Extraction of alternative fuels from fire debris samples*

Alternative fuels, specifically biodiesel, biodiesel blends, and E85 fuel, have been gaining a market share over the past few years. With the emergence of these fuels, fire debris analysts should be able to recognize their characteristics since these fuels may be encountered in casework. In this study, pure biodiesel (B100) and a 20% blend of pure biodiesel with petroleum diesel (B20) are examined as liquids and are extracted from debris samples using both passive headspace concentration and solvent extraction. Typical fire debris instrumental conditions are used to analyze these samples. Components of B100 and B20 may be observed in debris samples extracted using the passive headspace concentration method, but the chromatographic patterns are different from the pure liquid samples. When solvent extraction is used as a secondary extraction method on debris samples, the resulting patterns are consistent with the pure liquids of B100 and B20. E85 fuel, a blend of 85% ethanol and 15% gasoline, can be extracted using a typical fire debris extraction technique but requires slight modifications to typical fire debris instrumental conditions. E85 is shown at various stages of evaporation to demonstrate the resiliency of the ethanol. Additionally, samples of E85 were placed on carpet, burned and extinguished to demonstrate the effects of the suppression medium on the retention of ethanol.     

ATD—GC—MS法测定火场样品中痕量汽油燃烧残留物

目的为火场样品中痕量汽油残留物的检测建立一种简便、高灵敏度的检验方法和可靠的检验结果评判方法。方法用TenaxTA吸附管吸附富集火场样品中的汽油成分,然后用ATD—GC—MS法自动解吸和检测。通过模拟燃烧实验,探讨了检验结果的评判方法：根据样品的m／z（57＋85）、m/z（91＋105＋119）、m／z（117＋131）和m/z（128＋142＋156）四个质量色谱图与已知汽油作比较来对检验结果作评判。结果6组模拟燃烧实验中凡有汽油作助燃剂的样品．均检出汽油残留物成分。结论所建立的方法具有操作简便,检测灵敏度高,杂质干扰少,定性结论准确可靠等特点。可用于实际火场样品中痕量汽油残留物的检测。     

Weight of evidence from mRNA data: Implementation of an LR-system for forensic body fluid identification in casework

After developing an LR-system to calculate weight of evidence from mRNA data [1] we here present how this LR-system is used in forensic casework. We aim to convey the weight of the evidence in forensic reports.     

The evaluation of the extent of transporting or "tracking" an identifiable ignitable liquid (gasoline) throughout fire scenes during the investigative process

Tests have determined that boots or shoes of individuals at a fire scene do not transport sufficient contaminants ("tracking") through the fire scene to produce a positive laboratory result for the presence of gasoline in a fire scene that was not present at the time of the fire. Questions about the validity of forensic laboratory results have been raised on the basis that low-level gasoline residues detected in the laboratory samples could have been the result of transporting the residue by footwear contaminated from the fire scene ("tracking"). The data collected in this study establish that "tracking" does not lead to false-positive laboratory results. Canines trained and experienced in the detection of trace ignitable liquid residues were also utilized in this study. The canine results confirmed that properly trained canines show a higher sensitivity than do standard ASTM laboratory techniques for fire debris analysis. In a few cases, canines responded to contamination, but laboratory testing (which is the definitive indicator) did not produce positive results.     

Evaluation of Cross‐contamination of Nylon Bags with Heavy‐loaded Gasoline Fire Debris and with Automotive Paint Thinner

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.     

建立火场样品中汽油残留物ATD-GC-MS检验结果的评价方法

目的建立火场中汽油燃烧残留物ATD-GC-MS检验结果评价方法。方法将模拟燃烧样品用ATD-GC-MS法检验,检验结果通过对芳烃、烷烃、茚满、和萘系列的4个特征离子色谱图与已知汽油作比较,并利用向量夹角法计算样品与汽油色谱指纹图的相似度来对检验结果作评价。结果有汽油作助燃剂的模拟燃烧样品与汽油色谱指纹图的相似度一般大于90%,无汽油作助燃剂的样品则在60%以下。结论利用样品的4个特征离子色谱图与已知汽油作比较,并结合样品与汽油色谱指纹图相似度的计算,能对检验结果作出客观、可靠和准确的评价。     

Statistical discrimination of liquid gasoline samples from casework

The intention of this study was to differentiate liquid gasoline samples from casework by utilizing multivariate pattern recognition procedures on data from gas chromatography-mass spectrometry. A supervised learning approach was undertaken to achieve this goal employing the methods of principal component analysis (PCA), canonical variate analysis (CVA), orthogonal canonical variate analysis (OCVA), and linear discriminant analysis. The study revealed that the variability in the sample population was sufficient enough to distinguish all the samples from one another knowing their groups a priori. CVA was able to differentiate all samples in the population using only three dimensions, while OCVA required four dimensions. PCA required 10 dimensions of data in order to predict the correct groupings. These results were all cross-validated using the "jackknife" method to confirm the classification functions and compute estimates of error rates. The results of this initial study have helped to develop procedures for the application of multivariate analysis to fire debris casework.     

火场样品中汽油与稀释剂燃烧残留物的区分方法探讨

目的探讨火场样品中汽油与稀释剂燃烧残留物的区分方法。方法样品用ATD—GC—MS法检验,检验结果通过对芳烃、烷烃、茚满、和萘系列的4个特征离子色谱图与已知汽油和稀释剂作比较,并结合向量夹角法计算样品与汽油色谱指纹图的相似度来区分汽油与稀释剂残留物。结果个别品种的稀释剂燃烧残留物与汽油很相似,但彼此有某些差别。结论使用本方法,一般能将汽油与稀释剂燃烧残留物区分开。     

Effect of evaporation and matrix interferences on the association of simulated ignitable liquid residues to the corresponding liquid standard

Identification of an ignitable liquid in fire debris evidence can be complicated due to evaporation of the liquid, matrix interferences, and thermal degradation of both the liquid and the matrix. In this research, liquids extracted from simulated fire debris were compared to the original liquid using multivariate statistical procedures. Neat and evaporated gasoline and kerosene standards were spiked onto nylon carpet, which was subsequently burned. The ignitable liquid residues were extracted using a passive headspace procedure and analyzed by gas chromatography-mass spectrometry. Pearson product moment correlation coefficients, hierarchical cluster analysis, and principal components analysis were used to compare the liquids extracted from the carpet to the corresponding neat liquid. For each procedure, association of the extracts according to liquid type was possible, albeit not necessarily to the specific evaporation level. Of the three procedures investigated, principal components analysis offered the most promise since contributions from matrix interferences were essentially eliminated.     

A solid-phase microextraction method for the detection of ignitable liquids in fire debris

A solid-phase microextraction (SPME) procedure involving direct contact between the SPME fibers and the solid matrix and subsequent gas chromatography/mass spectrometric analysis for the detection of accelerants in fire debris is described. The extraction performances of six fibers (100 mum polydimethylsiloxane, 65 mum polydimethylsiloxane-divinylbenzene, 85 mum polyacrylate, 85 mum carboxen-polydimethylsiloxane, 70 mum Carbowax-divinylbenzene, and 50/30 mum divinylbenzene-Carboxen-polydimethylsiloxane) were investigated by directly immersing the fibers into gasoline, kerosene, and diesel fuel. For simulated fire debris, in the direct contact extraction method, the SPME fiber was kept in contact with the fire debris matrix during extraction by penetrating plastic bags wrapping the sample. This method gave comparable results to the headspace SPME method in the extraction of gasoline and kerosene, and gave an improved recovery of low-volatile components in the extraction of diesel fuel from fire debris. The results demonstrate that this procedure is suitable as a simple and rapid screening method for detecting ignitable liquids in fire debris packed in plastic bags.     

Using Alkylate Components for Classifying Gasoline in Fire Debris Samples

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.     

Comparison of gasolines using gas chromatography-mass spectrometry and target ion response

Gas chromatography-mass spectrometry was used to compare gasoline samples obtained from different sources based on the difference in amounts of certain components found in the headspace of gasoline using target response data. Many suspected arson cases involve comparing an ignitable liquid extracted from fire debris to a liquid found in a suspect's possession to determine if they could have had a common source. Various component ratios are proposed for determining if an unevaporated gasoline sample could have originated from the same source as an evaporated gasoline extracted from fire debris. Fifty and 75% evaporated gasoline samples were both found to contain similar ratios of certain components when compared with its unevaporated source gasoline. The results of the comparisons in this study demonstrate that for cases involving gasoline that has been evaporated up to 50% and extracted from pine, it is possible to eliminate comparison samples as originating from the same source. The results of the 75% comparisons suggest it may be possible to apply the same type of comparison to cases involving 75% evaporated gasoline.     

GC/MS/MS时间编程在火灾现场助燃剂检测中的应用

运用Varian SATURN2000气质联用仪通过GC/MS、GC/MS/MS、时间编程 GC/MS/MS对汽油样品进行分析比对,发现利用时间编程GC/MS/MS,对检测火灾现场残留汽油效果很好,可彻底排除样品中基体的背景干扰,大大提高检测灵敏度;同时对混合助燃剂（汽油+煤油、汽油+柴油）进行了实验探索。     

Extraction, derivatization, and analysis of vegetable oils from fire debris

Vegetable oils have the ability to spontaneously heat under certain conditions, which may lead to spontaneous ignition. While the oils are not often encountered in forensic casework, they may be suspected in some fire cases. As these oils are not effectively analyzed using traditional fire debris analysis methods, a protocol must be established for extracting vegetable oils from fire debris. In this study, a protocol was developed for the extraction, derivatization, and analysis of vegetable oils from fire debris. Three derivatization methods were compared to establish an optimal derivatization procedure to convert the fatty acids found in vegetable oils to the fatty acid methyl esters (FAMEs) used in analysis. Three different gas chromatograph columns and programs were examined to determine which was best suited for the separation and analysis of FAMEs. The procedure was tested and refined using a variety of neat and burned vegetable oils, in addition to extractions from oils burned on commonly encountered fire debris materials. The findings of this research will serve as a starting point for further understanding and research of vegetable oils in fire debris.     

自动热脱附气相色谱-质谱法分析火场助燃剂汽油成分

目的建立检验纵火案件现场燃烧残留物中助燃剂汽油成分的方法。方法利用自动热脱附技术对火场残留物中的助燃剂进行富集、浓缩、脱附后经气-质联用仪（GG-MS）分析。结果结合现场燃烧环境运用目标化合物法能够判定是否含有助燃剂汽油成分。结论该方法简便易行。     

Likelihood ratio methods for forensic comparison of evaporated gasoline residues

In the investigation of arson, evidence connecting a suspect to the fire scene may be obtained by comparing the composition of ignitable liquid residues found at the crime scene to ignitable liquids found in possession of the suspect. Interpreting the result of such a comparison is hampered by processes at the crime scene that result in evaporation, matrix interference, and microbial degradation of the ignitable liquid.Most commonly, gasoline is used as a fire accelerant in arson. In the current scientific literature on gasoline comparison, classification studies are reported for unevaporated and evaporated gasoline residues. In these studies the goal is to discriminate between samples of several sources of gasoline, based on a chemical analysis. While in classification studies the focus is on discrimination of gasolines, for forensic purposes a likelihood ratio approach is more relevant.In this work, a first step is made towards the ultimate goal of obtaining numerical values for the strength of evidence for the inference of identity of source in gasoline comparisons. Three likelihood ratio methods are presented for the comparison of evaporated gasoline residues (up to 75% weight loss under laboratory conditions). Two methods based on distance functions and one multivariate method were developed. The performance of the three methods is characterized by rates of misleading evidence, an analysis of the calibration and an information theoretical analysis.The three methods show strong improvement of discrimination as compared with a completely uninformative method. The two distance functions perform better than the multivariate method, in terms of discrimination and rates of misleading evidence.     

The use of vapour phase ultra-violet spectroscopy for the analysis of arson accelerants in fire scene debris.

A method has been developed for the analysis of arson accelerants in fire scene debris by vapour phase ultra-violet (UV) spectroscopy. The method is rapid, inexpensive, simple to use and is sufficiently sensitive and discriminating to be of use for the analysis of crime scene samples. Application to casework samples is described. On occasion, the method offers additional information to that which can be obtained by gas chromatography-flame ionisation detection (GC-FID) and gas chromatography-mass spectrometry (GC-MS) and represents a useful adjunct to these techniques. In addition, the method offers advantages where the use of GC-MS analysis of arson accelerants in fire scene debris is not a practical proposition.     

Chemical fingerprinting of gasoline. 2. Comparison of unevaporated and evaporated automotive gasoline samples

Analysis of the C(0)- to C(2)-naphthalene compounds present in automotive gasoline using gas chromatography-mass spectrometry with selected ion monitoring (GC-MS (SIM)) and principal component analysis (PCA) was used to discriminate between different samples of gasoline. Phase one of this study explored the ability of this method to differentiate gasoline samples at different levels of evaporation. A total of 35 random samples of unevaporated gasoline, covering three different grades (regular unleaded, premium unleaded and lead replacement), were collected in Sydney, Australia and examined. The high-boiling C(0)- to C(2)-naphthalene compounds present in the gasoline were used to chemically fingerprint each sample at different levels of evaporation. Samples of 25, 50, 75 and 90% evaporated gasoline (by weight) were generated from the 35 samples of unevaporated gasoline. Analysis of the data by PCA followed by linear discriminant analysis (LDA) showed that the 35 samples formed 18 unique groups, irrespective of the level of evaporation. Good discrimination between gasoline samples that were collected on the same day was obtained. Phase two of this study examined the change in gasoline samples over time. The C(0)- to C(2)-naphthalene composition in 96 samples of gasoline collected from three service stations over a 16-week period was examined using the method described. In most cases, it was found that the C(0)- to C(2)-naphthalene profile changed from week to week, and from station to station. In a comparison of all 96 samples together it was found that the majority could be differentiated from one another. The application of the method to forensic casework is discussed.     

Prediction and preliminary standardization of fire debris constituents with the advanced distillation curve method

The recent National Academy of Sciences report on forensic sciences states that the study of fire patterns and debris in arson fires is in need of additional work and eventual standardization. We discuss a recently introduced method that can provide predicted evaporation patterns for ignitable liquids as a function of temperature. The method is a complex fluid analysis protocol, the advanced distillation curve approach, featuring a composition explicit data channel for each distillate fraction (for qualitative, quantitative, and trace analysis), low uncertainty temperature measurements that are thermodynamic state points that can be modeled with an equation of state, consistency with a century of historical data, and an assessment of the energy content of each distillate fraction. We discuss the application of the method to kerosenes and gasolines and outline how expansion of the scope of fluids to other ignitable liquids can benefit the criminalist in the analysis of fire debris for arson.     

Total Ion Spectra versus Segmented Total Ion Spectra as Preprocessing Tools for Gas Chromatography – Mass Spectrometry Data

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.