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Statistical Assessment of the Probability of Correct Identification of Ignitable Liquids in Fire Debris Analysis

NCJ Number
Date Published
121 pages
Michael Sigman Ph.D.
Publication Type
Report (Study/Research), Report (Grant Sponsored)
Grant Number(s)
This report examines a major challenge in the analysis of possible arson-related fire debris, the identification of ignitable liquid residues in the presence of background interferences.
Identification of ignitable liquid residues in the presence of background interferences, especially those arising from pyrolysis processes, is a major challenge for the fire debris analyst. This research examined a mathematical model that allows for the detection of an ignitable liquid in a fire debris sample and the classification of the ignitable liquid. This project proposed to investigate the development of a method for classifying fire debris GC-MS data sets as: 1) containing or not containing an ignitable liquid, 2) classifying any ignitable liquid that may be present, and 3) estimating the statistical certainty of the answers to questions 1 and 2. The proposed approach was to build a mathematical model that can correctly classify data from ignitable liquids and pyrolyzed substrates (wood, plastic, etc.). The model would then be applied to data from laboratory-generated fire debris samples, as well as ignitable liquids and substrates that were not used to build the model. The classification success of the model would allow a determination of the statistical performance of the model. The model would be developed based on the total ion spectrum, which has already shown a propensity for classifying a set of ignitable liquids drawn from multiple ASTM classes.
Date Created: February 9, 2015