ABSTRACT
The effect of substrate interferences from high-density polyethylene (HDPE) on the ability to associate an ignitable liquid residue with the corresponding liquid standard, using statistical procedures, is demonstrated. Gasoline, kerosene, and lighter fluid, at three different evaporation levels, were spiked onto HDPE and subsequently burned to generate simulated ignitable liquid residues (ILRs). Samples were extracted using a passive headspace procedure and analyzed by gas chromatography-mass spectrometry. The total ion chromatograms were subjected to data pretreatment procedures prior to principal components analysis and Pearson product moment correlation. Using the combination of these statistical procedures, simulated ILRs were successfully associated with the corresponding liquid type, despite the presence of compounds inherent to the HDPE substrate, as well as those resulting from pyrolysis of the substrate.
ABSTRACT
Identification of an ignitable liquid in fire debris evidence can be complicated due to evaporation of the liquid, matrix interferences, and thermal degradation of both the liquid and the matrix. In this research, liquids extracted from simulated fire debris were compared to the original liquid using multivariate statistical procedures. Neat and evaporated gasoline and kerosene standards were spiked onto nylon carpet, which was subsequently burned. The ignitable liquid residues were extracted using a passive headspace procedure and analyzed by gas chromatography-mass spectrometry. Pearson product moment correlation coefficients, hierarchical cluster analysis, and principal components analysis were used to compare the liquids extracted from the carpet to the corresponding neat liquid. For each procedure, association of the extracts according to liquid type was possible, albeit not necessarily to the specific evaporation level. Of the three procedures investigated, principal components analysis offered the most promise since contributions from matrix interferences were essentially eliminated.