Compound-specific isotope analysis of diesel fuels in a forensic investigation

Compound-specific isotope analysis (CSIA) offers great potential as a tool to provide chemical evidence in a forensic investigation. Many attempts to trace environmental oil spills were successful where isotopic values were particularly distinct. However, difficulties arise when a large data set is analyzed and the isotopic differences between samples are subtle. In the present study, discrimination of diesel oils involved in a diesel theft case was carried out to infer the relatedness of the samples to potential source samples. This discriminatory analysis used a suite of hydrocarbon diagnostic indices, alkanes, to generate carbon and hydrogen isotopic data of the compositions of the compounds which were then processed using multivariate statistical analyses to infer the relatedness of the data set. The results from this analysis were put into context by comparing the data with the δ13C and δ2H of alkanes in commercial diesel samples obtained from various locations in the South Island of New Zealand. Based on the isotopic character of the alkanes, it is suggested that diesel fuels involved in the diesel theft case were distinguishable. This manuscript shows that CSIA when used in tandem with multivariate statistical analysis provide a defensible means to differentiate and source-apportion qualitatively similar oils at the molecular level. This approach was able to overcome confounding challenges posed by the near single-point source of origin, i.e., the very subtle differences in isotopic values between the samples

Forensic differentiation of diesel fuels using hydrocarbon isotope fingerprints

Abstract Compound-specific isotope analysis (CSIA) is fast becoming an important tool to provide chemical evidence in a forensic investigation. Attempts to trace environmental oil spills were successful where isotopic values were particularly distinct. However, difficulties arise when a large dataset is analyzed and the isotopic differences between samples are subtle. Thus, this study intends to demonstrate any linkages between diesel fuels in a large number of datasets where subtlety in the isotopic values is accentuated by the near single-point source of origin. Diesel fuels were obtained from various locations in the South Island of New Zealand. Aliquots of these samples were diluted with n-pentane and subsequently analyzed with gas chromatography-isotope ratio mass spectrometry (GC-IRMS) for carbon and hydrogen isotope values. The data obtained were subjected to principal component analysis (PCA) and hierarchical clustering. A wide range of δ13C and δ2H values were determined for the ubiquitous alkane compounds (the greatest values being −4.5‰ and −40‰, respectively). Based on the isotopic character of the alkanes it is suggested that diesel fuels from different locations were distinguishable and that the key components in the differentiation are the δ2H values of the shorter chain-length alkanes. However, while the stable isotope measurements may provide information to classify a sample at a broad scale, much more detailed information is required on the temporal and spatial variability of diesel compositions. The subtle differences of the stable isotope values within the alkanes of different diesel fuels highlighted the power of CSIA as a means of differentiating petroleum products of different origins, even more so when two or more stable isotopes data are combined. This paper shows that CSIA when used in tandem with multivariate statistical methods can provide suitable tools for source apportionment of hydrocarbons by demonstrating a straightforward approach, thus eliminating lengthy analytical processes

A Review of Pyrene Bioremediation Using <i>Mycobacterium</i> Strains in a Different Matrix

Polycyclic aromatic hydrocarbons are compounds with 2 or more benzene rings, and 16 of them have been classified as priority pollutants. Among them, pyrene has been found in higher concentrations than recommended, posing a threat to the ecosystem. Many bacterial strains have been identified as pyrene degraders. Most of them belong to Gram-positive strains such as Mycobacterium sp. and Rhodococcus sp. These strains were enriched and isolated from several sites contaminated with petroleum products, such as fuel stations. The bioremediation of pyrene via Mycobacterium strains is the main objective of this review. The scattered data on the degradation efficiency, formation of pyrene metabolites, bio-toxicity of pyrene and its metabolites, and proposed degradation pathways were collected in this work. The study revealed that most of the Mycobacterium strains were capable of degrading pyrene efficiently. The main metabolites of pyrene were 4,5-dihydroxy pyrene, phenanthrene-4,5-dicarboxylate, phthalic acid, and pyrene-4,5-dihydrodiol. Some metabolites showed positive results for the Ames mutagenicity prediction test, such as 1,2-phenanthrenedicarboxylic acid, 1-hydroxypyrene, 4,5-dihydropyrene, 4-phenanthrene-carboxylic acid, 3,4-dihydroxyphenanthrene, monohydroxy pyrene, and 9,10-phenanthrenequinone. However, 4-phenanthrol showed positive results for experimental and prediction tests. This study may contribute to enhancing the bioremediation of pyrene in a different matrix