skip navigation


Register for Latest Research

Stay Informed
Register with NCJRS to receive NCJRS's biweekly e-newsletter JUSTINFO and additional periodic emails from NCJRS and the NCJRS federal sponsors that highlight the latest research published or sponsored by the Office of Justice Programs.

NCJRS Abstract

The document referenced below is part of the NCJRS Virtual Library collection. To conduct further searches of the collection, visit the Virtual Library. See the Obtain Documents page for direction on how to access resources online, via mail, through interlibrary loans, or in a local library.


NCJ Number: 240684 Find in a Library
Title: Application of Chemometrics and Fast GC-MS Analysis for the Identification of Ignitable Liquids in Fire Debris Samples
Author(s): Michael Sigman, Ph.D.; Mary Williams, M.S.
Date Published: December 2012
Page Count: 45
Sponsoring Agency: National Institute of Justice (NIJ)
Washington, DC 20531
NCJRS Photocopy Services
Rockville, MD 20849-6000
Grant Number: 2008-DN-BX-K069
Sale Source: NCJRS Photocopy Services
Box 6000
Rockville, MD 20849-6000
United States of America
Document: PDF
Type: Report (Study/Research)
Format: Document; Document (Online)
Language: English
Country: United States of America
Annotation: The goal of this research was to develop a data-analysis method that can classify ignitable liquid residue in the presence of background interferences found in fire debris.
Abstract: The research developed a novel method for classifying ignitable liquid residues into the ASTM classes in the presence of a strong background signal. The method uses target factor analysis (TFA) in combination with Bayesian decision theory, which provides results in the form of posterior probabilities that a set of samples from a fire scene contain an ignitable liquid of a specific ASTM class; however, error rates are not currently available for fire debris analysis, other than extrapolations from proficiency tests. The method was further refined by introducing a sensitivity parameter that made the method conservative in its predictions. The method allows classification of a sample into multiple classes creating the possibility of not assigning the sample to any of the available classes. The work was divided into three tasks. Task I focuses on the development of the combined TFA and Bayesian decision theory, as well as the testing of the method by using computationally constructed data-sets prepared by using total ion spectra (TIS) from ignitable liquids and burned substrates from the Ignitable Liquids Reference Collection and Database and the Substrate Databases, respectively. Both are NCFS/TWGFEX databases. Task II tested the method by using laboratory-generated burn samples. Data-sets were produced by burning common building/furnishing materials with differing amounts of applied ignitable liquid, as well as by varying both the amount of applied liquid and the relative amount of substrate materials. Task II further tested the method on large-scale burn samples produced specifically for testing the methods. The 15-percent incorrect classifications included those samples in which the ignitable liquid residue was heavily weathered; and in some cases, the liquid may have completely evaporated. 15 figures, 6 tables, 24 references, 3 listings of publications disseminating the research, and appended supplementary data
Main Term(s): Forensic sciences
Index Term(s): Arson investigations; Chromatography; Investigative techniques; Mass spectroscopy; NIJ final report; NIJ grant-related documents
To cite this abstract, use the following link:

*A link to the full-text document is provided whenever possible. For documents not available online, a link to the publisher's website is provided. Tell us how you use the NCJRS Library and Abstracts Database - send us your feedback.