Two-dimensional Gas Chromatography Research Articles

Novel Models for Accurate Estimation of Air-Blood Partitioning: Applications to Individual Compounds and Complex Mixtures of Neutral Organic Compounds.

The air-blood partition coefficient (Kab) is extensively employed in human health risk assessment for chemical exposure. However, current Kab estimation approaches either require an extensive number of parameters or lack precision. In this study, we present two novel and parsimonious models to accurately estimate Kab values for individual neutral organic compounds, as well as their complex mixtures. The first model, termed the GC×GC model, was developed based on the retention times of nonpolar chemical analytes on comprehensive two-dimensional gas chromatography (GC×GC). This model is unique in its ability to estimate the Kab values for complex mixtures of nonpolar organic chemicals. The GC×GC model successfully accounted for the Kab variance (R2 = 0.97) and demonstrated strong prediction power (RMSE = 0.31 log unit) for an independent set of nonpolar chemical analytes. Overall, the GC×GC model can be used to estimate Kab values for complex mixtures of neutral organic compounds. The second model, termed the partition model (PM), is based on two types of partition coefficients: octanol to water (Kow) and air to water (Kaw). The PM was able to effectively account for the variability in Kab data (n = 344), yielding an R2 value of 0.93 and root-mean-square error (RMSE) of 0.34 log unit. The predictive power and explanatory performance of the PM were found to be comparable to those of the parameter-intensive Abraham solvation models (ASMs). Additionally, the PM can be integrated into the software EPI Suite, which is widely used in chemical risk assessment for initial screening. The PM provides quick and reliable estimation of Kab compared to ASMs, while the GC×GC model is uniquely suited for estimating Kab values for complex mixtures of neutral organic compounds. In summary, our study introduces two novel and parsimonious models for the accurate estimation of Kab values for both individual compounds and complex mixtures.

Catchment area, fate, and environmental risks investigation of micropollutants in Danish wastewater

This study aimed to investigate the spatial distribution of micropollutants in wastewater related to catchment area, and their environmental risks and fate. About 24-h flow proportional effluent (n = 26) wastewater samples were collected from eight WWTPs across Denmark. From five of these WWTPs corresponding influent samples (n = 20) were collected. Samples were enriched by multi-layer solid phase and analysed by liquid chromatography–high-resolution mass spectrometry and comprehensive two-dimensional gas chromatography with high-resolution mass spectrometry detection. We detected and quantified 79 micropollutants from a list of 291 micropollutants in at least one influent or effluent wastewater sample. From this we found that 54 micropollutants decreased in concentrations during wastewater treatment, while O-desmethylvenlafaxine, carbamazepine, amitriptyline, benzothiazole, terbutryn, and citalopram increased in concentrations through the WWTP.The toxicity of effluent wastewater samples was assessed by EC50 using Raphidocelis subcapitata (R. subcapitata) and LC50 using the crustacean Daphnia magna (D. Magna), for which six micropollutants were detected above the predicted no-effect concentration. Our study demonstrates that catchment area influences the micropollutant composition of wastewater. Out of 19 pharmaceuticals, the measured concentration in influent wastewater was predicted within a factor of 10 from sale numbers and human excretion, which demonstrates the strong influence of catchment area on micropollutant composition.

Identifying the Early Post-Mortem VOC Profile from Cadavers in a Morgue Environment Using Comprehensive Two-Dimensional Gas Chromatography

Understanding the VOC profile released during the early post-mortem period is essential for applications in training human remains detection dogs and urban search and rescue operations (USAR) to rapidly locate living and deceased victims. Human cadavers were sampled at the UQTR morgue within a 0–72 h post-mortem interval. VOC samples were collected from the headspace above the cadavers, using Tenax TA/Carbograph 5TD dual sorbent tubes, and analyzed using GC×GC-TOFMS. Multiple data processing steps, including peak table alignment and filtering, were undertaken using LECO ChromaToF and custom scripts in R programming language. This study identified 104 prevalent VOCs, some of which are linked to human decomposition, while others are connected to the persistence of living scent. Principal Component Analysis (PCA) further highlighted that VOC profiles can change dynamically over time, even in a controlled setting. The findings underscore the complexity and variability in VOC profiles during the early post-mortem period. This variability is influenced by multiple factors including the individual’s biological and physiological conditions. Despite the challenges in characterizing these profiles, the identified VOCs could potentially serve as markers in forensic applications. The study also highlights the need for additional research to build a dataset of VOCs for more robust forensic applications.

Leveraging the use of ionic liquid capillary columns and GC×GC-MS for fatty acid profiling in human colostrum samples.

Lipids in human colostrum provide the majority of energy intake and essential fatty acids for developing infants. The fatty acid composition of human colostrum is highly variable and influenced by multiple factors. Human colostrum is a complex sample bringing challenges to fatty acid profiling. This work aimed to optimize the use of ionic liquid (IL) columns and flow-modulated comprehensive two-dimensional gas chromatography coupled to mass spectrometry (FM-GC×GC-MS) for fatty acid profiling in human colostrum. Derivatization strategies were optimized and the elution behavior of fatty acid methyl esters (FAME) on various 1D column phases (Solgel-WAX, SLB-IL60i, SLB-IL76i, and SLB-IL111i). Derivatization with sodium methoxide yielded a satisfactory recovery rate (90%) at milder conditions and reduced time. The use of IL60 as the 1D column provided superior separation, good peak shape, and better utilization of elution space. As a proof of concept, the developed method was applied to access the effects of the mode of neonatal delivery (vaginal vs. C-section) on the fatty acid profile of human colostrum samples. The integrated multidimensional gas chromatography strategy improved FAME detection and separation and can be a useful tool for accessing the effects of different factors on the fatty acid profiling of complex samples.

Distribution and geochemical significance of alkylbenzenes for crude oil with different depositional environments and thermal maturities

A total of 45 alkylbenzenes were detected and identified in crude oils with different depositional environments and thermal maturities from the Tarim Basin, Beibuwan Basin, and Songliao Basin using comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC × GC-TOFMS). By analyzing the distribution characteristics of C0–C5 alkylbenzenes, it is found that the content of some alkylbenzenes varies greatly in crude oils. Based on the distribution characteristics of 1,2,4,5-tetramethylbenzene (TeMB) and 1,2,3,4-TeMB, the ratio of 1,2,4,5-TeMB to 1,2,3,4-TeMB is proposed to indicate the organic matter origin and depositional environment of ancient sediments. Oil samples originated mainly from lower hydrobiont, algae, bacteria and source rocks deposited under reducing/anoxic conditions have low 1,2,4,5-/1,2,3,4-TeMB values (less than 0.6), while oil samples originated mainly from terrestrial higher plants and source rocks deposited under oxic/sub-oxic conditions have higher 1,2,4,5-/1,2,3,4-TeMB values (greater than 1.0). The significant difference of 1,2,4,5-/1,2,3,4-TeMB values is controlled by 1,2,4,5-TeMB content. 1,2,4,5-TeMB content in oils derived from source rocks deposited in oxidized sedimentary environment (greater than 1.0 mg/g whole oil) is higher than that in oils from source rocks deposited in reduced sedimentary environment (less than 1.0 mg/g whole oil). 1,2,4,5-/1,2,3,4-TeMB ratio might not or slightly be affected by evaporative fractionation, biodegradation and thermal maturity. 1,2,4,5-/1,2,3,4-TeMB ratio and 1,2,4,5-TeMB content can be used as supplementary parameter for the identification of sedimentary environment and organic matter input. It should be noted that compared to the identification of organic matter sources, the 1,2,4,5-/1,2,3,4-TeMB parameter is more effective in identifying sedimentary environments.

Molecular fingerprints and health risks of smoke from home-use incense burning

Abstract. The burning of incense for home use is a widespread practice that has been shown to have significant negative impacts on human health and air quality. However, there is a lack of understanding regarding its emission profiles and associated health risks. To address this knowledge gap, we utilized a state-of-the-art thermal-desorption comprehensive two-dimensional gas chromatography–mass spectrometer (TD-GC × GC-MS) to (semi-)quantify the emission factors (EFs) of 317 volatile compounds and thoroughly investigate the organic profiles of smoke from incense burning across a full-volatility range. Results showed that toluene (70.8±35.7 µg g−1) is the most abundant compound in smoke from incensing burning, followed by benzene, furfural, and phenol. Phenol, toluene, furfural, 2-furanmethanol, benzene, and benzyl alcohol are the main contributors to ozone and secondary organic aerosol (SOA) estimation. Intermediate volatility organic compounds (IVOCs) accounted for 19.2 % of the total EFs but 40.0 % of the estimated SOA. Additionally, a novel pixel-based method, combined with aroma analysis, revealed that furfural can act as a key tracer of incense burning and is responsible for the distinctive aroma of incense smoke. High-bioaccumulation-potential (BAP) assessment using pixel-based partition coefficient estimation revealed that acenaphthylene, dibenzofuran, and phthalate esters (PAEs) are chemicals of high-risk concern and warrant further control. Our results highlight the critical importance of investigating home-use incense burning and provide new insights into the health impacts of smoke from incense burning using novel approaches.

Investigating sensory-classified roasted arabica coffee with GC × GC-TOFMS and chemometrics to understand potato taste defect

The presence of flavor defects in coffee beans can negatively impact quality, the consumer experience, and commercial trade. Potato taste defect (PTD), a flavor defect specific to East African coffee, is often characterized by a musty, vegetable-like aroma. While previous work has correlated PTD with the presence of 2-isopropyl-3-methoxypyrazine (IPMP), additional changes in the volatile profile of these beans can further amplify the distinct odor of this defect. The aim of this work was to develop a volatile fingerprint of PTD in roasted arabica coffee using headspace solid-phase microextraction coupled to comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (HS-SPME-GC × GC-TOFMS) and chemometrics. Examination of the HS-SPME-GC × GC-TOFMS data with tile-based Fisher ratio (F-ratio) analysis discovered 359 analytes that differentiated clean coffee samples from those impacted by severe PTD (p-value < 0.01). It was determined that 327 of the identified analytes were more prevalent in the clean coffee samples while 32 analytes, including IPMP, exhibited higher signals in the impacted coffee samples. Principal components analysis (PCA) of the F-ratio results demonstrated that the coffee samples clustered based on the presence of PTD. Partial least squares (PLS) regression modeling further demonstrated that the compounds discovered by F-ratio analysis were correlated with PTD by accurately predicting the concentration of IPMP in the samples. Investigation of the compounds highly weighted in both the PCA and PLS loadings suggest that the presence of microorganisms on coffee beans after antestia bug damage could be a potential pathway for PTD. This damage results in an overall decrease of analytes that are known to have positive sensory contributions to coffee aroma. Collectively, the volatile fingerprint shown herein illustrates that PTD alters the biochemical process in coffee beans.

Classification of produced water samples using class-oriented chemometrics and comprehensive two-dimensional gas chromatography coupled to mass spectrometry

Produced water (PW) is a type of wastewater that arises during oil and gas production. Due to its potential environmental impact, PW is one of the most closely monitored forms of wastewater in the petroleum industry. The total oil and grease (TOG) content in the water is a crucial parameter for assessing the environmental impact of PW. Traditional methods for analyzing TOG in PW can be time-consuming and may not be compatible with green chemistry principles. In this study, an alternative method for classifying PW samples is proposed using a one-class classifier (OCC) model, which has proven useful for classification problems. To achieve this goal, headspace solid-phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography (GC×GC) were employed to obtain TOG profiles from PW. A series of simulated PW samples containing TOG were generated using a mixture design comprising four petrochemicals at concentrations ranging from 10 mg L-1 to 50 mg L-1. The polydimethylsiloxane (PDMS) fiber showed the most representative extraction of analytes. The optimization of the HS-SPME method was performed using a Doehlert design with two variables, and the final conditions were set at 80 °C and 70 min for extraction temperature and time, respectively. A pixel-based data approach was used to implement data-driven soft independent modeling by class analogy (DD-SIMCA). Although DD-SIMCA is a developing area in GC×GC studies, the proposed model produced outstanding results with a sensitivity of 94.3 %, specificity of 95.0 %, and accuracy of 94.5 %, considering the complex and broad compositional range of the modeled mixtures. These findings demonstrated the effectiveness of the OCC model approach in classifying PW samples according to environmental regulations.

Chemical elucidation of recycled plastic pyrolysis oils by means of GC×GC-PI-TOF-MS and GC-VUV

Detailed chemical characterization of the composition of pyrolysis oils produced from plastics is a mandatory step in understanding the recycling process. Even though the chemical composition of pyrolysis plastic waste oils shows similarities with fossil-based oils, e.g. PIONA related compounds, the relative proportions of the chemical classes are significantly different, resulting in important changes in the global properties of these fluids. In this context, an analytical method based on comprehensive two-dimensional gas chromatography (GC×GC), coupled with photoionization (PI) – time-of-flight mass spectrometry (TOF MS) was developed to obtain a detailed chemical characterization of plastic pyrolysis-oil. A group-type analysis was achieved thanks to the detection of molecular ions by soft ionization PI-TOF MS. Moreover, olefins were successfully distinguished from naphthenes by in-depth consideration of MS spectra, even though such compounds elute very close in the 2D chromatographic separation space. A part of the olefins identified by PI was further confirmed by GC coupled to vacuum ultraviolet detection (VUV) since olefins VUV spectra differ from other compounds. The overall combination of the entire set of data of this multi-modal approach was valuable in studying the pyrolyzed plastic oil composition. It was furthermore applied to monitor the efficiency of upgrading processes that were applied to the oils to remove specific contaminants such as the diolefins. This approach has the potential to support the production of plastic pyrolysis oils that could efficiently be reintroduced in the market to sustain economic circularity needs.

Region of interest selection for GC×GC–MS data using a pseudo fisher ratio moving window with connected components segmentation

Comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC–MS) data present several challenges for analysis largely because chemical factors drift along the chromatographic modes across different chromatographic runs, and there is frequently a lack of reliable molecular ion measurements with which to align data across multiple samples. Tensor decomposition techniques such as Parallel Factor Analysis (PARAFAC2/PARAFAC2×N) allow analysts to deconvolve closely eluting signals for quantitative and qualitative purposes. These techniques make relatively few assumptions about chromatographic peak shapes or the relative abundance of noise and allow for highly accurate representations of the underlying chemical phenomena using well-characterized and scrutinized principles of chemometrics. However, expert intervention and supervision is required to select appropriate Regions of Interest (ROI) and numbers of chemical components present in each ROI. We previously reported an automated ROI selection algorithm for GC–MS data in Giebelhaus et al. where we observed the ratio of the first and second eigenvalues within a moving window across the entire chromatogram. Here, we present an extension of this work to automatically detect ROIs in GC×GC–MS chromatograms, while making no assumptions about peak shape. First, we calculate the probabilities of each acquisition being in a ROI, then apply connected components segmentation to discretize the regions of interest. For sparse chromatograms we found the algorithm detected spurious peaks. To address this, we implemented an iterative ROI selection process where we autoscaled the moving window to the standard deviation of the noise from the previous iteration. Using three user-defined parameters, we generated informative ROIs on a wide range of GC×GC-TOFMS chromatograms.

Characterization of the odor compounds in human milk by DHS/GC × GC-O-MS: A feasible and efficient method

Odor analysis of human milk (HM) is often challenging. Here, a new strategy for the analysis of odorants in HM using dynamic headspace sampling combined with comprehensive two-dimensional gas chromatography–olfactometry-mass spectrometry (DHS/GC × GC-O-MS) was established based on the comparison of different extraction methods and instrument modes. Overall, DHS/GC × GC-O-MS was proved to be able to provide higher extraction efficiency and better analytical results of the odor-active compounds (OACs) in HM, meanwhile, the salt addition during the extraction further promoted the release of the odorants. Twenty key OACs in HM were identified by flavor dilution analysis and odor activity calculation, of which 1-octen-3-one, 2,3-butanedione, (E)-2-nonenal, and nonanal contributed significantly to the odor of HM. In addition, 2,3-pentanedione was detected as a key OAC in HM for the first time. This study provided a powerful analytical strategy for the comprehensive odor analysis of HM.

Complex origins of naphthenic oils in the Junggar Basin, China: Biodegradation vs. non-biodegradation

Naphthenic crude oils are scarce resources of great value. Their origins are generally considered to be related to biodegradation, which consumes paraffins and enriches naphthenes. However, other possible controls on the origins of the naphthenic oils remain insufficiently clear. To fill the knowledge gap, we conducted a case study in the Junggar Basin by using comprehensive two-dimensional gas chromatography–mass spectrometry for semi-quantitative analysis of naphthenes in combination with relevant organic geochemical data, and address its global implications by synthesizing the typical naphthenic oils discovered worldwide. It was found that the occurrence of naphthenic crude oils in the basin was not caused by biodegradation alone, while sedimentary paleoenvironments and source-rock biological inputs (i.e., indicative of organofacies) are important controlling factors. Naphthenic crude oils are mainly derived from dolomitic source rocks of the Permian Fengcheng Formation in the Mahu Sag of the northwestern basin, where the average naphthene content is 43.8 %, with an average naphthene/paraffin (N/P) ratio of 1.24. Source rocks were deposited in a reducing, hypersaline and stratified alkaline lake (0.75 < pristane/phytane (Pr/Ph) < 1.46, gammacerane/C30αβ hopane > 0.23), with source-rock biological inputs being dominated by halophilic algae (steranes/hopanes > 1, C28/C27-29-steranes > 40 %). In contrast, crude oils in the Jimusaer Sag of the southeastern basin are paraffinic–naphthenic with an average naphthene content of 24.8 % and an average N/P ratio of 0.75. Source rocks here were deposited in an anoxic–oxic lake of low salinity (1.05 < Pr/Ph < 1.59, 0.15 < gammacerane/C30αβH < 0.18), and organic matter consists of mixed bacteria, algae, and terrigenous higher plants (steranes/hopanes < 1, C28/C27-29-steranes < 40 %). Thermal maturity and biodegradation also control the composition of naphthenic oils. High thermal maturity promotes cracking of naphthenic groups, whereas moderate biodegradation (rank PM < 6) promotes naphthenic groups by preferentially catabolizing paraffins. Our results suggest that halophilic algae in strongly-reducing alkaline lakes provide important material for the generation of naphthenic oils in the Mahu Sag and the occurrence of naphthenic crude oils is not controlled solely by biodegradation; influencing factors are complex and vary between regions without universality. This may be the reason for their limited and sparse distribution worldwide.

Identification, Quantitation, and Sensory Evaluation of Thiols in Bordeaux Red Wine with Characteristic Aging Bouquet.

Great Bordeaux red wines are known for their distinctive aging bouquet. However, the nature of volatile chemicals underpinning this sensory expression is not fully understood. This work investigated the empyreumatic aging bouquet of a collection of premium Bordeaux red wines using silver-ion (Ag+) solid-phase extraction, cryogenic heart-cutting multidimensional gas chromatography mass spectrometry/olfactometry, and comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry. In doing so, a substantial number of "meaty" odors were revealed. Three detected "meaty" notes were tentatively or unequivocally attributed to furan thiols. Among them, 2-methyltetrahydrofuran-3-thiol (1) with a pleasant "meaty" aroma was reported in wine for the first time. Its trans isomer (trans-1a) was resolved from its racemate by chemical modification, which confirmed its presence in wine. The odor detection threshold of trans-1a in the model wine was determined at 55 ng/L. Moreover, an additive effect between 1 and literature-known 2-methyl-3-furanthiol was observed. By a new ultra high-performance liquid chromatography quadrupole Orbitrap high-resolution mass spectrometry method, the concentration of trans-1a, in addition to those of 2-methyl-3-furanthiol and 2-furfuryl thiol, was measured in the wines at ng/L levels.

Theoretical modeling and machine learning-based data processing workflows in comprehensive two-dimensional gas chromatography—A review

In recent years, comprehensive two-dimensional gas chromatography (GC × GC) has been gradually gaining prominence as a preferred method for the analysis of complex samples due to its higher peak capacity and resolution power compared to conventional gas chromatography (GC). Nonetheless, to fully benefit from the capabilities of GC × GC, a holistic approach to method development and data processing is essential for a successful and informative analysis. Method development enables the fine-tuning of the chromatographic separation, resulting in high-quality data. While generating such data is pivotal, it does not necessarily guarantee that meaningful information will be extracted from it. To this end, the first part of this manuscript reviews the importance of theoretical modeling in achieving good optimization of the separation conditions, ultimately improving the quality of the chromatographic separation. Multiple theoretical modeling approaches are discussed, with a special focus on thermodynamic-based modeling. The second part of this review highlights the importance of establishing robust data processing workflows, with a special emphasis on the use of advanced data processing tools such as, Machine Learning (ML) algorithms. Three widely used ML algorithms are discussed: Random Forest (RF), Support Vector Machine (SVM), and Partial Least Square–Discriminate Analysis (PLS-DA), highlighting their role in discovery-based analysis.

Exploring the visualization of human milk odor profiles: Intuitive characterization and construction of the link between odor compounds and sensory attributes

Studies on odor are not negligible in the human milk (HM) science field because it plays an irreplaceable role in the feeding process of infants. This study aimed to investigate the odor skeleton components (OSCs) in HM and verify and construct an intuitive link between them and the HM odor attributes. A total of 72 odor-active compounds were identified from 32 HMs using the comprehensive two-dimensional gas chromatography–olfactometry-mass spectrometry. Twenty of these compounds were identified as OSCs (average FD ≥ 1 and average OAV ≥ 1), and their actual odor contribution was clarified. Furthermore, the connection of the 20 OSCs with their corresponding eight odor attributes was visualized by constructing a molecular sensory odor wheel. Of them, 2,3-butanedione, (E)-2-decenal, nonanal, (E)-2-nonenal, octanal, 1-octen-3-one, hexanal, methional, and butanoic acid were the most important contributors to dairy-sweet, fishy, dairy-fat, metallic/iron, flour, grassy/green, cooked, and sweaty/rancid odor of HM.

Analysis of volatile organic compounds and potential odour compounds in food contact paperboard using headspace two-dimensional GC-QTOF-MS

The objective was to establish a robust and reliable approach for the characterisation of volatile organic compounds (VOCs) present in food contact paperboard. This was achieved through the utilisation of headspace solid-phase microextraction in tandem with comprehensive two-dimensional (2D) gas chromatography (GC) and quadrupole time-of-flight mass spectrometry (HS-SPME-GC × GC-QTOF-MS). The experimental parameters were optimised, involving the use of a DVB/C-WR/PDMS fibre at a temperature of 80 °C for a duration of 30 min. A total of 344 VOCs comprising aldehydes, ketones, alcohols, ethers, esters, alkanes and aromatic compounds, were tentatively identified in the samples. Twelve compounds believed to be from biogenic sources had a high odour impact making them major contributors to potential taint from the paperboard samples. Significant attention should be devoted to five compounds namely, 2-methylnaphthalene, 2-pentyl-furan, furfural, 1-octen-3-one and 1-octen-3-ol due to their potential adverse impact on the organoleptic qualities of packaged food items and their potential toxicity. Abbreviations: C-WR: carbon wide range; DVB: divinylbenzene; GC-MS: gas chromatography - mass spectrometry; GCxGC-QTOF-MS: comprehensive two-dimensional gas chromatography coupled to quadrupole-time-of-flight - mass spectrometry; HS-SPME: headspace - solid phase microextraction; LOD: limit of detection; LOQ: limit of quantification; OAV: odor activity values; PDMS: polydimethylsiloxane; RI: retention index; TTC: threshold of toxicological concern; VOC: volatile organic compound

Investigations into the transition to sustainable alternative fuels in a South African underground platinum mine

Adverse environmental impacts associated with the use of fossil fuels and the over-dependence thereon has made energy security and sustainability a critical issue worldwide particularly for key energy intensive economic sectors which are heavily dependent on diesel. We thus investigated the feasibility of a transition to two different alternative fuels namely, rapeseed methyl ester (RME) biodiesel and gas-to-liquid fuel (GTL), in the platinum mining industry in South Africa. Load haul dump vehicles are the most abundant workhorses underground and were the selected vehicles to test alternative fuels at 100% without any engine modification. Potential reduction of harmful unregulated polycyclic aromatic hydrocarbon (PAH) emissions was the focus of the research due to their adverse impacts on the environment, human health and engine operations. Quantitative collection of gas and particle phase PAHs was made possible using portable denuder devices followed by analysis by two-dimensional gas chromatography coupled to time-of-flight mass spectrometry. Results showed that total PAH emissions from a high idling vehicle decreased dramatically when diesel was substituted with both biofuels (total gas phase PAH concentrations of 34; 14 and 9 µg m-3 for diesel, GTL and RME, respectively) and no substantial hinderance on engine performance was reported. This novel sector specific study on unmodified heavy duty working vehicles can potentially translate into a real-world, immediate solution, as not only would the selected biofuels be able to directly replace diesel, but both have high potential of being locally produced in South Africa and assist in the promotion of a circular economy.

Direct extraction with acetonitrile of hemp seed oil for the analysis of pesticides by using comprehensive two-dimensional gas chromatography-triple quadrupole mass spectrometry

The method herein described involves a rapid and limited-volume (0.5 mL of acetonitrile) solvent-extraction sample preparation process, for pesticide determination in hemp seed oil. The extraction method was characterized by the absence of both clean-up or pre-concentration steps. The extracts were directly analyzed through cryogenic-modulation comprehensive two-dimensional gas chromatography coupled to triple quadrupole mass spectrometry. The novelty characterizing the present research [compared to a previous one (Arena et al., 2023)] is related to the extension of the number of pesticides (97), and to the investigation of a more challenging matrix, contained in a vegetable oil of increasing interest among consumers.Linearity, limits of detection and quantification, accuracy, precision, recovery, and matrix effect were measured. Particular emphasis was devoted to the matrix effect, with the co-extracted matrix amount defined. Three international regulations (Canada, California, Europe) were considered, and the obtained limits of quantification were found to be too high in five (Canada) and twelve (Europe) cases, for a total number of 15 pesticides.The analysis of ten commercial samples showed the presence of seven pesticide residues in four of them, at concentration levels ranging from 0.02 to 0.98 mg kg−1, with most over the regulation residue limits.

Variation in the chemical composition of essential oils from Mangifera indica L. leaves by comprehensive two-dimensional gas chromatography

The leaves of Mangifera indica L. have been used in the medical system of India to treat diseases such as asthma, dysentery, cough, leucorrhea, jaundice, pain, and malaria. The analysis of different varieties of the same species is intended to determine if the compounds have a differential distribution. The present study investigates the volatile compounds from the leaves of two M. indica varieties extracted by hydrodistillation and analyzed by comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC�GC/TOFMS). The number of compounds identified by GC�GC/TOFMS was superior to that obtained by gas chromatography/mass spectrometry (GC/MS) for the same variety of M. indica. This study demonstrates the applicability of the GC�GC/TOFMS for the comprehensive profiling of essential oils from M. indica, in which 125 and 95 compounds were identified in the varieties �espada� and �cora��o de boi�, respectively. These results show that the compositions of the two analyzed essential oils present differences concerning the GC�GC/TOFMS and conventional chromatography technique, the GC/MS.

Unraveling the complexity of pyrolysates from residual fuels by Py-GCxGC-FID/SCD/TOF-MS with an innovative data processing method

Residual fuels, often called ’bottom-of-the-barrel’ are expected to play an important role in the transition towards a purely renewable energy market. Processes are required to upgrade such fuels and convert them into energy more cleanly and sustainably. To this goal, researchers aim to improve the understanding of their structure and reactivity. Given their complex nature and different chemical compositions, comprehensive two-dimensional gas chromatography (GCxGC) is well suited to provide a detailed characterization of the volatiles released during the pyrolysis of the residual fuels. This study reports a detailed characterization of pyrolysates released during the pyrolysis of two oil samples analyzed using a Py-GCxGC-FID/SCD/TOF-MS. The mass spectra generated with the electron impact ionization TOF-MS detection were used for species identification. An algorithm was developed and described here for the screening and post-processing of the detected peaks. Following algorithm post-processing, the species identification confirms that this workflow is suitable for unraveling the complex nature of the complex mixture released during the pyrolysis of the oil samples. The algorithm results were verified using information from a flame ionization detector (FID) and a sulfur chemiluminescence detector (SCD), and the extraction of fragmentation patterns based on the literature. The chemical structure of pyrolysis products is described and classified into 26 molecular classes. The methodology presented in this work can be extended to other complex mixtures, such as bio-oils, plastics, and biomasses.