based on IR, GC-FID and GC-MS analyses: application to the Prestige wreackage.

This paper compares the weathering patterns of two similar fuel oils: a fuel oil spilled after a ship accident (Prestige-Nassau, off the Galician coast -NW Spain-) and a fuel designed to cope with the numerous quests for samples to carry out scientific studies (IFO). Comparative studies were made to evaluate the capability of common fingerprinting analytical techniques to differentiate the fuels, as well as their capabilities to monitor their weathering. The two products were spilled under controlled conditions during ca. four months to assess how they evolved on time. Mid-IR spectrometry and gas chromatography (flame ionization and mass spectrometry detectors) were used. IR indexes related to total aromaticity, type of substituents (branched or linear chains) and degree of aromatic substitution reflected well the differences between the fuels during weathering. Regarding the chromatographic measurements, the n-alkanes became highly reduced for both fuel oils and it was found that the PAHs of the synthetic fuel (IFO) were more resistant to weathering. Regarding biomarkers, the different profiles of the steranes, diasteranes and triaromatic steroids allowed for a simple differentiation amongst the two products. The %D2/P2 ratio differentiated both products whereas the %N3/P2 one ordered the samples according to the extent of their weathering.

Identification of fuel samples from the Prestige wreckage by pattern recognition methods.

A set of 34 worldwide crude oils, 12 distilled products (kerosene, gas oils, and fuel oils) and 45 oil samples taken from several Galician beaches (NW Spain) after the wreckage of the Prestige tanker off the Galician coast was studied. Gas chromatography with flame ionization detection was combined with chemometric multivariate pattern recognition methods (principal components analysis, cluster analysis and Kohonen neural networks) to differentiate and characterize the Prestige fuel oil. All multivariate studies differentiated between several groups of crude oils, fuel oils, distilled products, and samples belonging to the Prestige's wreck and samples from other illegal discharges. In addition, a reduced set of 13 n-alkanes out of 36, were statistically selected by Procrustes Rotation to cope with the main patterns in the datasets. These variables retained the most important characteristics of the data set and lead to a fast and cheap analytical screening methodology.

Identification of petroleum hydrocarbons using a reduced number of PAHs selected by Procrustes rotation.

Identifying petroleum-related products released into the environment is a complex and difficult task. To achieve this, polycyclic aromatic hydrocarbons (PAHs) are of outstanding importance nowadays. Despite traditional quantitative fingerprinting uses straightforward univariate statistical analyses to differentiate among oils and to assess their sources, a multivariate strategy based on Procrustes rotation (PR) was applied in this paper. The aim of PR is to select a reduced subset of PAHs still capable of performing a satisfactory identification of petroleum-related hydrocarbons. PR selected two subsets of three (C(2)-naphthalene, C(2)-dibenzothiophene and C(2)-phenanthrene) and five (C(1)-decahidronaphthalene, naphthalene, C(2)-phenanthrene, C(3)-phenanthrene and C(2)-fluoranthene) PAHs for each of the two datasets studied here. The classification abilities of each subset of PAHs were tested using principal components analysis, hierarchical cluster analysis and Kohonen neural networks and it was demonstrated that they unraveled the same patterns as the overall set of PAHs.

Development of a fast analytical tool to identify oil spillages employing infrared spectral indexes and pattern recognition techniques.

A fast analytical tool based on attenuated total reflectance mid-IR spectrometry is presented to evaluate the origin of spilled hydrocarbons and to monitor their fate on the environment. Ten spectral band ratios are employed in univariate and multivariate studies (principal components analysis, cluster analysis, density functions - potential curves - and Kohonen self organizing maps). Two indexes monitor typical photooxidation processes, five are related to aromatic characteristics and three study aliphatic and branched chains. The case study considered here comprises 45 samples taken on beaches (from 2002 to 2005) after the Prestige carrier accident off the Galician coast and 104 samples corresponding to weathering studies deployed for the Prestige's fuel, four typical crude oils and a fuel oil. The univariate studies yield insightful views on the gross chemical evolution whereas the multivariate studies allow for simple and straightforward elucidations on whether the unknown samples match the Prestige's fuel. Besides, a good differentiation on the weathering patterns of light and heavy products is obtained.