Comprehensive two-dimensional gas chromatography in forensic science: A critical review of recent trends

Online sequential analysis of volatile and semivolatile organic compounds in water matrices by double robotic sample preparations and dual-channel mono and comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry system

The monitoring of organic compounds in aquatic matrices poses challenges due to its complexity and time-intensive nature. To address these challenges, we introduce a novel approach utilizing a dual-channel mono (1D) and comprehensive two-dimensional (2D) gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS) system, integrated with a robotic pretreatment platform, for online monitoring of both volatile organic compounds (VOCs) and semivolatile organic compounds (SVOCs) in water matrices. Employing the robotic platform, we establish a suite of online liquid-liquid extraction (LLE) pretreatment processes for water samples, marking the first instance of such procedures. Leveraging the automatic headspace (HS) module, dual robotic preparations of HS and LLE are sequentially executed to extract VOCs and SVOCs from water matrices. The GC × GC-TOFMS system is distinguished by its dual-channel analytical column configuration, facilitating sequential analysis of VOCs in GC-TOFMS mode and SVOCs in GC × GC-TOFMS mode. Quantitative detection of 55 target VOCs and 104 SVOCs is achieved in a water sample using the instrument system. Our method demonstrates excellent correlation coefficients ranging from 0.990 to 1.000, method detection limits ranging from 0.08 to 4.78 μg L-1, relative standard deviations below 19.3 %, and recovery rates ranging from 50.0 % to 124.0 %. To validate the online monitoring capabilities of our system, we assess target SVOCs at three different concentration levels over a 3-day period. Most compounds exhibit recovery rates ranging from 70.0 % to 130.0 %. Furthermore, we apply our method to analyze a real water sample, successfully identifying over 100 target and nontarget VOCs/SVOCs, including alcohols, aldehydes, ketones, acids, esters, and phenols. These results highlight the efficacy of the proposed analysis system, capable of conducting two distinct analyses in automatic sequence, thereby enhancing the efficiency and accuracy of organic compound analysis in water matrices.

Unveiling the aromatic differences of low-salt Chinese horse bean-chili-paste using metabolomics and sensomics approaches

To achieve salt reduction while ensuring flavor quality of Chinese horse bean-chili-paste (CHCP), we comprehensively explored the effect of indigenous strains Tetragenococcus halophilus and Candida versatilis on the aroma profiles of low-salt CHCP by metabolomics and sensomics analysis. A total of 129 volatiles and 34 aroma compounds were identified by GC × GC-MS and GC-O-MS, among which 29 and 20 volatiles were identified as significant difference compounds and aroma-active compounds, respectively. Inoculation with the two indigenous strains could effectively relieve the undesired acidic and irritative flavor brought by acetic acid and some aldehydes in salt-reduction samples. Meanwhile, inoculated fermentation provided more complex and richer volatiles in low-salt batches, especially for the accumulation of 3-methylbutanol, 1-octen-3-ol, benzeneacetaldehyde, phenylethyl alcohol, and 4-ethyl-phenol etc., which were confirmed as essential aroma compounds of CHCP by recombination and omission tests. The research elucidated the feasibility of bioturbation strategy to achieve salt-reducing fermentation of fermented foods.

Characterisation of flavour profiles and microbial communities of fermented peppers with different fermentation years by combining flavouromics and metagenomics

The changes in flavours, volatile aromas and microbial communities of fermented peppers with different fermentation years and their relationships were investigated in this study. Results indicated a gradual increase in organic acids during fermentation, whereas free amino acids and capsaicinoids reached stability after 1 year of fermentation. Overall, the analysis detected 340 volatile compounds in fermented peppers and regarded 69 of them as differential compounds. Peppers fermented for 2 (FY2) and 4 years (FY4) possessed a greater number of differential volatiles with large odour activity values, thus endowing them with more favourable flavours. Hence, metagenomic analysis compared their microbial communities and functional annotations. Results revealed that Lactiplantibacillus plantarum and Zygosaccharomyces rouxii were the dominant bacterium and fungus, and metabolism was the main Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway in FY2. Correlation analysis demonstrated that Hyphopichia, Kazachstania and Clavispora were highly positively correlated with 12 key aroma flavours.

Characterization and comparison of flavors in fresh and aged fermented peppers: Impact of different varieties

The flavor profiles of fresh and aged fermented peppers obtained from four varieties were thoroughly compared in this study. A total of 385 volatile compounds in fermented pepper samples were detected by flavoromics (two-dimensional gas chromatography-time-of-flight mass spectrometry). As fermentation progressed, both the number and the total concentration of volatile compounds changed, with esters, alcohols, acids, terpenoids, sulfur compounds, and funans increasing, whereas hydrocarbons and benzenes decreased. In contrast to the fresh fermented peppers, the aged fermented samples exhibited lower values of pH, total sugars, and capsaicinoids but higher contents of organic acids and free amino acids. Furthermore, the specific differences and characteristic aroma substances among aged fermented peppers were unveiled by multivariate statistical analysis. Overall, 64 volatiles were screened as differential compounds. In addition, Huanggongjiao samples possessed the most abundant differential volatiles and compounds with odor activity values > 1, which were flavored with fruity, floral, and slightly phenolic odors. Correlation analysis demonstrated that the levels of 23 key aroma compounds (e.g., ethyl 2-methylbutyrate, 1-butanol, and ethyl valerate) showed a significantly positive correlation with Asp, Glu and 5 organic acids. By contrast, there is a negative association between the pH value and total sugar. Overall, aging contributed significantly to the flavor attributes of fermented peppers.

Analytical Tools and Methods for Explosive Analysis in Forensics: A Critical Review

This review summarizes (i) compositions and types of improvised explosive devices; (ii) the process of collection, extraction and analysis of explosive evidence encountered in explosive and related cases; (iii) inter-comparison of analytical techniques; (iv) the challenges and prospects of explosive detection technology. The highlights of this study include extensive information regarding the National & International standards specified by USEPA, ASTM, and so on, for explosives detection. The holistic development of analytical tools for explosive analysis ranging from conventional methods to advanced analytical tools is also covered in this article. The most important aspect of this review is to make forensic scientists familiar with the challenges during explosive analysis and the steps to avoid them. The problems during analysis can be analyte-based, that is, interferences due to matrix or added molding/stabilizing agents, trace amount of parent explosives in post-blast samples and many more. Others are techniques-based challenges viz. specificity, selectivity, and sensitivity of the technique. Thus, it has become a primary concern to adopt rapid, field deployable, and highly sensitive techniques.

Algorithm for tracking peaks amongst numerous datasets in comprehensive two-dimensional chromatography to enhance data analysis and interpretation

Analytical data processing often requires the comparison of data, i.e. finding similarities and differences within separations. In this context, a peak-tracking algorithm was developed to compare multiple datasets in one-dimensional (1D) and two-dimensional (2D) chromatography. Two application strategies were investigated: i) data processing where all chromatograms are produced in one sequence and processed simultaneously, and ii) method optimization where chromatograms are produced and processed cumulatively. The first strategy was tested on data from comprehensive 2D liquid chromatography and comprehensive 2D gas chromatography separations of academic and industrial samples of varying compound classes (monoclonal-antibody digest, wine volatiles, polymer granulate headspace, and mayonnaise). Peaks were tracked in up to 29 chromatograms at once, but this could be upscaled when necessary. However, the peak-tracking algorithm performed less accurate for trace analytes, since, peaks that are difficult to detect are also difficult to track. The second strategy was tested with 1D liquid chromatography separations, that were optimized using automated method-development. The strategy for method optimization was quicker to detect peaks that were still poorly separated in earlier chromatograms compared to assigning a target chromatogram, to which all other chromatograms are compared. Rendering it a useful tool for automated method optimization.

Human scent characterization: A review

Human scent has long been cited as a probable parameter that can be exploited as a biometric measure. Identifying the scent of individual persons using specially trained canines is a well-known forensic method which is frequently used in criminal investigations. To date there has been limited research on the chemical components present in human scent and their usefulness in distinguishing between people. This review delivers insight into studies which have dealt with human scent in forensics. Sample collection methods, sample preparation, instrumental analysis, compounds identified in human scent and data analysis techniques are discussed. Methods for sample collection and preparation are presented, but to date, there is no available validated method. Instrumental methods are presented and from the overview it is clear that gas chromatography combined with mass spectrometry is the method of choice. New developments such as two-dimensional gas chromatography offer exiting possibilities to collect more information. Given the amount and complexity of data, data processing is used to extract the relevant information to discriminate people. Finally, sensors offer new opportunities for the characterization of human scent.

HS-SPME-GC × GC/MS combined with multivariate statistics analysis to investigate the flavor formation mechanism of tank-fermented broad bean paste

With the advancement of industrialization, tank fermentation technology is promising for Pixian broad bean paste. This study identified and analyzed the general physicochemical factors and volatile metabolites of fermented broad beans in a thermostatic fermenter. Headspace solid-phase microextraction (HS-SPME)-two-dimensional gas chromatography-mass spectrometry (GC × GC-MS) was applied to detect the volatile compounds in fermented broad beans, while metabolomics was used to explore their physicochemical characteristics and analyze the possible metabolic mechanism. A total of 184 different metabolites were detected, including 36 alcohols, 29 aldehydes, 26 esters, 21 ketones, 14 acids, 14 aromatic compounds, ten heterocycles, nine phenols, nine organonitrogen compounds, seven hydrocarbons, two ethers, and seven other types, which were annotated to various branch metabolic pathways of carbohydrate and amino acid metabolism. This study provides references for subsequent functional microorganism mining to improve the quality of the tank-fermented broad beans and upgrade the Pixian broad bean paste industry.

Portable comprehensive two-dimensional micro-gas chromatography using an integrated flow-restricted pneumatic modulator

Two-dimensional (2D) gas chromatography (GC) provides enhanced vapor separation capabilities in contrast to conventional one-dimensional GC and is useful for the analysis of highly complex chemical samples. We developed a microfabricated flow-restricted pneumatic modulator (FRPM) for portable comprehensive 2D micro-GC (μGC), which enables rapid 2D injection and separation without compromising the 1D separation speed and eluent peak profiles. 2D injection characteristics such as injection peak width and peak height were fully characterized by using flow-through micro-photoionization detectors (μPIDs) at the FRPM inlet and outlet. A 2D injection peak width of ~25 ms could be achieved with a 2D/1D flow rate ratio over 10. The FRPM was further integrated with a 0.5-m long 2D μcolumn on the same chip, and its performance was characterized. Finally, we developed an automated portable comprehensive 2D μGC consisting of a 10 m OV-1 1D μcolumn, an integrated FRPM with a built-in 0.5 m polyethylene glycol 2D μcolumn, and two μPIDs. Rapid separation of 40 volatile organic compounds in ~5 min was demonstrated. A hybrid 2D contour plot was constructed by using both 1D and 2D chromatograms obtained with the two μPIDs at the end of the 1D and 2D μcolumns, which was enabled by the presence of the flow resistor in the FRPM.

Simulating comprehensive two-dimensional gas chromatography mass spectrometry data with realistic run-to-run shifting to evaluate the robustness of tile-based Fisher ratio analysis

Untargeted analysis of comprehensive two-dimensional (2D) gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) data has the potential to be hindered by run-to-run retention time shifting. To address this challenge, tile-based Fisher ratio (F-ratio) analysis (FRA) has been developed, which utilizes a supervised, untargeted approach involving a chromatographic segmentation routine termed "tiling" combined with the ANOVA F-ratio statistic to discover class-distinguishing analytes while minimizing false positives arising from shifting. The tiling algorithm is designed to account for retention shifting in both separation dimensions. Although applications of FRA have been reported, there remains a need to thoroughly evaluate the robustness of FRA for different levels of run-to-run retention shifting in order to broaden the scope of its application. To this end, a novel method of simulating GC×GC-TOFMS chromatograms with realistic run-to-run shifting is presented by random generation of low-frequency "shift functions". The dimensionless retention-time precision, <δ_r>, which is four times the standard deviation in retention time normalized to the peak width-at-base is used as a key modeling variable along with the 2D chromatographic saturation, α_e,2D, and within-class relative standard deviation in peak area, RSD_wc. We demonstrate that all three of these variables operate together to impact true positive discovery. To quantify the "success" of true positive discovery, GC×GC-TOFMS datasets for various combinations of <δ_r>, α_e,2D, and RSD_wc were simulated and then analyzed by FRA using a wide range of relative tile areas (RTA), which is a dimensionless measure of tile size. Since each hit in the FRA hit list was known a priori as either a true or false positive based on the simulation inputs, receiver operating characteristic (ROC) curves were readily constructed. Then, the area under the ROC curve (AUROC) was used as a metric for discovery "success" for various combinations of the modeling variables. Based on the results of this study, recommendations for tile size selection and experimental design are provided, and further supported by comparison to previous tile-based FRA applications. For instance, values for <δ_r>, α_e,2D, and RSD_wc obtained from a GC×GC-TOFMS dataset of yeast metabolites suggested an optimum RTA of 6.25, corresponding closely to the RTA of 4.00 employed in the study, implying the simulation results obtained here can be generalized to real datasets.

Current Role of Mass Spectrometry in the Determination of Pesticide Residues in Food

The extensive use of pesticides represents a risk to human health. Consequently, legal frameworks have been established to ensure food safety, including control programs for pesticide residues. In this context, the performance of analytical methods acquires special relevance. Such methods are expected to be able to determine the largest number of compounds at trace concentration levels in complex food matrices, which represents a great analytical challenge. Technical advances in mass spectrometry (MS) have led to the development of more efficient analytical methods for the determination of pesticides. This review provides an overview of current analytical strategies applied in pesticide analysis, with a special focus on MS methods. Current targeted MS methods allow the simultaneous determination of hundreds of pesticides, whereas non-targeted MS methods are now applicable to the identification of pesticide metabolites and transformation products. New trends in pesticide analysis are also presented, including approaches for the simultaneous determination of pesticide residues and other food contaminants (i.e., mega-methods), or the recent application of techniques such as ion mobility–mass spectrometry (IM–MS) for this purpose.

Identification of a New Family of Prenylated Volatile Sulfur Compounds in Cannabis Revealed by Comprehensive Two-Dimensional Gas Chromatography

Cannabis sativa L. produces over 200 known secondary metabolites that contribute to its distinctive aroma. Studies on compounds traditionally associated with the scent of this plant have focused on those within the terpenoid class. These isoprene-derived compounds are ubiquitous in nature and are the major source of many plant odors. Nonetheless, there is little evidence that they provide the characteristic "skunk-like" aroma of cannabis. To uncover the chemical origins of this scent, we measured the aromatic properties of cannabis flowers and concentrated extracts using comprehensive two-dimensional gas chromatography equipped with time-of-flight mass spectrometry, flame ionization detection, and sulfur chemiluminescence. We discovered a new family of volatile sulfur compounds (VSCs) containing the prenyl (3-methylbut-2-en-1-yl) functional group that is responsible for this scent. In particular, the compound 3-methyl-2-butene-1-thiol was identified as the primary odorant. We then conducted an indoor greenhouse experiment to monitor the evolution of these compounds during the plant's lifecycle and throughout the curing process. We found that the concentrations of these compounds increase substantially during the last weeks of the flowering stage, reach a maximum during curing, and then drop after just one week of storage. These results shed light on the chemical origins of the characteristic aroma of cannabis and how volatile sulfur compound production evolves during plant growth. Furthermore, the chemical similarity between this new family of VSCs and those found in garlic (allium sativum) suggests an opportunity to also investigate their potential health benefits.

Recent forensic applications of enhanced chromatographic separation methods

This study reviews the recent applications of enhanced separation methods employed in forensic analysis utilizing gas chromatography, liquid chromatography, and supercritical fluid chromatography published between 2015 to 2020, except papers previously covered in relevant review articles. Applications of enhanced chromatographic separation methods to arson investigations, environmental forensics, sexual assault investigations, drug analysis, and toxicology are discussed. Future directions for enhanced chromatographic separation methods in forensic science are also explored.

Baseline correction method for dynamic pressure gradient modulated comprehensive two-dimensional gas chromatography with flame ionization detection

A baseline correction method is developed for comprehensive two-dimensional (2D) chromatography (GC × GC) with flame-ionization detection (FID) using dynamic pressure gradient modulation (DPGM). The DPGM-GC × GC-FID utilized porous layer open tubular (PLOT) columns in both dimensions to focus on light hydrocarbon separations. Since DPGM is nominally a stop-flow modulation technique, a rhythmic baseline disturbance is observed in the FID signal that cycles with the modulation period (P_M). This baseline disturbance needs to be corrected to optimize trace analysis. The baseline correction method has three steps: collection of a background "blank" chromatogram and multiplying it by an optimized normalization factor, subtraction of the normalization-optimized background chromatogram from a sample chromatogram, and application of Savitzky-Golay smoothing. An alkane standard solution, containing pentane, hexane and heptane was used for method development, producing linear calibration curves (r² > 0.991) over a broad concentration range (7.8 ppm - 4000 ppm). Further, the limit-of-detection (LOD) and limit-of-quantification (LOQ) were determined for pentane (LOD = 2.5 ppm, LOQ = 8.2 ppm), hexane (LOD = 0.9 ppm, LOQ = 3.0 ppm), and heptane (LOD = 1.9 ppm, LOQ = 6.4 ppm). A natural gas sample separation illustrated method applicability, whereby the DPGM produced a signal enhancement (SE) of 30 for isopentane, where SE is defined as the height of the tallest ²D peak in the modulated chromatogram for the analyte divided by the height of the unmodulated ¹D peak. The 30-fold SE resulted in about a 10-fold improvement in the signal-to-noise ratio (S/N) for isopentane. Additional versatility of the baseline correction method for more complicated samples was demonstrated for an unleaded gasoline sample, which enabled the detection (and visual appearance) of trace components.

Unique ion filter-A data reduction tool for chemometric analysis of raw comprehensive two-dimensional gas chromatography-mass spectrometry data

Comprehensive gas chromatography with time of flight mass spectrometry is a powerful tool in the analysis of complex samples. Chemometric analysis of raw chromatographic data is more useful in one- and two-dimensional separations relative to peak tables. The data volume from such experiments generally necessitates the use of data reduction tools. Such tools often sacrifice some of the multivariate information in the mass to charge ratio dimension. The unique ion filter reduces the over-redundancy in two-dimensional gas chromatography-mass spectrometry data by limiting the data to a few unique/pseudo-unique ions, sub-peaks/slices in the first dimension, and spectra in the second dimension. We explore the performance of this algorithm through careful inspection of two-dimensional gas chromatography-mass spectrometry data before and after application of the filter. A reduction (99%) in the number of variables in a two-dimensional gas chromatography-mass spectrometry chromatogram passed on to subsequent analysis was observed. Feature selection times for model optimization reduced from 229 (±13) to 6.8 (±0.5) min when the filter was applied. An estimate of two unique/pseudo-unique ions, one sub-peak in the first dimension and five spectra in the second dimension were considered to provide a true representation of each chromatogram and provided enough information to achieve 100% model prediction accuracy.

Untargeted SPME-GC-MS Characterization of VOCs Released from Spray Paint

Paints are a common form of physical evidence encountered at crime scenes. This research presents an optimized method for the untargeted analysis of volatile organic compounds (VOCs) in spray paint using solid-phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS). The presence and persistence of VOCs were monitored in 30 minute intervals, over a 4 hour period, in a triplicate time study. As predicted, spray paint solvents are lost to the environment readily, whereas few VOCs remained present in the headspace in low concentrations beyond 4 hours. The VOCs that were observed to have the highest persistence in the headspace were aromatic compounds and those with longer hydrocarbon chains. We present this study in a forensic science context and suggest that the interpretation of the results may be useful for forensic applications in establishing a time since deposition of a spray-painted surface.

A unique data analysis framework and open source benchmark data set for the analysis of comprehensive two-dimensional gas chromatography software

Comprehensive two-dimensional gas chromatography (GC × GC) is amongst the most powerful separation technologies currently existing. Since its advent in early 1990, it has become an established method which is readily available. However, one of its most challenging aspects, especially in hyphenation with mass spectrometry is the high amount of chemical information it provides for each measurement. The GC × GC community agrees that there, the highest demand for action is found. In response, the number of software packages allowing for in-depth data processing of GC × GC data has risen over the last couple of years. These packages provide sophisticated tools and algorithms allowing for more streamlined data evaluation. However, these tools/algorithms and their respective specific functionalities differ drastically within the available software packages and might result in various levels of findings if not appropriately implemented by the end users. This study focuses on two main objectives. First, to propose a data analysis framework and second to propose an open-source dataset for benchmarking software options and their specificities. Thus, allowing for an unanimous and comprehensive evaluation of GC × GC software. Thereby, the benchmark data includes a set of standard compound measurements and a set of chocolate aroma profiles. On this foundation, eight readily available GC × GC software packages were anonymously investigated for fundamental and advanced functionalities such as retention and detection device derived parameters, revealing differences in the determination of e.g. retention times and mass spectra.

The current role of mass spectrometry in forensics and future prospects

Mass spectrometry (MS) techniques are highly prevalent in crime laboratories, particularly those coupled to chromatographic separations like gas chromatography (GC) and liquid chromatography (LC). These methods are considered "gold standard" analytical techniques for forensic analysis and have been extensively validated for producing prosecutorial evidentiary data. However, factors such as growing evidence backlogs and problematic evidence types (e.g., novel psychoactive substance (NPS) classes) have exposed limitations of these stalwart techniques. This critical review serves to delineate the current role of MS methods across the broad sub-disciplines of forensic science, providing insight on how governmental steering committees guide their implementation. Novel, developing techniques that seek to broaden applicability and enhance performance will also be highlighted, from unique modifications to traditional hyphenated MS methods to the newer "ambient" MS techniques that show promise for forensic analysis, but need further validation before incorporation into routine forensic workflows. This review also expounds on how recent improvements to MS instrumental design, scan modes, and data processing could cause a paradigm shift in how the future forensic practitioner collects and processes target evidence.

Statistical inference of mass channel purity from Fisher ratio analysis using comprehensive two-dimensional gas chromatography with time of flight mass spectrometry data

Tile-based Fisher ratio (F-ratio) analysis has recently been developed and validated for discovery-based studies of highly complex data collected using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS). In previous studies, interpretation and utilization of F-ratio hit lists has relied upon manual decomposition and quantification performed by chemometric methods such as parallel factor analysis (PARAFAC), or via manual translation of the F-ratio hit list information to peak table quantitative information provided by the instrument software (ChromaTOF). Both of these quantification approaches are bottlenecks in the overall workflow. In order to address this issue, a more automatable approach to provide accurate relative quantification for F-ratio analyses was investigated, based upon the mass spectral selectivity provided via the F-ratio spectral output. Diesel fuel spiked with 15 analytes at four concentration levels (80, 40, 20, and 10 ppm) produced three sets of two class comparisons that were submitted to tile-based F-ratio analysis to obtain three hit lists, with an F-ratio spectrum for each hit. A novel algorithm which calculates the signal ratio (S-ratio) between two classes (eg., 80 ppm versus 40 ppm) was applied to all mass channels (m/z) in the F-ratio spectrum for each hit. A lack of fit (LOF) metric was utilized as a measure of peak purity and combined with F-ratio and p-values to study the relationship of each of these metrics with m/z purity. Application of a LOF threshold coupled with a p-value threshold yielded a subset of the most pure m/z for each of the 15 spiked analytes, evident by the low deviations (< 5%) in S-ratio relative to the true concentration ratio. A key outcome of this study was to demonstrate the isolation of pure m/z without the need for higher level signal decomposition algorithms.

Determination and comparison of agarwood from different origins by comprehensive two-dimensional gas chromatography-quadrupole time-of-flight mass spectrometry

Agarwood, a species of resinous heartwood, is a precious medicinal plant and a type of rare natural spice, which is widely used in medicine, cosmetics, religious activities, and other fields. In this study, agarwood samples from eight different regions across four countries were analyzed by comprehensive two-dimensional gas chromatography-quadrupole time-of-flight mass spectrometry. A total of 232 species were identified (the match factors of these compounds were above 750). The main compounds of agarwood are oxygenated sesquiterpenes and chromones. The compositions of India1 and Malaysia2 were significantly different from those of other samples, which might be attributed to the different production processes of agarwood. For further investigation, factor analysis was conducted for six agarwood samples. The results showed that the data classification possessed a regional characteristic; according to the retention time and relative content, characteristic compositions were determined by factor scores. Finally, the differences of characteristic compositions were simply analyzed, and the reasons were speculated.

Interpol review of fire investigation 2016–2019

This review paper covers the forensic-relevant literature in fire analysis and investigation sciences from 2016 to 2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/14458/file/Interpol%20Review%20Papers%202019.pdf.

Comparison of Pre-Processing and Variable Selection Strategies in Group-Based GC×GC-TOFMS Analysis

Chemometric analysis of comprehensive two-dimensional chromatography coupled to time-of-flight mass spectrometry (GC×GC-TOFMS) data has been reported with various workflows, yet little effort has been devoted to evaluating the impacts of workflow variation on study conclusions. The report presented herein aims to investigate the effects of different pre-processing and variable selection strategies on the scores’ plot outputs from GC×GC-TOFMS data acquired from lavender and tea tree essential oils. Our results suggest that pre-processing, such as applying log transformation to the data set, can result in significant differentiation of sample clustering when compared to only mean centering. Additionally, exploring differences between analysis of variance, Fisher-ratio, and partial least squares-discriminant analysis feature selection resulted in little variation in scores plots. This work highlights the effects different chemometric workflows can have on results to help facilitate harmonization efforts.

"-Omics" workflow for paleolimnological and geological archives: A review

"-Omics" is a powerful screening method with applications in molecular biology, toxicology, wildlife biology, natural product discovery, and many other fields. Genomics, proteomics, metabolomics, and lipidomics are common examples included under the "-omics" umbrella. This screening method uses combinations of untargeted, semi-targeted, and targeted analyses paired with data mining to facilitate researchers' understanding of the genome, proteins, and small organic molecules in biological systems. Recently, however, the use of "-omics" has expanded into the fields of geology, specifically petrology, and paleolimnology. Specifically, untargeted analyses stand to transform these fields as petroleomics, and sediment-"omics" become more prevalent. "-Omics" facilitates the visualization of small molecule profiles from environmental matrices (i.e. oil and sediment). Small molecule profiles can provide improved understanding of small molecules distributions throughout the environment, and how those compositions can change depending on conditions (i.e. climate change, weathering, etc.). "-Omics" also facilities discovery of next-generation biomarkers that can be used for oil source identification and as proxies for reconstructing past environmental changes. Untargeted analyses paired with data mining and multivariate statistical analyses represents a powerful suite of tools for hypothesis generation, and new method development for environmental reconstructions. Here we present an introduction to "-omics" methodology, technical terms, and examples of applications to paleolimnology and petrology. The purpose of this review is to highlight the important considerations at each step in the "-omics" workflow to produce high quality and statistically powerful data for petrological and paleolimnological applications.

The Blossoming of Technology for the Analysis of Complex Aroma Bouquets-A Review on Flavour and Odorant Multidimensional and Comprehensive Gas Chromatography Applications

Multidimensional approaches in gas chromatography have been established as potent tools to (almost) attain fully resolved analyses. Flavours and odours are important application fields for these techniques since they include complex matrices, and are of interest for both scientific study and to consumers. This article is a review of the main research studies in the above theme, discussing the achievements and challenges that demonstrate a maturing of analytical separation technology.

Characterization of Polycyclic Aromatic Compounds in Commercial Pavement Sealcoat Products for Enhanced Source Apportionment

Coal tar-based sealcoat (CTSC) products are an urban source of polycyclic aromatic compounds (PACs) to the environment. However, efforts to assess the environmental fate and impacts of CTSC-derived PACs are hindered by the ubiquity of (routinely monitored) PACs released from other environmental sources. To advance source identification of CTSC-derived PACs, we use comprehensive two-dimensional gas chromatography-high resolution mass spectrometry (GC × GC/HRMS) to characterize the major and minor components of CTSC products in comparison to those in other sources of PACs, viz., asphalt-based sealcoat products, diesel particulate, diesel fuel, used motor oil and roofing shingles. GC × GC/HRMS analyses of CTSC products led to the confident assignment of compounds with 88 unique elemental compositions, which includes a set of 240 individual PACs. Visualization of the resulting profiles using Kendrick mass defect plots and hierarchical cluster analysis highlighted compositional differences between the sources. Profiles of alkylated PAHs, and heteroatomic (N, O, S) PACs enabled greater specificity in source differentiation. Isomers of specific polycyclic aromatic nitrogen heterocycles (PANHs) were diagnostic for coal tar-derived PAC sources. The compounds identified and methods used for this identification are anticipated to aid in future efforts on risk assessment and source apportionment of PACs in environmental matrices.

Profiling of individual naphthenic acids at a composite tailings reclamation fen by comprehensive two-dimensional gas chromatography-mass spectrometry

Naphthenic acids (NAs) are naturally occurring in the Athabasca oil sands region (AOSR) and accumulate in tailings as a result of water-based extraction processes. NAs exist as a complex mixture, so the development of an analytical technique to characterize them has been an on-going challenge. The aim of this study was to use comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry to monitor individual NAs within a wetland reclamation site in the AOSR. Samples were collected from four monitoring wells at the site and the extracts were found to contain numerous resolved isomers of classical (monocyclic-, bicyclic-, adamantane-, indane-, and tetralin-type carboxylic acids) and sulfur-containing NAs (thiamonocyclic- and thiophene-type carboxylic acids). The absolute abundances of the monitored NAs were compared between four monitoring wells and unique profiles were observed at each well. Few significant changes in absolute abundances were observed over the sampling period, with the exception of one well (Well 6A). In addition, isomeric percent compositions were calculated for each set of structural isomers, and one-way analysis of variance (ANOVA) and two-dimensional hierarchical cluster analysis revealed high spatial variation at the site. However, consistent distributions were observed at each of the monitoring wells for some sets of NA isomers (such as: adamantane NAs), which may be useful for forensic applications, such as identifying sources of contamination or demonstrating biodegradation. The methods and results presented in this study demonstrate the utility of monitoring individual NAs, since both changes in absolute abundances of individual NAs and the distribution of NA isomers have the ability to provide insight into their sources and the processes controlling their concentrations that are not only of relevance to the Alberta Oil Sands, but also to other petroleum deposits and environmental systems.

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.