Uncovering the Fingerprints of Gasoline Residues: A Chromatographic and Chemometric Analyses of Burned Matrices in Malaysia for Forensic Intelligence
27 Pages Posted: 1 Mar 2023
Abstract
The difficulty in identifying accelerants in arson investigations is exacerbated by significant evaporation and weathering of the substance at high temperatures. Moreover, studies on chemicals fingerprints of ignitable liquid residues for determining the source of fire from tropical countries like Malaysia, experiencing high daily rainfall, temperature and humidity, remain unreported. Hence, this present research attempted to identify compounds that can be used for identification of the unburnt and burnt gasoline A and B residues exposed to tropical condition. In addition, utilization of the Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) for differentiating the unburnt experimental gasoline A and B, as well as the fire debris recovered after the complete burning using the same types of gasoline exposed to the Southwest and Northeast monsoons in Malaysia (at 3-9 hours after the cessation of burning) was made. The statistical models were tested using the fire debris exhibits from real arson cases, involving gasoline, kerosine and diesel. The gas chromatography-mass spectrometry (GC-MS) data revealed the presence of toluene, p-xylene, benzene, propyl-, benzene, 1-ethyl-2-methyl-, 1,3,5-trimethylbenzene and indane in all burnt matrices analysed, with significant variations observed for samples exposed to 9-hour interval (p<0.05). Moreover, results from the iterative approach revealed 90.0% to 98.0% of correct classification rate by the LDA. While the findings supported the combinatory use of chromatographic analysis with chemometrics for forensic discrimination of gasoline residues, fire investigators must be made aware of the potential loss of important compounds should the period of collection of evidence exceeded 9-hour post fire.
Keywords: arson, gasoline, monsoons, Principal Component Analysis, linear discriminant analysis, Malaysia
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