Forensic Investigations of Diesel Oil Spills in the Environment Using Comprehensive Two-Dimensional Gas Chromatography-High Resolution Mass Spectrometry and Chemometrics: New Perspectives in the Absence of Recalcitrant Biomarkers.

Forensic investigations of oil spills aim to find the responsible source(s) of the spill. Oil weathering processes change the chemical composition of the spilled oil and make the matching of oil spill samples to potential sources difficult. Diesel oil spill cases are more challenging, because biomarkers recalcitrant to long-term weathering are absent. We developed and tested a new method for the analysis and matching of diesel oil spills using two-dimensional gas chromatography-high resolution mass spectrometry (GC × GC - HRMS) and 2D-CHEMSIC (2-Dimensional CHEMometric analysis of Selected Ion Chromatograms), an extension of the CHEMSIC method to GC × GC data. The 2D-CHEMSIC performs pixel-based analysis using chemometrics on concatenated sections of 2D extracted ion chromatograms to assess the overall chemical variability of the samples, with potential applications for matching spill-source pairs in forensic investigations. The method was tested on samples from a number of diesel oil spill cases, (i) distinguishing chemically similar source diesels, (ii) investigating weathering effects on spill samples to determine type and degree of weathering, and (iii) improving the matching of diesel oil spills affected by weathering. Positive matches for spill-source pairs were identified after excluding the signals from the hydrocarbons most susceptible to evaporation, and photo-oxidized spills were also matched due to the presence of unaffected hydrocarbons. Forensic diagnostics obtained by the 2D-CHEMSIC were validated by the conventional CEN-Tr method.

Optimizing loop-type cryogenic modulation in comprehensive two-dimensional gas chromatography using time-variable combination of the dual-stage jets for analysis of crude oil.

The enhanced chromatographic capability of the comprehensive two-dimensional gas chromatography (GC×GC) has already found several applications in analytical chemistry comprising complex samples. However, setting the appropriate chromatographic conditions that maximize sensitivity and separation efficiency in GC×GC may be more difficult than in conventional one-dimension gas chromatography, mainly due to the additional parameters strictly related to the modulation. Loop-type cryogenic modulators have been currently used for crude oil analysis using GC×GC, requiring sometimes a laborious try-and-error procedure to properly tune the dual-jets elapsed times on modulation. In this work, the advantages of choosing a time-variable combination of cold and hot jets pulses in a loop-type cryogenic modulator is presented when performing the fingerprinting analysis of crude oils using GC×GC-QMS, contrary to the conventional procedure based on a single combination for the dual-stage jets. A design of experiments approach is proposed to most effectively optimize the time-variable combination of the dual-jets elapsed times while modulating the wide hydrocarbons range along the GC×GC analysis. The most abundant classes of hydrocarbons contained in the maltenes fraction of a crude oil sample, such as paraffins, aromatics, steranes and hopanes were successfully resolved.

Discriminating Brazilian crude oils using comprehensive two-dimensional gas chromatography-mass spectrometry and multiway principal component analysis.

The geochemical characterization of petroleum is an essential task to develop new strategies and technologies when analyzing the commercial potential of crude oils for exploitation. Due to the chemical complexity of these samples, the use of modern analytical techniques along with multivariate exploratory data analysis approaches is an interesting strategy to extract relevant geochemical characteristics about the oils. In this work, important geochemical information obtained from crude oils from different production basins were obtained analyzing the maltene fraction of the oils by comprehensive two-dimensional gas chromatography coupled to quadrupole mass spectrometry (GC×GC-QMS), and performing multiway principal component analysis (MPCA) of the chromatographic data. The results showed that four MPC explained 93.57% of the data variance, expressing mainly the differences on the profiles of the saturated hydrocarbon fraction of the oils (C13-C18 and C19-C30n-alkanes and the pristane/phytane ratio). The MPC1 grouped the samples severely biodegraded oils, while the type of the depositional paleoenvironments of the oils and its oxidation conditions (as well as their thermal maturity) could be inferred analysing others relevant MPC. Additionally, considerations about the source of the oil samples was also possible based on the overall distribution of relevant biomarkers such as the phenanthrene derivatives, tri-, tetra- and pentacyclic terpanes.