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The aim of the research is to determine changes in the composition of selected gasoline compounds in cotton carpet samples due to different weathering times. EVO 95 gasoline was used as a fire accelerant and a cotton carpet was used as a matrix. The samples were exposed to various weathering durations (0–360 min) in laboratory conditions. We investigated samples that were unburnt (only weathered) and samples that were burned and subsequently subjected to further weathering. Residual gasoline compounds in carpet samples were determined by gas phase extraction (headspace – HS) coupled with gas chromatography (GC) and mass spectrometry (MS). We focused on the comparison of selected gasoline compounds; toluene, ethylbenzene, p-xylene, 1,2,3-trimethylbenzene (TMB), 1,3,5-trimethylbenzene and naphthalene. The biggest changes were determined in the reduction of the intensity of most volatile compounds (alkylalkanes), where toluene decreased by 11.92%. A similar but not so pronounced trend, occurred in the burned samples, where toluene decreased by 7.40%. Minor changes occurred in alkyl derivatives of benzene, where some of the total 15 gasoline markers also occur, e.g. (1,2,3-trimethylbenzene, 1,3,5-trimethylbenzene). On the contrary, naphthalene as a heavier compound showed an increase in intensity about 0.42%. For burnt samples, the increase was 1.31%. The results show that largest changes can be observed after four or five hours of weathering, which implies the need for rapid sampling and subsequent timely analysis. [ABSTRACT FROM AUTHOR]

As the combustibles are almost in contact with the oxidizers and mostly all conditions are available to start a fire, this review covers the fire scene which could be intentionally or unintentionally started using a combustible liquid. The first step in the way of investigation is identifying the starting point of the fire, followed by knowing the causes of the fire and collecting fire debris samples to determine the presence of ignitable liquid residues. The fire debris collected from the crime scene is subjected to different extractions that including solvent extraction, distillation, headspace, and solid phase micro-extraction. Among the commonly used extraction methods, headspace and solid phase micro-extraction are on top because they are fast, solvent-less, and have no loss of sample concentration. The sample is usually analyzed by the gas chromatography technique, which is the most sensitive and effective method for detecting and characterizing ignitable liquid residues, to identify the components.

The Grenfell Tower fire in London in 2017 is popularly associated with a litany of failures: political, structural, moral, material. But while the official inquiry has sought to frame the fire as a discrete event, for local residents it is inextricable from accumulated histories of injustice and inequality. Years on, the fire still reverberates, its afterlife constellating with new narratives and politics. Drawing on literature on ruination and remains, as well as methodological theory, this essay examines how the form of failure is never pre‐known but must be made to appear. Through diverse encounters with the tower's debris – material and conceptual – failure is made to matter, acting both backwards and forwards in time. Reflecting on remainders and erasures at the tower site, as well as debates about the parameters of the inquiry, I explore how failure is continually recomposed, becoming both an object of knowledge and an instrument for its formation. [ABSTRACT FROM AUTHOR]

F-500 Encapsulator Agent (EA) is a fire suppression agent that is an alternative to traditional firefighting foams. It is marketed as having the capability to act on all four parts of the fire tetrahedron as well as being environmentally friendly and non-toxic. An internal survey of the use of F-500 EA by fire departments encountered by the Bureau of Alcohol, Tobacco, Firearms and Explosives (ATF) ignitable liquid detection canine (ILDC) handlers in 2022 showed that this product is not yet in widespread use across the country, but where it has been implemented, it is frequently utilized on a variety of types of fires. Additional agencies are researching the product to determine if it should be adopted. As this product appears to be growing in popularity, it is important to understand whether the use of the product would affect a canine's ability to detect ignitable liquids or a forensic laboratory's ability to identify the presence of an ignitable liquid. Burned wood and burned carpet, two commonly encountered substrates, were spiked with gasoline or a heavy petroleum distillate (HPD) and F-500 EA was applied. At various time intervals, ILDC teams surveyed the samples and laboratory analysis was conducted. Results showed that the presence of F-500 EA can negatively affect canine alerts and the laboratory's ability to identify ignitable liquids. • F-500 Encapsulator Agent appears in data during routine ignitable liquid analysis with passive headspace concentration. • The effect of the product on canine detection and ignitable liquid analysis varied based on substrate and ignitable liquid. • Results show the product has the potential to interfere with canine detection of ignitable liquids and laboratory analysis. [ABSTRACT FROM AUTHOR]

In arson fires, ignitable liquids (ILs) are frequently used to start combustion. For this reason, detecting IL residues (ILRs) at the fire scene is a key factor in fire investigation to determine whether a crime has been committed as well as to establish the modus operandi of the perpetrator. In the present study, the application of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) for the detection of ILRs in fire debris from complex matrices in combination with machine learning (ML) tools is proposed as an alternative to the traditional method, based on gas chromatography–mass spectrometry (GC-MS), described by the ASTM E1618 standard method. For this purpose, petroleum-derived substrates (vinyl, nylon, and polyester) and natural substrates (cotton, cork and linoleum) burned alone and with different ILs (gasoline, diesel, ethanol and charcoal starter with kerosene) were used. In addition, samples were taken at different times (0, 1, 6, 12, 24 and 48 h) after the fire was finished. The ion mobility sum spectrum (IMSS) of each sample was obtained and different ML algorithms were applied. The first derivative was performed at the IMSS, as well as a Savitzky-Golay filter. Hierarchical cluster analysis (HCA) revealed a clustering trend as a function of substrate and ILs used, where the studied sampling times did not affect the resulting clusters. The classification models for the detection of the presence of ILRs have high performance with an accuracy of 100% for support vector machines (SVM) and random forest model (RF), followed by linear discriminant analysis (LDA) with an accuracy of 86.67%. When discriminating the type of ILs used, the RF model obtained an accuracy of 100%, followed by the LDA with 97.22% and finally the SVM model with an accuracy of 93.06%. In addition, a simple web application has been developed where the trained models can be used, so any researcher can apply the method to detect ILRs in fire debris.

Rubber is prone to introduce matrix interference on gasoline identifications due to its petrochemical origin. As a typical rubber product, automobile tire is also commonly extracted physical evidence in automobile fire scenes. On account of the various rubber components in tires of different parts and brands, the characteristic compounds extracted in their corresponding residues also differ since combustion products are closely related to chemical components, which may lead to different extents of interference. The research herein qualitatively analyzed the combustion residues of tires with and without gasoline via gas chromatography–mass spectrometry (GC–MS). Alkylbenzenes, condensed ring aromatics and the homolog of indanes generated during the combustion of tires notably interfered with gasoline identifications. Specifically, more types of C4-alkylbenzenes were detected in treads than sidewalls did. The residues of tires and gasoline can be distinguished by P-phenylenediamine and long-chain alkanes (C11 ~ C15). When loaded with gasoline, some diagnostic PAHs for gasoline identifications were absent, causing a negative effect on fire debris analysis. Compared with Michelin tires, the EIC of PAHs was more severely distorted due to the involvement of Kumho tires. The experimental data and conclusions about the interference from tires on gasoline identifications can provide solid supports for debris identifications practically. [ABSTRACT FROM AUTHOR]

Deadly and destructive debris flows often follow wildfire, but understanding of changes in the hazard potential with time since fire is poor. We develop a simulation‐based framework to quantify changes in the hydrologic triggering conditions for debris flows as postwildfire infiltration properties evolve through time. Our approach produces time‐varying rainfall intensity‐duration thresholds for runoff‐ and infiltration‐generated debris flows with physics‐based hydrologic simulations that are parameterized with widely available hydroclimatic, vegetation reflectance, and soil texture data. When we apply our thresholding protocol to a test case in the San Gabriel Mountains (California, USA), the results are consistent with existing regional empirical thresholds and rainstorms that caused runoff‐ and infiltration‐generated debris flows soon after and three years following a wildfire, respectively. We find that the hydrologic triggering mechanisms for the two observed debris flow types are coupled with the effects of fire on the soil saturated hydraulic conductivity. Specifically, the rainfall intensity needed to generate debris flows via runoff increases with time following wildfire while the rainfall duration needed to produce debris flows via subsurface pore‐water pressures decreases. We also find that variations in soil moisture, rainfall climatology, median grain size, and root reinforcement could impact the median annual probability of postwildfire debris flows. We conclude that a simulation‐based method for calculating rainfall thresholds is a tractable approach to improve situational awareness of debris flow hazard in the years following wildfire. Further development of our framework will be important to quantify postwildfire hazard levels in variable climates, vegetation types, and fire regimes. Plain Language Summary: Wildfire can radically change a mountainous landscape such that even a modest rainstorm is capable of producing deadly and destructive flash flooding and debris flows. While we have tools to understand the likelihood of debris flows immediately following a fire, we lack the tools to assess debris flow hazard with time as the burned landscape recovers. We develop an approach to calculate the time‐variable criteria for the initiation of postwildfire debris flows with a simulation framework that is computationally efficient and makes use of widely available input data. Our protocol produces warning criteria that are consistent with observations of debris flows immediately after and three years following a wildfire that occurred in southern California. We find that the effect of fire on the infiltration of water into soil can markedly influence the triggering conditions for debris flows. As wildfire activity extends into areas for which debris flow susceptibility is an open question, our work indicates that a simulation‐based approach that can account for the time‐variable effects of fire on the surface hydrology could be an effective tool to better inform the emergency management community. Key Points: Developed methodology to identify time‐variable thresholds for postwildfire debris flows with hydrologic and slope stability modelingResultant thresholds are consistent with postwildfire debris flow observations and existing empirical thresholds in southern CaliforniaSimulation‐based framework is a tractable approach to develop warning criteria for debris flow hazard in the years following wildfire [ABSTRACT FROM AUTHOR]

[Display omitted] • HS-GC–MS method was successfully optimized for the classification of fire debris. • ILRs from ACS were thermally desorbed as a safer and greener alternative. • Total ion spectrum instead of chromatography data was used for data interpretation. • PCA showed a classification based on the presence/absence and classification of ILs. The main goal of any fire investigation is to find the origin and cause of fire. Fire is commonly initiated or accelerated by using ignitable liquids (ILs). The analysis of fire debris can contribute to the determination of the origin of the fire. In this study, the thermal desorption of IL residues (ILRs) from activated charcoal strips (ACS) was optimized prior to headspace- gas chromatography- mass spectrometry (HS-GC–MS) analysis for the identification and classification of ILRs in fire debris samples. A Box-Behnken Design (BBD) coupled with Response Surface Methodology (RSM) were used to determine the optimized conditions in the following ranges: incubation temperature (80–140 ˚C), incubation time (30–60 min), and agitation speed (250–750 rpm). The sum of the differences between the total ion spectrum (TIS) of gasoline and diesel was used as dependent variables. The quadratic model was significant with a p - value of 0.0061 and a coefficient of determination equals to 0.911. RSM revealed that an increase in incubation temperature and agitation speed increases the response. The optimized conditions were 140 °C and 750 rpm. Further optimization of the incubation time was studied by analyzing fire debris samples at different times (5–30 min) and 5 min was determined as the optimum condition. The final optimized conditions were applied in combination with chemometrics for the characterization of fire debris samples burned with different ILs. The obtained results demonstrate the feasibility of the method in fire debris analysis which avoids the use of organic solvents providing a greener and faster alternative method. [ABSTRACT FROM AUTHOR]

Analysis of fire debris for triglyceride‐based oils may be of interest to fire investigators depending on the circumstances of a particular fire. Such circumstances include accidental or intentionally set cooking oil fires, fires involving triglyceride‐based "eco" fire log products, and spontaneous ignition fires that involve drying oils on rags. Many forensic laboratories utilize gas chromatography‐mass spectrometry following fatty acid methyl esterification to identify triglyceride residues in fire debris extracts. This study explores an alternate approach, which involves the identification of intact triglycerides by liquid chromatography‐mass spectrometry‐mass spectrometry (LC‐MS/MS). 52 triglyceride‐based oils and fats (22 different types) were analyzed by LC‐MS/MS using multiple reaction monitoring to investigate variation in triglyceride content between different brands and types of oil and fat. Selected oils were then degraded by exposure to air, typical cooking conditions and/or fire conditions to simulate samples that are typically encountered by Fire Debris Analysts in fire investigation cases. Triglycerides were identified in all pristine and degraded oil samples, and relative peak areas for degraded samples often resembled their pristine oil counterparts. In samples where relative peak area differences were noted, more predominant degradation was observed for triglycerides with a higher proportion of poly‐unsaturated fatty acids. Variability in triglyceride content between different brands and types of oil are discussed, as well as factors affecting the identification of triglyceride peaks in commercial oil samples, as compared to the corresponding analytical standard. [ABSTRACT FROM AUTHOR]

The article deals with the current issue of evaluation of qualitative results uncertainty of chemical analyses in the example of chromatographic analyses of specimens of accelerants from a fire place with the SPME-GC/MS technique. The suitability of this technique demonstrates with the results of alidation measurements of analytical characteristics: sensitivity, detection limits, linearity, selectivity and repeatability. It characterizes briefly the current state of knowledge in the area and applies the Bayesian theory for the unconditional “a-priori” probability of an analyte presence in a sample, P (H) of 0.5 and 0.95 for calculation estimates the “a-posteriori” conditional probability of the presence of the analyte in the sample relative to the experimental evidence, P (H / E) with the results of 0.97 and 0.98. This result can be interpreted as a high level of assurance of the hypothesis of presence of the analyte in the sample. In conclusion it is stated that the knowledge can also be applied in the field of construction not only in qualitative analyses of building materials / products, e. g, by FTIR, but also in the probability risk assessment.

Postfire debris flows are particularly complex to study because they do not form discrete initiation locations and commonly involve multiple simultaneously operating erosional processes. Although recent work has begun to elucidate a more mechanistic understanding of postfire debris flows, there is still a paucity of detailed sediment budgets characterizing these events. In this study, we seek to understand how postfire sediment sources and erosional processes change over multiple storm cycles. To do this, we performed repeat high‐resolution change detection in a headwater catchment burned by the 2018 Holy Fire in the Santa Ana Mountains, California, USA. This included terrestrial laser scanning in a zero‐order catchment (0.95 ha) and unmanned aerial vehicle structure from motion of a headwater channel network (up to 6.5 ha). During the initial storm events that produced runoff‐generated debris flows, we found that the evacuation of dry ravel and prefire colluvium accounted for half of the eroded material. These initial flows also acted to clear out much of the material stored within downstream headwater channel networks. In subsequent storm events of equal or greater rainfall intensity, total erosion from the study site was subdued, and the relative importance of shallow hillslope erosion from interrill and rill erosion was increased, as has been noted in similar studies in the region. Overall, this suggests that channel sediment supplies may be more rapidly depleted than hillslope sources, which may drive a trend of decreasing sediment fluxes over time from burned headwater catchments subject to repeated runoff events. Key Points: Repeat change detection was employed to explore the evolution of postfire sediment sources over a series of storms following wildfireHeadwater channel erosion decreased significantly over time, increasing the importance of shallow hillslope sources later in the seasonEvent‐scale sediment fluxes decreased over the season, which was driven by declining channel sediment supply [ABSTRACT FROM AUTHOR]

Chemometric applications related to the analysis of ignitable liquids (ILs) and fire debris samples have evolved over the last 30 years. Most older papers focused on the use of chemometrics for classification of ILs by manufacturer, grade or into classes defined by the American Society for Testing and Material (ASTM) standard test method ASTM E1618. More recently, chemometric studies in fire debris analysis have focused on estimating the strength of the evidence in the form of a likelihood ratio (LR). The progression of chemometric methods from simple classification tasks to the calculation of LRs and statements of evidentiary value has implications across all disciplines of forensic science. Most of the data analyzed by chemometric methods in forensic fire debris analysis come from gas chromatography–mass spectrometry, although several studies have examined data from head space‐mass spectrometry and other sensors. Retention time alignment is a challenge that must be addressed if chemometric methods are intended to have interlaboratory applicability. Several of the reports reviewed here rely on data representations that avoid retention time alignment issues. Attempts to apply chemometric methods to the analysis of ILs and fire debris samples has for the most part been an academic exercise and the results have not made their way into accredited forensic laboratories and established protocols. The chemometric methods are well‐founded in statistical principles and they can provide a means of strengthening forensic fire debris analysis in the future. This article is categorized under:Forensic Chemistry and Trace Evidence > Fire Debris AnalysisForensic Chemistry and Trace Evidence > Trace EvidenceForensic Chemistry and Trace Evidence > Presentation and Evaluation of Forensic Science Output [ABSTRACT FROM AUTHOR]

The detection and identification of cigarette ash in fire debris can be meaningful in fire investigations caused by burning cigarettes. In this work, a novel analytical method based on negative chemical ionization time-of-flight mass spectrometry (NCI/TOFMS) combined with a phosphoric-acid-enhanced evaporation strategy has been developed for the discrimination of cigarette ash samples (CAs) and common household decoration material ash samples (CHDMAs). A series of characteristic ions representing the acidified products HNCO and formic acid in the CAs were achieved, whose signal responses were enhanced with the help of mechanical agitation operation. To account for both the signal responses of the characteristic ions and acid corrosion of the ion source, the dynamic-purge gas was chosen to be 200 mL/min. The whole time for analysis was only 5 min, which is suitable for high-throughput measurements of large quantities of fire debris. As a result, a preliminary discrimination was achieved between the CAs and CHDMAs by virtue of the chemometric tool of principal components analysis (PCA) based on intensity differences of the characteristic ions. The results are encouraging and highlight the potential of NCI/TOFMS without complicated sample preparation steps for the accurate and high-throughput identification of cigarette ash on substrates in fire debris. [ABSTRACT FROM AUTHOR]

Fast Gas Chromatography (GC) allows for analysis times that are a fraction of those seen in traditional capillary GC. Key modifications in fast GC include using narrow, highly efficient columns that can resolve mixtures using a shorter column length. Hence, a typical fast GC column has an inner diameter of 100–180 μm. However, to maintain phase ratios that are consistent with typical GC columns, the film thickness of fast GC stationary phases are also low (e.g., 0.1–0.18 μm). Unfortunately, decreased film thickness leads to columns with very low sample capacity and asymmetric peaks for analytes that are not sufficiently dilute. This paper describes micro-bore (50 μm i.d.) capillary columns with thick films (1.25 μm), and low phase ratios (10). These columns have greater sample capacity yet also achieve minimum plate heights as low as 110 μm. Hence, separation efficiency is much higher than would be obtained using standard GC columns. The capillary columns were prepared in-house using a simple static-coating procedure and their plate counts were determined under isothermal conditions. The columns were then evaluated using temperature programming for fast GC–MS analysis of ignitable liquids and their residues on fire debris exemplars. Temperature ramps of up to 75 °C min−1 could be used and separations of ignitable liquids such as gasoline, E85 fuel, and lighter fluid (a medium petroleum distillate) were complete within 3 min. Lastly, simulated fire debris consisting of ignitable liquids burned on carpeting were extracted using passive headspace absorption-elution and the residues successfully classified. • In-house Fast GC columns prepared balancing separation efficiency and loadability. • Full separation of ASTM e1618 test mixture in less than three minutes. • Separations for classification of gasoline in less than three minutes. • Demonstrated application of columns to ignitable liquid residues on fire debris. [ABSTRACT FROM AUTHOR]

Abstract 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. Graphical abstract fx1 Highlights • A novel method based on the direct analysis of the headspace by IMS is proposed. • IMS combined with chemometrics allows the determination of the presence of ILRs. • Full discrimination among different ILRs from fire debris was achieved. • The developed fingerprints allow for a fast characterization of ILRs. • IMS is a very promising tool and a good alternative for fire debris analysis. [ABSTRACT FROM AUTHOR]

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Highlights • Post-fire litters contain more water extractable organic carbon than litters not affected by fire. • The effect of fire was greater for pine litter than native litter. • Water extractable organic carbon varies linearly with microbial activity. Abstract Under conditions of increased fire season length and area affected by fire, stocks of carbon stored in forests are at increased risk of burning. While much research has investigated the immediate loss of above ground and below ground carbon stocks through combustion during a fire, there has been little research on subsequent organic matter cycling in post-fire environments. Fire can introduce new organic matter to the litter layer through the formation of a post-fire litter layer composed of debris from fire induced plant stress or death. This litter may have different chemistry and decomposition dynamics to the pre-fire litter due to the changed pathway from plant to ground and the narrow age range of the debris. In this study, litters collected from two vegetation types (Pinus and Eucalyptus dominated) and from adjacent areas either fire affected (FA) or not fire affected (NFA) were incubated as litter, or as water extracts of litter, in soils to determine fire induced changes in nutrient pools, microbial biomass and microbial activity. Post-fire litters contained more labile C (15 and 30 mg C g native/pine litter−1, respectively) than litters unaffected by fire (4 mg C g litter−1). Increased labile C concentration correlated (r2 > 0.95) with increased microbial activity without a concurrent change in nitrogen (microbial) or phosphorus (resin and microbial) pools. Our results suggest that labile C in post-fire litter can alter microbial carbon cycling and that effects may be more pronounced under pine compared to native forest. [ABSTRACT FROM AUTHOR]

Recent research efforts in the domain of fire debris analysis have been mainly oriented towards the development of innovative analytical procedures and chemometric approaches for the detection and classification of ignitable liquids in fire specimens according to the ASTM E1618. However, less attention has been brought to the question of the source inference of ignitable liquids. Infer the identity of source of ignitable liquids recovered from arson sites is still a challenging and ongoing research area. In this study, the objective is to link neat gasoline samples sharing a common source through the use of an untargeted chemometric approach applied to data acquired by automated thermodesorption (ATD)-GC-MS following passive headspace extraction onto Tenax TA tubes. To that end, 190 unique gasoline samples from 19 gas stations collected over a year were used. A general and automated chemometric methodology for data treatment involving the following main steps is proposed: feature detection, normalization by exhaustive calculation of ratios between areas of pairs of features and selection of most discriminant ratios. The ratio selection procedure used here is based on the calculation of similarity measurements between pairs of samples sharing a common source or not. The algorithm maximizes the separation of the distributions of similarity measurements for related and unrelated samples by selecting a subset of ratios maximizing the area under the Receiver Operating Characteristics curve. The approach presented here was successfully applied to neat gasoline samples in order to assess if two gasoline samples share a common source or not. [ABSTRACT FROM AUTHOR]

An estimation method for debris flow potential is proposed to evaluate the possibility of the occurrence of rain-triggered debris flows. Sakurajima volcano has repeatedly erupted (Vulcanian type) and has continuously emitted volcanic ash at the Minamidake summit crater or Showa crater east of the summit since 1955, and debris flows have frequently occurred at rates of 10 to 111 events per year. Ground deformation associated with debris flows along the Arimura River were analyzed for the period from 2009 to 2016. Downward tilt (10-450 nrad) in the direction of the river and extensional strain (3-138 nstrain) were detected during occurrence of the debris flows. The tilt and strain changes were modeled using a point load caused by debris flow deposition beside a sabo dam. Depositional weights of individual debris flow events were estimated to range from 6 to 276 kt. The total weight of the debris flows was 2,154 kt, which is approximately 5% of the total weight of volcanic ash ejected from the craters during the study period. Debris flow potential (DFP) was defined as the difference in the volcanic ash deposits along the upper stream of the river (5% of the total) and the lower stream of the river, and the temporal change of the debris flow potential was investigated. When the debris flow potential reached a level of 0.4Mt resulting froman increase in eruptive activity, debris flows frequently occurred or large debris flows were induced during rainy seasons. The concept of debris flow potential was applied to volcanoes in Indonesia as lahar potential. After the 2010 eruption at Merapi volcano, lahar potential, perhaps, quasi-exponentially decays during the dormant period. The lahar potential of Sinabung volcano complicatedly varies because of long-term eruptivity beginning in 2014. [ABSTRACT FROM AUTHOR]

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.

The sample analysis and data interpretation is the most challenging step of fire debris analysis, due to the presence of combustion and pyrolysis products in the substrate material. In this study, a headspace solid phase microextraction (HS-SPME) procedure was applied to the extraction of combustion and pyrolysis products from three commonly used carpet substrate materials, made of nylon 6,6 and polyesters. Each carpet sample was burned with and without two different ignitable liquids (ILs), i.e., gasoline and kerosene, and the Total Ion Chromatograms (TICs) and Extracted Ion Profiles of characteristic class compounds of ILs were obtained and compared to those of unburned neat ILs, using gas-chromatography mass spectrometry (GC-MS), to study the possible interferences of these substrate materials in fire debris analysis.

Identification of ignitable liquids from fire debris is such a major part of an arson investigation that much time and effort has gone into advancing sample preparation techniques to capture complicated and unexpected hydrocarbon compounds. Advancements in sample preparation have been made in order to account for biodegradation of commonly used accelerants, rarely encountered compounds, such as vegetable oils, biodiesel, and alcohols. Improvements have also been made to manage interference from the sample matrix, particularly with regards to new materials. This paper is a review of the sample preparation techniques that are foundational to fire debris analysis as well as recent advances. Also explored are modifications to the traditional sample preparation methods to accommodate the analysis of environmental samples (soil and water), and the presence of vegetable oils and biofuels on the fire scene. [ABSTRACT FROM AUTHOR]

Rainfall-induced debris flows in recently burned mountainous areas cause significant economic losses and human casualties. Currently, prediction of post-fire debris flows is widely based on the use of power-law thresholds and logistic regression models. While these procedures have served with certain success in existing operational warning systems, in this study we investigate the potential to improve the efficiency of current predictive models with machinelearning approaches. Specifically, the performance of a predictive model based on the random forest algorithm is compared with current techniques for the prediction of post-fire debris flow occurrence in the western United States. The analysis is based on a database of post-fire debris flows recently published by the United States Geological Survey. Results show that predictive models based on random forest exhibit systematic and considerably improved performance with respect to the other models examined. In addition, the random-forest-based models demonstrated improvement in performance with increasing training sample size, indicating a clear advantage regarding their ability to successfully assimilate new information. Complexity, in terms of variables required for developing the predictive models, is deemed important but the choice of model used is shown to have a greater impact on the overall performance. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract: Alignment of fire debris data from GC‐MS for chemometric analysis is challenged by highly variable, uncontrolled sample and matrix composition. The total ion spectrum (TIS) obviates the need for alignment but loses all separation information. We introduce the segmented total ion spectrum (STIS), which retains the advantages of TIS while retaining some retention information. We compare the performance of STIS with TIS for the classification of casework fire debris samples. TIS and STIS achieve good model prediction accuracies of 96% and 98%, respectively. Baseline removal improved model prediction accuracies for both TIS and STIS to 97% and 99%, respectively. The importance of maintaining some chromatographic information to aid in deciphering the underlying chemistry of the results and reasons for false positive/negative results was also examined. [ABSTRACT FROM AUTHOR]

Abstract: Soils in post‐wildfire environments are often characterized by a low infiltration capacity with a high degree of spatial heterogeneity relative to unburned areas. Debris flows are frequently initiated by run‐off in recently burned steeplands, making it critical to develop and test methods for incorporating spatial variability in infiltration capacity into hydrologic models. We use Monte Carlo simulations of run‐off generation over a soil with a spatially heterogenous saturated hydraulic conductivity (Ks) to derive an expression for an aerially averaged saturated hydraulic conductivity ( K e *) that depends on the rainfall rate, the statistical properties of Ks, and the spatial correlation length scale associated with Ks. The proposed method for determining K e * is tested by simulating run‐off on synthetic topography over a wide range of spatial scales. Results provide a simplified expression for an effective saturated hydraulic conductivity that can be used to relate a distribution of small‐scale Ks measurements to infiltration and run‐off generation over larger spatial scales. Finally, we use a hydrologic model based on K e * to simulate run‐off and debris flow initiation at a recently burned catchment in the Santa Ana Mountains, CA, USA, and compare results to those obtained using an infiltration model based on the Soil Conservation Service Curve Number. [ABSTRACT FROM AUTHOR]

The characteristic that discriminates gasoline from other ignitable liquids is that it contains high-octane blending components. This study elaborates on the idea that the presence of gasoline in fire debris samples should be based on the detection of known high-octane blending components. The potential of the high-octane blending component alkylate as a characteristic feature for gasoline detection and identification in fire debris samples is explored. We have devised characteristic features for the detection of alkylate and verified the presence of alkylate in a large collection of gasoline samples from petrol stations in the Netherlands. Alkylate was detected in the vast majority of the samples. It is demonstrated that alkylate can be detected in fire debris samples that contain traces of gasoline by means of routine GC-MS methods. Detection of alkylate, alongside other gasoline blend components, results in a more solid foundation for gasoline detection and identification in fire debris samples. [ABSTRACT FROM AUTHOR]

The article deals with the current issue of evaluation of qualitative results uncertainty of chemical analyses in the example of chromatographic analyses of specimens of accelerants from a fire place with the SPME-GC/MS technique. The suitability of this technique demonstrates with the results of alidation measurements of analytical characteristics: sensitivity, detection limits, linearity, selectivity and repeatability. It characterizes briefly the current state of knowledge in the area and applies the Bayesian theory for the unconditional "a-priori" probability of an analyte presence in a sample, P (H) of 0.5 and 0.95 for calculation estimates the "a-posteriori" conditional probability of the presence of the analyte in the sample relative to the experimental evidence, P (H / E) with the results of 0.97 and 0.98. This result can be interpreted as a high level of assurance of the hypothesis of presence of the analyte in the sample. In conclusion it is stated that the knowledge can also be applied in the field of construction not only in qualitative analyses of building materials / products, e. g, by FTIR, but also in the probability risk assessment. [ABSTRACT FROM AUTHOR]

Forensic fire debris analysis is an important part of fire investigation, and gas chromatography–mass spectrometry (GC-MS) is the accepted standard for detection of ignitable liquids in fire debris. While GC-MS is the dominant technique, comprehensive two-dimensional gas chromatography–mass spectrometry (GC×GC-MS) is gaining popularity. Despite the broad use of these techniques, their sensitivities are poorly characterized for petroleum-based ignitable liquids. Accordingly, we explored the limit of identification (LOI) using the protocols currently applied in accredited forensic labs for two 75% evaporated gasolines and a 25% evaporated diesel as both neat samples and in the presence of interfering pyrolysate typical of fire debris. GC-MSD (mass selective detector (MS)), GC-TOF (time-of-flight (MS)), and GC×GC-TOF were evaluated under matched conditions to determine the volume of ignitable liquid required on-column for correct identification by three experienced forensic examiners performing chromatographic interpretation in accordance with ASTM E1618-14. GC-MSD provided LOIs of ~0.6 pL on-column for both neat gasolines, and ~12.5 pL on-column for neat diesel. In the presence of pyrolysate, the gasoline LOIs increased to ~6.2 pL on-column, while diesel could not be correctly identified at the concentrations tested. For the neat dilutions, GC-TOF generally provided 2× better sensitivity over GC-MSD, while GC×GC-TOF generally resulted in 10× better sensitivity over GC-MSD. In the presence of pyrolysate, GC-TOF was generally equivalent to GC-MSD, while GC×GC-TOF continued to show 10× greater sensitivity relative to GC-MSD. Our findings demonstrate the superior sensitivity of GC×GC-TOF and provide an important approach for interlaboratory benchmarking of modern instrumental performance in fire debris analysis.

Composite material structures are commonly used in many industrial sectors (aerospace, automotive, transportation), and can operate in harsh environments where impacts with other parts or debris may cause critical safety and functionality issues. This work presents a method for improving the accuracy of impact position determination using acoustic source triangulation schemes based on the data collected by piezoelectric sensors attached to the structure. A novel approach is used to estimate the Differential Time-of-Arrival (DToA) between the impact response signals collected by a triplet of sensors, overcoming the limitations of classical methods that rely on amplitude thresholds calibrated for a specific sensor type. An experimental evaluation of the proposed technique was performed with specially made circular piezopolymer (PVDF) sensors designed for Structural Health Monitoring (SHM) applications, and compared with commercial piezoelectric SHM sensors of similar dimensions. Test impacts at low energies from 35 mJ to 600 mJ were generated in a laboratory by free-falling metal spheres on a 500 mm × 500 mm × 1.25 mm quasi-isotropic Carbon Fiber Reinforced Polymer (CFRP) laminate plate. From the analysis of many impact signals, the resulting localization error was improved for all types of sensors and, in particular, for the circular PVDF sensor an average error of 20.3 mm and a standard deviation of 8.9 mm was obtained. [ABSTRACT FROM AUTHOR]

Aerodynamics of the firebrands' flight is fundamental to fire spotting; yet, this phenomenon is relatively poorly understood. Variants of Tachikawa's transport models have been developed for different shapes of debris but, only simplified versions are implemented in firebrand transport models. Failure to include lift and rotational forces reduces the problem to a two-dimensional one, in contrast to the 3D trajectories observed. As such, many studies may have under-/overestimated the flight distance and failed to capture the spotting distribution, accurately. Also, there is virtually no detailed quantitative experimental validation available for rod-like debris transport models. Hence, a set of free-fall experiments with non-combusting model firebrands were run in the absence of cross-wind. The results are employed for verification and performance evaluation of a 3D deterministic 6-Degrees-Of-Freedom (DOF) rod-like debris transport model. It is shown that a transport model must include the complete 6-DOF aerodynamics of the debris for estimating the flight characteristics, such that results are not statistically significantly different from the experimental data. The findings have applications beyond firebrand transport, as they represent the most comprehensive experimental data set and analysis of rod-like debris transport, currently in the literature. [ABSTRACT FROM AUTHOR]

Examination of fire debris can provide information about the types of materials which were present at the time of the fire to give insights for fire scene reconstruction and understanding compartment fire dynamics. This paper demonstrates the ability of Raman spectroscopy for material identification postfire in complex situations, such as the production of fused masses during fire dropdown. A validated Raman spectral library is combined with Raman mapping in three fire case studies, to determine the individual materials in the fused masses formed. The case studies accessed material combinations of several common polymers. Raman mapping was carried out on a 10 μm × 10 μm square of the masses. Material identification using this technique ranged from a high of 85% match to a low of 40% match. This work demonstrated that complex masses found in the fire debris can be resolved into the individual material components for identification and spatial distribution. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The Transverse Ranges of southern California often experience fire followed by flood. This sequence sometimes causes post-fire debris flows (PFDFs) that threaten life and property situated on alluvial fans. The combination of steep topography, highly erodible rock and soil, and wildfire, coupled with intense rainfall, can initiate PFDFs even in cases of relatively small storm rainfall totals. This study identifies common atmospheric conditions during which damaging PFDFs occur in the Transverse Ranges during the cool season, defined here as November-March. A compilation of 93 PFDF events during 1980-2014 triggered by 19 precipitation events is compared against previous studies of the events, reanalysis, precipitation, and radar data to estimate PFDF trigger times. Each event was analyzed to determine common atmospheric features and their range of values present at and preceding the trigger time. Results show atmospheric rivers are a dominant feature, observed in 13 of the 19 events. Other common features include low-level winds orthogonal to the Transverse Ranges and other conditions favorable for orographic forcing, a strong upper level jet south of the region, and moist-neutral static stability. Several events included closed low-pressure systems or narrow cold frontal rain bands. These findings can help forecasters identify more precisely the synoptic-scale atmospheric conditions required to produce PFDF-triggering rainfall and thus reduce uncertainty when issuing warnings. [ABSTRACT FROM AUTHOR]

This work presents, and demonstrates through application to California, a data-driven methodology that can be used to identify areas at elevated risk of experiencing wildland fires capable of causing large-scale structure loss. A 2D Eulerian level set fire spread model is used as the computational engine for Monte Carlo simulation with ignition points placed randomly across the landscape. For each randomly-placed ignition point, wind and weather conditions are also selected randomly from a 10-year climatology that has been developed by others using the Weather Research and Forecasting (WRF) mesoscale weather model at a resolution of 2 km. Fuel and topography inputs are obtained from LANDFIRE. Housing density is estimated from 2010 Census block data. For each randomly-selected combination of ignition location and wind/weather, fire progression is modeled so that fire area and number of impacted structures can be recorded. This is repeated for over 100 million discrete ignition points across California to generate “heat maps” of fire probability, fire consequence, and fire risk. In this work, fire volume (spatial integral of burned area and flame length) is used as a proxy for fire probability since quickly spreading fires with large flame lengths are most likely to escape initial attack and become extended attack fires. Fire consequence is taken as the number of impacted structures. Fire risk is then estimated as the product of probability and consequence. The methodology is assessed comparing the resultant fire risk raster with perimeters from California's 20 most damaging fires as tabulated by the California Department of Forestry and Fire Protection (CALFIRE). It is found that these historical perimeters from damaging fires correlate well with areas identified as high risk in the Monte Carlo simulation, suggesting that this methodology may be capable of identifying areas where similarly damaging fires may occur in the future. [ABSTRACT FROM AUTHOR]

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 10 min 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. [ABSTRACT FROM AUTHOR]

In the wildland-urban interface, wood decks are a target for wildfire and may be ignited by firebrands or flaming debris. Wood decks also present a potential source for ignition of structures in the wildland-urban interface. However, their role in ignition of the adjacent structure is unclear and current regulation is based in part on anecdotal evidence. This paper examines the results of a set of preliminary laboratory experiments used to determine how experimental variables affect the thermal exposure from a burning wood deck to an attached structure. The experimental setup consists of a test deck of 609 mm by 711 mm (24 inches by 28 inches) on a stand with an attached back wall equipped with two heat flux sensors and twelve thermocouples. Two ignition sources were considered: a below deck flame test using a propane burner and an above deck test using a Class A burning brand. The initial tests study the effect of wind and burner size and were all conducted on redwood decking. The experimental data from these tests showed that wind speeds of 2.9 m/s (6.5 mph) and 5.4 m/s (12 mph) had the highest temperature and heat flux on the wall. These winds were then further tested on three different species; redwood and inert deck boards. The test methods developed herein and the data obtained can be used to gain insight into how a burning wood deck contributes to structural ignition. [ABSTRACT FROM AUTHOR]

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 C 5 –C 9 n -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. [ABSTRACT FROM AUTHOR]

Polytetrafluoroethylene (PTFE) possesses remarkable heat stability, combustibility and low coefficient of friction. In this paper, a kind of new PTFE yarn was spun from PTFE membrane via the method of scrolled-membrane spinning. The morphology of the resultant yarns was characterized by scanning electron microscope. Furthermore, the properties of the yarns were investigated as follow: Single-Yarn Electronic Tensile Strength Tester was used to test the mechanical property, and the dynamic coefficient of friction tester was used to calculate the friction coefficient. And the thermodynamic property of the PTFE yarns was shown by DSC, which the remarkable heat stability demonstrated, containing thermal shrinkage property. Furthermore, the combustibility was investigated and the result showed that the PTFE fiber and Nomex/PTFE fabric possessed desirable thermal properties, where the former was better than the latter. [ABSTRACT FROM AUTHOR]

This review describes recent advances and current trends in fire debris analysis from 2014 to 2021. Onsite analytical techniques used for fire scene investigation, identifying samples of interest for later analysis as well as onsite confirmatory techniques are examined. Laboratory techniques are reviewed both from a perspective of instrumentation and data analysis. Advances in analytical techniques include GC x GC-TOFMS, DART-MS, HS-GC-IMS. New and emerging methods of data analysis including those using machine learning are assessed. Each aspect is essential for forensic scientists to obtain the correct conclusion when collecting, examining, analysing, and interpreting fire debris. This review concludes that there is a need for the validity and certainty of all methods to be assessed if they are to be used to generate reports or draw conclusions. • Detection, recovery, analysis and interpretation of ignitable liquids from fire debris. • Emerging onsite detection technologies are beginning to supersede canines. • GC-MS remains a standard technique despite emerging technologies of greater capability. • Developments in data analysis methodologies are moving towards automation and AI. [ABSTRACT FROM AUTHOR]

We developed a gain–loss approach to estimating the dynamics of the dead organic matter pool in northern Australian savannas consistent with the Intergovernmental Panel on Climate Change 2006 guidance. Previously, only emissions of methane and nitrous oxide were accounted in greenhouse gas budgets. The new approach is based on a modification of the Olson fuel accumulation equation. This modification includes the mean post-fire residue and accounts for losses from both fire and decomposition and for gains from grass production, tree litter fall and the death of trees. We apply the approach to a case study in western Arnhem Land, Northern Territory, Australia, in which the fire regime has been changed and the project has achieved recognised abatement of methane and nitrous oxide emissions. The carbon sequestration in the dead organic matter is ~85 times the annual emissions abatement in this project area and when expressed as an annual rate is ~3.5 times the abatement. We also show that the emissions abatement has previously been underestimated owing to an inability to fully account for dead organic matter dynamics. Future work could refine the models of dead organic matter to include seasonal dynamics in inputs. [ABSTRACT FROM AUTHOR]

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.

A fast and correct identification of ignitable liquid residues in fire debris investigation is of high importance in forensic research. Advanced fast analytical methods combined with chemometric tools are usually applied for these purposes. In the present study, the Headspace Gas Chromatography-Ion Mobility Spectrometry (HS-GC-IMS) combined with chemometrics is proposed as a promising technique for the identification of ignitable liquid residues in fire debris samples. Fire debris samples were created in the laboratory, according to the Destructive Distillation Method for Burning that is provided by the Bureau of Forensic Fire and Explosives. Four different substrates (pine wood, cork, paper, and cotton sheet) and four ignitable liquids of dissimilar composition (gasoline, diesel, ethanol, and paraffin) were used to create the fire debris. The Total Ion Current (TIC) Chromatogram combined with different chemometric tools (hierarchical cluster analysis and linear discriminant analysis) allowed for a full discrimination between samples that were burned with and without ignitable liquids. Additionally, a good identification (95% correct discrimination) for the specific ignitable liquid residues in the samples was achieved. Based on these results, the chromatographic data from HS-GC-IMS have been demonstrated to be very useful for the identification and discrimination of ignitable liquids residues. The main advantages of this approach vs. traditional methodology are that no sample manipulation or solvent is required; it is also faster, cheaper, and easy to use for routine analyses.

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).

This paper reviews a large fire loss that occurred at a seasonally operated Canadian food-processing facility. The fire occurred when the facility was not in production and started near a work area where employees had been previously unloading a trailer. The origin and cause investigation revealed different metal building insulation (MBI) products were used throughout the building on walls and ceilings. It was suspected that MBI material contributed to the rapid fire spread to otherwise empty parts of the building and that this material did not meet the relevant Building Code requirements. The facility used MBI product consisting of a polypropylene moisture barrier over fiberglass insulation. A detailed analysis of recovered MBI materials found that some of the material was flame retardant and some was not flame retardant. Additional testing of the materials was used to calibrate computational fire model inputs in order to estimate the behavior of MBI coatings by simulating fire scenarios in the full building. The intent of the analysis was to evaluate the relative propensity of the two MBI insulation products to facilitate flame spread from the area of fire origin in a comparative, qualitative framework. Test results showed that flame retardant MBI material substantially reduced fire spread compared with the non-flame retardant material. The ignition temperatures derived from cone calorimeter testing were higher (407°C compared with 226°C) and the peak heat release per unit area was lower for the flame retardant MBI coatings. The non-flame retardant MBI had a measured flame spread rating of 120, which was greater than the maximum flame spread rating of 25 permitted by the Building Code for ceiling finishes. Computational modeling correlates with non-flame retardant coated insulation (noncompliant) being present in the area where the fire originated, facilitating significant fire spread. The model predicted that the presence of non-flame retardant MBI on the ceiling facilitated flame spread across a significant distance from the area of origin within the first 300 s to 400 s, while the flame retardant MBI product yielded minimal flame spread beyond the incident area over a 20 min exposure. [ABSTRACT FROM AUTHOR]

Nylon bags are used for packaging fire debris in several countries, particularly in Europe. The possibility of cross‐contamination during transport from the fire scene to the laboratory, in normal casework conditions in the U.K., was studied for two brands of nylon bags, using simulated heavy‐loaded fire debris. Three experiments were carried out with each brand, using as sample a piece of cotton fabric soaked with gasoline. One experiment was carried out using automotive paint thinner (oxygenated solvent). Each sample was sealed in a nylon bag and stored in contact with eight empty bags. The empty bags were analysed at regular intervals for a period of time up to 8 weeks, using SPME and GC/MS. Cross‐contamination was found for components of gasoline (toluene and C2‐alkylbenzenes) in the two brands of nylon bags used, after 4 days and 2 weeks. Cross‐contamination using automotive topcoat thinner was detected after 2 days. [ABSTRACT FROM AUTHOR]

ABSTRACT Forest fire is one of the most important ecological disturbances affecting habitat of the declining California spotted owl ( Strix occidentalis occidentalis) population in southern California. We analyzed foraging location data collected 3 and 4 years post-fire, from 8 radio-tagged California spotted owls whose home ranges included forest burned in the 5,176-ha Slide Fire in the San Bernardino Mountains, California, USA. We analyzed foraging habitat selection with sensitivity analysis using 3 different spatial extents to define available resource area: utilization distribution, minimum convex polygon, and capture radius. At all 3 extents of available habitat these spotted owls selected foraging sites close to their territory centers and riparian areas. Resource selection functions indicated burned forests were generally used in proportion to their availability, with the exception of significant selection for moderate-severity burned forests farther from territory centers at the largest available habitat extent (capture radius). Riparian habitats should be preserved for California spotted owls in southern California, and forests burned by high-severity fire should be considered potentially suitable foraging habitat. We suggest researchers perform habitat selection analyses at multiple spatial extents of availability and describe the sensitivity of their results. © 2016 The Wildlife Society. [ABSTRACT FROM AUTHOR]