Download Free Gc Ms Data From Fire Debris Samples Book in PDF and EPUB Free Download. You can read online Gc Ms Data From Fire Debris Samples and write the review.

Mass chromatography is currently being adapted by many forensic laboratories as the preferred approach for interpreting GC/MS data from fire debris samples. This paper first describes software approaches for minimizing interferences and for facilitating the identification of petroleum liquids when using this approach. Next, guidelines are developed for recognizing chromatographic distortion that often occurs when petroleum liquids are recovered using the popular solid adsorption/elution method. It is seen that for a given petroleum liquid, paraffinic:aromatic ratios can vary eight fold depending on the recovery conditions and sample concentration. Finally, the application of these software tools and guidelines to case samples is illustrated, and an approach for categorizing an exemplar collection on the basis of qualitative features and peak height ratios is demonstrated.
The study of fire debris analysis is vital to the function of all fire investigations, and, as such, Fire Debris Analysis is an essential resource for fire investigators. The present methods of analysis include the use of gas chromatography and gas chromatography-mass spectrometry, techniques which are well established and used by crime laboratories throughout the world. However, despite their universality, this is the first comprehensive resource that addresses their application to fire debris analysis. Fire Debris Analysis covers topics such as the physics and chemistry of fire and liquid fuels, the interpretation of data obtained from fire debris, and the future of the subject. Its cutting-edge material and experienced author team distinguishes this book as a quality reference that should be on the shelves of all crime laboratories. Serves as a comprehensive guide to the science of fire debris analysis Presents both basic and advanced concepts in an easily readable, logical sequence Includes a full-color insert with figures that illustrate key concepts discussed in the text
The practice of arson analysis in a forensic science laboratory is based upon detecting the presence of ignitable liquids. If an ignitable liquid is present, it is suggestive of arson; if no ignitable liquid is found an arson claim is more difficult to assert. Ignitable liquids are detected using gas chromatography coupled with mass spectrometry. Instrumental results from a GC/MS can display components of an ignitable liquid but an analyst needs to make the final decision. Even with correct instrumentation and suggested guidelines, ignitable liquid analysis can be subjective and based upon the analysts' education and experience. To better understand the interpretive practices of the fire debris analysis community, a survey consisting of reference samples, mixture standards, and multiple unknowns was created in consultation with the Los Angeles Police Department Arson Unit. The samples consisted of different substrates with varying classes and volumes of ignitable liquid. They were created using a destructive distillation method first developed by the State of Florida Bureau of Forensic Fire and Explosives Analysis. Extraction of the samples was completed using a carbon strip to perform passive headspace absorption following the ASTM E 1412 method. The samples were analyzed with a GC/MS following National Commission on Forensic Science parameters. To maintain confidentiality, participant responses are stripped of identifiers and the results of the survey, details about the procedure, and discussions will be presented.
Arson is one of the most challenging crimes for forensic scientists to investigate. The variability in the composition of ignitable liquids, including changes in chemical composition during and after the fire, and the presence of pyrolysis products generated from burning substrates yields a very complex mixture of volatile compounds in samples of fire debris. Headspace extraction of debris samples followed by gas chromatography-mass spectrometry (GC-MS) is the most common approach for fire investigation. For many laboratories, data interpretation is the bottleneck in the workflow, consuming an inordinate amount of analyst time. It is also a process that is highly dependent on the experience and skill of analysts which gives rise to subjective results. Chemometrics offers an alternative to manual data interpretation. However, for this work to be applicable in real-world fire investigations, the chemometric model must be able to classify all major classes of ignitable liquids that can be possibly found in a fire. Construction of a chemometric model requires abundant casework data. This is this not a problem for gasoline, which is the most commonly used ignitable liquid, but it is a challenge for other ILs. The lengthy time needed for the collection of casework debris containing other ILs for the model construction limits the practical use of this work. Therefore, it would be a great benefit if models applicable to casework samples could be generated based on simulated debris profiles. An established debris simulation protocol has been shown to be effective in generating realistic debris for training human analysts. This thesis evaluates the applicability of this simulation protocol for generating debris that are chemometrically identical to casework debris. It was discovered that models trained on the simulated debris were not applicable to casework samples without a significant loss in the accuracy of the model. It was established that the reason for the inadequacy of the simulated debris was that it did not contain sufficient C2-alkyl benzenes and non-aromatic hydrocarbons. Consequently these features which are not characteristic of gasoline were selected by the chemometric model and model quality degraded for real samples. Thus research turned to a study of the effects of temperature on the pyrolysis of household materials, mainly flooring and roofing materials, at temperatures above 400 °C. I was particularly interested in finding conditions that will generate additional BTEX and aliphatic hydrocarbons, which were generally lacking in debris pyrolyzed at 400 °C with the established simulation method.
The goal of the research conducted under this grant was to develop a chemometric method of data analysis that would facilitate the identification of GC-MS patterns associated with ignitable liquid classes, as designated under ASTM E 1618-10. The objective of the research was to develop a data analysis method that would classify ignitable liquid residue in the presence of background interferences found in fire debris. Pattern recognition and classification methods available at the onset of this research did not explicitly take into account background interference issues. A novel method was developed under this research to classify ignitable liquid residues into the ASTM classes, even in the presence of a strong background signal, without a priori knowledge of the background signature. The method makes use of target factor analysis (TFA) in combination with Bayesian decision theory. The use of Bayesian decision theory 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. 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 which made the method very conservative in its predictions, and gave a true "soft" classifier. Soft classifiers allow classification of a sample into multiple classes and afford the possibility of not assigning the sample to any of the available classes. In order to achieve the goals, this work was broken down into three tasks.