Environmental and human health impacts of volatile organic compounds: A perspective review

Agri-food waste biosorbents for volatile organic compounds removal from air and industrial gases - A review

Approximately 1.3 billion metric tons of agricultural and food waste is produced annually, highlighting the need for appropriate processing and management strategies. This paper provides an exhaustive overview of the utilization of agri-food waste as a biosorbents for the elimination of volatile organic compounds (VOCs) from gaseous streams. The review paper underscores the critical role of waste management in the context of a circular economy, wherein waste is not viewed as a final product, but rather as a valuable resource for innovative processes. This perspective is consistent with the principles of resource efficiency and sustainability. Various types of waste have been described as effective biosorbents, and methods for biosorbents preparation have been discussed, including thermal treatment, surface activation, and doping with nitrogen, phosphorus, and sulfur atoms. This review further investigates the applications of these biosorbents in adsorbing VOCs from gaseous streams and elucidates the primary mechanisms governing the adsorption process. Additionally, this study sheds light on methods of biosorbents regeneration, which is a key aspect of practical applications. The paper concludes with a critical commentary and discussion of future perspectives in this field, emphasizing the need for more research and innovation in waste management to fully realize the potential of a circular economy. This review serves as a valuable resource for researchers and practitioners interested in the potential use of agri-food waste biosorbents for VOCs removal, marking a significant first step toward considering these aspects together.

Boosting the sensitivity of single photon ionization time-of-flight mass spectrometry using a segmented focus quadrupole-ion guide

Single photon ionization time-of-flight mass spectrometry (SPI-TOF-MS) is a powerful analytical technique for real-time detection of trace VOCs. However, efficient ion transmission within the ionization chamber has always been a challenging issue in SPI-TOF-MS. In this study, a novel ion guide termed the Segmented Focus Quadrupole Ion Guide (SFQ-IG) was introduced for SPI-TOF-MS. The SFQ-IG device consists of 12 printed circuit boards (PCB), each containing four quarter-ring electrodes with inner diameters progressively decreasing from 26 to 4 mm. The simulation results demonstrated that SFQ-IG exhibited superior ion transmission efficiency than both ion funnel (IF) field and direct current-only (DC-only) field. By integrating into a SPI-TOF-MS, this ion guide was optimized in terms of the ionization source pressure, direct current gradient, and radio frequency amplitude. Further comparative experiments demonstrated that the SPI-TOF-MS with the SFQ-IG exhibited higher sensitivity than both the IF field (1.3-7.4 times) and DC-only field (3.5-8.8 times) for the test VOCs. The improvements in limit of detection (LOD) with the SFQ-IG ranged from 1.6 to 5.3 times compared to the DC-only field for the test VOCs. Fabricated using PCB technology, the SFQ-IG is characterized by its cost-effectiveness, compact size, and high transmission efficiency, facilitating its integration into other mass spectrometers.

Combined association of urinary volatile organic compounds with chronic bronchitis and emphysema among adults in NHANES 2011-2014: The mediating role of inflammation

Evidence on the association of volatile organic compounds (VOCs) with chronic bronchitis (CB) and emphysema is spare and defective. To evaluate the relationship between urinary metabolites of VOCs (mVOCs) with CB and emphysema, and to identify the potential mVOC of paramount importance, data from NHANES 2011-2014 waves were utilized. Logistic regression was conducted to estimate the independent association of mVOCs with respiratory outcomes. Least absolute shrinkage and selection operator (LASSO) regression was performed to screen a parsimonious set of CB- and emphysema-relevant mVOCs that were used for further co-exposure analyses of weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR). Mediation analysis was employed to detect the mediating role of inflammatory makers in such associations. In single exposure analytic model, nine mVOCs were individually and positively associated with CB, while four mVOCs were with emphysema. In WQS regression, positive association between LASSO selected mVOCs and CB was identified (OR = 1.82, 95% CI: 1.25 to 2.69), and N-acetyl-S-(4-hydroxy-2-butenyl)-l-cysteine (MHBMA3) weighted the highest. Results from BKMR further validated such combined association and the significance of MHBMA3. As for emphysema, significantly positive overall trend of mVOCs was only observed in BKMR model and N-acetyl-S-(N-methylcarbamoyl)-l-cysteine (AMCC) contributed most to the mixed effect. White blood cell count (WBC) and lymphocyte number (LYM) were mediators in the positive pattern of mVOCs mixture with CB, while association between mVOCs mixture and emphysema was significantly mediated by LYM and segmented neutrophils num (NEO). This study demonstrated that exposure to VOCs was associated with CB and emphysema independently and combinedly, which might be partly speculated that VOCs were linked to activated inflammations. Our findings shed novel light on VOCs related respiratory illness, and provide a new basis for the contribution of certain VOCs to the risk of CB and emphysema, which has potential public health implications.

Characteristics and Source Apportionment of Volatile Organic Compounds in a Coastal Industrial Area: A Case Study in the Yangtze River Delta of China

In recent years, the coastal area in East China has experienced elevated volatile organic compounds (VOCs) levels during specific periods. VOCs have become one of the major atmospheric pollutants in these areas. In this study, 64 compounds including alkanes, alkenes, halohydrocarbons, aromatics, and oxygenated VOCs (OVOCs) were obtained by the TO-15 method through a 12-month campaign in industrial, urban and suburban areas in the Yangtze River Delta of China. The overall trends of total VOC (TVOC) concentrations at eight sampling sites were as follows: winter > autumn > spring > summer. The proportion of VOC categories was various at industrial sites, while OVOCs and halohydrocarbons had high proportions at urban sites and suburban sites, respectively. Coating, vehicle emission, petrochemical source, industrial source, and gasoline volatilization were identified as the major VOC emission sources by the positive matrix factorization model. Petrochemical and coating sources were the prime VOC sources at industrial sites. Aromatics contributed the most ozone formation potential at industrial sites, while OVOCs provided the main contributions at both urban and suburban sites during four seasons. According to the health risk assessment, a high probability of non-carcinogenic risk existed at three industrial sites. Special attention should be given to certain VOCs, such as acrolein and 1,2-dibromoethane in industrial areas.

The association between exposure to volatile organic chemicals and serum α-Klotho in USA middle to old aged population: A cross-sectional study from NHANES 2011-2016

BACKGROUND

Volatile Organic Compounds (VOCs) constitute an omnipresent category of environmental contaminants. Numerous studies have identified associations between various VOCs and human diseases. The anti-aging protein α-Klotho has been shown to exert protective influences across a variety of disease origins and progressions. This study aims to explore the relationship between serum α-Klotho levels and exposure to VOCs in humans.

METHODS

This analysis utilized data from 1672 participants aged from 40 to 79 years in 2011-2016 NHANES. Exposure to VOCs was assessed through measurements of urinary VOC metabolites (mVOCs), with 16 mVOCs selected for analysis. Multivariate generalized linear models (GLM), restricted cubic splines (RCS), weighted quantile sum (WQS) regression models, and Bayesian kernel machine regression (BKMR) models were employed to examine the connection between serum α-Klotho and individual mVOCs and mVOCs mixtures, as well as to identify the primary monomeric mVOCs responsible for these associations.

RESULTS

Our research revealed that 8 mVOCs exhibited inverse associations with serum α-Klotho levels in GLM and RCS models. Particularly noteworthy, N-Acetyl-S-(2-cyanoethyl)-L-cysteine (CYMA), a metabolite of acrylonitrile, emerged as the most influential mVOC in both WQS and BKMR models. Furthermore, the mVOCs mixture was found to be negatively correlated with serum α-Klotho. The detrimental effects of mVOCs on serum α-Klotho were observed to significantly diminish in individuals with elevated serum vitamin D levels.

CONCLUSION

Our study highlights a significant inverse relationship between serum α-Klotho and the mixture of mVOCs, indicating that exposure to VOCs may impact the molecular pathways of aging and related diseases by influencing α-Klotho concentrations. Remarkably, the attenuation of this association by high serum vitamin D levels implies potential therapeutic strategies. Our study underscores the importance of minimizing VOCs exposure to mitigate the adverse effects on α-Klotho. Further research is warranted to elucidate the underlying mechanisms of these relationships.

Association between volatile organic compounds exposure and periodontitis: A representative cross-sectional study

AIM

Periodontitis is one of the most common oral diseases and a major cause of tooth loss in adults. Environmental pollution is closely associated with the prevalence of periodontitis. However, few studies have focused on the association between volatile organic compounds (VOCs) and periodontitis. This cross-sectional study aims to examine whether exposure to VOCs is associated with periodontitis, based on data from the National Health and Nutrition Examination Survey (NHANES, 2011-2014).

MATERIALS AND METHODS

We analysed data on blood VOC levels, periodontitis and related covariates from 2772 participants of the NHANES. The association between the blood VOCs and periodontitis was analysed using weighted logistic regression analysis, the restricted cubic spline (RCS) model and the weighted quantile sum (WQS) regression model. Interaction tests and mediation analysis were also conducted.

RESULTS

After adjusting for covariates, for each natural constant-fold increase in 1,4-dichlorobenzene, the odds of having periodontitis increased by 16% (odds ratio = 1.16; 95% confidence interval: 1.08-1.24, p < .001). WQS regression model indicated that 1,4-dichlorobenzene contributed the most to the association between VOC co-exposure and periodontitis. Mediation analysis further revealed that total bilirubin levels mediated the association between 1,4-dichlorobenzene and the prevalence of periodontitis, accounting for 4.32%. In addition, the positive association between o-xylene and periodontitis was more pronounced in the <65-year-old group.

CONCLUSIONS

This study has provided relatively little evidence to demonstrate a specific link between VOCs and periodontitis. Nonetheless, exposure to VOCs remains a non-negligible public health concern, and further research is required to investigate the association and potential mechanisms of action between VOCs and periodontitis.

Data-driven, explainable machine learning model for predicting volatile organic compounds' standard vaporization enthalpy

The accurate prediction of standard vaporization enthalpy (ΔvapHm°) for volatile organic compounds (VOCs) is of paramount importance in environmental chemistry, industrial applications and regulatory compliance. To overcome traditional experimental methods for predicting ΔvapHm° of VOCs, machine learning (ML) models enable a high-throughput, cost-effective property estimation. But despite a rising momentum, existing ML algorithms still present limitations in prediction accuracy and broad chemical applications. In this work, we present a data driven, explainable supervised ML model to predict ΔvapHm° of VOCs. The model was built on an established experimental database of 2410 unique molecules and 223 VOCs categorized by chemical groups. Using supervised ML regression algorithms, the Random Forest successfully predicted VOCs' ΔvapHm° with a mean absolute error of 3.02 kJ mol-1 and a 95% test score. The model was successfully validated through the prediction of ΔvapHm° for a known database of VOCs and through molecular group hold-out tests. Through chemical feature importance analysis, this explainable model revealed that VOC polarizability, connectivity indexes and electrotopological state are key for the model's prediction accuracy. We thus present a replicable and explainable model, which can be further expanded towards the prediction of other thermodynamic properties of VOCs.

Emissions of volatile organic compounds from Chinese coal-fired power plants: Characteristics, source profile, inventories, and impacts

Volatile organic compounds (VOCs) are key precursors for secondary organic aerosols (SOA) and ozone, imposing severe impacts on human health and environment. Considering the massive coal consumption, coal fired power plants (CFPPs) in China are non-negligible VOCs contributors, whose emission characteristics remain inadequately understood. Here, we investigated emission characteristics of 117 VOCs by field tests in four typical CFPPs, and a latest localized CFPPs source profile was compiled by integrating literature reviews. Then speciated-VOCs emission inventories for 2018-2022 were established based on dynamic emission factors and unit-level activity data. The results suggested that oxygenated VOCs (OVOCs) constituted the dominant group (76.5 %), with propionaldehyde (32.0 %) and formaldehyde (24.5 %) being the predominant species. OVOCs (93.2 %) and aromatics (77.4 %) were identified as the primary contributors to ozone and SOA, respectively. Driven by both the rise in coal consumption and technological advancements, nationwide VOCs emissions decreased from 83,393 t in 2018 to 53,251 t in 2022. Regional disparities and varying rates of decline in provincial emissions were evident, with VOCs emissions predominantly concentrated in northern and eastern provinces. Neimenggu, Shandong, Shanxi, Jiangsu, and Guangdong were identified as the top five provinces with the highest emissions. We believe this study would be conducive to a more comprehensive understanding and effective control of VOCs emissions from CFPPs in China.

Association between Volatile Organic Compound Exposure and Sex Hormones in Adolescents: The Mediating Role of Serum Albumin

The associations between VOCs and sex hormones in adolescents remain unclear, and the role of serum albumin in these associations deserves to be explored. We conducted cross-sectional analyses using generalized linear models (GLMs), weighted quantile sum (WQS) regression, and mediation analysis, based on data from 584 adolescents from the National Health and Nutrition Examination Survey (NHANES). The GLM analyses revealed that seven kinds of mVOCs potentially affected sex hormone levels. According to the WQS regression results, 2-aminothiazoline-4-carboxylic acid (ATCA) was the major contributor to the significant associations of mixed mVOC exposure with testosterone, estradiol, and free androgen index in males; N-acetyl-S-(N-methylcarbamoyl)-L-cysteine (AMCC) was the major contributor to the significant associations of mixed mVOC exposure with sex hormone-binding globulin in males; and N-acetyl-S-(benzyl)-L-cysteine (BMA) was the major contributor to the significant associations of mixed mVOC exposure with the ratio of testosterone to estradiol in females. Moreover, serum albumin could mediate up to 9.2% of the associations between mixed exposure to mVOCs and sex hormones. Our findings could provide a reference for studies on the mechanisms underlying the effects of VOCs on sex hormones in adolescents and emphasize the necessity of reducing exposure to ATCA, AMCC, BMA, and their parent compounds.

Canine sentinels and our shared exposome

Dogs are distinctly positioned to be indicators of human health and well-being.

Using Hybrid PDI-Fe3O4 Nanoparticles for Capturing Aliphatic Alcohols: Halogen Bonding vs. Lone Pair-π Interactions

In this study, Fe3O4 nanoparticles (FeNPs) decorated with halogenated perylene diimides (PDIs) have been used for capturing VOCs (volatile organic compounds) through noncovalent binding. Concretely, we have used tetrachlorinated/brominated PDIs as well as a nonhalogenated PDI as a reference system. On the other hand, methanol, ethanol, propanol, and butanol were used as VOCs. Experimental studies along with theoretical calculations (the BP86-D3/def2-TZVPP level of theory) pointed to two possible and likely competitive binding modes (lone pair-π through the π-acidic surface of the PDI and a halogen bond via the σ-holes at the Cl/Br atoms). More in detail, thermal desorption (TD) experiments showed an increase in the VOC retention capacity upon increasing the length of the alkyl chain, suggesting a preference for the interaction with the PDI aromatic surface. In addition, the tetrachlorinated derivative showed larger VOC retention times compared to the tetrabrominated analog. These results were complemented by several state-of-the-art computational tools, such as the electrostatic surface potential analysis, the Quantum Theory of Atoms in Molecules (QTAIM), as well as the noncovalent interaction plot (NCIplot) visual index, which were helpful to rationalize the role of each interaction in the VOC···PDI recognition phenomena.

Exposure to volatile organic compounds and mortality in US adults: A population-based prospective cohort study

Volatile organic compounds (VOCs) are ubiquitous in both indoor and outdoor environments. Evidence on the associations of individual and joint VOC exposure with all-cause and cause-specific mortality is limited. Measurements of 15 urinary VOC metabolites were available to estimate exposure to 12 VOCs in the National Health and Nutritional Examination Survey (NHANES) 2005-2006 and 2011-2018. The environment risk score (ERS) was calculated using LASSO regression to reflect joint exposure to VOCs. Follow-up data on death were obtained from the NHANES Public-Use Linked Mortality File through December 31, 2019. Cox proportional hazard models and restricted cubic spline models were applied to evaluate the associations of individual and joint VOC exposures with all-cause and cause-specific mortality. Population attributable fractions were calculated to assess the death burden attributable to VOC exposure. During a median follow-up of 6.17 years, 734 (8.34 %) deaths occurred among 8799 adults. Urinary metabolites of acrolein, acrylonitrile, 1,3-butadiene, and ethylbenzene/styrene were significantly associated with all-cause, cardiovascular disease (CVD), respiratory disease (RD), and cancer mortality in a linear dose-response manner. Linear and robust dose-response relationships were also observed between ERS and all-cause and cause-specific mortality. Each 1-unit increase in ERS was associated with a 33.6 %, 39.1 %, 109.8 %, and 67.8 % increase for all-cause, CVD, RD, and cancer mortality risk, respectively. Moreover, joint exposure to VOCs contributed to 17.95 % of all-cause deaths, 13.49 % of CVD deaths, 35.65 % of RD deaths, and 33.85 % of cancer deaths. Individual and joint exposure to VOCs may enhance the risk of all-cause and cause-specific mortality. Reducing exposure to VOCs may alleviate the all-cause and cause-specific death burden.

The exposure to volatile organic compounds associate positively with overactive bladder risk in U.S. adults: a cross-sectional study of 2007-2020 NHANES

Objective

The aim of this study was to comprehensively investigate the potential relationship between blood volatile organic compounds (VOCs) and overactive bladder (OAB) risk.

Methods

A total of 11,183 participants from the 2007-2020 National Health and Nutrition Examination Survey (NHANES) were included in this cross-sectional study. We used multivariate logistic regression models to investigate the relationship between nine blood VOCs and OAB risk. Restricted cubic spline (RCS) analysis was used to investigate the dose-response relationship between blood VOCs and OAB. In addition, the overall association of blood VOCs with OAB risk was assessed by weighted quantile sum (WQS) regression model. Finally, we conducted subgroup analyses to explore the findings in different high-risk populations.

Results

After adjusting for potential confounders, logistic regression analysis revealed that blood 2,5-dimethylfuran (aOR = 2.940, 95% CI: 1.096-7.890, P = 0.032), benzene (aOR = 1.460, 95% CI: 1.044-2.043, P = 0.027) and furan (aOR = 9.426, 95% CI: 1.421-62.500, P = 0.020) were positively independent associated with the risk of OAB. And dose-response risk curves indicated that 2,5-dimethylfuran, benzene and furan in the blood were linearly positive associated with OAB risk. WQS regression analysis showed that exposure to mixed blood VOCs increased the risk of OAB (OR = 1.29, 95% CI: 1.11-1.49), with furans having the greatest weight. In subgroup analyses, we found that OAB was more susceptible to blood VOCs in young and middle-aged, male, non-hypertensive, and alcohol-drinking populations.

Conclusions

The results of this study indicate that high exposure to VOCs is independently and positively associated with OAB risk in U.S. adults, particularly 2,5-dimethylfuran, benzene, and furan. In addition, age, gender, hypertension and alcohol consumption may influence the association. Our study provided novel epidemiologic evidence to explore the potential role of environmental pollutants in OAB.

Atomistic molecular dynamics simulation and COSMO-SAC approach for enhanced 1,3-propanediol extraction with imidazolium-based ionic liquids

CONTEXT

1,3-Propanediol (1,3-PDO) is a key chemical in various industries, including pharmaceuticals and material sciences, and is projected to see significant market growth. However, the current challenges in its downstream processing, particularly in terms of cost and efficiency, highlight the need for innovative solutions. Our study delves into using ionic liquids (ILs) as a potential alternative, aiming to address these critical separation challenges more sustainably and efficiently. In this study, we utilized molecular dynamics (MD) simulations and the COSMO-SAC to examine 1,3-propanediol (1,3-PDO) extraction using four imidazolium-based ionic liquids with 1-butyl-3-methylimidazolium [Bmim] cation and with different anions bis(pentafluoroethanesulfonyl)imide [NPF2]-, bis(trifluoromethylsulfonyl)imide [NTF2]-, thiocyanate [SCN]-, and trifluoromethanesulfonate [TFO]-. Molecular dynamics simulations, incorporating analysis of radial distribution functions (RDF) and spatial distribution functions (SDF), revealed that [Bmim][SCN] and [Bmim][TFO] exhibit enhanced interactions with 1,3-PDO. Notably, [Bmim][SCN] formed the most hydrogen bonds, averaging 1.639 per molecule, due to its coordinating [SCN]- anion. This was in contrast to the fewer hydrogen bonds formed by non-coordinating anions in [Bmim][NPF2] and [Bmim][NTF2]. In ternary systems, [Bmim][SCN] and [Bmim][TFO] demonstrated superior selectivity for 1,3-PDO extraction compared to the other ionic liquids, with selectivity values around 29. These findings, supported by COSMO-SAC predictive modeling, highlight the potential of [Bmim][SCN] as a promising candidate for 1,3-PDO extraction, emphasizing the importance of anion selection in optimizing ionic liquid properties for this application.

METHODS

In our study, we employed MD simulations, incorporating the OPLS-AA force field, and COSMO-SAC to investigate the extraction of 1,3-PDO using imidazolium-based ionic liquids: [Bmim][NTF2], [Bmim][NPF2], [Bmim][SCN], and [Bmim][TFO]. The MD simulations were conducted using LAMMPS software, focusing on elucidating the RDF, SDF, and hydrogen bonding. Analysis of the distribution coefficient (β) and selectivity (S) for the ternary mixture was also conducted. These aspects of the simulation were analyzed using TRAVIS and VMD software. Additionally, the COSMO-SAC model was employed to determine the activity coefficients of 1,3-PDO in the ionic liquids, with molecular optimization conducted using Gaussian16 and sigma profile calculations performed using COSMO-SAC.

Single and mixed effects of multiple volatile organic compounds exposure on hematological parameters in the U.S. adult population

BACKGROUND

Most research exploring the correlation between volatile organic compounds (VOCs) and hematological parameters have focused on single VOCs. Our study aimed to explore the single and combined effects of VOCs on hematological parameters through three statistical models.

METHODS

Data from 4 cycles of the National Health and Nutrition Examination Survey (NHANES) were used in this study. The correlations between single exposure to 16 VOCs and hematological parameters in the general population were assessed by weighted multiple linear regression. Weighted quantile sum (WQS) and Bayesian kernel machine regression (BKMR) models were used to explore the relationship between the combined important VOCs selected by the least absolute shrinkage and selection operator (LASSO) and hematological parameters, as well as the effects of smoking status on them.

RESULTS

A total of 4089 adults were included in the study. We found that a variety of VOCs were significantly associated with hematological parameters. Among them, N-acetyl-S-(benzyl)-l-cysteine (BMA) was significantly negatively correlated with white blood cell (WBC), red blood cell (RBC), lymphocyte, and neutrophil counts. N-acetyl-S-(3-hydroxypropyl-1-methyl)-l-cysteine (HPMMA) was significantly positively correlated with WBC, monocyte, lymphocyte, and neutrophil counts. In the WQS analysis, the WQS index of the VOCs mixtures was positively correlated with WBC (β: 0.031; P < 0.001), monocyte (0.023; P = 0.021), and neutrophil (0.040; P = 0.001) counts, while negatively associated with RBC (-0.013; P < 0.001) counts. The BKMR model revealed that combined exposure to VOCs levels ≥70th percentile was significantly associated with lower RBC counts, and BMA was identified as the dominant contributor. Smoking significantly influenced the relationship between VOCs and hematological parameters.

CONCLUSIONS

Our study indicated the effects of single and overall VOCs exposure on hematological parameters and suggested the hematotoxicity as well as pro-inflammatory effects of VOCs, which had strong public health implications for reducing the potential health hazards of VOCs exposure to the hematologic system.

Synchronous removal of gaseous toluene and benzene and degradation process shifts in microbial fuel cell-biotrickling filter system

Illustrating the biodegradation processes of multi-component volatile organic compounds (VOCs) will expedite the implication of biotechnology in purifying industrial exhaust. Here, performance shifts of microbial fuel cell and biotrickling filter combined system (MFC-BTF) are investigated for removing single and dual components of toluene and benzene. Synchronous removal of toluene (95 %) and benzene (97 %) are achieved by MFC-BTF accompanied with the output current of 0.41 mA. Elevated content of extracellular polymeric substance facilitates the mass transfer of benzene with the presence of toluene. Strains of Bacteroidota, Proteobacteria and Chloroflexi contribute to the removal of dual components VOCs. Empty bed reaction time and the VOCs concentration are the important factors influencing their dissolution in the system. The biodegradation of toluene and benzene proceeds with 2-hydroxymuconic semialdehyde and o-hydroxybenzoic acid as the main intermediates. These results provide a comprehensive understanding of multi-component VOCs removal by MFC-BTF and guide the system design, optimization, and scale-up.

Electrokinetic bioremediation of trichloroethylene and Cr/As co-contaminated soils with elevated sulfate

Co-contaminants and complex subsurface conditions pose great challenges to site remediation. This study demonstrates the potential of electrokinetic bioremediation (EK-BIO) in treating co-contaminants of chlorinated solvents and heavy metals in low-permeability soils with elevated sulfate. EK-BIO columns were filled with field soils, and were fed by the electrolyte containing 20 mg/L trichloroethylene (TCE), 250 μM Cr(VI), 25 μM As(III), 10 mM lactate, and 10 mM sulfate. A dechlorinating consortium containing Dehalococcoides (Dhc) was injected several times during a 199-d treatment at ∼1 V/cm. Sulfate reduction, Cr/As immobilization, and complete TCE biodechlorination were observed sequentially. EK-BIO facilitated the delivery of lactate, Cr(VI)/As(III), and sulfate to the soils, creating favorable reductive conditions for contaminant removal. Supplementary batch experiments and metagenomic/transcriptomic analysis suggested that sulfate promoted the reductive immobilization of Cr(VI) by generating sulfide species, which subsequently enhanced TCE biodechlorination by alleviating Cr(VI) toxicity. The dechlorinating community displayed a high As(III) tolerance. Metagenomic binning analysis revealed the dechlorinating activity of Dhc and the potential synergistic effects from other bacteria in mitigating heavy metal toxicity. This study justified the feasibility of EK-BIO for co-contaminant treatment and provided mechanistic insights into EK-BIO treatment.

Insights into the Paulownia Shan tong (Fortunei × Tomentosa) Essential Oil and In Silico Analysis of Potential Biological Targets of Its Compounds

The volatile composition of Paulownia Shan tong (Fortunei × Tomentosa) essential oil isolated by steam distillation (yielding 0.013% v/w) from flowers (forestry wastes) was investigated by gas chromatography-mass spectrometry. Thirty-one components were identified, with 3-acetoxy-7, 8-epoxylanostan-11-ol (38.16%), β-monoolein (14.4%), lycopene, 1,2-dihydro-1-hydroxy- (10.21%), and 9,12-octadecadienoic acid, 2-phenyl-1,3-dioxan-5-yl ester (9.21%) as main compounds. In addition, molecular docking was employed to identify potential protein targets for the 31 quantified essential oil components. Inhibition of these targets is typically associated with antibacterial or antioxidant properties. Molecular docking revealed that six of these components, namely, 13-heptadecyn-1-ol, ascabiol, geranylgeraniol, anethole, and quinol dimethyl ether, outperformed the native ligand (hypoxanthine) of xanthine oxidase in terms of theoretical binding affinity, therefore implying a significant in silico inhibitory potential against xanthine oxidase. These findings suggest that the essential oil extracted from Paulownia Shan tong flowers could be valuable for developing protein-targeted antioxidant compounds with applications in the food, pharmaceutical, and cosmetic industries.

Self-aspiration sampling design for rapid analyses of volatile organic compounds based on atmospheric pressure chemical ionization/photoionization combined ionization source mass spectrometry

Development of combined mass spectrometry ionization sources has enabled expansion of the application and scope of mass spectrometry. A novel hybrid ionization system combining vacuum ultraviolet (VUV) and atmospheric pressure chemical ionization (APCI) was constructed. Gaseous samples were self-aspirated into an ionization zone through a capillary by negative pressure, generated by high-speed airflow based on the Venturi effect. Compared with APCI mode alone, the signal-to-noise ratio (S/N) in APCI/VUV mode was increased by about 276-times. To increase the ionization efficiency further, correlated experimental conditions were optimized. Four types of volatile organic compounds (VOCs) were tested to evaluate the performance of the APCI/VUV ion source. Excellent linearity and limit of detection were achieved for compounds in mixed solutions. Quantitative analyses of four VOCs (toluene, cyclohexanone, styrene and ethylbenzene) using APCI/VUV-MS were done, and the relative standard deviations (RSDs) were 1.57%, 6.30%, 4.49% and 8.21%, respectively, indicating that the APCI/VUV ionization source had excellent reproducibility. Our results demonstrated that the developed method was promising for analyzing VOCs as well as being rapid, simple, and easy to operate.

Understanding the spatial and seasonal variation of the ground-level ozone in Southeast China with an interpretable machine learning and multi-source remote sensing

Ground-level ozone (O3) pollution poses significant threats to both human health and air quality. This study uses ground observations and satellite retrievals to explore the spatiotemporal characteristics of ground-level O3 in Zhejiang Province, China. We created data-driven machine learning models that include meteorological, geographical and atmospheric parameters from multi-source remote sensing products, achieving good performance (Pearson's r of 0.81) in explaining regional O3 dynamics. Analyses revealed the crucial roles of temperature, relative humidity, total column O3, and the distributions and interactions of precursor (volatile organic compounds and nitrogen oxides) in driving the varied O3 patterns observed in Zhejiang. Furthermore, the interpretable modeling quantified multifactor interactions that sustain high O3 levels in spring and autumn, suppress O3 levels in summer, and inhibit O3 formation in winter. This work demonstrates the value of a combined approach using satellite and machine learning as an effective novel tool for regional air quality assessment and control.

Data-driven autonomous operation of VOCs removal system

Removal of volatile organic compounds (VOCs) from the air has been an important issue in many industrial fields. Traditionally, the operation of VOCs removal systems has relied on fixed operating conditions determined by domain experts based on their expertise and intuition. In practice, this manual operation cannot respond immediately to changes in the system environment. To facilitate the autonomous operation of the system, the operating conditions should be optimized properly in real time to adapt to the changes in the system environment. Recently, optimization frameworks have been widely applied to real-world industrial systems across various domains using different approaches. The primary motivation for this study is the effective implementation of an optimization framework targeting a VOCs removal system. In this paper, we present a data-driven autonomous operation method for optimizing the operating conditions of a VOCs removal system to enhance the overall performance. An optimization problem is formulated with the decision variables denoting the parameters associated with the operating condition, the environmental variables representing the measurements for the system environment, the constraints specifying the control ranges of the parameters, and the objective function representing the system performance as determined by the operating conditions and environment. Using the previous operation data from the system, a neural network is trained to model the system performance as a function of the decision and environmental variables to approximate the objective function. For the current state of the system environment, the optimal operating condition is derived by solving the optimization problem. A case study of a targeted VOCs removal system demonstrates that the proposed method effectively optimizes the operating conditions for improved system performance without intervention from domain experts.

The urinary metabolites of volatile organic compounds and asthma in young children: NHANES 2011-2018

The vast majority of volatile organic compounds (VOCs) are of biological origin and do not affect human health, while some VOCs or their oxidation products can damage the respiratory system, nervous system, digestive system and blood system after long-term inhalation by humans. There is limited evidence regarding the association of VOCs exposure with childhood asthma. In this study, we examined the associations between metabolites of VOCs (mVOCs) in urine and childhood asthma. We included a total of 1542 children aged 3-12 years who had information on urinary mVOCs, asthma and essential covariates in the current analyses. After controlling for covariates, we used logistic regression to assess the association between urinary mVOCs and childhood asthma. Then, we examined effect measure modification by child age, gender, race/ethnicity and serum cotinine. 2-Methylhippuric acid (xylene metabolites) (OR: 1.14; 95 % CI: 0.87, 1.59), N-acetyl-S-(benzyl)-l-cysteine (toluene metabolites) (OR: 1.15 95 % CI: 0.76, 1.71), N-acetyl-S-(2-carboxyethyl)-l-cysteine (acrolein metabolites) (OR: 1.09; 95 % CI: 0.61, 1.75), N-acetyl-S-(3-hydroxypropyl)-l-cysteine (acrolein metabolites) (OR: 1.10; 95 % CI: 0.66, 1.80), and N-acetyl-S-(3-hydroxypropyl-1-methyl)-l-cysteine (crotonaldehyde metabolites) (OR: 1.18; 95 % CI: 0.68, 2.01) were weakly associated with the prevalence of asthma in children. Among female children, 2MHA (2-methylhippuric acid) in urine was significantly associated with the prevalence of asthma (OR: 1.81 95 % CI: 1.07, 3.05). At the same time, BMA (N-acetyl-S-(benzyl)-l-cysteine) was significantly associated with the prevalence of asthma in non-Hispanic White (OR:2.09 95 % CI: 0.91, 4.66) and Black (OR:1.90 95 % CI: 0.96, 3.71) children. We found that gender modified the associations between urinary 2MHA and the odds of asthma (interaction term p value = 0.03). Therefore, exposure to VOCs and the development of childhood asthma remains controversial, and the interpretation of these results needs to be treated with caution and should be confirmed in future studies.Therefore, exposure to VOCs and the development of childhood asthma remains controversial, and the interpretation of these results needs to be treated with caution and should be confirmed in future studies.

Volatile organic compounds exposure associated with depression among U.S. adults: Results from NHANES 2011-2020

Volatile organic compounds (VOCs) are important contributors to air pollution. VOCs exposure was associated with various human diseases. Depression is one of the most prevalent mental disorders and poses a serious mental health burden. Although VOCs are neurotoxic and can damage the central nervous system, the association between VOCs exposure and depression remains obscure. Based on data from the National Health and Nutrition Examination Survey, we included 5676 adult individuals and 15 major components of urinary volatile organic compound metabolites (mVOCs). We comprehensively evaluated the potential association between each single urinary mVOC exposure and depressive symptoms using binary logistic and restricted cubic spline regression, whereas the weighted quantile sum regression and least absolute shrinkage and selection operator regression model were used to explore the mixture co-exposure association. The results indicated significantly higher mean concentrations of the 11 urinary mVOC components in the depression group than that in the non-depression group. And 12 mVOC components had a significantly positive association with depression. The overall effect of all 15 mVOCs components was also significantly positive. The corresponding odds ratio was 1.56 (95%CI: 1.2-2.03) in the categorical variable model and the regression coefficient was 0.36 (95%CI: 0.12-0.6) in the numerical variable model. Five urinary mVOCs (URXCYM, URXPHG, URX34 M, URXMB3, and URXAMC) were identified as the most relevant components associated with depression, with 89.06% total weights in the categorical variable model and 89.39% in the numerical variable model. The mVOCs were the biomarkers of VOCs, their concentrations in urine could specifically represent the contents of their metabolic parents in the human body. Considering that the metabolic parents of the above five mVOCs were predominantly acrylonitrile, toluene, styrene, acrylamide, 1,3-Butadiene, and xylenes, our results further indicated that exposure to these VOCs was closely related to depression, and more attention should be paid to the mental health risks of VOCs exposure.

Exposure to volatile organic compounds is a risk factor for diabetes retinopathy: a cross-sectional study

Introduction

A few past experimental studies have indicated that exposure to volatile organic compounds (VOCs) might be a potential risk factor for diabetes retinopathy (DR). However, these findings lack substantial support from extensive epidemiological research. This large-scale cross-sectional study aimed to examine whether exposure to low levels of VOCs in the general population is associated with diabetes mellitus (DM) and DR.

Methods

The analytical data was from the National Health and Nutrition Examination Survey (NHANES) dataset (2011-2018). To minimize the potential impact of gender and age on the findings, propensity score matching was utilized to align the data selection. Relationships between blood VOCs and DM and DR were assessed in a sample of 2,932 adults using the logistic regression models. Additionally, Bayesian kernel machine regression (BKMR) models and Weighted Quantile Sum (WQS) were conducted for mixture exposure analysis.

Results

The result shows VOCs were positive associated with DM and DR in US adults, as assessed by WQS model, and the calculated odd ratios (ORs) [95% confidence interval (C.I)] were 53.91(34.11 ~ 85.22) and 7.38(3.65 ~ 14.92), respectively. Among the components of VOCs, 1,2-Dibromoethane, Carbon Tetrachloride and 2,5-Dimethylfuran were positive related with the DR, and ORs (95%C.I) were 2.91(2.29 ~ 3.70), 2.86(2.25 ~ 3.65) and 2.19(1.79 ~ 2.94), respectively. BKMR model shows that there was a dose-response relationship between combined VOCs and DR, although the relationship was non-linearly.

Conclusion

This study suggested that exposure to VOCs may increase the risk of DR, which had important public health implications.

Whole-body aging mediates the association between exposure to volatile organic compounds and osteoarthritis among U.S. middle-to-old-aged adults

BACKGROUND

Humans are constantly exposed to various volatile organic compounds (VOCs) because of their widespread sources and characteristic of easy evaporation. Existing evidence regarding the association between VOC exposure and osteoarthritis (OA) risk is limited.

PURPOSE

This study aimed to investigate the associations between individual urinary VOC metabolites (VOCMs) and the VOCM mixture, representing internal exposure levels of VOCs, with prevalent OA risk and to explore the mediating effect of aging and oxidative stress (OS) in these associations.

METHODS

Data from the National Health and Nutrition Examination Surveys 2005-2020 were analyzed. Weighted generalized linear regression was employed to explore the associations between individual VOCMs and OA risk, as well as aging and OS biomarkers. A five-repeated ten-fold cross-validation elastic net model was used to identify critical VOCMs for the weight quantile sum (WQS) analysis, which was performed to explore the VOCM mixture and OA risk association. Parallel and serial mediation analyses were conducted to identify the potential mediators and mediation pathways.

RESULTS

This study included 6578 American adults aged ≥40 years, among whom 1052 (16.0 %) individuals reported prevalent OA. Urinary levels of N-acetyl-S-(benzyl)-L-cysteine, mandelic acid and phenylglyoxylic acid were positively associated with OA risk. Eleven VOCMs with nonzero coefficients were identified and included in the WQS analysis, and results revealed an average increase of 24.4 % in OA risk (OR = 1.244, 95 % CI: 1.041, 1.486) per one-quantile increment in the VOCM mixture. Two aging biomarkers, phenotypic age and biological age, parallelly mediated the association between the VOCM mixture and OA risk, with mediation effect proportions of 9.0 % and 16.4 %, respectively.

CONCLUSIONS

Exposure to VOCs is associated with an increased OA risk in middle-to-old aged American adults. The mediating effect of aging contributes to the association between co-exposure to VOCs and OA risk. Further prospective studies are required to substantiate these findings.

Serum HDL partially mediates the association between exposure to volatile organic compounds and kidney stones: A nationally representative cross-sectional study from NHANES

Environmental exposure to volatile organic compounds (VOCs) is ubiquitous, and this study explored whether exposure to VOCs is associated with the risk of kidney stones. We performed a nationally representative US cross-sectional study using data from five survey cycles (2011-2020) of the National Health and Nutrition Examination Survey (NHANES) program. Exposure to VOCs was determined by urine creatinine-corrected metabolites of VOCs (mVOCs). In total 5505 participants and 15 urine mVOCs were included for analysis, and the prevalence of kidney stones was 9.57 % (527/5505). Multivariable logistic regression showed that urine AMCC (parent VOCs (pVOCs): N, N-Dimethylformamide), 3,4-MHA (pVOCs: xylene), MA (pVOCs: ethylbenzene; styrene), DHBMA (pVOCs: 1,3-butadiene), HMPMA (pVOCs: crotonaldehyde) and 2HPMA (pVOCs: propylene oxide) were significantly associated with an increased risk of kidney stones in US general population. Sub-analysis revealed that there was a more pronounced association in women and the overweight/obesity group (body mass index ≥ 25). Moreover, the weighted quantile sum (WQS) regression model and the Bayesian kernel machine regression (BKMR) model consistently identified a positive association between co-exposure to VOCs and the risk of kidney stones, in which AMCC played the most important role among the 15 mVOCs. Mediation analysis further identified serum high-density lipoprotein cholesterol (HDL) as a mediator of the association between VOC co-exposure and kidney stones. Our study draws attention to the previously unknown positive associations between non-occupational VOC exposure and the risk of kidney stones in the general population. However, further studies are required to clarify the existence of such causation.

Associations of individual and mixture exposure to volatile organic compounds with metabolic syndrome and its components among US adults

BACKGROUND

People are exposed to various volatile organic compounds (VOCs) in their environment. Our study aims to examine the links between VOCs exposure and metabolic syndrome (MetS) and its components, as well as identify critical VOCs.

METHOD

In this study, we enrolled 8223 adults from the National Health and Nutrition Examination Survey (NHANES) and analyzed 15 kinds of urinary VOCs metabolites. The Spearman correlation model, generalized linear regression model, restricted cubic spline (RCS), weighted quantile sum (WQS) analysis, and Bayesian kernel machine regression (BKMR) were used to evaluate the association between individual VOC/VOCs mixture and MetS as well as its components.

RESULTS

In generalized linear regression model, compared to the lowest quartile of urinary VOCs metabolites, the highest quartiles of urinary VOC metabolites were positively associated with MetS including N-Acetyl-S-(N-methylcarbamoyl)-l-cysteine (AMCC) (OR: 1.22, 95%CI: 1.00, 1.49), N-Acetyl-S-(2-carboxyethyl)-l-cysteine (CEMA) (OR: 1.71, 95%CI: 1.41, 2.07), N-Acetyl-S-(3-hydroxypropyl)-l-cysteine (3HPMA) (OR: 1.32, 95%CI: 1.11, 1.63), and N-Acetyl-S-(3-hydroxypropyl-1-methyl)-l-cysteine (HMPMA) (OR: 1.34, 95%CI: 1.09, 1.64). Consistent results were found in the dose-response relationship in RCS model. Results of WQS showed that VOCs mixture was positively associated with MetS (OR: 1.16, 95%CI: 1.06, 1.28), elevated WC (OR: 1.25, 95%CI: 1.13, 1.37), elevated FBG (OR: 1.24, 95%CI: 1.12, 1.37), elevated TG (OR: 1.34, 95%CI: 1.21, 1.49), and reduced HDL-C (OR: 1.20, 95%CI: 1.09, 1.33). However, the WQS index was negatively associated with elevated BP (OR: 0.81; 95%CI: 0.70, 0.94). BKMR analysis confirmed that the urinary VOCs mixture was positively associated with MetS, elevated WC, elevated TG, reduced HDL-C, elevated FBG, but negatively associated with elevated BP. CEMA was defined as the most heavily weighted chemical in the WQS and BKMR models.

CONCLUSION

Our findings suggested that exposure to specific VOC or VOCs mixture is associated with the higher risk of MetS and its components, except for elevated BP.

Identifying multiple soil pollutions of potentially contaminated sites based on multi-gate mixture-of-experts network

With the rapid increase in the amount and sources of big data, using big data and machine learning methods to identify site soil pollution has become a research hotspot. However, previous studies that used basic information of sites as pollution identification indexes mainly have problems of low accuracy and efficiency when conducting complex model predictions for multiple soil pollution types. In this study, we collected the environmental data of 199 sites in 6 typical industries involving heavy metal and organic pollution. After feature fusion and selection, 10 indexes based on pollution sources and pathways were used to establish the soil pollution identification index system. The Multi-gate Mixture-of-Experts network (MMoE) were constructed to carry out the multi-tasks of soil heavy metals, VOCs and SVOCs pollution identification simultaneously. The SHAP framework was used to reveal the importance of pollution identification indexes on the multiple outputs of MMoE and obtain their driving factors. The results showed that the accuracies of MMoE model were 0.600, 0.783 and 0.850 for soil heavy metals, VOCs and SVOCs pollution identifications, respectively, which were 0-20 % higher than their accuracies of BP neural networks of single tasks. The indexes of raw material containing organic compounds, enterprise scale, soil pollution traces and industry types have the different significant importance on site soil pollutions. This study proposed a more efficient and accurate method to identify site soil pollutions and their driving factors, which offers a step towards realizing intelligent identification and risk control of site soil pollution globally.

Metabolomic Alterations of Volatile Organic Compounds and Bile Acids as Biomarkers of Microbial Shifts in a Murine Model of Short Bowel Syndrome

Pediatric short bowel syndrome (SBS) is a rare condition characterized by a massive loss of the small intestine, leading to the inability to meet nutritional requirements without the use of parenteral or enteral supplementation. SBS causes profound alterations in the intestinal microbiome and metabolome. The aim of this study was a detailed assessment of the intestinal microbiome and metabolome in a murine model of SBS. We performed a 60% proximal small bowel resection versus a sham operation in C57BL/6 mice. Four weeks postoperatively, the microbial communities of different intestinal segments (jejunum, ileum, colon) and stool were assessed by 16S rRNA gene sequencing. Bile acids in serum and stool and volatile organic compounds (VOCs) in the fecal headspace were assessed using LC-MS and GC-MS techniques. The α-diversity of the different intestinal segments did not significantly differ between the two groups. β-diversity significantly differed between sham and SBS mice. While in the jejunum, Faecalibaculum was significantly increased in SBS animals, a significant reduction in Lactobacillus and Sporosarcina was detected in the ileum of SBS mice. In the colon of SBS mice, a significant decrease in Ruminococcaceae and a significant increase in Proteobacteria such as Faecalibaculum and Escherichia-Shigella were found. Serum levels of deoxycholic, taurocholic and taurochenodeoxycholic acids were significantly higher in the SBS group. Of the 29 VOCs tested, hexane, isoflurane and pentane were significantly higher in the SBS group, and pyrrole was significantly lower. We were able to show that SBS causes shifts in the murine intestinal microbiome and metabolome including serum BAs and fecal VOCs.

Volatile organic compounds emitted by conventional and "green" cleaning products in the U.S. market

Exposure to cleaning products has been associated with harm to the respiratory system, neurotoxicity, harm to the reproductive system, and elevated risk of cancer, with greatest adverse impacts for workers exposed in an occupational setting. Social and consumer interest in cleaning products that are safer for health created a market category of "green" products defined here as products advertised as healthier, non-toxic, or free from harmful chemicals as well as products with a third-party certification for safety or environmental features. In the present study we examined the air quality impacts of cleaning products and air fresheners, measuring the number, concentrations, and emission factors of volatile organic compounds (VOCs) in an air chamber following product application. Across seven common product categories, 30 products were tested overall including 14 conventional, 9 identified as "green" with fragrance, and 7 identified as "green" and fragrance-free. A total of 530 unique VOCs were quantified with 205 additional VOCs detected below the limits of quantification. Of the quantifiable VOCs, 193 were considered hazardous according to either the California's Department of Toxic Substances Control Candidate Chemicals List or the European Chemical Agency's Classification and Labeling Inventory. The total concentration of VOCs and total emission factors across all products with detections ranged from below limits of detection to 18,708 μg/m3, 38,035 μg/g product and 3803 μg/application. Greater total concentration, total emission factors, and numbers of VOCs were generally observed in conventional cleaning products compared to products identified as "green", particularly compared to fragrance-free products. A hazard index approach was utilized to assess relative risk from measured VOC emissions. The five products with the highest hazard indices were conventional products with emissions of 2-butoxyethanol, isopropanol, toluene and chloroform. Overall, this analysis suggests that the use of "green" cleaning products, especially fragrance-free products, may reduce exposure to VOC emissions.

Valorization of Nam Wah Banana (Musa paradisiaca L.) Byproducts as a Source of Bioactive Compounds with Antioxidant and Anti-inflammatory Properties: In Vitro and In Silico Studies

Nam Wah banana (Musa paradisiaca L.) is the most common banana cultivar in Thailand. Large amounts of its non-consumable byproducts are considered undervalued and thrown as waste. Exploring the potential utilization and application of banana byproducts for human benefit can add to their value and minimize the risk of threats. This study aimed to investigate phytochemicals, antioxidant and anti-inflammatory activities, and toxicity of Nam Wah banana byproducts. Five banana plant parts, including the midrib, leaf, peduncle, unripe and ripe peels, were extracted using hexane, ethyl acetate, ethanol, and water. Among the extracts tested, the ethyl acetate leaf extract showed the strongest antioxidant capacity and anti-inflammatory activity, probably through the inhibition of inducible nitric oxide synthase (iNOS) and 15-lipoxygenase (15-LOX). Positive correlations existed between the activities and the total phenolic/flavonoid content of banana byproducts. An in silico docking analysis demonstrated that flavonoid glycosides in banana byproducts, such as kaempferol-3-O-rutinoside and rutin, may bind to inducible iNOS, whereas omega-3-polyunsaturated fatty acids, such as eicosapentaenoic acid, may bind to 15-LOX and cyclooxygenase-2 (COX-2). The extracts showed either low or no toxicity. These findings suggest that banana byproducts are a natural source of antioxidant and anti-inflammatory compounds. It is recommended that additional investigations be conducted to explore their potential therapeutic applications in treating disorders linked with oxidative stress or inflammation. This research has the potential to enhance the value of banana byproducts.

Exposure to volatile organic compounds is a risk factor for diabetes: A cross-sectional study

Currently, more studies showed that environmental chemicals were associated with the development of diabetes. However, the effect of volatile organic compounds (VOCs) on diabetes remained uncertain and needed to be studied. This cross-sectional study examined whether exposure to low levels of VOCs was associated with diabetes, insulin resistance (TyG index) and glucose-related indicators (FPG,HbA1c, insulin) in the general population by using the NHANES dataset (2013-2014 and 2015-2016). We analyzed the association between urinary VOC metabolism (mVOCs) and these indicators in 1409 adults by multiple linear regression models or logistic regression models, further Bayesian kernel machine regression (BKMR) models were performed for mixture exposure analysis. The results showed positive associations between multiple mVOCs and diabetes, TyG index, FPG, HbA1c and insulin, respectively. Among them, HPMMA concentration in urine was significantly positively correlated with diabetes and related indicators (TyG index, FPG and HbA1c), and the concentration of CEMA was significantly positively correlated with insulin. The positive association of mVOCs with diabetes and its related indicators was more significant in the female group and in the 40-59 years group. Thus, our study suggested that exposure to VOCs affected insulin resistance and glucose homeostasis, further affecting diabetes levels, which had important public health implications.

A Study on the Gaseous Benzene Removal Based on Adsorption onto the Cost-Effective and Environmentally Friendly Adsorbent

Removal of benzene is essential for human and environmental health because it has toxic and hazardous properties at various concentrations. Theseneed to be effectively eliminated with carbon-based adsorbents. PASACs, carbon-based adsorbents obtained from using the needles of Pseudotsuga menziesii, were produced by optimized HCl- and H₂SO₄-impregnated approaches. Regarding physicochemical structure, the optimized PASAC23 and PASAC35 with surface areas of 657 and 581 m²/g and total pore volumes of 0.36 and 0.32 cm³/g showed ideal temperatures of 800 °C. In order to investigate and compare internal benzene removal efficiency, PASAC23 and PASAC35 were studied separately. Initial concentrations were found to range from 5 to 500 mg/m³, and between 25 and 45 °C. The removal rate of benzene by PASAC23 and PASAC35 was 97 and 94% at low concentrations, respectively. While the highest capture amount for PASAC23 and PASAC35 was found to be at 25 °C with 141 and 116 mg/g, the adsorption capacity decreased to 102 and 90 mg/g at 45 °C. The holding capacity decreased between 22.41 and 27.66% due to increasing temperatures. After five cycles of PASAC23 and PASAC35 regeneration, we found that they could remove 62.37 and 58.46% of benzene, respectively. These results confirmed that PASAC23 is a promising environmentally adsorbent for effectively removing benzene with a competitive yield.