Application of an HS-MS for the detection of ignitable liquids from fire debris

In arson attacks, accelerants such as ignitable liquids are commonly used to initiate or accelerate a fire. The detection of ignitable liquid residues at fire scenes is therefore a key step in fire investigations. The most widely used analytical technique for the analysis of accelerants is GC-MS. However, pre-concentration of the ignitable liquid residues is required prior to the chromatographic analysis. The standard method, ASTM E1412, involves passive headspace concentration with activated charcoal strips as a method to isolate the ignitable liquid residues from fire debris and these residues are subsequently desorbed from the carbon strip with solvents such as carbon disulfide. In the work described here, an alternative analytical technique based on an HS-MS (headspace mass spectrometry) has been developed for the thermal desorption of the carbon strips and analysis of different ignitable liquid residues in fire debris. The working conditions for the HS-MS analytical procedure were optimized using different types of fire debris (pine wood burned with gasoline and diesel). The optimized variables were desorption temperature and desorption time. The optimal conditions were 145 degrees C and 15 min. The optimized method was applied to a set of fire debris samples. In order to simulate post burn samples several accelerants (gasoline, diesel, citronella, kerosene, paraffin, and alcohol) were used to ignite different substrates (wood, cotton, cork, paper, and paperboard). chemometric methods (duster analysis and discriminant analysis) were applied to the total ion spectrum obtained from the MS (45-200 m/z) to discriminate between the burned samples according to the accelerant used. The method was validated by analyzing all samples by GC-MS according to the standard methods ASTM E1412 and ASIM E1618. The results obtained on using the method developed in this study were comparable to those obtained with the reference method. However, the newly developed HS-MS method is faster, safer, and more environmental friendly than the standard method. (C) 2015 Elsevier B.V. All rights reserved.