Identifying Ignitable Liquids In Fire Debris

Identifying Ignitable Liquids in Fire Debris: A Guideline for Forensic Experts discusses and illustrates the characteristics of different ignitable liquid products. This guideline builds on the minimum criteria of the ignitable liquid classes defined in the internationally accepted standard ASTM E1618 Standard Test Method for Ignitable Liquid Residues in Extracts from Fire Debris Samples by Gas Chromatography-Mass Spectrometry. The volume provides information on the origin of the characteristics of these ignitable liquid products and provides a summary of characteristics to demonstrate a positive identification of the particular product class. Topics such as the term ignitable liquid, relevant guidelines for fire debris analysis, production processes of ignitable liquids, fire debris analysis methods, and interferences in fire debris analysis, are briefly discussed as these topics are essential for the understanding of the identification and classification of ignitable liquid residues in fire debris. Discusses the characteristics and variations in chemical composition of different classes of the ignitable liquid products defined by ASTM E1618:14 Covers the General Production Processes of Ignitable Liquid Products Includes a guide for the Identification of Ignitable Liquids in Fire Debris

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 rapidly increasing number of different ignitable liquid formulations available today poses a new challenge to fire debris analysts and other forensic chemistry specialists -- that of accurately identifying and classifying ignitable liquids with unfamiliar chromatographic patterns. GC-MS Guide to Ignitable Liquids addresses that challenge with a selection of more than 100 different ignitable liquid formulations designed to supplement the laboratory's standard collection. Both total ion chromatograms and extracted ion chromatograms (mass chromatograms) are included. Written by authors who are also experienced forensic chemists, this complete reference is the only single source of information on ignitable liquids - a must for students of fire science, forensic chemists, and anyone conducting fire debris analysis.

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.

This text provides training on the fundamental tools and methodologies used in active forensic laboratories for the complicated analysis of fire debris and explosives evidence. It is intended to serve as a gateway for students and transitioning forensic science or chemistry professionals. The book is divided between the two disciplines of fire debris and explosives, with a final pair of chapters devoted to the interplay between the two disciplines and with other disciplines, such as DNA and fingerprint analysis. It brings together a multi-national group of technical experts, ranging from academic researchers to active practitioners, including members of some of the premier forensic agencies of the world. Readers will gain knowledge of practical methods of analysis and will develop a strong foundation for laboratory work in forensic chemistry. End-of-chapter questions based on relevant topics and real-world data provide a realistic arena for learners to test newly-acquired techniques.

Within modern forensic science and criminal investigation, experts face several challenges including managing huge amounts of data, handling miniscule pieces of evidence in a chaotic and complex environment, navigating traditional laboratory structures, and, sometimes, dealing with insufficient knowledge. These challenges must be overcome to avoid failure in investigation or miscarriage of justice. Technologies to Advance Automation in Forensic Science and Criminal Investigation provides a platform for researchers to present state-of-the-art technologies within forensic science and criminal investigation. Covering topics such as financial fraud, machine learning, and source camera identification, this book is an essential reference for criminal investigators, justice departments, law enforcement, legislators, computer scientists, automation professionals, researchers, academicians, and students and educators in higher education.

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.

Ongoing advances in arson detection tools and techniques increase the importance of scientific evidence in related court proceedings. In order to assemble an airtight case, investigators and forensic scientists need a resource that assists them in properly conducting the chemical analysis and interpretation of physical evidence found at scenes of s