Affiliations 

  • 1 Department of Chemistry, University of Otago Dunedin, New Zealand ; Environmental Technology Division, School of Industrial Technology, Universiti Sains Malaysia Pulau Pinang, Malaysia ; Doping Control Centre, Universiti Sains Malaysia Pulau Pinang, Malaysia
  • 2 Department of Chemistry, University of Otago Dunedin, New Zealand ; Division of Nuclear Applications in Food and Agriculture, International Atomic Energy Agency Vienna, Austria
  • 3 Department of Chemistry, University of Otago Dunedin, New Zealand
Front Chem, 2015;3:12.
PMID: 25774366 DOI: 10.3389/fchem.2015.00012

Abstract

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 δ(13)C and δ(2)H 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.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.