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

Syahidah A Muhammad,Russell D Frew,Alan R Hayman

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 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.

Highlights

Compound-specific isotopic analysis (CSIA) is a technique that is becoming increasingly popular as a forensic tool to measure stable isotope composition of chemical compounds, such as hydrocarbons, which can be likened to fingerprinting at the molecular level
A large population of commercial diesel fuels obtained from various areas in the South Island of New Zealand was included in the data set to rule out statistical coincidence as well to put the data into context providing an informed assessment of the analysis
Discrimination of the diesel samples into groups was evident by comparing the subtle differences in the stable isotope values of the alkane compounds using multivariate statistical analyses such as principal component analysis (PCA) and hierarchical clustering analysis (HCA)

Summary

Introduction

Compound-specific isotopic analysis (CSIA) is a technique that is becoming increasingly popular as a forensic tool to measure stable isotope composition of chemical compounds, such as hydrocarbons, which can be likened to fingerprinting at the molecular level. From a forensic perspective, it is important to infer a link between a sample to a suspected source(s) by obtaining chemical information from both data sets or to differentiate the sample in question from the other samples of known origin, i.e., a population study where an informed assessment can be made by obtaining the profiles of the sample population to provide context for the data. Stable isotope fingerprinting provides the resolution to the question of whether two compounds or substances are distinguishable, i.e., un-related. If the two samples are indistinguishable this supports the hypothesis that they are related. With the help of stable isotope fingerprinting, forensic scientists are able to support inferences to link a person to an event, a crime scene, or a criminal organization, based on a unique characteristic of some physical evidence. To have methods to unambiguously characterize, identify and assign sources is key to withstand the legal scrutiny in the court of law

Objectives

Methods

Results

Conclusion