Chemometric approach for the discrimination of petroleum based accelerants from fire debris

Abstract

Petroleum-based accelerants are commonly associated with arson-related fire. In most arson cases, accelerants such gasoline, kerosene and diesel used to increase the rate and intensity of fire. However, other petroleum based accelerants such as turpentine and thinner cannot be ignored because of their easy availability. These accelerants composed of hundreds of compounds that can make identification of fire debris very difficult. Furthermore, the complex nature of petroleum based accelerants pose a problem for the arson investigator to determine the origin of the fire and the cause of the fire. Therefore, correct identification of accelerants is crucial to arson investigation. The application of gas chromatography/mass spectrometry (GC/MS) and chemometric techniques for petroleum-based accelerant identification is presented in this study. Extraction of accelerant was done by using dynamic adsorption-elution headspace technique and analyzed using GC-FID and GC-MS. The petroleum based accelerants used in this study were gasoline, diesel, kerosene, turpentine and thinner. Chemometric approaches were employed to simplify data obtained by allowing them for more accurate classification to their respective groups. Principal component analysis (PCA), cluster analysis and soft independent modeling class analog analysis (SIMCA) were explored for their effectiveness in establishing accelerant groupings. This was done on normalized data of total ion chromatogram and peak areas which were obtained from GC-MS. The extraction of fire debris using the dynamic adsorption/elution technique was successful in isolating the accelerants compounds from the samples. Beside that, PCA and cluster analysis were successfully classify the accelerants according to their respective groups compared to SIMCA analysis.