Ignitable Liquid Residues Research Articles

Validation of ground truth fire debris classification by supervised machine learning

A set of 767 laboratory-generated fire debris samples of known ground truth as to whether an ignitable liquid residue was present (class IL) or absent (class SUB) were used to train five machine learning classifiers. Linear and quadratic discriminant analysis (LDA and QDA), k-nearest neighbors (kNN), and support vector machines with radial and linear kernels (SVMr and SVMl) were tested for their performance in correctly classifying the fire debris samples into class IL or class SUB. Each classifier was trained and tested/validated on 500 class-balanced data sets, each comprised of 400 fire debris samples (200 IL and 200 SUB) that were bootstrapped from the 767 laboratory-generated samples. Each bootstrapped data set was split into subsets for training (75%, 300 samples) and testing/validation (25%, 100 samples). The LDA, SVMr and SVMl were found to give satisfactory performance based on area under the receiver operating characteristic curve (0.86–0.92), equal error rates (17%−22%) and well-calibrated probabilities. The three satisfactory classifiers were further applied to a set of 129 fire debris samples produced in large-scale test burns. The classifications generated by the machine learning models were compared with the sample classes assigned by an informed analyst having knowledge of the chromatographic patterns of the ignitable liquids use to start the large-scale fires. The LDA and SVMl models gave results most closely aligned with the informed analyst.

Method development for optimizing analysis of ignitable liquid residues using flow-modulated comprehensive two-dimensional gas chromatography

The abundance and composition of matrix compounds in fire debris samples undergoing ignitable liquid residue analysis frequently leads to inconclusive results, which can be diminished by applying comprehensive two-dimensional gas chromatography (GC × GC). Method development must be undertaken to fully utilize the potential of GC × GC by maximizing separation space and resolution.. The three main areas to consider for method development are column selection, modulator settings and parameter optimization. Seven column combinations with different stationary phase chemistry, column dimensions and orthogonality were assessed for suitability based on target compound selectivity, retention, resolution, and peak shapes, as well as overall peak capacity and area use. Using Box-Behnken design of experimentation (DoE), the effect of modulator settings such as flow ratio and loop fill capacity were evaluated using carbon loading potential, dilution effect, as well as target peak amplitude and skewing effect. The run parameters explored for parameter optimization were oven programming, inlet pressure (column flow rate), and modulation period. Comparing DoE approaches, Box-Behnken and Doehlert designs assessed sensitivity, selectivity, peak capacity, and wraparound; alongside target peak retention, resolution, and shape evaluation. Certified reference standards and simulated wildfire debris were used for method development and verification, and wildfire debris case samples scrutinized for method validation. The final method employed a low polarity column (5% diphenyl) coupled to a semi-polar column (50% diphenyl) and resulted in an average Separation Number (SN) exceeding 1 in both dimensions after optimization. Separation Numbers of 18.16 for first and 1.46 for second dimension without wraparound for compounds with at least four aromatic rings signified successful separation of all target compounds from varied matrix compositions and allowed for easy visual comparison of extracted ion profiles. Mass spectrometry (MS) was required during validation to differentiate ions where no baseline separation between target compounds and extraneous matrix compounds was possible. The resulting method was evaluated against ASTM E1618 and found to be an ideal routine analysis method providing great resolution of target compounds from interferences and excellent potential for ILR classification within a complex sample matrix.

A Forensic Approach to Evaluate the Effect of Different Matrices and Extraction Solvents for the Identification of Diesel Residue in Simulated Arson by GC–MS

Investigation of an arson case presents several challenges to the forensic investigator. Identification of the ignitable liquid residues in the fire debris is one of the crucial tasks that may help to determine the nature and cause of fire. Detection of the ignitable liquids using different analytical methods has been practiced for a long period across the globe. Diesel is a petroleum product that shows stable burning than gasoline and it is frequently used as accelerant also. This study was conducted to diagnose the efficiency of solvent as well as of the matrices for the detection of diesel residue. In this study, four different matrices (cotton cloth, wood, glaze tile, and PVC) were selected to create simulated miniature version of arson with diesel as an accelerant. After extinguishing the fire, diesel residues were extracted from the fire debris using hexane and diethylether as extraction solvents under ultrasonication. Gas Chromatography coupled with mass spectrometry was used to identify the major compounds from standard and burnt diesel. Diethylether extracted higher amount of diesel residues from the burnt matrices than hexane. Tile and cotton proved to be the better matrices for the extraction in hexane solvent. However, diethylether present advantageous results and significantly detected the diesel residues in tile, wood and cotton. Findings of this study may help an investigator to select the suitable matrices and solvent for the extraction of diesel residues and may efficaciously contribute in the forensic arson investigation.

Discrimination of Ignitable Liquid Residues in Burned Petroleum-Derived Substrates by Using HS-MS eNose and Chemometrics.

Interpretation of data from fire debris is considered as one of the most challenging steps in fire investigation. Forensic analysts are tasked to identify the presence or absence of ignitable liquid residues (ILRs) which may indicate whether a fire was started deliberately. So far, data analysis is subjected to human interpretation following the American Society for Testing and Materials’ guidelines (ASTM E1618) based on gas chromatography–mass spectrometry data. However, different factors such as interfering pyrolysis compounds may hinder the interpretation of data. Some substrates release compounds that are in the range of common ignitable liquids, which interferes with accurate determination of ILRs. The aim of the current research is to investigate whether headspace–mass spectroscopy electronic nose (HS-MS eNose) combined with pattern recognition can be used to classify different ILRs from fire debris samples that contain a complex matrix (petroleum-based substrates or synthetic fibers carpet) that can strongly interfere with their identification. Six different substrates—four petroleum-derived substrates (vinyl, linoleum, polyester, and polyamide carpet), as well as two different materials for comparison purposes (cotton and cork) were used to investigate background interferences. Gasoline, diesel, ethanol, and charcoal starter with kerosene were used as ignitable liquids. In addition, fire debris samples were taken after different elapsed times. A total of 360 fire debris samples were analyzed. The obtained total ion mass spectrum was combined with unsupervised exploratory techniques such as hierarchical cluster analysis (HCA) as well as supervised linear discriminant analysis (LDA). The results from HCA show a strong tendency to group the samples according to the ILs and substrate used, and LDA allowed for a full identification and discrimination of every ILR regardless of the substrate.

Characterization of a headspace sampling method with a five-component diesel fuel surrogate

PLOT-cryoadsorption concentrates headspace vapors by sweeping them through porous layer open tubular (PLOT) capillaries chilled to 0 °C to promote adsorption onto an alumina layer. Compared to passive headspace concentration employing activated charcoal strips (ACSs) as adsorbents, PLOT-cryoadsorption has several potential advantages for extracting ignitable liquid (IL) residue from fire debris evidence. Capillary vapor traps can be monitored for breakthrough to avoid problematic displacement that occurs when an adsorbent becomes saturated. Capillaries can also be eluted with acetone to avoid highly toxic carbon disulfide. Future adoption of PLOT-cryoadsorption for fire debris analysis requires investigation of sampling parameters including collection volume, flow rate, and temperature. Here we employ a simple five-component surrogate for diesel fuel (that is, a simulated or artificial diesel fuel) to study the effect of flow rate and sample temperature on the composition and spatial distribution of the collected headspace. Flow rates at or below 1.5 scc (standard cubic centimeters)/min yielded the most repeatable results. Across the range 60 °C to 120 °C, we found that high sample temperatures allowed for the collection of more total sample and shifted its composition towards lower-volatility components. Consistent with chromatographic theory, higher-volatility components traveled furthest along the length of the capillary and were more prone to breakthrough. We conclude that the surrogate mixture allowed for effective, quantitative comparisons between sampling conditions that could be translated to real diesel fuel.

Development of retention time indices for comprehensive multidimensional gas chromatography and application to ignitable liquid residue mapping in wildfire investigations

In this study, we introduce a simple three-step workflow for a universally applicable RI system, to be used in GC×GC analysis of ignitable liquid residue (ILR) for arson investigations. The proposed RI system applies a combination of two well-established GC RI systems: non-isothermal Kovats (K) index in the first dimension and Lee (L) index in the second dimension. The proposed KLI RI system showed very good correlations when compared with predicted values and existing RI systems (r2 = 0.97 in first dimension, r2 = 0.99 in second dimension) and was valid for a wide range of analyte concentrations and operational settings (coefficient of variance (CV) < 1% in first dimension, < 10% in second dimension). Using the KLI RI, an ILR classification contour map was created to assist with the identification of ILR types within ASTM E1618. The contour map was successfully applied to neat fuels and a fire scene sample, highlighting the application to wildfire investigation. Standardizing the RI process and establishing acceptable error margins allows the exploration and comparison of comprehensive data generated from GC×GC analysis of ILRs regardless of location, time, or system, further enhancing comprehensive and tenable chemometric analyses of samples. Overall, the KLI workflow was inexpensive, quick to apply, and user-friendly with its simple 3-step design.

Detection of gasoline on suspects’ hands: Study of different sampling alternatives

Arsonists may use ignitable liquids to start, accelerate and amplify fires. The sampling of volatiles present on the hands of suspected arsonists is therefore sometimes carried out in the course of the investigation of (possible) deliberate fires. Several collection protocols have been proposed, relying on the concentration of volatiles by the transfer on PVC gloves and further passive headspace extraction with Activated Charcoal Strips (ACS). Previous research findings assessing the use of Activated Carbon Cloth (ACC) – initially developed for the adsorption of gas in military applications – opens the path to new perspectives regarding the extraction and the concentration of ignitable liquid residues in general, and for the sampling on hands in particular. Five alternative methods (four relying on the use of ACC and one on ACS) were considered for the collection of gasoline traces present on the hands and their subsequent analysis by gas chromatography – mass spectrometry.Gasoline was deposited onto the palms of volunteers to study the differences between the collection method using ACS and those using ACC. For the latter, either the volunteer hands were placed in nylon bags with an ACC on the palm or suspended, or, powder-free latex gloves were used, with an ACC on the palm or in a separate extraction, with the glove in a nylon bag and the ACC suspended.The results showed that the background contamination was not distinguishable between ACS and ACC and their sampling ability was comparable. The two methods relying on the deposition of ACC directly on the surface of the palm where gasoline was deposited showed significantly higher collection capacity than other methods, provided that the ACC was in direct contact with the contaminated zone. The results showed that three main factors affected the collection of gasoline on the hands: the distance between the skin and the sorbent (ACC or ACS) in case of direct concentration of volatiles on the sorbent, the exposure time, and the space between the hand and the glove or bag (i.e. the headspace volume).This research opens new perspectives for the sampling of ignitable liquid residues through the use of ACC. It corroborates the perceived potential of ACC for the extraction and concentration of volatile compounds, particularly for fire debris analysis purposes. While the experiments were focused on the collection of gasoline on hands, the results provide valuable information in a more general way for the sampling of fire debris.

Influence of thermal environment in fire on the identification of gasoline combustion residues

Recent advances in fire investigation have engendered significant interest in fire debris analysis. Many factors in fire scenes, however, may interfere with the identification of ignitable liquid residues (ILRs). Generally, all ILRs suffer unavoidably from thermal destruction in fires. In contrast to weathering, the thermal effects on ILRs involve evaporation, thermal degradation and other chemical reactions. In order to study the influence of the thermal environment in fire scenes on the stability of target compounds for ILRs identification, gasoline combustion residues were reheated at different temperatures and analyzed by gas chromatography-mass spectrometry (GC–MS) systematically. The results showed that polycyclic aromatic hydrocarbons (PAHs) and indanes were more susceptible to thermal destruction, and could not be detected effectively after heating. On the other hand, alkylbenzenes and condensed ring aromatics were comparatively more stable. When the temperature rose to 600 °C, almost all the target compounds were lost after reheating again for 2 min. The research provides an important reference for gasoline combustion residues identification, and care should be taken on the interpretation of results due to the inevitable thermal damage to ILRs in fires.

The use of hydrophobic pads to recover ignitable liquids from water

Significant amounts of water are used to extinguish fires, and finding evidence of ignitable liquid residue can be challenging for investigators. Hydrophobic pads have been designed to collect oil-based products from the surface of water and preferentially absorb non-polar compounds while repelling water. In this study hydrophobic pads are used to collect various classifications of ignitable liquids from the surface of water for analysis using passive headspace concentration and GC/MS analysis. Hydrophobic pads were found to be effective in collecting ignitable liquids containing hydrocarbons greater than C8, classifications medium and heavy petroleum distillates, from 10 microliters of ignitable liquids added to the surface of 100 milliliters of water. Gasoline and 50% evaporated gasoline were also recovered using the hydrophobic pads with 25 microliters of sample.

Comparison of portable and benchtop GC–MS coupled to capillary microextraction of volatiles (CMV) for the extraction and analysis of ignitable liquid residues

A novel extraction device, capillary microextraction of volatiles (CMV) was coupled to a TRIDION-9 GC–MS with a needle trap (NTD) and evaluated for the analysis of ignitable liquids fire debris. The performance of the TRIDION-9 was compared to a benchtop GC–MS using CMV. A system detection limit of ~10 ng for each of 20 key ignitable liquid residue (ILR) compounds was determined for the T9 GC–MS. Dynamic headspace sampling of simulated ILRs was performed in closed and open-air systems. Closed system evaluations the CMV/NTD technique resulted in extraction performance similar to the CMV alone; however, ILR analysis on the T9 was impacted by limited chromatographic resolution. Compound identification was possible for 14 out of the 20 selected compounds on the T9 when 1 µL of a 1% standard accelerant mixture (SAM) was sampled, compared to 17 compounds on the benchtop GC–MS for the same mass loading. Open-air sampling with a modified vapor source resulted in the retention of most compounds with as low as 5 min. sampling, and equilibrium concentrations were reached after 10 min. No significant differences were observed between CMV and CMV/NTD sampling suggesting that the combined technique does not suffer from affinity bias. While the potential of the CMV/NTD extraction coupled to a T9 GC–MS for fire debris analysis was limited by the chromatographic resolution of the instrument, this study serves as proof of concept for the CMV’s potential for the extraction of ILRs in combination with portable GC–MS systems.

The application of comprehensive two-dimensional gas chromatography to the analysis of wildfire debris for ignitable liquid residue

Arsonous wildfires are complex investigations due to the high abundance of natural background compounds and subsequent pyrolysis by-products formed during combustion. These interfering compounds can be present in large concentrations and overwhelm the marker compounds used to identify ignitable liquid residue (ILR). Complex matrix effects often interfere with the identification of ILR, providing ambiguous results. The use of comprehensive two-dimensional gas chromatography with time of flight mass spectrometry (GC×GC-TOFMS) separates natural compounds from interfering with ILR compounds of interest. When compared to standard gas chromatography-mass spectrometry (GC–MS) analysis, GC×GC was able to reduce the number of tentative results by 20%. Certain compounds were determined to be unusable for the identification of ILR in wildfire debris samples, in particular the Three Musketeer Group (ethylbenzene, m,p-xylene, and o-xylene), which are ubiquitous in all samples, as well as long chain n-alkylbenzenes, which are formed in the pyrolysis of organic matter. Conversely, the presence of C1- and C2-alkylnaphthalenes were excellent indicators of the presence of gasoline-type ILR. A sizeable number of background samples were collected that helped to provide additional lines of evidence when classifying samples for ILR. Given the complicated matrices encountered in arsonous wildfires, it is evident that GC×GC provides better capabilities at identifying ILR than the standard GC–MS analytical technique.

Effect of Different Matrices on the Identification of Ignitable Liquid Residue in Post Burn Arson Debris: A Multi-Derivative UV-Visible Spectrophotometric Approach

Analysis of arson debris is the foremost challenging task to the forensic investigators. Identification of the ignitable liquid residues in the fire debris is one of the prime objectives of forensic quest. This study evaluates the potential of derivative ultraviolet-visible spectrophotometric methods for the analysis and identification of ignitable liquid residues. In this work, arson was simulated using kerosene as an ignitable liquid on various matrices. Derivative UV spectra of kerosene were recorded in their neat state and compared with those obtained from simulated fire debris samples for the identification and detection of ignitable liquid residues. It was observed that different burnt substrates did not cause any interference. The obtained results indicated that the ignitable liquid absorption capacity of the substrate can play an important role in the extraction and identification of ignitable liquid from fire debris. The used technique proved to be rapid, easy, reproducible and efficient.

Detection and Classification of Ignitable Liquid Residues in the Presence of Matrix Interferences by Using Direct Analysis in Real Time Mass Spectrometry.

Conventional Gas Chromatography-Mass Spectrometry (GC-MS) methods for the analysis of ignitable liquids (ILs) are usually time-consuming, and the data produced are difficult to interpret. A fast IL screening method using direct analysis in real time mass spectrometry (DART-MS) is proposed in this study. GC-MS, QuickStrip DART-MS, and thermal desorption DART-MS methods were used to analyze neat ILs and thermal desorption DART-MS without extraction was used to analyze ILs on five substrates (e.g., carpet, wood, cloth, sand, and paper). Compared to GC-MS, DART-MS methods generated different spectral profiles for neat ILs with more peaks in the higher mass range and also provided better detection of less volatile compounds. ILs on substrates were successfully classified (98±1%) using partial least squares discriminant analysis (PLS-DA) models based on thermal desorption DART-MS data. This study shows that DART-MS has great potential for the high-throughput screening of ILs on substrates.

Novel method based on ion mobility spectrometry sum spectrum for the characterization of ignitable liquids in fire debris

The destructive nature of fire together with a variety of interfering products from pyrolysis or background compounds among others, still offer a challenge on the proper identification of ignitable liquid residues (ILRs) in fire investigations. Nowadays, analysts use chromatography-mass spectrometry to try and classify ignitable liquids (IL) into one of the classes in the American Standards Testing Material method (ASTM E1618). In this study, an alternative approach is proposed to such analysis of fire debris. The proposed method would be based on ion mobility spectrometry sum spectrum (IMSSS) from headspace analysis, in combination with pattern recognition tools (Linear Discriminant Analysis, LDA). Four different substrates (pinewood, cork, paper, and cotton sheet) were burnt with and without different ILs (gasoline, diesel, ethanol, and paraffin). According to LDA, 100% of fire debris samples were correctly classified for presence/absence and type of IL. A characteristic fingerprint for each ILR was created for quick discrimination. These results demonstrate the potential of using IMSSS for a fast, objective and easy interpretation of fire debris data. In addition, ion mobility spectrometry (IMS) presents some advantages over traditional techniques such as its real-time monitoring capability and its capacity to work at atmospheric pressure, which allow the development of portable devices that would perform the analysis at the fire scene.

Fire Debris Analysis: A Need to Develop Databases

Fire debris analysis is a branch of forensic chemistry which deals with the examination and analysis of fire debris samples in order to detect and identify ignitable liquid residues in them. In addition to arson, fire debris analysis is usually performed in cases of fires of suspicious origin [1]. In addition to this, petrol bombs are used in social or religious riots, and terrorist activities. In a developing country like India, “bride burning” for dowry presents another aspect of such crimes and includes cases of homicidal or suicidal burning which require such examination [2]. Fire debris analysis is performed to determine the presence or absence of ignitable liquids in samples, to identify the chemical composition of ignitable liquid, the class of ignitable liquid, and to establish an association between ignitable liquid residues and its source.

The potential interference of body products and substrates to the identification of ignitable liquid residues on worn clothing

The question of whether deposits on clothing as well as their chemical composition are being mistaken for ignitable fluids is a concern for forensic analysts. Body products and oil secretions can have similar chemical profiles to ignitable liquid residues (ILRs) as a result of comparable chemical compounds that may be found in both sources. This study investigated whether substrates of unworn and worn clothing, with endogenous body secretions and body products could interfere with ILR analysis. Sample extraction was completed by passive headspace concentration with activated charcoal strips (ACS) and desorption with carbon disulfide followed by analysis with gas chromatography-mass spectrometry (GC–MS). Results showed that some body products produce similar patterns to heavy petroleum distillates and most clothing contained components that are commonly found in ignitable liquids. It was concluded that the clothing, body products and compounds released by the body all contribute to the GC–MS profile of worn clothing. These components can mimic or mask the presence of ILRs, however educated and experienced analysts would likely be able to differentiate these substrate patterns from ILRs.

Application of Self-Organizing Maps to the Analysis of Ignitable Liquid and Substrate Pyrolysis Samples

Classification of un-weathered ignitable liquids is a problem that is currently addressed by visual pattern recognition under the guidelines of Standard Test Method for Ignitable Liquid Residues in Extracts from Fire Debris Samples by Gas Chromatography-Mass Spectrometry, ASTM E1618-14. This standard method does not separately address the identification of substrate pyrolysis patterns. This report details the use of a Kohonen self-organizing map coupled with extracted ion spectra to organize ignitable liquids and substrate pyrolysis samples on a two-dimensional map with groupings that correspond to the ASTM-classifications and separate the substrate pyrolysis samples from the ignitable liquids. The component planes give important information regarding the ions from the extracted ion spectra that contribute to the different classes. Some additional insight is gained into grouping of substrate pyrolysis samples based on the nature of the unburned material as a wood or non-wood material. Further subclassification was not apparent from the self-organizing maps (SOM) results.

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.

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.

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

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