Fire incidents are a major contributor to the number of deaths and property losses within the United States each year. Fire investigations determine the cause of the fire resulting in an assignment of responsibility. Current methods of fire debris analysis are reviewed including the preservation, extraction, detection and characterization of ignitable liquids from fire debris. Leak rates were calculated for the three most common types of fire debris evidence containers. The consequences of leaking containers on the recovery and characterization of ignitable liquids were demonstrated. The interactions of hydrocarbons with activated carbon during the extraction of ignitable liquids from the fire debris were studied. An estimation of available adsorption sites on the activated carbon surface area was calculated based on the number of moles of each hydrocarbon onto the activated carbon. Upon saturation of the surface area, hydrocarbons with weaker interactions with the activated carbon were displaced by more strongly interacting hydrocarbons thus resulting in distortion of the chromatographic profiles used in the interpretation of the GC/MS data. The incorporation of an additional sub-sampling step in the separation of ignitable liquids by passive headspace sampling reduces the concentration of ignitable liquid accessible for adsorption on the activated carbon thus avoiding saturation of the activated carbon. A statistical method of covariance mapping with a coincident measurement to compare GC/MS data sets of two ignitable liquids was able to distinguish ignitable liquids of different classes, sub-classes and states of evaporation. In addition, the method was able to distinguish 10 gasoline samples as having originated from different sources with a known statistical certainty. In a blind test, an unknown gasoline sample was correctly identified from the set of 10 gasoline samples without making a Type II error.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-4412 |
Date | 01 January 2007 |
Creators | Williams, Mary |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations |
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