Comprehensive Analysis of Emissions from Wood and Cow Dung Burning using Chemometrics and Two-Dimensional Gas Chromatography.

Biomass burning is a global source of climate- and health-affecting emissions. The impacts of biomass burning emissions (BBE) are tied to their complex and variable chemical makeup. For instance, the nitrogen content of BBE influences their capacity to absorb light, and therefore affect the Earth's radiative budget. Factors such as temperature, biomass type, or air flow rate during the combustion all modify the composition of BBE, making accurate characterization challenging. Herein, for the first time, principal component analysis (PCA) was applied to emissions gathered during laboratory-based combustion of wood and cow dung biomass in a tube furnace. A thermal desorption two dimensional time-of-flight gas chromatography mass spectrometry (TD-GC×GC-ToF-MS) setup was employed to separate and identify chemical species. By combining these techniques with a feature selection algorithm, we determined that low temperature and air flow rate lead to greater feature separation on PCA scores plots. Of the 729 variables used to construct the plots, 61 were identified as significant. These species - including sugars such as D-Allose and melezitose, as well as tracers such as levoglucosan and guaiacol - significantly differentiated emissions from wood versus cow dung biomass, especially at lower temperatures. In particular, combustion of either fuel at 0.2 slpm and 500 °C, lead to 20 times the variability in levoglucosan peak area over more efficient furnace parameters. Chemical species evolved only from dung burning contained on average 0.595 nitrogen atoms versus 0.515 for wood, indicating that a higher nitrogen content of the base fuel may not necessarily translate into emission of unique nitrogen containing species, potentially causing the underestimation of dung burning impacts. Overall, TD-GC×GC-ToF-MS coupled to PCA reliably separated emissions from wood and dung biomass while simultaneously identifying significant chemical features, displaying the suitability of this combination of techniques towards characterizing complex BBE matrices in the future.

Artificial intelligence decision making tools in food metabolomics: Data fusion unravels synergies within the hazelnut (Corylus avellana L.) metabolome and improves quality prediction.

This study investigates the metabolome of high-quality hazelnuts (Corylus avellana L.) by applying untargeted and targeted metabolome profiling techniques to predict industrial quality. Utilizing comprehensive two-dimensional gas chromatography and liquid chromatography coupled with high-resolution mass spectrometry, the research characterizes the non-volatile (primary and specialized metabolites) and volatile metabolomes. Data fusion techniques, including low-level (LLDF) and mid-level (MLDF), are applied to enhance classification performance. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) reveal that geographical origin and postharvest practices significantly impact the specialized metabolome, while storage conditions and duration influence the volatilome. The study demonstrates that MLDF approaches, particularly supervised MLDF, outperform single-fraction analyses in predictive accuracy. Key findings include the identification of metabolites patterns causally correlated to hazelnut's quality attributes, of them aldehydes, alcohols, terpenes, and phenolic compounds as most informative. The integration of multiple analytical platforms and data fusion methods shows promise in refining quality assessments and optimizing storage and processing conditions for the food industry.

Comprehensive analysis of the effects of the traditional stir-fry process on the dynamic changes of volatile metabolites in Hainan camellia oil.

The traditional stir-fry process before pressing is crucial to manufacture Hainan camellia oil. To assess the effects of the stir-fry process on Hainan camellia oil, six samples across different stir-fry stages were analyzed. The stir-fry process modified odors, volatile metabolite profiles, and human health-promoting functions of Hainan camellia oil. Totally, 350 volatile metabolites were detected, and heterocyclic compounds were revealed as the main contributors of strong aroma. Potential indicators for monitoring the stir-fry degree were established. Eight key aroma volatile metabolites were identified, including three new ones (1-octen-3-one, 2,3-butanedione, and vanillin). Lipids degradation and the Millard reaction are probably the main pathways for aroma generation. Over-stir-fry treatment diminished the contents of some important volatile metabolites but increased the risk of arising burnt odor. Our work offered insights into the effects of the stir-fry process and over-stir-fry treatment on Hainan camellia oil, which is meaningful for improving the hot-pressing technique.

Quantitative determination of olefins in pyrolysis oils from waste plastics and tires using selective adsorption by Ag-SiO2 followed by GC×GC-FID.

Determination of olefins in pyrolysis oils from waste plastics and tires is crucial for optimizing the pyrolysis process and especially for the further advanced valorization of these oils in terms of the circular economy. Identifying olefins, even using high-resolution techniques like GC×GC, is challenging without TOF-MS, which allows modification of the ionization step. Currently, the only method for determining olefins in plastic pyrolysis oils is GC-VUV, recently standardized as ASTM D8519. However, TOF-MS and VUV are not affordable instruments for many research teams working on plastics recycling. This paper introduces a simple method for the selective micro-scale adsorption of olefins over AgNO3/SiO2, followed by the GC×GC-FID analysis. Olefins are determined indirectly from the loss of chromatographic area in respective hydrocarbon groups before and after removal. Only 50 µL sample and 15 min of sample separation are needed. Our method was extensively validated and provides a reliable determination of olefin content in a wide range of pyrolysis oils from plastics and tires and their products after mild hydrotreatment. It is affordable to all researchers and industrial companies working on plastics recycling by thermochemical processes as it does not require an MS detector.

Utility of an Untargeted Metabolomics Approach Using a 2D GC-GC-MS Platform to Distinguish Relapsing and Progressive Multiple Sclerosis.

Multiple sclerosis (MS) is the most common inflammatory neurodegenerative disease of the central nervous system (CNS) in young adults and results in progressive neurological defects. The relapsing-remitting phenotype (RRMS) is the most common disease course in MS, which ultimately progresses to secondary progressive MS (SPMS), while primary progressive MS (PPMS) is a type of MS that worsens gradually over time without remissions. There is a gap in knowledge regarding whether the relapsing form can be distinguished from the progressive course, or healthy subjects (HS) based on an altered serum metabolite profile. In this study, we performed global untargeted metabolomics with the 2D GC-GC-MS platform to identify altered metabolites between RRMS, PPMS, and HS. We profiled 235 metabolites in the serum of patients with RRMS (n = 41), PPMS (n = 31), and HS (n = 91). A comparison of RRMS and HS patients revealed 22 significantly altered metabolites at p < 0.05 (false-discovery rate [FDR] = 0.3). The PPMS and HS comparisons revealed 28 altered metabolites at p < 0.05 (FDR = 0.2). Pathway analysis using MetaboAnalyst revealed enrichment of four metabolic pathways in both RRMS and PPMS (hypergeometric test p < 0.05): (1) galactose metabolism; (2) amino sugar and nucleotide sugar metabolism; (3) phenylalanine, tyrosine, and tryptophan biosynthesis; and (4) aminoacyl-tRNA biosynthesis. The Qiagen IPA enrichment test identified the sulfatase 2 (SULF2) (p = 0.0033) and integrin subunit beta 1 binding protein 1 (ITGB1BP1) (p = 0.0067) genes as upstream regulators of altered metabolites in the RRMS vs. HS groups. However, in the PPMS vs. HS comparison, valine was enriched in the neurodegeneration of brain cells (p = 0.05), and heptadecanoic acid, alpha-ketoisocaproic acid, and glycerol participated in inflammation in the CNS (p = 0.03). Overall, our study suggests that RRMS and PPMS may contribute metabolic fingerprints in the form of unique altered metabolites for discriminating MS disease from HS, with the potential for constructing a metabolite panel for progressive autoimmune diseases such as MS.

Failure of the three-way catalyst (TWC) introduces "super emitters".

Vehicle exhaust is one of the major organic sources in urban areas. Old taxis equipped with failed three-way catalysts (TWCs) have been regarded as "super emitters". Compressed natural gas (CNG) is a regular substitution fuel for gasoline in taxis. The relative effect of fuel substitution and TWC failure has not been thoroughly investigated. In this work, vehicle exhausts from gasoline and CNG taxis with optimally functioning and malfunctioning TWCs are sampled by Tenax TA tubes and then analyzed by a comprehensive two-dimensional gas chromatography-mass spectrometer (GC×GC-MS). A total of 216 organics are quantified, including 80 volatile organic compounds (VOCs) and 132 intermediate volatility organic compounds (IVOCs). Failure of TWC introduces super emitters with 30 - 70 times emission factors (EFs), 60 - 112 times ozone formation potentials (OFPs), and 34 - 92 times secondary organic aerosols (SOAs) more than normal vehicles. Specifically, for the taxi with failed TWC, the total organic EF of CNG is 16 times that of gasoline, indicating that the failure of TWC exceeds the emission reduction achieved by CNG-gasoline substitution. A significant but unbalanced reduction of ozone and SOA is observed after TWC, whereas a notable "enrichment" in IVOCs was observed. Naphthalene is a typical IVOC component strongly associated with CNG-gasoline substitution and TWC failure, which is lacking in current VOC measurement. We especially emphasize that there is an urgent need to scrap vehicles with failed TWCs in order to significantly reduce air pollution.

Optimization of headspace high-capacity tool coupled to two-dimensional gas chromatography-mass spectrometry for mapping the volatile organic compounds of raw pistachios. A proof-of-concept on the classification ability by geographic origin.

An optimized procedure for extracting and analyzing raw pistachio volatiles was developed through headspace sampling with high-capacity tools and subsequent analysis using comprehensive two-dimensional gas chromatography coupled with mass spectrometry. The examination of 18 pistachio samples belonging to different geographic areas led to the identification of a set of 99 volatile organic compounds (VOCs). Molecules were putatively identified using linear retention index, mass spectra similarity, and two-dimensional plot location. The impact of preprocessing and processing techniques on the aligned data matrix from a set of samples of different geographical origins, after removing contaminants, was evaluated. The combination of scaling with log-transformation, normalization with z-score, and data reduction with random forest machine learning algorithm generated a panel of 16 discriminatory VOC molecules. As a proof of concept, raw pistachios' VOC profile was employed for the first time to tentatively classify them based on their geographical origin.

PFAS emissions from functional textiles using micro-chamber and thermal desorption coupled to two-dimensional gas chromatography-time of flight mass spectrometry (TD-GC×GC-TOF MS).

Per- and polyfluoroalkyl substances (PFAS), in the polymeric form, have been used extensively in functional textiles, including firefighter's turnout gear (e.g., jackets and pants), where PFAS are applied to confer oil and water resistance. However, growing concerns over the persistence, potential toxicity, and environmental impact of PFAS have prompted a thorough assessment of potential exposure pathways. Here, we report the emission of PFAS from three firefighter turnout gear jackets at 38 °C. Volatile emissions from the three layers (outer layer, moisture barrier, and thermal liner) were collected onto sorbent tubes via dynamic headspace sampling using a micro-scale chamber device kept at 38 °C for one hour. The emission was characterized using thermal desorption (TD) coupled to two-dimensional gas chromatography - time-of-flight mass spectrometry (GC×GC-TOF MS). The enhanced separation capacity of GC×GC was essential due to the high number of compounds present in each sample, especially for the fabrics from used turnout gear jackets. Based on the filtering expressions, including two-dimensional retention time (1tr and 2tr) and PFAS diagnostic fragment ions (m/z 69, 95, and 131), fluorotelomer alcohols (FTOHs) and fluorotelomer acrylates were identified using standards and spectral matching with the NIST database. After conducting a non-targeted tile-based workflow, jackets (both used and unused) and layers were compared, resulting in the identification of the top 15 discriminating features from over 400 chromatographic peaks. Finally, preliminary FTOH emission experiments showed some usage and layers trends that are aligned with those reported using solvent extraction. Highest levels of FTOHs were found in the moisture barrier, followed by the outer layer and the thermal liner. Older jackets emitted higher levels of 8:2 FTOH and 10:2 FTOH than a newer jacket. In contrast, a newer jacket used for one year had emissions containing higher levels of 6:2 FTOH. Investigating routes of exposure and identifying new PFAS targets are critical steps in evaluating the environmental and health impacts of these persistent chemicals.

Identification of organic constituents on atmospheric particulate matter in the East Asian background air of free troposphere by GC×GC-TOFMS.

The presence of organic compounds on the particulate matter (PM) or aerosols can arise from the condensation of gaseous organic compounds on the existing aerosols, or from organic precursors to form secondary organic aerosols (SOA) through photochemistry. The objective of this study is to characterize organic constituents on aerosols relevant to their emission sources and the key compounds revealing the evolution of aerosols with the use of a novel analytical technique. A time-of-flight mass spectrometry (TOFMS) coupled with comprehensive two-dimensional gas chromatography (GC×GC) was developed using a flow type of modulator instead of a thermal type as a prelude to field applications without the need for cryogen. The methodology of GC×GC-TOFMS is discussed in this study in detail. Since the coarse PM (PM10-2.5) may exhibit with a relatively high OC content compared to PM2.5, the GC×GC results have been obtained by analyzing PM10 samples collected in parallel with OC/EC analysis of PM2.5 samples at the Lulin Atmospheric Background Station (LABS, 23.47°N, 120.87°E, 2862 m ASL) as the high-mountain background site in East Asia. We found that the organic analytes were in a majority in the range of 12-30 carbon numbers falling in the category of semi-volatile organic compounds (SVOCs) with 43 compounds of alcohol, aldehyde, ketone, and ester varieties if excluding alkanes. Intriguingly, trace amounts of plasticizers and phosphorus flame retardants such as phthalates (PAEs) and triphenyl phosphate (TPP) were also found, likely originating from regions involved in open burning of household solid waste in Southeast Asia or e-waste recycling in southern China and along the long-range transport route. Compounds such as these are unique to the specific sources, demonstrating the wide spread of these hazardous compounds in the environment.

Comparative analysis of additive decomposition using one-dimensional and two-dimensional gas chromatography: Part I - Irganox 1010, Irganox 1076, and BHT.

Plastics incorporate diverse additives, including primary antioxidants with a typical amount between 0.05 to 3 wt.%, to enhance plastics functionality and durability, preventing their oxidation and maintaining their mechanical properties. While these antioxidants offer substantial benefits, their degradation can significantly impact plastic pyrolysis by changing the pyrolysis oil product distribution. Understanding the intricate distribution of decomposition products resulting from pyrolysis is essential yet often overlooked. This study delved into the analysis of the decomposition of common primary antioxidants, namely, Irganox 1010, Irganox 1076, and butylated hydroxytoluene (BHT), utilizing both one-dimensional gas chromatography coupled with a quadruple mass spectrometer (GC-MS) and two-dimensional gas chromatography equipped with flame ionization detector and time-of-flight mass spectrometer (GC×GC-FID/TOF-MS). This study showed that GC×GC-FID/TOF-MS provided a more detailed characterization of the pyrolysis product distribution of primary antioxidants used in plastics in comparison to GC-MS. For each of the antioxidants, using the GC×GC-FID/TOF-MS analytical approach enhanced the identification of degradation products at least fivefold. Furthermore, GC×GC-FID/TOF-MS identified products of more chemical classes than GC-MS. For instance, compounds from 14 chemical classes were identified from GC×GC-FID/TOF-MS in the pyrolysis of Irganox 1010, whereas only 9 chemical classes were identified in GC-MS. Olefins were the major chemical class for both Irganox 1010 and Irganox 1076 in the decomposition process, accounting for 23.25 wt.% and 20.76 wt.%, respectively. Ketones were the major chemical class in the case of BHT, having a 6.68 wt.% yield. This research enhanced the understanding of the decomposition of primary antioxidant and their product distribution during pyrolysis and shed light on the potential necessity for using two-dimensional gas chromatography.

Comparative analysis of additive decomposition using one-dimensional and two-dimensional gas chromatography: Part II - Irgafos 168 and zinc stearate.

Plastic production has experienced a significant increase in the last sixty years due to its cost-efficiency and adaptable characteristics, leading to the extensive use of additives to improve its performance and longevity. Due to the high demand for plastic, plastic waste production has increased, contaminating the environment and living beings by leaching additives, among other substances. Pyrolysis stands out among recycling techniques because it can handle mixed polymer waste feedstock. However, understanding the pyrolyzates distribution of additives is fundamental to assessing pyrolysis process of plastic waste. This study investigated the pyrolysis product distributions of two commonly used antioxidants, namely, Irgafos 168 and zinc stearate (ZnSt), using one-dimensional gas chromatography equipped with a quadruple mass spectrometer (GC-MS) and two-dimensional gas chromatography coupled to flame ionization detector and time-of-flight mass spectrometer (GC×GC-FID/TOF-MS). While GC separation technique provided limited information on product distribution, GC×GC offered enhanced resolution and identification of the decomposition products. In the pyrolysis of Irgafos 168 at 550 °C, GC identified 18 products, while GC×GC identified 198 products, representing an increase of approximately 11-fold. Similarly, for ZnSt, GC identified 67 products, while GC×GC identified 434 products, representing a 6-fold increase. GC×GC identified decomposition products from 15 different chemical classes for Irgafos 168 and 16 chemical classes for ZnSt, compared to 4 and 11 chemical classes identified by GC, respectively. Phenols and their derivatives were the major chemical class in the decomposition products of Irgafos 168 with a yield of 9.51 wt.%. In contrast, olefinic products were the dominant ones for ZnSt, with a yield of 9.73 wt.%. The major decomposition product of Irgafos 168 and ZnSt was 2­tert­butyl­methylphenol (C11H16O) and C6 olefin (C6H12) with yields of 3.88 wt.%, and 1.13 wt.%, respectively. Utilizing the GC×GC separation method improved the ability to identify decomposition products, which can ultimately lead to a better understanding of antioxidant degradation that occurs during the pyrolysis process. GC×GC also provided thorough characterization of minor and co-eluted products along with major antioxidant degradation products. Additionally, the decomposition product distribution of Irgafos 168 and ZnSt was also compared with the primary antioxidants, Irganox 1010, Irganox 1076, and BHT, studied in part 1. The analysis indicated that the olefinic chemical class was the predominant one in Irganox 1010, Irganox 1076, and ZnSt, while ketones were the major chemical class in the decomposition of BHT and phenolics had the highest yield in Irgafos 168.

Screening for compounds with bioaccumulation potential in breast milk using their retention behavior in two-dimensional gas chromatography.

Discovery of emerging pollutants in breast milk will be helpful for understanding the hazards to human health. However, it is difficult to identify key compounds among thousands present in complex samples. In this study, a method for screening compounds with bioaccumulation potential was developed. The method can decrease the number of compounds needing structural identification because the partitioning properties of bioaccumulative compounds can be mapped onto GC×GC chromatograms through their retention behaviors. Twenty pooled samples from seven provinces in China were analyzed. 1,286 compounds with bioaccumulation potential were selected from over 3,000 compounds. Sixty-two compounds, including aromatic compounds, phthalates, and phenolics etc., were identified with a high level of confidence and then quantified. Among them, twenty-seven compounds were found for the first time in breast milk. Three phthalate plasticizers and two phenolic antioxidants were found in significantly higher concentrations than other compounds. A toxicological priority index approach was applied to prioritize the compounds considering their concentrations, detection frequencies and eight toxic effects. The prioritization indicated that 13 compounds, including bis(2-ethylhexyl) phthalate, dibutyl phthalate, 1,3-di-tert-butylbenzene, phenanthrene, 2,6-di-tert-butyl-1,4-benzoquinone, 2,4-di-tert-butylphenol, and others, showed higher health risks. Meanwhile, some compounds with high risk for a particular toxic effect, such as benzothiazole and geranylacetone, were still noteworthy. This study is important for assessing the risks of human exposure to organic compounds.

Upgrade of Acetone-Butanol-Ethanol Mixture to High-Value Biofuels over Ca-Doped Ni-CaO-SiO2 catalyst.

The selective conversion of biomass fermentation derived from an acetone-butanol-ethanol (ABE) mixture into high-value biofuels is of paramount importance for industrial applications. However, challenges persist in effectively controlling the selectivity of long carbon chain ketones in elevated ABE conversion. In this research, a Ca-doped Ni-CaO-SiO2 catalyst was designed and employed to achieve a remarkable conversion of 89.9% into ketone products from the extracted ABE mixture. The selectivity for C8+ ketones reaches 41.8%, demonstrating exceptional performance. The reversible phase transition between Ca2SiO4 and CaCO3 enhances the recyclability, thereby improving the sustainability of the process. Additionally, the trace intermediate 3-hepten-2-one was successfully detected using two-dimensional GC×GC-MS, elucidating the conversion pathway in the catalytic upgrading of the ABE mixture. This finding offers a potential route for the efficient utilization of biomass and the highly selective production of value-added chemicals.

Identification of Aroma-active Compounds in Milk by GC×GC-O-TOF-MS Combined with Check-all-that-apply.

Understanding consumers' sensory preferences for dairy products is essential. This study employed sensory analysis and instrumental techniques to analyze the flavor of pasteurized milk and ultra-high temperature (UHT) milk. There were 6 milk samples with similar fat content (4.0-4.6 g/100mL) and protein content (3.2-3.8 g/100mL). Sensory data from consumer tests was collected using CATA (n = 100) and 9-point hedonic preferences. Research showed that Chinese consumers could distinguish the flavor of the 2 types of milk, and UHT milk showed a higher preference score, which may be due to the more pronounced milky flavor and sweet taste of UHT milk. A total of 48 aroma-active compounds were sniffed through GC × GC-O-TOF-MS, among which 11 were determined as key aroma-active compounds. Correlation analysis showed that milky odor, sweetness, and aftertaste-milky were positively correlated with γ-dodecalactone and γ-nonanolactone. Cooked and oxidized taste were positively correlated with 1-octen-3-ol and E-2-octenal. This study is important for developing Chinese dairy products and exporting dairy products to China by multinational companies.

Dynamic Changes in Qidan Aroma during Roasting: Characterization of Aroma Compounds and Their Kinetic Fitting.

Qidan is one of the most famous varieties of Wuyi Rock tea and has a strong aroma. The aroma-active compounds in Qidan subject to different roasting times were analyzed using solid-phase microextraction two-dimensional gas chromatography-olfactometry-mass spectrometry (SPME-GC×GC-O-MS), and a total of 92 aroma-active compounds were detected. Multivariate statistical analysis showed that the roasting time had a significant effect on the aroma characteristics of Qidan, and that the key products in the Maillard reaction accumulated with the extension of the roasting time; these key products were screened out according to the calculation of the odor activity values (OAVs), from which kinetic equations were established. It was found that the levels of 2-methylbutanal, 3-methylbutanal, 2-methylpyrazine, 2-ethyl-5-methylpyrazine, and benzaldehyde increased with time, while the contents of benzeneacetaldehyde showed a tendency to first increase and then decrease. This study provides a theoretical basis for flavor quality control during Qidan processing.

Volatile organic compounds produced during postmortem processes can be linked via chromatographic profiles to individual postmortem bacterial species.

Decomposition odor is produced during postmortem mammalian tissue breakdown by bacteria, insects, and intrinsic chemical processes. Past research has not thoroughly investigated which volatile organic compounds (VOCs) can be linked directly to individual bacterial species on decomposing remains. The purpose of this study was to profile the VOCs produced over time by individual species of bacteria using comprehensive two-dimensional gas chromatography (GC×GC) to expand our foundational knowledge of what each bacterial species contributes to decomposition odor. Five different species of bacteria (Bacillus subtilis, Ignatzschineria indica, Ignatzschineria ureiclastica, Curtobacterium luteum, and Vagococcus lutrae) were cultured on standard nutrient agar individually and monitored daily using solid phase microextraction arrow (SPME Arrow) and GC×GC in combination with quadrupole mass spectrometry (qMS) and flame ionization detection (FID). The GC×GC-qMS/FID approach was used to generate rich VOC profiles that represented the bacterial species' metabolic VOC production longitudinally. The data obtained from the chromatographic output was used to compare with a prior study using one-dimensional GC-qMS, and also between each of the five species to investigate the extent of overlap between species. No single VOC could be found in all five bacterial species investigated, and there was little overlap in the profile between species. To further visualize these differences, chromatographic peak data was investigated using two different ordination strategies, principal component analysis (PCA) and principal coordinate analysis (PCoA). The two ordination strategies were compared with each other using a Procrustes analysis. This was performed to understand differences in ordination strategies between the separation science community and chemical ecological community. Overall, ordination strategies were found to produce similar results, as evidenced by the correlation of PCA and PCoA in the Procrustes analysis. All analysis strategies yielded distinct VOC profiles for each species. Further study of additional species will support understanding of the holistic view of decomposition odor from a chemical ecology perspective, and further support our understanding of the production of decomposition odor that culminates from such a complex environment.

Key Aroma Differences in Volatile Compounds of Aged Feng-Flavored Baijiu Determined Using Sensory Descriptive Analysis and GC×GC-TOFMS.

Sensory descriptive analysis of aged feng-flavored Baijiu liquor indicated notable differences in samples of different ages. The samples of freshly distilled Baijiu and those with shorter storage times exhibit bran and fresh green flavors, whereas, with increasing storage time, honey, sweet, and floral fragrances are gradually enhanced. Samples of feng-flavored Baijiu were prepared using headspace solid-phase microextraction, followed by comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry. A total of 496 compounds were identified in all samples, mainly categorized as 14 groups of substances, including esters and aldehydes. Interestingly, 42 of these substances were found in Feng-flavored Baijiu for the first time. Chemometrics was used to analyze the key differential compounds. First, 143 differential compounds closely related to aging were preliminarily screened, and principal component analysis revealed that these compounds were separated by baijiu age. Then, 65 differential compounds were selected by partial least squares discriminant analysis. Furthermore, 43 key differential compounds were selected by combined analysis with variable importance in projection and Pearson correlation coefficients. Partial least squares regression was used to study the correlation between the sensory properties and key differential compounds, and the results indicated that most compounds were closely related to the aging period of the Baijiu. The results of this study provide a theoretical basis and reference for flavor research on feng-flavored Baijiu.

Comprehensive investigation on the dynamic changes of volatile metabolites in fresh scent green tea during processing by GC-E-Nose, GC-MS, and GC × GC-TOFMS.

Processing technology plays a crucial role in the formation of tea aroma. The dynamic variations in volatile metabolites across different processing stages of fresh scent green tea (FSGT) were meticulously tracked utilizing advanced analytical techniques such as GC-E-Nose, GC-MS, and GC × GC-TOFMS. A total of 244 volatile metabolites were identified by GC-MS and GC × GC-TOFMS, among which 37 volatile compounds were concurrently detected by both methods. Spreading and fixation stages were deemed as pivotal processes for shaping the volatile profiles in FSGT. Notably, linalool, heptanal, 2-pentylfuran, nonanal, ß-myrcene, hexanal, 2-heptanone, pentanal, 1-octen-3-ol, and 1-octanol were highlighted as primary contributors to the aroma profiles of FSGT by combining odor activity value assessment. Furthermore, lipid degradation and glycoside hydrolysis were the main pathways for aroma formation of FSGT. The results not only elucidate the intricate variations in volatile metabolites but also offer valuable insights into enhancing the processing techniques for improved aroma quality of green tea.

Screening Disinfection Byproducts in Arid-Coastal Wastewater: A Workflow Using GC×GC-TOFMS, Passive Sampling, and NMF Deconvolution Algorithm.

Disinfection during tertiary municipal wastewater treatment is a necessary step to control the spread of pathogens; unfortunately, it also gives rise to numerous disinfection byproducts (DBPs), only a few of which are regulated because of the analytical challenges associated with the vast number of potential DBPs. This study utilized polydimethylsiloxane (PDMS) passive samplers, comprehensive two-dimensional gas chromatography (GC×GC) coupled with time-of-flight mass spectrometry (TOFMS), and non-negative matrix factorization (NMF) spectral deconvolution for suspect screening of DBPs in treated wastewater. PDMS samplers were deployed upstream and downstream of the chlorination unit in a municipal wastewater treatment plant located in Abu Dhabi, and their extracts were analyzed using GC×GC-TOFMS. A workflow incorporating a multi-tiered, eight-filter screening process was developed, which successfully enabled the reliable isolation of 22 candidate DBPs from thousands of peaks. The NMF spectral deconvolution improved the match factor score of unknown mass spectra to the reference mass spectra available in the NIST library by 17% and facilitated the identification of seven additional DBPs. The close match of the first-dimension retention index data and the GC×GC elution patterns of DBPs, both predicted using the Abraham solvation model, with their respective experimental counterparts-with the measured data available in the NIST WebBook and the GC×GC elution patterns being those observed for the candidate peaks-significantly enhanced the accuracy of peak assignment. Isotopic pattern analysis revealed a close correspondence for 11 DBPs with clearly visible isotopologues in reference spectra, thereby further strengthening the confidence in the peak assignment of these DBPs. Brominated analogues were prevalent among the detected DBPs, possibly due to seawater intrusion. The fate, behavior, persistence, and toxicity of tentatively identified DBPs were assessed using EPI Suite™ and the CompTox Chemicals Dashboard. This revealed their significant toxicity to aquatic organisms, including developmental, mutagenic, and endocrine-disrupting effects in certain DBPs. Some DBPs also showed activity in various CompTox bioassays, implicating them in adverse molecular pathways. Additionally, 11 DBPs demonstrated high environmental persistence and resistance to biodegradation. This combined approach offers a powerful tool for future research and environmental monitoring, enabling accurate identification and assessment of DBPs and their potential risks.

Comprehensive Two-Dimensional Gas Chromatography-Mass Spectrometry as a Tool for the Untargeted Study of Hop and Their Metabolites.

Since hop secondary metabolites have a direct correlation with the quality of beer and other hop-based beverages, and the volatile fraction of hop has a complex composition, requiring effective separation, here we explore the application of headspace solid-phase microextraction as a sample preparation method, coupled with comprehensive two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) analysis. The methodology involved the use of a DVB/PDMS fibre with 500 mg of hop cone powder, extracted for 40 min at 50 °C, for both GC-MS and GC×GC-MS. The varieties Azacca, Cascade, Enigma, Loral, and Zappa were studied comprehensively. The results demonstrate that GC×GC-MS increases the number of peaks by over 300% compared to classical GC-MS. Overall, 137 compounds were identified or tentatively identified and categorised into 10 classes, representing between 87.6% and 96.9% of the total peak area. The composition revealed the highest concentration of sesquiterpene hydrocarbons for Enigma, whilst Zappa showed a relatively significant concentration of monoterpene hydrocarbons. Principal component analysis for all compounds and classes, along with hierarchical cluster analysis, indicated similarities between Zappa and Cascade, and Azacca and Loral. In conclusion, this method presents an optimistic advancement in hop metabolite studies with a simple and established sample preparation procedure in combination with an effective separation technique.