Fire Debris Analysis Research Articles

Fixed- and Variable-Temperature Kinetic Models to Predict Evaporation of Petroleum Distillates for Fire Debris Applications

Forensic fire debris analysis focuses on the identification of a foreign ignitable liquid in debris collected from the scene of a suspected intentional fire. Chromatograms of the extracted debris are compared to a suitable reference collection containing chromatograms of unevaporated and evaporated ignitable liquids. However, there is no standardized method for the evaporation of ignitable liquids and the process itself can be time consuming, which limits the number of chromatograms of evaporated liquids included in the reference collection. This work describes the development and application of a variable-temperature kinetic model to predict evaporation rate constants and mathematically predict chromatograms corresponding to evaporated ignitable liquids. First-order evaporation rate constants were calculated for 78 selected compounds in diesel, which were used to develop predictive models of evaporation rates. Fixed-temperature models were developed to predict the rate constants at five temperatures (5, 10, 20, 30, 35 °C), yielding a mean absolute percent error (MAPE) of 10.0%. The variable-temperature model was then created from these data by multiple linear regression, yielding a MAPE of 16.4%. The model was applied to generate a reference collection of predicted chromatograms of diesel and kerosene corresponding to a range of evaporation levels. Using the modeled reference collection, successful identification of the liquid and level of evaporation in a test set of chromatograms was demonstrated.

Developing a Method for the Collection and Analysis of Burnt Remains for the Detection and Identification of Ignitable Liquid Residues Using Body Bags, Dynamic Headspace Sampling, and TD-GC×GC-TOFMS

In cases of suspected arson, a body may be intentionally burnt to cause loss of life, dispose of remains, or conceal identification. A primary focus of a fire investigation, particularly involving human remains, is to establish the cause of the fire; this often includes the forensic analysis of fire debris for the detection of ignitable liquid residues (ILRs). Commercial containers for the collection of fire debris evidence include metal cans, glass jars, and polymer/nylon bags of limited size. This presents a complication in cases where the fire debris consists of an intact, or partially intact, human cadaver. This study proposed the use of a body bag as an alternative sampling container. A method was developed and tested for the collection and analysis of ILRs from burnt porcine remains contained within a body bag using dynamic headspace sampling (using an Easy-VOC™ hand-held manually operated grab-sampler and stainless steel sorbent tubes containing Tenax TA) followed by thermal desorption comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry (TD-GC×GC-TOFMS). The results demonstrated that a body bag containing remains burnt with gasoline tested positive for the presence of gasoline, while blank body bag controls and a body bag containing remains burnt without gasoline tested negative. The proposed method permits the collection of headspace samples from burnt remains before the remains are removed from the crime scene, limiting the potential for contamination and the loss of volatiles during transit and storage.

Model Distribution Effects on Likelihood Ratios in Fire Debris Analysis

Computational models for determining the strength of fire debris evidence based on likelihood ratios (LR) were developed and validated against data sets derived from different distributions of ASTM E1618-14 designated ignitable liquid class and substrate pyrolysis contributions using in-silico generated data. The models all perform well in cross validation against the distributions used to generate the model. However, a model generated based on data that does not contain representatives from all of the ASTM E1618-14 classes does not perform well in validation with data sets that contain representatives from the missing classes. A quadratic discriminant model based on a balanced data set (ignitable liquid versus substrate pyrolysis), with a uniform distribution of the ASTM E1618-14 classes, performed well (receiver operating characteristic area under the curve of 0.836) when tested against laboratory-developed casework-relevant samples of known ground truth.

Detection and Characterization of Ignitable Liquid Residues in Forensic Fire Debris Samples by Comprehensive Two-Dimensional Gas Chromatography

This study covers an extensive experimental design that was developed for creating simulated fire debris samples under controlled conditions for the detection and identification of ignitable liquids (IL) residues. This design included 19 different substrates, 45 substrate combinations with and without ignitable liquids, and 45 different ILs from three classes (i.e., white spirit, gasoline, and lamp oil). Chemical analysis was performed with comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC-TOFMS) for improved separation and compound identification. The enhanced peak capacity offered by GC×GC-TOFMS allowed the use of a target compound list in combination with a simple binary decision model to arrive at quite acceptable results with respect to IL detection (89% true positive and 7% false positive rate) and classification (100% correct white spirit, 79% correct gasoline, and 77% correct lamp oil assignment). Although these results were obtained in a limited set of laboratory controlled fire experiments including only three IL classes, this study confirms the conclusions of other studies that GC×GC-TOFMS can be a powerful tool in the challenging task of forensic fire debris analysis.

Effects of Fire Suppression Agents and Weathering in the Analysis of Fire Debris by HS-MS eNose.

In arson attacks the detection of ignitable liquid residues (ILRs) at fire scenes provides key evidence since ignitable liquids, such as gasoline, are commonly used to initiate the fire. In most forensic laboratories gas chromatography-mass spectrometry is employed for the analysis of ILRs. When a fire occurs, suppression agents are used to extinguish the fire and, before the scene is investigated, the samples at the scene are subjected to a variety of processes such as weathering, which can significantly modify the chemical composition and thus lead to erroneous conclusions. In order to avoid this possibility, the application of chemometric tools that help the analyst to extract useful information from data is very advantageous. The study described here concerned the application of a headspace-mass spectrometry electronic nose (HS-MS eNose) combined with chemometric tools to determine the presence/absence of gasoline in weathered fire debris samples. The effect of applying two suppression agents (Cafoam Aquafoam AF-6 and Pyro-chem PK-80 Powder) and delays in the sampling time (from 0 to 48 h) were studied. It was found that, although the suppression systems affect the mass spectra, the HS-MS eNose in combination with suitable pattern recognition chemometric tools, such as linear discriminant analysis, is able to identify the presence of gasoline in any of the studied situations (100% correct classification).

Analysis of volatiles in fire debris by combination of activated charcoal strips (ACS) and automated thermal desorption–gas chromatography–mass spectrometry (ATD/GC–MS)

Adsorption of volatiles in gaseous phase to activated charcoal strip (ACS) is one possibility for the extraction and concentration of ignitable liquid residues (ILRs) from fire debris in arson investigations. Besides liquid extraction using carbon dioxide or hexane, automated thermo-desorption can be used to transfer adsorbed residues to direct analysis by gas chromatography–mass spectrometry (GC–MS). We present a fire debris analysis work-flow with headspace adsorption of volatiles onto ACS and subsequent automated thermo-desorption (ATD) GC–MS analysis. Only a small portion of the ACS is inserted in the ATD tube for thermal desorption coupled to GC–MS, allowing for subsequent confirmation analysis with another portion of the same ACS. This approach is a promising alternative to the routinely used ACS method with solvent extraction of retained volatiles, and the application to fire debris analysis is demonstrated.

Practical methods for mitigating microbial degradation of ignitable liquids in soil samples

In fire debris analysis, it is commonly accepted that soil samples can potentially cause degradation of ignitable liquids through microbial activity. Temperature- and solvent-based mitigation methods have been explored, but space and practical application limitations potentially cause problems for these mitigation methods. Alternate mitigation methods using carbon dioxide cartridges, dry ice, and oxygen-adsorbent pouches were cursorily explored as possible practical options to slow microbial activity through the displacement or removal of oxygen within the sample cans. Sample cans were left at room temperature, refrigerated, or treated with a mitigation agent and tested for up to four weeks after application of the gasoline, with cans prepared in triplicate for each time point and storage condition.The carbon dioxide cartridges were ultimately found to be unreliable and widely variable with respect to ignitable liquid contamination. Dry ice did not mitigate the microbial degradation and added additional safety concerns. The oxygen-adsorbent pouches prevented the degradation of gasoline for up to four weeks in the examined soil and did not introduce contamination or safety hazards. Further research is needed to more fully evaluate this potential mitigation method prior to introduction into the field.

Model-effects on likelihood ratios for fire debris analysis

A simple method is introduced for assessing the evidentiary value of fire debris samples. The method relies on models built by random draws from a database of ignitable liquid and substrate pyrolysis samples. A stratified random draw from database records belonging to each ASTM E1618 ignitable liquid class and the substrate class is taken in proportion to a prescribed distribution. The likelihood ratios are estimated by direct calculation from a one-level Gaussian kernel density model based on the covariance structure and multivariate means resulting from each random draw. Multiple draws result in model-related variation in the calculated likelihood ratios. The method is demonstrated for 500 random draws with replacement based on three distributions. Ten-fold cross-validation is performed for each model, with subsequent testing on laboratory burn samples. The average cross-validated receiver operating characteristic areas under the curve were 0.959, 0.956 and 0.947, for the three distributions. The mean log (base 10) of the likelihood ratio (LLR) values for the laboratory test burns of gasoline on polyester carpet and carpet padding were in the range of 1.5 to −3.1 and were qualitatively consistent with the observed gasoline contributions to the total ion chromatograms for the samples. The LLR values for laboratory test burns of a petroleum distillate on polyester carpet and carpet padding, 1.7 to −3.3, were also in qualitative agreement with the observed chromatographic patterns. The calculated LLR values for laboratory burns of a set of polyester carpet and padding samples were in the range −0.9 to −6.7.

C&EN talks with José Almirall, forensic chemist

Jose Almirall started his career 31 years ago in the forensic science laboratory of the Miami-Dade Police Department. Now a professor at Florida International University, he develops analytical tools for forensic investigators, including matching broken glass shards to their source using trace-element analysis and detecting crime-related volatiles, such as those found in drugs or gunshot residue. Almirall is a leader in standardizing and improving the methods used in many types of forensic science. He recently chaired an American Association for the Advancement of Science (AAAS) working group on the current quality of fire scene investigations and fire debris analysis. He talked with Louisa Dalton about the complex chemistry of fire and about what forensic tools and standards are needed to safeguard justice in courts. The AAAS working group you chaired set out to identify critical issues in the field of fire investigations. What are some unique challenges of fire investigations?

Analysis of Petroleum Products in Fire Debris Residues by Gas Chromatography: A Literature Review

This review gives a brief overview of developments in the analysis of petroleum products (PP) in fire debris residues (FDR) by gas chromatography (GC). The review covers different aspects of analysis such as the substrates involved, isolation procedures, column and mobile phase used, and subsequent detection in tabular form. This paper covers detection of PP such as petrol, kerosene, and diesel in various types’ of samples of interest to fire debris analysts. Solid phase microextraction is most frequently used along with gas chromatography-mass spectrometry (GC-MS) for the extraction and identification of PP from FDR. Chemometric tools should be used to improve the significance and reliability of results obtained from the analysis of FDR. However, the potential utility of portable GC-MS in fire debris analysis cannot be ignored, and its proper development and validation is required before using it for this purpose.

Fire debris analysis for forensic fire investigation using laser induced breakdown spectroscopy

The possibility verification of the first attempt to apply LIBS to arson investigation was performed. LIBS has capabilities for real time in-situ analysis and depth profiling. It can provide valuable information about the fire debris that are complementary to the classification of original sample components and combustion residues. In this study, fire debris was analyzed to determine the ignition source and existence of a fire accelerant using LIBS spectra and depth profiling analysis. Fire debris chemical composition and carbon layer thickness determines the possible ignition source while the carbon layer thickness of combusted samples represents the degree of sample carbonization. When a sample is combusted with fire accelerants, a thicker carbon layer is formed because the burning rate is increased. Therefore, depth profiling can confirm the existence of combustion accelerants, which is evidence of arson. Also investigation of fire debris by depth profiling is still possible when a fire is extinguished with water from fire hose. Such data analysis and in-situ detection of forensic signals via the LIBS may assist fire investigation at crime scenes.

Validation of an HS-MS method for direct determination and classification of ignitable liquids

Fire debris analysis is a key step in fire investigation. Most of the analytical methods used for the analysis of ignitable liquid residues in fire debris require pre-concentration of the ignitable liquid residues prior to the chromatographic analysis. The standard method, ASTM E1412, involves a passive headspace concentration with activated charcoal strips to isolate the ignitable liquid residues from fire debris followed by a desorption procedure from the carbon strip with carbon disulfide.In this study a non-separative analytical method based on HS-MS eNose (headspace mass spectrometry electronic nose) in combination with chemometric tools, including hierarchical cluster analysis and linear discriminant analysis, has been used to detect and classify ignitable liquid residues in fire debris into the classes defined by the ASTM E1618 standard method. This method allows a direct analysis of fire debris in 10min and avoids the use of solvent and sorbents.The method was validated by analyzing a set of burned samples by GC–MS according to the standard methods ASTM E1412 and ASTM E1618. The results obtained on using the method proposed in this study were comparable to those obtained with the reference method. The correct classification rates for assigning ignitable liquid residues into ASTM E1618 classes were in the range of 90% for both methods. In comparison to the standard methods HS-MS does have specific advantages. Apart from the speed of the analysis and the fact that the sample does not require sample pre-concentration, this technique is also safer and ecofriendly since it does not use any solvents or produce any residues.

Detection and characterization of volatile organic compounds from burned human and animal remains in fire debris

Debris collected from various test sites where mammalian remains (human and porcine) had been burned in a variety of full-scale fire scenarios was evaluated for the presence of volatile residues that could be characteristic of those remains. Levels of volatiles were measured using the method commonly used for fire debris analysis: gas chromatography–mass spectrometry. Homologous n-aldehydes (from n-pentanal to n-nonanal) proved to be a significant indicator of the presence of burned animal tissue as they were observed in nearly all of the samples. Such aldehydes are created by the combustion of animal fats. One aldehyde, n-hexanal, appeared more frequently than the other aldehydes, n-pentanal, n-heptanal, n-octanal, and n-nonanal. Ethanol was detected in two-thirds of the samples, while acetone appeared in about three-fourths of the samples, but both were detected at much lower concentrations than n-hexanal. These appear to have been combustion products of the substrates on which each body burned, rather than originating from the combustion of the body. There appeared to be no qualitative distinction between volatile products produced from burned porcine carcasses and those from human cadavers. Since a homologous series of C5–C9n-aldehydes is not produced as a dominant species by the pyrolysis or combustion of any normally encountered substrate (carpet, bedding, wood products or upholstery), their detection by normal fire debris methods appears to be a valid indicator of the presence of burned animal remains. These data will also provide guidance to fire debris analysts as to the nature of volatiles associated with the combustion of human bodies in real-world fires.

Local Ion Signatures (LIS) for the examination of comprehensive two-dimensional gas chromatography applied to fire debris analysis

Forensic examination of fire debris evidence is a notoriously difficult analytical task due to the complexity and variability of sample composition. The use of comprehensive two-dimensional gas chromatography with mass spectrometry detection (GC×GC–MS) allows the coupling of orthogonal retention mechanisms and therefore a high peak capacity.We demonstrate recent innovations in combining chemometric techniques for data reduction and feature selection, with evaluation of the evidence for forensic questions pertaining to the detection and subsequent classification of ignitable liquid residue (ILR) in fire debris samples. Chromatograms are divided into non-overlapping spatially delimited regions; for each of these regions a Local Ion Signature (LIS) is computed by summing the intensities, per nominal mass/charge over all points contained within each region. This yields a reduced feature space representing the original data as a set of consolidated ion traces. Subsequent feature selection is performed by evaluating the individual efficacy of each feature using a univariate score-based likelihood ratio (LR) approach for discriminating between pairs of same or different type samples. The retained features are used to model each ILR class using linear discriminant analysis (LDA).Results are demonstrated for 155 arson samples containing a diversity of substrate compounds and several known ignitable liquids. ILR detection is performed at 84% accuracy with fewer than 1% false positives followed by subsequent classification. Likelihood ratio distributions are presented referring to both detection and classification tasks.

Achieving a Near-Theoretical Maximum in Peak Capacity Gain for the Forensic Analysis of Ignitable Liquids Using GC×GC-TOFMS

At present, gas chromatography–quadrupole mass spectrometry (GC-qMS) is considered the gold standard amongst analytical techniques for fire debris analysis in forensic laboratories worldwide, specifically for the detection and classification of ignitable liquids. Due to the highly complex and unpredictable nature of fire debris, traditional one-dimensional GC-qMS often produces chromatograms that display an unresolved complex mixture containing only trace levels of the ignitable liquid among numerous background pyrolysis products that interfere with pattern recognition necessary to verify the presence and identification of the ignitable liquid. To combat these challenges, this study presents a method optimized to achieve a near-theoretical maximum in peak capacity gain using comprehensive two-dimensional gas chromatography (GC×GC) coupled to time-of-flight mass spectrometry (TOFMS) for the forensic analysis of petroleum-based ignitable liquids. An overall peak capacity gain of ~9.3 was achieved, which is only ~17% below the system’s theoretical maximum of ~11.2. In addition, through the preservation of efficient separation in the first dimension and optimal stationary phase selection in the second dimension, the presented method demonstrated improved resolution, enhanced sensitivity, increased peak detectability and structured chromatograms well-suited for the rapid classification of ignitable liquids. As a result, the method generated extremely detailed fingerprints of petroleum-based ignitable liquids including gasoline, kerosene, mineral spirits and diesel fuel. The resultant data was also shown to be amenable to chromatographic alignment and multivariate statistical analysis for future evaluation of chemometric models for the rapid, objective and automated classification of ignitable liquids in fire debris extracts.

Mathematically modeling chromatograms of evaporated ignitable liquids for fire debris applications

Ignitable liquid reference collections used in fire debris analysis often contain chromatograms of the liquids evaporated to various levels. In this work, a mathematical model was used to predict the chemical composition of several ignitable liquids at various evaporation levels. The model requires only the chromatogram of the unevaporated liquid and offers the potential to generate chromatograms of evaporated liquids in a time- and cost-efficient manner.A set of petroleum distillates and gasoline were experimentally evaporated to 30–90% by mass and analyzed by gas chromatography–mass spectrometry (GC–MS). The resulting chromatograms were compared to modeled chromatograms corresponding to the same evaporation levels. For the petroleum distillates, strong correlation was observed between the modeled and experimentally derived chromatograms, with Pearson product-moment correlation (PPMC) coefficients ranging from 0.920 (90% evaporated lamp oil) to 0.998 (30% evaporated lamp oil). For gasoline, moderate to strong correlation was observed between the modeled and experimentally derived chromatograms, with PPMC coefficients ranging from 0.772 (90% evaporated) to 0.949 (30% evaporated). The lower correlation was due to the presence of highly volatile compounds in gasoline that were not observed using the conventional GC–MS analysis method but contributed to the volume and mass loss. A modeled reference collection of evaporated liquids was generated and used to successfully indicate the presence of gasoline in simulated fire debris samples.

Determination of gasoline and diesel residues on wool, silk, polyester and cotton materials by SPME–GC–MS

The identification of ignitable liquids is very important and challenging aspect in arson crime investigations. The detection of gasoline and diesel fuel components using solid phase micro-extraction prior to gas chromatography–mass spectrometry for the forensic analysis of fire debris has been carried out. Previous works show that the absorption characteristics of the substrate are one of the most important factors in determining the evaporation rate of the accelerants. In order to determine the presence of the fuel residues, four of the most common substrate materials were tested in this work; wool, cotton, silk and polyester. The obtained results indicate that both gasoline and diesel fuel accelerants persisted longer on wool and silk than on the other selected substrates. Such information illustrates the influence of fuel persistence times after extinguishing and the best materials to be scanned for ignitable liquids at the fire scene.

Assessing evidentiary value in fire debris analysis by chemometric and likelihood ratio approaches

Results are presented from support vector machine (SVM), linear and quadratic discriminant analysis (LDA and QDA) and k-nearest neighbors (kNN) methods of binary classification of fire debris samples as positive or negative for ignitable liquid residue. Training samples were prepared by computationally mixing data from ignitable liquid and substrate pyrolysis databases. Validation was performed on an unseen set of computationally mixed (in silico) data and on fire debris from large-scale research burns. The probabilities of class membership were calculated using an uninformative (equal) prior and a likelihood ratio was calculated from the resulting class membership probabilities. The SVM method demonstrated a high discrimination, low error rate and good calibration for the in silico validation data; however, the performance decreased significantly for the fire debris validation data, as indicated by a significant increase in the error rate and decrease in the calibration. The QDA and kNN methods showed similar performance trends. The LDA method gave poorer discrimination, higher error rates and slightly poorer calibration for the in silico validation data; however the performance did not deteriorate for the fire debris validation data.

The influence of temperature on the pyrolysis of household materials

We have previously demonstrated the successful application of multivariate statistical (i.e. chemometric) techniques to the classification of casework fire debris based on gasoline content, with the objective to expedite the data interpretation process for the forensic analysis of fire debris. We have also shown that it is possible to classify simulated fire debris based on gasoline content using simulated fire debris; however, models trained on simulated debris are not applicable to casework samples without a significant loss in model accuracy. A previously developed simulation protocol that works well for generating debris to train human analysts was inadequate for training either partial least-squares discriminant analysis (PLS-DA) or soft independent modelling by class analogy (SIMCA) models to identify casework debris due mainly to its inability to generate a sufficient amount of benzene, toluene, ethylbenzene, and xylenes (BTEX) and non-aromatic hydrocarbon compounds. This method relied on pyrolyzing materials at 400°C. Here we examine the effects of pyrolysis conditions on household materials, including spruce plywood, vinyl sheet flooring, polyethylene terephthalate (PET) carpet, Nylon 6 carpet, polyurethane (PU) foam carpet underlay, asphalt shingle, medium-density fireboard (MDF) shelving, and spruce timber at temperatures above 400°C, in an attempt to generate additional BTEX and non-aromatic hydrocarbon compounds for the realistic simulation of fire debris. The work presented here showed that C3- to C5-alkylbenzenes, which are abundant in gasoline, were generally absent from the pyrolysates of all materials studied and at all temperatures studied (400, 700 and 900°C), only appearing in trace amounts on rare occasions. Based on our results, we propose that accurate simulation of fire debris could be achieved with a mixture of carpets, carpet underlay, and vinyl flooring pyrolyzed at 700°C; spruce plywood pyrolyzed at 900°C, and asphalt shingles pyrolyzed at 400 and 700°C. These conditions generated a substantial amount of BTEX and non-aromatic hydrocarbons in the debris matrix background. The testing of this ⿿recipe⿿ for generating simulated debris for training chemometric models that can classify casework debris is left for future experimentation.

Preliminary evaluation of a next-generation portable gas chromatograph mass spectrometer (GC-MS) for the on-site analysis of ignitable liquid residues

The detection of ignitable liquid residues (ILRs) at a fire scene can be valuable evidence to indicate if the fire may have been deliberately set. In this study, a commercially-available portable GC-MS, the TRIDION-9, was evaluated for the purpose of on-site fire debris analysis. The instrument, which incorporates a low thermal mass capillary GC and a miniaturised toroidal ion trap mass spectrometer, is designed to use solid-phase microextraction (SPME) as the default sampling method. Four ignitable liquids (petrol, mineral turpentine, kerosene and diesel) and seven substrates (nylon, polypropylene and wool carpet, rubber and foam underlay, untreated pine and polyurethane) were considered. After method optimisation, substrates were burned and spiked with 0.1 μL of ignitable liquid (mineral turpentine, kerosene, diesel fuel, and both neat and weathered unleaded petrol). Sampling was performed via passive headspace SPME adsorption over 3 min immediately followed by analysis using the TRIDION-9 (analysis time < 2 min). Field trials were performed on fire debris samples collected from an accelerated structural fire. The data from the portable GC-MS analyses permitted the detection and correct classification of ILRs in the majority of samples analysed. Overall, the TRIDION-9 was found to be well-suited to the field-based analysis of fire debris samples as a preliminary screen to provide rapid presumptive results for fire investigators.