Thermal Desorption-gas Chromatography-mass Spectrometry Research Articles

An alternative approach for compliance testing of food and skin contact silicone elastomers by specific determination of volatile cyclic siloxane oligomers via GC-FID

To date, silicone elastomers intended for food and skin contact are considered compliant as long as their weight loss during a thermal treatment (200 °C, 4 h) is below 0.5 wt.%. The common assumption is that this weight loss is caused almost entirely by potentially harmful volatile siloxane oligomers. The present study questions this assumption, first time balancing the initial content and the thermal removal of volatile siloxanes in 48 silicone materials. A GC-FID method for a specific determination of linear (L4 up to L24) and cyclic siloxane oligomers (D4 up to D25) was developed and validated against 1H-NMR and thermal desorption GC-MS analysis. All samples contained significant amounts of cyclic siloxanes, while linear trimethylsiloxy terminated oligomers were not detected. Only a weak correlation between the weight loss after thermal treatment and the initial content of cyclic siloxanes was determined for most samples. However, rapid adsorption of humidity from ambient air and its incomplete removal during sample conditioning were determined as crucial aspects in conventional gravimetric compliance testing for silicone articles. Consequently, the specific determination of volatile cyclic siloxane profiles via GC-FID is suggested as the more reliable approach for a compliance decision.

Breath Analysis: Identification of Potential Volatile Biomarkers for Non-Invasive Diagnosis of Chronic Kidney Disease (CKD).

Recently, volatile organic compound (VOC) determination in exhaled breath has seen growing interest due to its promising potential in early diagnosis of several pathological conditions, including chronic kidney disease (CKD). Therefore, this study aimed to identify the breath VOC pattern providing an accurate, reproducible and fast CKD diagnosis at early stages of disease. A cross-sectional observational study was carried out, enrolling a total of 30 subjects matched for age and gender. More specifically, the breath samples were collected from (a) 10 patients with end-stage kidney disease (ESKD) before undergoing hemodialysis treatment (DIAL); (b) 10 patients with mild-moderate CKD (G) including 3 patients in stage G2 with mild albuminuria, and 7 patients in stage G3 and (c) 10 healthy controls (CTRL). For each volunteer, an end-tidal exhaled breath sample and an ambient air sample (AA) were collected at the same time on two sorbent tubes by an automated sampling system and analyzed by Thermal Desorption-Gas Chromatography-Mass Spectrometry. A total of 110 VOCs were detected in breath samples but only 42 showed significatively different levels with respect to AA. Nonparametric tests, such as Wilcoxon/Kruskal-Wallis tests, allowed us to identify the most weighting variables able to discriminate between AA, DIAL, G and CTRL breath samples. A promising multivariate data mining approach incorporating only selected variables (showing p-values lower than 0.05), such as nonanal, pentane, acetophenone, pentanone, undecane, butanedione, ethyl hexanol and benzene, was developed and cross-validated, providing a prediction accuracy equal to 87% and 100% in identifying patients with both mild-moderate CKD (G) and ESKD (DIAL), respectively.

Effects of Wildfire Smoke on Volatile Organic Compound (VOC) and PM2.5 Composition in a United States Intermountain Western Valley and Estimation of Human Health Risk

With a warmer and drier climate, there has been an increase in wildfire events in the Northwest US, posing a potential health risk to downwind communities. The Lewis–Clark Valley (LCV), a small metropolitan area on the Washington/Idaho border in the United States Intermountain West region, was studied over the time period of 2017–2018. The main objective was to determine the community’s exposure to particulate matter (PM2.5) and volatile organic compounds (VOCs) during wildfire smoke events and to estimate the associated health risk. VOCs were analyzed previously in the LCV using sorbent tube sampling and thermal-desorption gas-chromatography mass-spectrometry (TD-GC-MS) during several local smoke events in the 2017–2018 fire seasons. PM2.5 measurements were obtained from nearby agency monitors. PM2.5 reached up to 200 µg/m3 in 2017 and over 100 µg/m3 in 2018 in the LCV, and has been observed to be increasing at a rate of 0.10 µg m−3/yr over the past two decades. Benzene, a carcinogen and air toxic, was measured with concentrations up to 11 µg/m3, over ten times the normal level in some instances, in the LCV. The health risk in the LCV from benzene was calculated at seven extra cancers per million for lifetime exposure and thirteen extra cancers per million considering all air toxics measured. The other cities monitored showed similar lifetime cancer risk, due to benzene of about 6–7 extra cancers per million. This work is important, as it measures ground-level exposures of VOCs and demonstrates decreases in PM2.5 air quality over time in the region.

Exploring exhaled breath volatile organic compounds in occupational asthma: a pilot cross-sectional study

Occupational asthma (OA) is divided into allergic asthma (AA) and irritant-induced asthma (IIA). IIA can be divided further into three different phenotypic subtypes. Volatile organic compounds (VOCs) in exhaled breath can reflect metabolic changes in the body, and a wide range of them have been associated with various diseases in the last two decades. This is the first known study to explore breath VOCs in subjects with OA, aimed to identify potential biomarkers to distinguish OA from healthy controls, as well as between different OA subgroups. In a cross-sectional investigation, exhaled breath from 40 patients with OA and 45 respiratory healthy healthcare workers were collected with ReCIVA® Breath Sampler. Samples were analyzed through an untargeted approach using thermal desorption-gas chromatography mass spectrometry (TD-GC-MS), and VOCs were identified according to tier classification. The data underwent analysis using both non-parametric and parametric statistical methods. 536 VOCs were identified. Significance (p<0.05) was observed in several emitted VOCs. Among these, compounds such as 1-hexadecanol, 2,3-butanediol, xylene, phenol, acetone, 3-methylhexane, methylcyclohexane, and isoprene have biological implications or are associated with exposures linked to OA. These VOCs may reflect metabolic changes in the body and the microbiome, as well as external exposures due to occupation.&#xD;In particular, 1-hexadecanol, 2,3-butanediol, xylene and phenol are associated with reduced nicotinamide adenine dinucleotide (NADH) and production of reactive oxygen species (ROS), mechanisms that can be linked to asthmatic diseases and therefore suggests its potential as biomarkers. This study demonstrates that VOCs detected in exhaled breath could serve as indicators of occupational exposure and enhance diagnostic accuracy for asthma.&#xD.

Analysis of forensic polymer samples using double shot pyrolysis gas chromatography – Mass spectrometry

Polymers are present in many different products, such as paints, plastics, and rubbers, which are routinely encountered in forensic casework. Comparison of such samples involves an initial visual examination followed by comparison of the chemical compositions of the exhibits. Techniques such as Fourier transform infrared spectroscopy (FTIR) and pyrolysis gas chromatography – mass spectrometry (PyGC-MS) have been reported for determining the chemical compositions of polymers in forensic samples. Double-shot pyrolysis gas chromatography – mass spectrometry (DS-PyGC-MS) is an extension of single-shot pyrolysis gas chromatography – mass spectrometry (SS-PyGC-MS) which is the current PyGC-MS method used in most forensic laboratories. DS-PyGC-MS involves a preliminary thermal desorption GC-MS step, followed by the pyrolysis GC-MS step, with this second step being analogous to SS-PyGC-MS. The pyrolyser furnace operates at a lower temperature during the thermal desorption step, allowing low volatility compounds, such as additives, to be thermally desorbed and detected, minimising interference from the polymeric component of the sample. This pilot study analysed four different polymeric substrates, commonly encountered in forensic casework, by DS-PyGC-MS. The substrates chosen were tyre rubber, road cones, cling film, and shotgun wads. The aim was to investigate whether more chemical information was generated by DS-PyGC-MS compared to SS-PyGC-MS, potentially providing increased discrimination of such samples. Qualitative results showed that tyre rubber and road cones were ideal substrates for DS-PyGC-MS. A wide range of additives were detected in these samples in the thermal desorption step, which were not detected using SS-PyGC-MS. All of the rubber tyres (n=5) and road cones (n=6) were able to be uniquely distinguished using DS-PyGC-MS. Some additional compounds were detected in the thermal desorption analysis of shotgun wads (n=4), providing increased discrimination compared to SS-PyGC-MS. For the cling film samples analysed (n=7) the polyethylene-based cling films (n=6) could not be distinguished from each other, with no compounds detected in the thermal desorption step. The other cling film sample contained a mixture of polylactic acid (PLA) and polybutylene adipate terephthalate (PBAT) and could easily be distinguished from the polyethylene-based cling films using either SS- or DS-PyGC-MS, or other common analytical methods such as Fourier transform infrared spectroscopy (FTIR). This pilot study has demonstrated that DS-PyGC-MS has the potential to provide more comprehensive chemical composition information for some polymeric substrates and is a promising method for the forensic comparison of polymer evidence.

Volatile organic compound detection of Buruli ulcer disease: Headspace analysis of Mycobacterium ulcerans and used gauzes of Buruli-compatible ulcers.

Diagnosing Buruli ulcer (BU) is complicated by limited access to the sensitive IS2404 qPCR. Experienced clinicians report a distinct odour of Buruli ulcers. We explored the potential of headspace analysis by thermal desorption-gas chromatography-mass spectrometry to detect volatile organic compounds (VOCs) from Mycobacterium ulcerans both in vitro and clinically. This study was conducted in two phases: a discovery and validation phase. During the discovery phase, VOCs that enable identification of M. ulcerans cultures were determined. During the validation phase, these VOCs were evaluated in clinical samples for which we used gauzes from patients with skin ulcerations in the Democratic Republic of Congo. Seven M. ulcerans headspace samples were compared with four from sterile growth medium and laboratory environmental air. The univariate analysis resulted in the selection of 24 retained VOC fragments and a perfect differentiation between cultures and controls. Sixteen of 24 fragments were identified, resulting in eleven unique compounds, mainly alkanes. Methylcyclohexane was the best performing compound. Based on these 24 fragments, headspace samples originating from gauzes of 50 open skin lesions (12 qPCR positive and 38 negative) were analysed and an AUC of 0.740 (95%-CI 0.583-0.897) was obtained. As this is an experimental study, future research has to confirm whether the identified compounds can serve as novel biomarkers.

Analysis of PFAS and further VOC from fluoropolymer-coated cookware by thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS)

Per- and polyfluoroalkyl substances (PFAS) are used in the production of PTFE based coatings for cookware. In this study, emission of PFAS and further volatile organic compounds (VOC) from kitchenware articles were investigated. First, method development for thermal extraction of baking trays, frying pans and baking mats at 250 °C was done by testing three different extraction devices. A thermal desorption oven showed the best blank and highest recoveries of PFAS analytes (70–101% for 12 perfluorocarboxylic acids (PFCAs), 2 fluorotelomer alcohls (FTOHs), 3 per- and polyfluoroether carboxylic acids (PFECAs), 1 polyfluoroether (PFE)). Second, 18 cookware samples, a PTFE micro powder and 2 lab made coating strips have been investigated. No PFAS were detected in 12 samples (limits of detection: 1–13 ng/dm2). PFCAs (C5–C23) were detected in a baking tray in amounts up to 34 ng/dm2. A baking mat contained 3 ng/dm2 PFOA. FTOHs were not detected in the samples. A PFECA (bC7O2) and its hydride (bC6O2H PFE) were detected in one coating intended for use in frying pans. The hydrides of the PFECA mixture, b(C3O1)nC3 PFECA (Krytox 157FSH), were detected in five baking trays. The PFAS target analytes were not detectable in the five investigated frying pans. Analysing further VOC in the emissions of coatings, 175 compounds could be identified, including alkanes, alkenes, aromatic substances, esters, aldehydes, ketones, ethers, alcohols, carboxylic acids, siloxanes and sulphur, nitrogen, as well as chlorine containing compounds (< 10 µg/dm2). The identified substances cannot be connected to the basic coating polymer of the kitchenware articles, which were PTFE and PES. All samples have undergone a threefold thermal extraction. No substances could be detected in the second and third consecutive extraction, which means that a removal and no new formation of the investigated PFAS as well as the further VOC at 250 °C has occurred.

Attraction of Nicotiana benthamiana to Bemisia tabaci is related to a chemical signal in plant volatile, undecane.

The whitefly Bemisia tabaci is one of the world's foremost agricultural pests. Recently, we found that a wild relative of tobacco (Nicotiana benthamiana) demonstrates remarkable attractiveness and nearly 100% lethality towards whiteflies. Therefore, it can act as a dead-end trap crop for whitefly control in the field. However, the underlying mechanism of the significant attractiveness of N. benthamiana towards whiteflies is unclear. Binary-choice assays and olfactory experiments showed that compared to common tobacco (N. tabacum), the volatile of N. benthamiana has a greater attraction to whiteflies. Then we analyzed and compared volatiles from these two Nicotiana species by thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). We identified 16 chemical compounds that are more abundant in N. benthamiana than in N. tabacum. Seven compounds were further tested with olfactometer assays and we found that, among them, undecane strongly attracted whiteflies. Further experiments revealed that even 0.005 μg mL-1 undecane is attractive to whiteflies. We also silenced the genes that may influence the biosynthesis of undecane and found the production of undecane decreased after silencing NbCER3, and that N. benthamiana plants with less undecane lost their attraction to whiteflies. In addition, we found that applying 0.005 μg mL-1 undecane on yellow sticky traps can increase the number of stuck insects on the traps by ≈40%. Undecane from the volatile of N. benthamiana is a critical chemical signal that attracts whiteflies and NbCER3 involved in the biosynthesis of undecane. Undecane may be used to improve the efficiency of yellow sticky traps for whitefly control. © 2024 Society of Chemical Industry.

Green Analytical Method for Perfluorocarboxylic Acids (PFCAs) in Water of Stir Bar Sorptive Extraction Coupled with Thermal Desorption–Gas Chromatography—Mass Spectroscopy

Perfluoroalkyl carboxylic acids (PFCAs) are a significant group of per- and polyfluoroalkyl substances (PFASs). They are persistent organic chemicals manufactured for their resistance to heat, water, and stains. PFCAs are ubiquitous in the environment, particularly in surface water and wastewater, because they are widely used in everyday consumer products. This contamination poses a risk to drinking water supplies and human health, necessitating sensitive and effective analytical methods. Traditional liquid chromatography–tandem mass spectrometry (LC-MS/MS) is commonly used but involves complex sample handling and high costs. In this study, we developed an enhanced stir bar sorptive extraction (SBSE) method coupled with thermal desorption–gas chromatography–mass spectrometry (TD-GC-MS) for the analysis of PFCAs in water. This method demonstrates linearity, with R2 values from 0.9892 to 0.9988, and low limits of detection (LOD) between 21.17 ng/L and 73.96 ng/L. Recovery rates varied from 47 to 97%, suggesting efficient extraction. Compared to traditional methods, the developed SBSE technique requires only a 1 mL sample volume and minimal amounts of solvents, enhancing eco-friendliness and reducing potential contamination and handling errors. This method also demonstrated good precision and robustness across various water matrices. Overall, the developed method offers a precise, eco-friendly, and reliable approach for analyzing PFCAs in diverse water samples.

Selective recovery of manganese from spent ternary lithium-ion batteries for efficient catalytic oxidation of VOCs: Unveiling the mechanism of activity Enhancement in recycled catalysts

With the widespread application of ternary lithium-ion batteries (TLBs) in various fields, the disposal of spent TLBs has become a globally recognized issue. This study proposes a novel method for reutilizing metal resources from TLBs. Through selective oxidation, manganese in a leaching solution of TLBs was converted into MnO2 with α, γ, and δ crystal phases (referred to as T-MnO2) for catalytic oxidation of volatile organic compounds (VOCs), while efficiently separating manganese from high-value metals such as nickel, cobalt, and lithium, achieving a manganese recovery rate of 99.99%. Compared to similar MnO2 prepared from pure materials, T-MnO2 exhibited superior degradation performance for toluene and chlorobenzene, with T90 decreasing by around 30 °C. The acidic synthesis environment provided by the leaching solution and the doping of trace metals altered the physicochemical properties of T-MnO2, such as increased specific surface area, elevated surface manganese valence, and improved redox performance and oxygen vacancy properties, enhancing its catalytic oxidation capacity. Furthermore, the degradation pathway of toluene on T-γ-MnO2 was inferred using thermal desorption-gas chromatography/mass spectrometry (TD-GC/MS) and in-situ DRIFTs. This study provides a novel approach for recycling spent TLBs and treating VOCs catalytically.

Depth dimension in seepage detection: Insights for exploration and geological gas storage surveillance

The search for surface hydrocarbon seeps has historically served as a fundamental tool in the early stages of oil and gas exploration. However, as easily detectable surface hydrocarbon seeps become increasingly scarce, advancement in analytical capabilities have shifted the focus towards detecting ultra-trace levels of hydrocarbons, commonly referred to as microseepages. While it is critical to understand the distribution of hydrocarbon microseepage for assessing petroleum systems and optimizing exploration efforts, the role of sampling depth in the detection of microseepage remains poorly understood. In this study, we investigated the influence of sampling depth on microseepage detection, using passive soil-gas sampling techniques at depths ranging from 0.5 to 10 m at sites with hydrocarbon-bearing reservoirs and dry wells. Organic geochemical analysis, including thermal desorption-gas chromatography-mass spectrometry (GC-MS), was employed to identify and quantify hydrocarbon and nonhydrocarbon compounds.The study result demonstrates that sampling at the Minimal Interference Zone (MIZ) depths of 5 m or greater significantly mitigates the risk of interference signals, thereby enabling the identification and quantification of hydrocarbon microseepages at trace and ultra-trace concentrations. At these depths, the attenuation of non-hydrocarbon compounds was observed, making the hydrocarbon signal markedly more distinguishable. Geochemical characterization of the samples revealed spatial and vertical heterogeneity in the distribution of hydrocarbon compounds, indicative of variations in the microseepage mechanisms potentially influenced by factors such as sedimentary basin settings and secondary alterations associated with the vadose zone. By utilizing passive soil-gas sampling techniques coupled with GC-MS, this study emphasizes the importance of sampling depth to improve the detection of reliable microseepage signal while reducing interference and background noise. The proposed technique not only refines existing methodologies for petroleum system assessments but also paves the way for broader geological applications. Specifically, the approach offers critical insights for the development of high-resolution geochemical surveys adaptable for surface background profiling in CO2 sequestration projects to monitor for storage efficiency and seal integrity.

Emission characteristics of volatile organic compounds from consumer spray products based on product type, spray method, and distance

Consumer spray products (CSPs) are widely used in daily life, yet it is challenging to find products that fully disclose all components posing health risks. Existing studies primarily focus on product components or VOC quantities emitted during use. Therefore, this study aimed to measure the VOC concentrations emitted by CSPs at varying distances. 47 CSPs available in the Korean market were selected, spanning three spray groups: antiseptics/insecticides (11), aromatic deodorants (16), and coating/polishing agents (20). VOC in air samples were collected using Tenax TA tube at a distance of 1 and 3 m from the sprayed CSPs and then analyzed by thermal desorption–gas chromatography–mass spectrometry system. Discrepancies were found between labeled and actual product components. Aromatic deodorants exhibited the highest total VOCs (TVOCs), while antiseptic/insecticide sprays exhibited the lowest. In the antiseptic/insecticide group and coating/polishing agent group, benzene as a propellant had a maximum concentration (30.9 ± 25.6 ppb), and as trigger, its concentration was 33.7 ± 30.7 ppb. Quantitative analysis using advanced analytical instruments only explained 26.1 ± 20.4% of toluene-equivalent TVOCs, suggesting the presence of additional substances. Concentrations varied by distance due to substance volatility and usage. Maintaining a distance of at least 1 m from CSPs is recommended.

Thermal desorption – gas chromatography – mass spectrometry (TD-GC-MS) analysis of PFAS used in food contact materials

Per- and polyfluoroalkyl substances (PFAS) are used in food contact materials (FCMs), e.g. as production aids in the fabrication of PTFE based coatings for kitchenware or as additives in paper and board. Growing concerns about the environment and health related to PFAS have led to an increasing interest in monitoring PFAS levels in FCMs as well as their migration into food. In this study, method development for the analysis of PFAS by thermal desorption – gas chromatography – mass spectrometry (TD-GC-MS) was done. In addition to fluorotelomer alcohols (FTOHs), which are the only PFAS commonly analysed by GC-MS, it was proven that perfluorocarboxylic acids (PFCAs) and per- and polyfluoroether carboxylic acids (PFECAs) as well as their thermolysis products, perfluoroethers (PFEs) and perfluoroalkenes, can be analysed by GC-MS without prior derivatization. Screening for PFCAs and FTOHs was possible by electron impact ionization (EI) using group specific SIM fragments. Confirmation of identity has been done by EI scans as well as chemical ionization (CI) SIM measurements. LODs (limits of detection) of PFCAs, FTOHs and PFECAs in the TD-GC-MS instrument were in the low pg range. Thermal degradation of PFCAs and PFECAs during TD-GC-MS measurement was investigated.

Profiling of Organosulfur Compounds in Onions: A Comparative Study between LC-HRMS and DTD-GC-MS

Onions are known not only for their culinary importance but also for their nutritional and health-promoting properties. Both properties are closely linked to their content of organosulfur compounds, which account for up to 5% of the dry weight of an onion. Given the importance of these compounds, suitable analytical methods are required for their study. Two techniques should be highlighted in this context: gas chromatography coupled to mass spectrometry (GC-MS), and liquid chromatography coupled to mass spectrometry (LC-MS). In this study, eight different onion varieties were analyzed using two distinct analytical techniques: direct thermal desorption–gas chromatography–mass spectrometry (DTD-GC-MS) and high-resolution mass spectrometry (HRMS) on an LC-ESI-QqTOF instrument. Each method identified different organosulfur compounds, with LC-HRMS targeting 15 non-volatile compounds, such as cysteine sulfoxides, and GC-MS targeting 18 volatiles, such as disulfides and trisulfides. The results obtained were studied using Pearson correlations and principal component analysis. No precise correlation was found between the initial organosulfur compounds in onions and their hydrolysates. Consequently, although GC is one of the most employed techniques in the scientific literature, the use of LC-HRMS or a combination of both techniques may offer a more comprehensive and accurate description of the metabolomic profile of onions.

Volatile Organic Compounds on Rhodes Island, Greece: Implications for Outdoor and Indoor Human Exposure.

Volatile organic compounds (VOC) are considered a class of pollutants with a significant presence in indoor and outdoor air and serious health effects. The aim of this study was to measure and evaluate the levels of outdoor and indoor VOCs at selected sites on Rhodes Island, Greece, during the cold and warm periods of 2023. Spatial and seasonal variations were evaluated; moreover, cancer and non-cancer inhalation risks were assessed. For this purpose, simultaneous indoor-outdoor air sampling was carried out on the island of Rhodes. VOCs were determined by Thermal Desorption-Gas Chromatography/Mass Spectroscopy (TD-GC/MS). Fifty-six VOCs with frequencies ≥ 50% were further considered. VOC concentrations (∑56VOCs) at all sites were found to be higher in the warm period. In the warm and cold sampling periods, the highest concentrations were found at the port of Rhodes City, while total VOC concentrations were dominated by alkanes. The Positive Matrix Factorization (PMF) model was applied to identify the VOC emission sources. Non-cancer and cancer risks for adults were within the safe levels.

Unveiling Small-Sized Plastic Particles Hidden behind Large-Sized Ones in Human Excretion and Their Potential Sources.

Health risks of microplastic exposure have drawn growing global concerns due to the widespread distribution of microplastics in the environment. However, more evidence is needed to understand the exposure characteristics of microplastics owing to the limitation of current spectrum technologies, especially the missing information on small-sized particles. In the present study, laser direct infrared spectroscopy and thermal desorption-gas chromatography-mass spectrometry combined pyrolysis using a tubular furnace (TD-GC/MS) were employed to comprehensively detect the presence of plastic particles down to 0.22 μm in human excreted samples. The results showed that polyethylene (PE), polyvinyl chloride, PE terephthalate (PET), and polypropylene dominated large-sized (>20 μm) and small-sized plastic plastics (0.22-20 μm) in feces and urine. Moreover, fragments accounted for 60.71 and 60.37% in feces and urine, respectively, representing the most pervasive shape in excretion. Surprisingly, the concentration of small-sized particles was significantly higher than that of large-sized microplastics, accounting for 56.54 and 50.07% in feces (345.58 μg/g) and urine (6.49 μg/mL). Significant positive correlations were observed between the level of plastic particles in feces and the use of plastic containers and the consumption of aquatic products (Spearman correlation analysis, p < 0.01), suggesting the potential sources for plastic particles in humans. Furthermore, it is estimated that feces was the primary excretory pathway, consisting of 94.0% of total excreted microplastics daily. This study provides novel evidence regarding small-sized plastic particles, which are predominant fractions in human excretion, increasing the knowledge of the potential hazards of omnipresent microplastics to human exposure.

Chemical characterization of volatile organic compounds emitted by animal manure

Animal manure is considered a valuable organic fertilizer due to its important nutrient content enhancing soil fertility and plant growth in agriculture. Besides its beneficial role as fertilizer, animal manure represents a significant source of volatile organic compounds (VOCs), playing a significant role in atmospheric chemistry. Understanding the composition of VOCs Understanding VOCs from animal manure is crucial for assessing their environmental impact, as they can cause air pollution, odors, and harm to human health and ecosystems. Laboratory studies enhance field measurements by providing a precise inventory of manure emissions, addressing gaps in existing literature. Both approaches complement each other in advancing our understanding of manure emissions. In this context, we conducted an experimental study involving various animal manures (cow, horse, sheep, and goat) taken from a farm in Grignon (near Paris, France). We employed atmospheric simulation chambers within a controlled laboratory environment. The analysis of VOCs involved the combination of Proton Transfer Reaction-Quadrupole ion guide-Time-of-Flight Mass Spectrometry (PTR-QiTOF-MS) and Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS). Using PTR-QiTOF-MS, 368 compounds were detected and quantified within the manure samples. The complementary analysis by TD-GC-MS enhanced our identification of VOCs. Our findings revealed various chemical groups of VOCs, including oxygenated compounds (e.g., ethanol, cresol, acetaldehyde, etc.), nitrogenated compounds (ammonia, trimethylamine, etc.), sulfur compounds (methanethiol, dimethyl sulfide, etc.), aromatic compounds (phenols and indoles), terpenes (isoprene, D-limonene, etc.) and halogenated compounds. Cow manure exhibited the highest VOC emission fluxes, followed by goat, sheep, and horse manures. Notably, oxygenated VOCs were dominant contributors to total VOC emission fluxes in all samples. Statistical analysis highlighted the distinct nature of cow manure emissions, characterized by oxygenated compounds and nitrogenated compounds. In addition, goat manure was isolated from the other samples with high emissions of compounds having both oxygen and nitrogen atoms in their molecular formulas (e.g., CH3NO2). The experimental dataset obtained in this study provides an inventory reference for both VOCs and their emission fluxes in animal manures. Furthermore, it highlights odorant compounds and VOCs that serve as atmospheric aerosol precursor. Future studies can explore the effectiveness of various manure treatment methods to promote sustainable agriculture practices.

Discovery and Validation of a Volatile Signature of Eosinophilic Airway Inflammation in Asthma.

Volatile organic compounds (VOCs) in asthmatic breath may be associated with sputum eosinophilia. We developed a volatile biomarker-signature to predict sputum eosinophilia in asthma. VOCs emitted into the space above sputum samples (headspace) from severe asthmatics (n=36) were collected onto sorbent tubes and analysed using thermal desorption gas chromatography-mass spectrometry (TD-GC-MS). Elastic net regression identified stable VOCs associated with sputum eosinophilia ≥3% and generated a volatile biomarker signature. This VOC signature was validated in breath samples from: (I) acute asthmatics according to blood eosinophilia ≥0.3x109cells/L or sputum eosinophilia of ≥ 3% in the UK EMBER consortium (n=65) and U-BIOPRED-IMI consortium (n=42). Breath samples were collected onto sorbent tubes (EMBER) or Tedlar bags (U-BIOPRED) and analysed by gas-chromatography-mass spectrometry (GC×GC-MS -EMBER or GC-MS -U-BIOPRED). The in vitro headspace identified 19 VOCs associated with sputum eosinophilia and the derived VOC signature yielded good diagnostic accuracy for sputum eosinophilia ≥ 3% in headspace (AUROC (95% CI) 0.90(0.80-0.99), p<0.0001), correlated inversely with sputum eosinophil % (rs= -0.71, p<0.0001) and outperformed FeNO (AUROC (95% CI) 0.61(0.35-0.86). Analysis of exhaled breath in replication cohorts yielded a VOC signature AUROC (95% CI) for acute asthma exacerbations of 0.89(0.76-1.0) (EMBER cohort) with sputum eosinophilia and 0.90(0.75-1.0) in U-BIOPRED - again outperforming FeNO in U-BIOPRED 0.62 (0.33-0.90). We have discovered and provided early-stage clinical validation of a volatile biomarker signature associated with eosinophilic airway inflammation. Further work is needed to translate our discovery using point of care clinical sensors.

Characterization of the SPIRITAS: A Disposable Sampling Setup for Volatile Organic Compound Collection and Analysis

Analyzing exhaled breath for volatile organic compounds (VOCs) using thermal desorption–gas chromatography–mass spectrometry (TD-GC-MS) offers a non-invasive diagnostic approach for various diseases. Despite its promise, the method faces challenges like sampling heterogeneity and high costs. Following the European Respiratory Society’s advocacy for methodological standardization, we developed the SPIRITAS (Standardized Product for Inexpensive Respiratory InvesTigation: A breath Sampler), a low-cost, disposable breath sampler. This study evaluates the SPIRITAS’s effectiveness in detecting targeted VOCs. We tested the SPIRITAS using the Peppermint Experiment, a standardized protocol that allows for comparison between different breath sampling and analytical practices by assessing the ability to detect five peppermint-specific VOCs after ingestion of a 200-milligram peppermint oil capsule. We included ten subjects and performed six breath samples per participant, including a baseline measurement taken before ingestion. We used the Wilcoxon signed-rank test to evaluate whether baseline values were significantly lower than the peak values of the targeted VOCs. Additionally, we conducted an experiment utilizing humidified medical-grade air to identify any VOCs attributable to the SPIRITAS setup itself. Results showed successful detection of four out of five targeted “peppermint-associated” VOCs: alpha-pinene (p ≤ 0.01), beta-pinene (p ≤ 0.01), menthone (p = 0.01), and menthol (p = 0.02), indicating significant differences between the baseline and peak values in the volunteers’ breath. However, detection of eucalyptol was inconsistent. In addition, we identified 16 VOCs that were released by the SPIRITAS, one of which remains unidentified. Our findings underscore the SPIRITAS’s potential for clinical applications, paving the way for broader biomarker research. The combination of ease of use, low cost, reduced risk of contamination, and standardization makes SPIRITAS very suitable for large-scale international studies. Furthermore, we have demonstrated the SPIRITAS’s effectiveness in detecting specific VOCs and identified 16 compounds originating from the SPIRITAS, ensuring that these compounds would not be mis-qualified as potential biomarkers in future clinical studies.

VOC data-driven evaluation of vehicle cabin odor: from ANN to CNN-BiLSTM.

Emissions of volatile organic compounds (VOCs) in vehicles represent a significant problem, causing unpleasant odors. To mitigate VOCs and odors in vehicles, it is critical to choose interior parts with low odor and VOC emissions. However, prevailing odor evaluation methods are subjective, costly, and potentially harmful to the health of evaluators. In this study, we analyzed 139 automotive interior parts and 92 vehicles, establishing a cost-effective, data-driven method for odor evaluation. The contents of benzene, toluene, ethylbenzene, xylene, styrene, formaldehyde, acetaldehyde, acrolein, and total volatile organic compounds (TVOC) were detected by thermal desorption gas chromatography-mass spectrometry (TD-GC/MS) and high-performance liquid chromatography with an ultraviolet detector (HPLC-UV). Professional odor evaluators assessed the odors, identifying intensity levels from 2.0 to 4.5 in interior parts and 2.5 to 3.5 in whole vehicles. Leveraging this data, we applied four supervised learning algorithms to develop predictive models for the odor intensity of both interior parts and entire vehicles. During model training, we implemented early stopping techniques for the artificial neural network (ANN) and convolutional neural network-bidirectional long short-term memory (CNN-BiLSTM) models, while optimizing the support vector machine (SVM) and extreme gradient boosting (XGBoost) models using the GridSearch algorithm. The evaluation results reveal that the CNN-BiLSTM model performs the best, achieving an average accuracy of 89% for unknown samples within an odor intensity level of 0.5. The root mean square error (RMSE) is 0.24, and the mean absolute error (MAE) is 0.08. The model also underwent a sevenfold cross-validation, achieving an accuracy of 83.43%. Additionally, we employed SHapley Additive exPlanations (SHAP) for the interpretative analysis of the model, which confirmed the consistency of each VOC's odor contribution with human olfactory rules. By predicting odors based on VOCs through supervised learning, this study reduces the costs and enhances the efficiency and applicability of odor assessment across various vehicle interiors.