Identification and Prioritization of Environmental Organic Pollutants: From an Analytical and Toxicological Perspective

Identifying and prioritizing organic toxicants in treated flowback and produced water from shale gas exploitation sites using an integrative effect-directed analysis and nontarget screening method

The use of hydraulic fracturing in shale gas exploitation has generated substantial amount of flowback and produced water (FPW), and ecological risk of these highly complex chemical mixtures has raised worldwide concern. Herein, an integrative effect-directed analysis (EDA) and nontarget screening (NTS) workflow was developed to identify and prioritize main toxicants in the treated FPW (T-FPW). The workflow included sample extraction and fractionation, zebrafish embryo toxicity tests, target and nontarget chemical analyses, and toxicity prioritization and confirmation using toxicological priority index (ToxPi). Results showed that less hydrophobic compounds (log Kow < 3.7) which were used in fracturing fluid and their degradation products were the potentially high-risk toxicants in T-FPW. Thirty-nine target compounds identified in toxic fraction explained 4.82% of the mortality. Additional 584 nontarget contaminants were annotated by NTS. Risk prioritization was achieved for 470 identified contaminants with ecotoxicity data available using a ToxPi method. Six nontarget toxicants were identified with higher ecological risks than all target contaminants, and their presence in FPW were confirmed using reference standards. A principal component analysis of NTS features revealed that EDA fractionation reduced mixture complexity and focused toxicant screening, which significantly improved NTS efficiency, highlighting advantages of integrative EDA and NTS for mixture risk assessment.

Systematic approach to online comprehensive 2D-LC method development for organic micropollutant profiling in wastewater

The increasing global contamination of freshwater systems with organic micropollutants (OMPs) is an important environmental problem. OMPs are frequently detected in the effluents of wastewater treatment plants (WWTPs), due to the inability of WWTPs to effectively remove them, and are subsequently discharged into surface waters, severely reducing water quality. The characterization of these complex wastewater samples is challenging, due to the large variety in physicochemical properties of OMPs and the presence of various matrix compounds, such as inorganic salts, humic acids and microorganisms. An emerging and promising technology to tackle this challenge is comprehensive two-dimensional liquid chromatography (LC x LC), combining two orthogonal separation modes to drastically enhance the separation power. However, the method development of LC x LC is complicated, currently confining its application mainly to academic research. It is difficult to predict which combinations will result in an increased peak capacity for a specific sample, and there is no consensus on how to best describe orthogonality. Furthermore, no single metric can fully assess all aspects of the quality of a 2D-LC separation. This study presents a systematic approach to evaluating the orthogonality of different separation modes for a given sample, more specifically for OMP profiling in wastewater, with less bias related to the sample and the user. To achieve this, an orthogonality score is defined, based on several orthogonality metrics commonly applied in 2D-LC studies. To automate the calculation of the orthogonality score, the mathematical algorithms of each metric as well as all other calculations are incorporated in a Python-based tool. Based on their orthogonality score and predicted peak capacity, LC x LC conditions are selected and then further optimized and applied to the analysis of real WWTP effluent samples. It is demonstrated that the optimized sub-hour RPLC x RPLCHRMS method achieves a peak capacity of 1887, emphasizing its potential for practical applications in environmental analysis.

Using machine learning models to predict the dose-effect curve of municipal wastewater for zebrafish embryo toxicity

Municipal wastewater substantially contributes to aquatic ecological risks. Assessing the toxicity of municipal wastewater through dose-effect curves is challenging owing to the time-consuming, labor-intensive, and costly nature of biological assays. This study developed machine learning models to predict wastewater dose-effect curves for zebrafish embryos. The influent and effluent samples from 176 wastewater treatment plants in China were analyzed to collect water quality data, including information on seven chemical parameters and the toxic effects on zebrafish embryos at eight relative enrichment factors (REFs) of wastewater. Using Spearman's rank correlation coefficient and the max-relevance and min-redundancy algorithm, the parameters of ammonium nitrogen content and toxic effect values at REFs of 2 and 25 (REF2 and REF25), were identified as crucial input features from 15 variables. Decision tree, random forest, and gradient-boosted decision tree (GBDT) models were developed. Among these, GBDT exhibited the best performance, with an average R2 value of 0.91 and an average mean absolute percentage error (MAPE) of 27.91 %. Integrating the dose-effect curve pattern into the machine learning model considerably optimized the GBDT model, reaching a minimum MAPE of 14.74 %. The developed model can accurately determine the dose-effect curves of actual wastewater, reducing at least 75 % of the experimental workload. These findings provide a valuable tool for assessing zebrafish embryo toxicity in municipal wastewater management. This study indicates that combining environmental expertise and machine learning models allows for a scientific assessment of the potential toxic risks in wastewater, providing new perspectives and approaches for environmental policy development.

Plant Secondary Metabolites-Central Regulators Against Abiotic and Biotic Stresses

As global climates shift, plants are increasingly exposed to biotic and abiotic stresses that adversely affect their growth and development, ultimately reducing agricultural productivity. To counter these stresses, plants produce secondary metabolites (SMs), which are critical biochemical and essential compounds that serve as primary defense mechanisms. These diverse compounds, such as alkaloids, flavonoids, phenolic compounds, and nitrogen/sulfur-containing compounds, act as natural protectants against herbivores, pathogens, and oxidative stress. Despite the well-documented protective roles of SMs, the precise mechanisms by which environmental factors modulate their accumulation under different stress conditions are not fully understood. This review provides comprehensive insights into the recent advances in understanding the functions of SMs in plant defense against abiotic and biotic stresses, emphasizing their regulatory networks and biosynthetic pathways. Furthermore, we explored the unique contributions of individual SM classes to stress responses while integrating the findings across the entire spectrum of SM diversity, providing a comprehensive understanding of their roles in plant resilience under multiple stress conditions. Finally, we highlight the emerging strategies for harnessing SMs to improve crop resilience through genetic engineering and present novel solutions to enhance agricultural sustainability in a changing climate.

Identification of novel tetrabromobisphenol A byproducts in industrial chemicals and the environment near a manufacturing site: an overlooked source of novel pollutants

To evaluate the migration, transformation, and fate of tetrabromobisphenol A (TBBPA) in the environment, the transformation/degradation (T/D) products of TBBPA and byproducts of industrial production should be distinguished. Herein, 7 reported T/D products (R1-R7) and 7 novel byproducts (N1-N7) of TBBPA were identified in industrial-grade TBBPA chemicals by using high-performance liquid chromatography coupled ion trap mass spectrometry and high-resolution mass spectrometry with a suspect screening strategy. The possible formation pathways of these byproducts were attributed to the bromination, debromination, methylation, demethylation, hydroxylation, substitution, and radical coupling reactions of bisphenol A (BPA), BPA impurities, and TBBPA. The detection frequencies of R1-R7 and N3 (80-100%) were higher than those of N1, N2, and N4-N7 (20-60%) in industrial-grade TBBPA chemicals, with contents extended to 2.29% and 0.0989%, respectively. In the soils and sediments near the TBBPA plants, R1-R4 and N1 were detected with the highest concentration of 1.56 × 102 ng g-1 dry weight, while in the river waters, only R1-R4 were detected with the highest concentration of 4.57 × 102 ng L-1. An in silico analysis indicated the potential toxicity of these compounds, including their hepatotoxicity and carcinogenicity. To accurately estimate the environmental effects of the T/D products of TBBPA, the contributions of byproducts in industrial-grade TBBPA chemicals should be considered separately.

Which Pollutants Should Be Prioritized for Control in Multipollutant Complex Contaminated Groundwater of Chemical Industrial Parks?

Increasing chemical pollutants in groundwater within chemical industrial parks pose a critical environmental challenge, necessitating innovative strategies to address contaminants with the highest risks to environmental health and ensure sustainable management. Herein, we investigated 277 chemical pollutants from 367 sampling points across 10 rounds, totaling 1,016,590 measured data points. An environmental health prioritization index (EHPI) was proposed and applied to integrate multiple criteria: occurrence, migration, persistence, bioaccumulation, acute and chronic toxicity, and health effects to rank the target pollutants for priority control. Thirty pollutants were classified as the top-priority group and 81 as high-priority, with metals, polycyclic aromatic hydrocarbons, and haloalkanes ranking highest, while emerging contaminants of concern ranked lower. The top 6 pollutants were beryllium, benzo(g,h,i)perylene, nickel, benzo(a)pyrene, chrysene, and arsenic. The EHPI method was compared against five other weighting schemes, including AHP (analytic hierarchy process), entropy, AHP-entropy, AHP-TOPSIS (technique for order preference by similarity to ideal solution), and entropy-TOPSIS. EHPI effectively captured and integrated the results from more simplistic prioritization schemes. Overall, 38 pollutants are recommended for inclusion in the priority control list, focusing on the top-priority group and high detection and exceedance categories. This framework provides critical guidance for focused monitoring, assessment, and control of the highest-risk groundwater pollutants, supporting more effective environmental and human health protection.

Modulation of Charge-Ordered Carriers Within 3D Fe3S4 Polyurethane Foam (Fe3S4-PUF) for Efficient Iron Redox Cycling and Continuous-Flow Photocatalytic Antibiotics Degradation

Photocatalytic antibiotic degradation is an energy-efficient and environmentally friendly approach with the potential for large-scale application but is severely constrained by the lack of efficient and stable catalysts to produce reactive oxygen species (ROS). This research introduces a charge-ordered 3D Fe3S4-PUF composite integrated into a custom-built photocatalytic tandem continuous-flow cylinder reactor (TCCR) for antibiotic degradation. The system consistently achieves 100% tetracycline (TC) degradation efficiency with Fe3S4-PUF during 130 h of continuous operation, benefiting from the charge-ordered 3D Fe3S4-PUF framework and the TCCR design. Mechanism investigations reveal that the abundant Lewis basic ≡SH site and light-induced sustainable Fe2+/Fe3+ redox cycling within Fe3S4 facilitates the production of H2O2 and ROS. Density functional theory (DFT) calculations indicate that Fe2+ acts as an active site for capturing and activating O2, leading to either one-electron (O2→O2 •-→H2O2→•OH) or two-electron transfer (O2→H2O2) pathways. Meanwhile, photogenerated electron and the oxygen atoms in H2O2 provide electrons to Fe3+, facilitating the reduction of Fe3+ to Fe2+, thus elucidating the Fe2+/Fe3+ redox cycling mechanism. Moreover, the 3D PUF structure enhances the mass transfer and pollutant-ROS interactions. The continuous-flow photocatalytic reaction validate the efficient antibiotic degradation of Fe3S4-PUF composite, suggesting its potential for implementation in large-scale antibiotic wastewater treatment systems.

Functional Nanofibres of Tb(III)-Coupled Metal-Organic Gel: Detection To Decontamination of Thiabendazole In Environmental Samples

Pollutant residues such as pharmaceuticals or pesticides in water bodies pose significant environmental and health risks, necessitating the development of advanced sensing and removal techniques to ensure safe and sustainable water resources. Tb-based luminescent sensors offer high sensitivity for pollutant residue analysis, but their application is often limited to detection. Developing Tb-derived metal-organic gel (ANS-4G-Tb) as soft supramolecular material is proposed to enhance trace contamination removal, integrating both sensing and sequestration capabilities. For the development of the self-assembled supramolecular material, ANS-4, a low molecular-mass organic gelator (LMOG) with a molecular weight of just about 215 g/mole, was selected, owing to its efficient single-step synthesis, and it was comprehensively characterized using single crystal XRD, and other routine spectroscopic techniques. Then, its nanosized ANS-4G-Tb metallogel was characterized using a comprehensive suite of analytical techniques to assess its structural, chemical, morphological, and optical characteristics. Upon interaction with parasiticide and fungicide thiabendazole (TBZ), a phase transformation from gel to sol is observed, enabling naked-eye detection and simultaneous turn-on photo-luminescence sensing (5D4→7F5 transition). Based on novel research, our study navigates through the photo-luminescence of lanthanide supramolecular complexes, transitioning from fundamental investigations to potential methodologies concerning analyte responsiveness and removal applications.

Superior selectivity for efficiently reductive degradation of hydrophobic organic pollutants in strongly competitive systems

Highly toxic halo-/nitro-substituted organics, often in low concentrations and with high hydrophobicity, make it difficult to obtain electrons for reduction when strongly electron-competing substances (e.g., O2, H+/H2O, NO3-) coexist. To address this barrier, we devised a new strategy to modify microscale zero-valent aluminum (mZVAl) with graphene (GE) by one-pot ball-milling for GE@mZVAl, which exhibits 99 % selective removal of halo-/nitro-substituted organic pollutants (e.g., carbon tetrachloride (CT), trichloroethylene (TCE), p-nitrophenol (PNP) and p-nitrochlorobenzene (p-NCB)) in the presence of multiple competing inorganics (O2, H+/H2O, Cr(VI), NO3- and BrO3-) and interfering ions (Cl-, CO32-, SO42- and PO43-). Notably, due to the fact that the side-reaction of H2 evolution and second-passivation are significantly suppressed, the electron utilization efficiency for organics degradation reaches an impressive 96 %, even under harsh pH conditions (3-11). GE@mZVAl contains an Al-C interface with a high concentration of C-O, which can form active sites for organics and perform selective electron transfer. Meanwhile, the organophilic catalyst GE also hinders the exposure of AlOH+/Al0 sites to shield the competing and interfering of inorganic substances. As a highly selective reduction system, this work may yield innovative insights for the selective removal of hydrophobic refractory pollutants in complex water matrices.

Tailored Fibrils Approach via Ag(I).Peptidomimetic-Based Interface Design: Efficient Encapsulation of Diverse Active Pharmaceutical Ingredients in Wastewater Remediation during Effluent Treatment Plant (ETP) Processing

Pharmaceutical pollution in wastewater poses significant environmental and public health concerns worldwide. Chloramphenicol (CP), an antibiotic widely used in medical and veterinary applications, is among the active pharmaceutical ingredients (APIs) frequently detected in aquatic environments. This study explored the encapsulation of chloramphenicol API in contaminated wastewater using rationally designed fibrations based on the silver metal ion-directed self-assembly of fibrillator-type self-assembling ligand (ANS-3). We further investigated the removal of various commonly prescribed drugs, including antibiotics such as β-lactam (amoxicillin), fluoroquinolone (ciprofloxacin), aminoglycoside (neomycin), and tetracycline; antiparasitic agents with antiprotozoal properties (praziquantel and metronidazole); nonsteroidal anti-inflammatory drugs (NSAIDs) such as phenylbutazone and ketoprofen; the vasodilator isoxsuprine; amphiphilic antidepressants (amitriptyline); and the antiviral drug amantadine. The findings validated the crucial influence of polar multifunctionality and structural complexity in enhancing interactions with Ag.ANS-3 matrix, emphasizing its potential for efficient drug sequestration. First, picolinic acid (PA) and phenylalanine (F) were evaluated for their ability to form fibrillar structures, and their morphological characterization revealed well-defined fibrillar networks with varying degrees of porosity and interconnectivity. Then, the strategic inclusion of leucine in synthesizing ANS-3 facilitated the formation of robust fibrillar networks, employing its hydrophobic interactions to drive the self-assembly process. Finally, the encapsulation of APIs was evaluated using Ag(I) metal ion-driven ANS-3 based self-assembled nanofibrous material. This research contributes to the development of innovative physicochemical wastewater treatment strategies for environmental remediation and validates the importance of rational design in encapsulation-based wastewater remediation technologies.

Identification and Prioritization of Emerging Organophosphorus Compounds Beyond Organophosphate Esters in Chinese Estuarine Waters

Organophosphorus compounds (OPCs) pose potential hazards to human health and aquatic ecosystems. However, limited knowledge of emerging OPCs beyond organophosphate esters (OPEs) hinders a thorough understanding of the environmental occurrence and exposure risks. Through target, suspect, and nontarget screening analysis, 64 OPCs were successfully identified in Chinese estuarine waters, including 24 known OPEs and 40 emerging analogues (i.e., quaternary phosphonium, phosphine oxide, organophosphonate, and organothiophosphate esters). Domestic wastewater and agricultural and industrial discharges were factors influencing the OPC distribution patterns. In particular, quaternary phosphoniums and phosphine oxides accounted for over 50% of the total OPC loading in the Yellow and Jia Rivers, which were likely polluted by phosphorus-related industries. Risk quotient (RQ) calculations showed that tetrabutylphosphonium contributed the most to algae toxicity due to the biocidal effects of onium salts, while chloroalkyl OPEs dominated the ecological risks for daphnia and fish. The multicriteria decision analysis approach was further introduced for relative chemical ranking by considering the variations in hazard criteria of environmental occurrence, fate, and toxicity of the OPCs. The results indicate that aryl phosphoniums and aryl phosphine oxides have a hazard priority similar to that of the OPEs and, therefore, require more attention.

Enhanced solid-liquid synergistic microextraction of nine bisphenols in serum using polyaniline functionalized metal-organic framework nanocomposites/methyl tert-butyl ether

Bisphenols, as a new class of environmental endocrine disruptors (EED), can interfere with the endocrine system of the human body and lead to various diseases. In this study, a novel polyaniline functionalized metal-organic framework (PANI@MIL-101@HF) was synthesized by utilizing hollow fibers (HF) as the the immobilization carrier, and combined with methyl tert-butyl ether (MTBE) for solid-liquid cooperative adsorption to determine bisphenols (BPs) in serum samples. The immobilized adsorbent exhibited excellent high stability and hydrophobicity. Furthermore, the inclusion of amino and benzene rings in PANI enhanced the adsorption efficiency of BPs through π-π and hydrogen bond interactions. Surprisingly, owing to the synergies of size exclusion effect of the MIL-101 and HF, the exclusion rate of protein reached as high as 99.2-99.9%. Based on its excellent adsorption properties and protein exclusion effect, the immobilized adsorbent PANI@MIL-101@HF was successfully used as a new restricted material for the high extraction performance with solid-liquid synergy of nine bisphenols (BPs) in serum samples. The operation process has also become more convenient without centrifuging. Integrated with ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), the nine BPs in serum samples have a wide linear range (2-200 ng mL-1) with low quantitative limits of 0.02 ng mL-1, and the recoveries ranged from 84.65 to 112.56%. The proposed method could be widely applied in convenient, green, and sensitive detection of endocrine disruptors from serum samples.

Assessing the environmental risks of sulfonylurea pollutants: Insights into the risk priority and structure-toxicity relationships

Sulfonylureas are widely used herbicides globally; however, the health risks associated with exposure to these compounds are poorly understood. This study used fuzzy clustering to categorize 44 sulfonylurea compounds into three risk priority levels (I, II, and III) and further investigated their structure-toxicity relationships. The order of the risk priority levels was level I＜level II＜level III. The pecking order of protein affinity was on the order of 104 M-1, which was consistent with the order of the risk priority levels. Moreover, toxic conjugations induced significant changes in protein conformation, with high-risk sulfonylurea causing substantial conformational changes. Given that the conformations of sulfonylurea within the reactive domain were highly similar, the patterns of toxic actions were considerably similar as well. Structure-toxicity relationship analysis indicated a positive correlation among Gibbs free energy change (ΔG°), affinity between sulfonylurea and protein, logarithm of the octanol-water partition coefficient (logKow), and risk priority. Specifically, a higher ΔG° value corresponded to stronger affinity, and a higher logKow value corresponded to a higher environment risk. The electronegativity of the aromatic ring on the left side of the sulfonylurea molecule is a key determinant influencing affinity - higher electronegativity of this aromatic ring weakened the affinity of sulfonylurea for protein and reduced the risk. When the aromatic ring on the left side of sulfonylurea was consistent, an increase in the electronegativity of the heterocyclic ring on the right side resulted in a stronger affinity for protein and an increased risk. This study provides a mechanistic foundation for evaluating the health risks associated with exposure to sulfonylurea.

Chemical exposure in females of childbearing age associated with sex hormones: Evidence from an untargeted exposomic approach

Exposure to organic chemicals can cause reproductive hormones disturbance in women. However, there is very limited evidence regarding real-world chemical exposures in reproductive-aged women and their joint effects on sex hormone levels. Here, we applied non-targeted screening workflow based on High-Performance Liquid Chromatography-High-Resolution Mass Spectrometry to investigate the serum chemical exposome of 156 women of childbearing age from Jinan, China. A total of 185 exogenous chemicals from 19 categories were identified in at least 80% of serum samples with confidence levels 1-3, 84 of which have never been reported in humans, and 9 of those showed active effects on multiple biological targets in ToxCast program. A combination of grouped weighted quantile sum regression (GWQS), weighted quantile sum regression (WQS), quantile g calculation (q g-comp), and Bayesian kernel machine regression (BKMR) models indicated significant associations of chemical mixture exposure with progesterone (P4), testosterone (T), and luteinizing hormone (LH)/follicle-stimulating hormone (FSH) ratios, and 7, 4, and 8 priority contributors were identified, respectively, such as fipronil sulfone for P4, dicyclohexyl phthalate for T, and 3-hydroxybenzyl alcohol for LH/FSH. Three chemicals closely related to androgen synthesis and metabolism were proposed. Restricted cubic spline curves showed that 10 of the 28 priority compound-hormone pairs displayed significant non-monotonic exposure-response relationships. This study provides more information on the chemical exposome in Chinese women of childbearing age and has important implications for understanding the effect of chemical co-exposure on sex hormone homeostasis in women.

Recent advancements in the synthesis of anion exchange membranes and their potential applications in wastewater treatment

Water treatment procedures are increasingly utilized for resource recovery and wastewater disinfection, addressing the current challenges of clean water depletion and wastewater management. Various pollutants, including dyes, acids, pharmaceuticals, and toxic heavy metals have been released into the environment through industrial, domestic, and agricultural activities, posing serious environmental and public health risks. Addressing these issues requires the development of more effective waste treatment processes. Membrane-based treatment technologies offer significant advantages, including high efficiency, versatility, and cost-effectiveness, making them a promising solution for mitigating the impact of these pollutants. In view of this, the potential of ion exchange membranes (IEMs) is continuously increasing due to their advanced characteristics compared to conventional techniques. Anion exchange membranes (AEMs), a special class of IEMs, selectively allow anions to pass through their pores due to the positive charge on their surface. This selective passage aids in resource recovery and removing specific types of pollutants. This review covers preparation methods, modification techniques, and classification of AEMs. It offers a practical classification based on the method of synthesis and structural properties of AEMs. The water-based applications of AEMs including, electrodialysis, diffusion dialysis, and electro-electrodialysis for various wastewater treatments such as heavy metal recovery, dye removal, pharmaceutical removal, and acid separation, have been discussed in detail. Additionally, the effect of various operational parameters on the performance and SWOT (strengths, weaknesses, opportunities, and threats) analysis of AEMs in effluent treatment are presented. The review provides detailed insights into the current status, challenges, and future directions of AEM-based technologies, offering suggestions for future advancements.

Evaluation of volatile safety in children's play mats based on non-targeted screening and risk prioritization

Given the widespread use of play mats and their close contact with children, it is crucial to identify potential chemical hazards associated with these products. In this study, 34 play mats, comprising four materials (3 EPE, 15 XPE, 5 PVC, 11 EVA), were subjected to non-targeted screening based on headspace gas chromatography-Orbitrap high-resolution mass spectrometry (HS-GC-Orbitrap HRMS), which screened out 71 volatile substances. The 20 significantly different substances were recognized by partial least squares discriminant analysis (PLS-DA), while the characteristic substances in each type of play mat were determined through clustering heat map and Venn diagram. To facilitate the rapid identification of high-risk substances, a risk scoring scheme was developed, taking into account detection rates, average peak areas, and substance hazardousness. The substances were then ranked based on their total risk scores. The distribution of peak areas for the top 14 high-risk substances, including α-methylstyrene, formamide, and toluene, in products was detailed, highlighting the need for further attention to these chemicals. Overall, the study found the volatile chemical safety of the four play mat types to be in the order of EPE > XPE > PVC > EVA. The differentiation analysis and risk scoring scheme proposed in this paper provide significant insights for the efficient regulation and quality improvement of play mats and other products.

Dialogue between algorithms and soil: Machine learning unravels the mystery of phthalates pollution in soil

Soil is a major environmental sink for the emerging organic pollutants phthalates (PAEs), and the determination of key factors influencing PAEs accumulation in soil is crucial for agricultural sustainability and food security. Aiming at the time-consuming and inefficient characteristics of traditional batch experiments and statistical prediction models in comprehensively capturing PAEs dynamics in soil, an intelligent analysis framework based on machine learning was proposed and developed. In this study, thirty features were incorporated, including soil PAEs-concentrations, pollutant emissions, agricultural inputs, soil physicochemical properties, and climatic parameters. Six data-driven machine learning models were established: Random Forest Regression (RFR), Gradient Boosting Regression Tree (GBRT), Extreme Gradient Boosting (XGBoost), Multilayer Perceptron (MLP), Support Vector Regression (SVR), and k-Nearest Neighbors (KNN). Results showed that the MLP model exhibited optimal performance in predicting soil PAEs concentrations (R²=0.8637), followed by SVR (R²=0.8132) and XGBoost (R²=0.8096). Through feature importance analysis, it was determined that hydrometeorological factors, soil moisture conditions, and nutritional characteristics were the key factors controlling PAEs spatial distribution. Furthermore, non-linear effect analysis elucidated significant synergistic interactions among these environmental covariates. The spatiotemporal prediction model revealed continuous declining trends in PAEs pollution levels in eastern coastal regions over the next 5-10 years, while accumulation tendencies were observed in inland provinces particularly in Guizhou. This study demonstrates the effectiveness and advantages of machine learning in predicting soil PAEs-pollution, providing a new perspective for pollutant risk assessment and management in the era of environmental big data.

Unveiling emerging polycyclic aromatic compounds in the urban atmospheric particulate matter

Despite the ubiquity and complexity of atmospheric polycyclic aromatic compounds (PACs), many of these compounds are largely unknown and lack sufficient toxicity data for comprehensive risk assessments. In this study, nontarget screening assisted by in-house and self-developed spectra databases was, therefore, employed to identify PACs in atmospheric particulate matter collected from multiple outdoor settings. Additionally, absorption, distribution, metabolism, excretion, and toxicity properties were evaluated to indicate PAC's overall abilities to cause adverse outcomes and incorporated into a novel health risk assessment model to assess their inhalation risks. Here, except for target PACs, 98 PAC analogues across eight categories were identified in the outdoor samples of atmospheric particulate matter. Their concentrations were source-specific and correlated to that of the total 16 priority polycyclic aromatic hydrocarbons (PAHs). Virtual high-throughput screening results suggested that metabolism disruption and endocrine disruption might be significant non-carcinogenic effects caused by the PACs. However, PAHs and oxygenated PAHs exhibited stronger overall abilities to induce non-carcinogenic adverse outcomes in human body when compared to the other PACs. Among PACs, total PAHs exhibited the highest carcinogenic and non-carcinogenic risks, while emerging PAHs accounted for 47% and 27% of total carcinogenic and non-carcinogenic risks, respectively. This study advances our understanding of the potential harmful effects of PACs and provides insights into mitigating the inhalation risks from complex PAC exposures based on classified risk levels.

Unravel the in-Source Fragmentation Patterns of Per- and Polyfluoroalkyl Substances during Analysis by LC-ESI-HRMS

In-source fragmentation (ISF) was inevitable during electrospray ionization (ESI) of per- and polyfluoroalkyl substances (PFAS) when analyzed by liquid chromatography coupled with mass spectrometry (LC-MS), resulting in reduced response of molecular ions and misannotation of MS features. Herein, we analyzed 82 PFAS across 12 classes to systematically identify the structures with ISF potentials and reveal the fragmentation pathways. We found up to 100% ISF for 38 PFAS in six classes, which all contain the carboxylate (CO2-) headgroup, including perfluoro(di)carboxylates (PF(di)CA), omega H/Cl substituted PFCA (ωH/Cl-PFCA), fluorotelomer carboxylates, and perfluoroalkyl ether carboxylates (PFECA). Seven ISF pathways were identified, including direct cleavage of C-CO2-, C-O, and C-C bonds and eliminations of HF/CO2HF through cyclic transition states by the mechanisms of β-elimination, McLafferty rearrangement, or H···F bridging. We found that the loss of CO2 is a prerequisite for most other pathways, explaining the absence of ISF for PFAS without a CO2- headgroup. The elevated bond dissociation energy of C-CO2- explained the reduced ISF for long-chain PFCA and ωH-PFCA. Raising the MS vaporizer and ion transfer tube temperatures significantly aggravated the ISF of most PFAS. These findings provide valuable references to inform the structural identification of PFAS and their degradation products.

First Evidence of Novel Organothiophosphate Esters as Prevalent New Pollutants in Dust from Automotive Repair Shops Discovered by High-Resolution Mass Spectrometry

The occurrence of organophosphorus compounds has garnered global concern due to their widespread production and potential environmental risks. Limited structural information has hindered a comprehensive understanding of their composition. By characteristic fragmentation-based nontarget analysis, the occurrence and composition of organothiophosphate esters (OTPEs), which are antiwear additives in lubricant oils that have received little attention previously, were investigated in dust from automotive repair shops and surrounding buildings. Fourteen OTPEs were tentatively identified, including four triarylphosphorothionates, six O,O-dialkyl phosphorothioates, and four O-alkyl O-alkyl sulfone phosphorothioates, among which four OTPEs were further confirmed by authentic standards or an industrial product. Triphenyl phosphorothioate (TPhPt) and tris(2,4-di-tert-butylphenyl) phosphorothioate (AO168=S) were prevalently detected in automotive repair shops with median concentrations of 230 and 246 ng/g, respectively, closely comparable to triphenyl phosphate (TPhP, median concentration: 302 ng/g). O,O-Dihexyl phosphorothioate (DHPt), O,O-dioctyl phosphorothioate (DOPt), O-hexyl O-hexyl sulfone phosphorothioate (DHSPt), and O-octyl O-octyl sulfone phosphorothioate (DOSPt) were the abundant analogues in automotive repair shops with semiquantitative median concentrations in the range of 119-1.05 × 103 ng/g. Hierarchical cluster analysis showed that OTPEs exhibited similar distribution patterns across automotive repair shops, indicating that these chemicals had similar sources. Moreover, the concentrations of OTPEs were usually higher in automotive repair shops than that in surrounding buildings, suggesting a motor vehicle related emission source. To our knowledge, 12 out of the 14 detected OPTEs were reported in the environment for the first time. The discovery of these OTPEs expanded the scope of known organophosphorus pollutants, highlighting the potential contaminants of OTPEs from lubricant oils for automotive and industrial applications.

Cooperative Molecular Interaction-Based Highly Efficient Capturing of Ultrashort- and Short-Chain Emerging Per- and Polyfluoroalkyl Substances Using Multifunctional Nanoadsorbents

The short-chain (C4 to C7) and ultrashort-chain (C3 to C2) per- and polyfluoroalkyl substances (PFAS) are bioaccumulative, carcinogenic to humans, and harder to remove using current technologies, which are often detected in drinking and environmental water samples. Herein, we report the development of nonafluorobutanesulfonyl (NFBS) and polyethylene-imine (PEI)-conjugated Fe3O4 magnetic nanoparticle-based magnetic nanoadsorbents and demonstrated that the novel adsorbent has the capability for highly efficient removal of six different short- and ultrashort-chain PFAS from drinking and environmental water samples. Reported experimental data indicates that by capitalizing the cooperative hydrophobic, fluorophilic, and electrostatic interaction processes, NFBS-PEI-conjugated magnetic nanoadsorbents can remove ∼100% short-chain perfluorobutanesulfonic acid within 30 min from the water sample with a maximum absorption capacity q m of ∼234 mg g-1. Furthermore, to show how cooperative interactions are necessary for effective capturing of ultrashort and short PFAS, a comparative study has been performed using PEI-attached magnetic nanoadsorbents without NFBS and acid-functionalized magnetic nanoadsorbents without PEI and NFBS. Reported data show that the ultrashort-chain perfluoropropanesulfonic acid capture efficiency is the highest for the NFBS-PEI-attached nanoadsorbent (q m ∼ 187 mg g-1) in comparison to the PEI-attached nanoadsorbent (q m ∼ 119 mg g-1) or carboxylic acid-attached nanoadsorbent (q m ∼ 52 mg g-1). In addition, the role of cooperative molecular interactions in highly efficient removal of ultrashort-chain PFAS has been analyzed in detail. Moreover, reported data demonstrate that nanoadsorbents can be used for effective removal of short-chain PFAS (<92%) and ultrashort-chain PFAS (<70%) simultaneously from reservoir, lake, tape, and river water samples within 30 min, which shows the potential of nanoadsorbents for real-life PFAS remediation.

Identifying Organic Chemicals with Acetylcholinesterase Inhibition in Nationwide Estuarine Waters by Machine Learning-Assisted Mass Spectrometric Screening

Neurotoxicity is frequently observed in the global aquatic environment, threatening aquatic ecosystems and human health. However, a very limited proportion of neurotoxic effects (∼1%) has been explained by known chemicals of concern. Here, we integrated machine learning, nontargeted analysis, and in vitro biotesting to identify neurotoxic drivers of acetylcholinesterase (AChE) inhibition in estuarine waters along the coast of China. Machine learning was used to predict AChE inhibitors in a large chemical space. The prediction output was profiled into a suspect screening list to guide high-resolution mass spectrometry (HRMS) screening of AChE inhibitors in estuarine water samples. Ultimately, 60 chemicals with diverse known and presently unknown structures were identified, explaining 82.1% of the observed AChE inhibition. Polyunsaturated fatty acids were unexpectedly found to be neurotoxic drivers, accounting for 80.5% of the overall effect. This proof-of-concept study demonstrates that machine learning-based toxicological prediction can achieve a virtual fractionation role to pinpoint HRMS features with the bioactivity potential. Our approach is expected to enable rapid and comprehensive screening of organic pollutants associated with various in vitro end points for large-scale monitoring of water quality.

Organophosphate esters in vehicle interior dust from Chinese urban areas: What are the influencing factors of the occurrence?

Organophosphate esters (OPEs) are a class of semi-volatile organic compounds frequently used to various products as flame retardants and plasticizers. As emerging pollutants, OPEs have attracted significant attention due to their potential impacts on human health and ecosystems. This study investigated the occurrence of OPEs in vehicle interior dust across 36 cities in China. The primary aims were to explore the correlations among OPE pollutants, identify potential emission sources, and examine the key factors influencing their distribution. The OPE concentrations ranged from 5450 ng/g to 63,700 ng/g, with the content of three categories of OPEs as follows: ΣChlorinated-OPEs (median: 17420 ng/g) > ΣAlkyl-OPEs (median: 3880 ng/g) > ΣAryl-OPEs (median: 1490 ng/g). In northern China, the aggregate concentration of OPEs in vehicle interior dust demonstrated higher levels compared to those in the western and mid-southeastern region, with the later two appeared to be comparable to each other. Coastal and inland cities displayed variations in OPE levels, with different representative OPEs. The occurrence of OPEs in vehicle interior dust was closely associated with regional economic development levels, motor vehicle parc, and road density. In contrast to other urban areas, first-tier cities showed the highest aggregate levels of OPEs in vehicle interior dust, with a significant increase observed specifically in the concentrations of Alkyl-OPEs and Aryl-OPEs.

Task decomposition strategy based on machine learning for boosting performance and identifying mechanisms in heterogeneous activation of peracetic acid process

Heterogeneous activation of peracetic acid (PAA) process is a promising method for removing organic pollutants from water. Nevertheless, this process is constrained by several complex factors, such as the selection of catalysts, optimization of reaction conditions, and identification of mechanism. In this study, a task decomposition strategy was adopted by combining a catalyst and reaction condition optimization machine learning (CRCO-ML) model and a mechanism identification machine learning (MI-ML) model to address these issues. The Categorical Boosting (CatBoost) model was identified as the best-performing model for the dataset (1024 sets and 7122 data points) in this study, achieving an R2 of 0.92 and an RMSE of 1.28. Catalyst composition, PAA dosage, and catalyst dosage were identified as the three most important features through SHAP analysis in the CRCO-ML model. The HCO3- is considered the most influential water matrix affecting the k value. The errors between all reverse experiment results and the predictions of the CRCO-ML and MI-ML models were <10 % and 15 %, respectively. This interdisciplinary work provides novel insights into the design and application of the heterogeneous activation of PAA process, significantly contributing to the rapid development of this technology.

Comprehensive Characterization of Oxidative Stress-Modulating Chemicals Using GPT-Based Text Mining

The screening of hazardous environmental pollutants is hindered by the limited availability of toxicological databases. Large language model (LLM)-based text mining holds the potential to automatically extract complex toxicological information from the literature. Due to its relevance to diseases and the challenge of comprehensive characterization, oxidative stress serves as a suitable case for research by texting mining. In this study, a robust workflow utilizing a LLM (i.e., GPT-4) was developed to extract information on oxidative stress tests, including data collection, text preprocessing, prompt engineering, and performance evaluation procedures. A total of 17,780 relevant records were extracted from 7166 articles, covering 2558 unique compounds. A rising interest in oxidative stress was observed over the past two decades. A list of known prooxidants (n = 1416) and antioxidants (n = 1102) was established, with the leading chemical categories being pharmaceuticals, pesticides, and metals for prooxidants and pharmaceuticals and flavonoids for antioxidants. Structural alert analysis identified potential prooxidant (e.g., chlorobenzene, nitrobenzene, and tertiary amines) and antioxidant (e.g., flavonoid and thiol) substructures. These findings illustrate the feasibility of building toxicological databases through LLM-based text mining in a cost-efficient manner, and the information obtained from the technique holds significant promise for future applications in environmental and health research.

Metabolite identification of emerging disinfection byproduct dibromo-benzoquinone in vivo and in vitro: Multi-strategy mass-spectrometry annotation and toxicity characterization

Halobenzoquinones (HBQs) are emerging disinfection byproducts (DBPs) of high toxicity and also are shared active toxic intermediates of multiple halogenated organic pollutants. Due to the strong oxidizing property and electrophilicity, HBQs exhibit extremely diverse metabolism pathways in organisms. The identification of toxic-decisive metabolites is pivotal, albeit challenging, for understanding the toxicity mechanisms of HBQs. We employed dibromo-benzoquinone (DBBQ) as a representative HBQ, and established a systematic analytical strategy using high-resolution mass spectrometry, which collectively coupled suspect screening (SS), mass defect filtering (MDF), product ion filtering (PIF), isotopic signature filtering (ISF), and molecular networking (MN). As a result, 20 biotransformation products of DBBQ were identified in vivo and in vitro, involving metabolism reactions such as hydroxylation, methylation, methoxylation, acetylation, sulfonation, glucuronidation, glutathionylation, dimerization, and conjugation with amino acids or fatty acids. Quantitative structure-activity relationship (QSAR) analysis and cytotoxicity experiments consistently demonstrated the significantly high toxicity of the fatty acid conjugate compared to the parent compound DBBQ and other metabolites, pinpointing the important role of the fatty acid conjugation in determining the metabolism and toxicity of HBQs. The research conducted a comprehensive evaluation of the metabolism of a typical HBQ with the combination of multiple analytical and toxicity characterization methods, therefore screen out the most important metabolism pathway of HBQs.

Biomarker and adverse outcome pathway responses of Tubifex tubifex (sludge worm) exposed to environmentally-relevant levels of acenaphthene: insights from behavioral, physiological, and chemical structure-activity analyses

Polycyclic aromatic hydrocarbons (PAHs), including acenaphthene, pose a significant threat to aquatic ecosystems by harming vital organisms such as benthic invertebrates. This study evaluated the impact of environmentally relevant concentrations of acenaphthene on Tubifex tubifex, focusing on sublethal acute toxicity and subchronic biomarker responses. Key biomarkers assessed included histopathological changes and the modulation of antioxidant enzymes: catalase (CAT), superoxide dismutase (SOD), glutathione S-transferase (GST), and malondialdehyde (MDA). Additionally, the study examined structure-activity relationships and species sensitivity distribution (SSD). Concentrations exceeding the solubility threshold of acenaphthene (3.9 mg/L) triggered distinct, concentration-dependent behavioral responses in Tubifex tubifex, such as clumping, mucus secretion, and body wrinkling. Prolonged exposure exacerbated these behavioral dysfunctions, while subchronic exposure resulted in significant histopathological alterations, including epithelial hyperplasia, inflammation, edema, fibrosis, and degenerative changes. The edematic appearance of the body wall suggested a potential immune response to exposure. Furthermore, increased activities of CAT, SOD, and GST indicated oxidative stress in the worms. The study found a 1.5-fold increase in CAT and GST activity, a fivefold increase in SOD, and a striking 100-fold increase in MDA levels compared to controls, signifying an overwhelmed antioxidant defense system and potential cellular disruption. The SSD curve revealed hazard concentrations (HC50 and HC90), indicating that Tubifex tubifex exhibited lower sensitivity to acenaphthene compared to other taxa. In silico analysis and read-across models confirmed the potential of acenaphthene to induce significant oxidative stress upon exposure. The correlation between biomarker responses and structure-activity relationship analysis highlighted the aromatic nature of acenaphthene as a key factor in generating reactive metabolites, inhibiting antioxidant enzymes, and promoting redox cycling, ultimately contributing to adverse outcomes. These findings, coupled with behavioral responses and SSD curve inferences, underscore the importance of the solubility threshold of acenaphthene as a critical benchmark for evaluating its ecological impact in aquatic environments.

Viologen-Derived Covalent Organic Frameworks: Advancing PFAS Removal Technology with High Adsorption Capacity

The escalating presence of per- and polyfluoroalkyl substances (PFAS) in drinking water poses urgent public health concerns, necessitating effective removal. This study presents a groundbreaking approach, using viologen to synthesize covalent organic framework nanospheres: MELEM-COF and MEL-COF. Characterized by highly crystalline features, these nanospheres exhibit exceptional affinity for diverse anionic PFAS compounds, achieving simultaneous removal of multiple contaminants within 30 min. Investigating six anionic PFAS compounds, MEL- and MELEM-COFs achieved 90.0-99.0% removal efficiency. The integrated analysis unveils the synergistic contributions of COF morphology and functional properties to PFAS adsorption. Notably, MELEM-COF, with cationic surfaces, exploits electrostatic and dipole interactions, with a 2500 mg g-1 adsorption capacity-surpassing all reported COFs to date. MELEM-COF exhibits rapid exchange kinetics, reaching equilibrium within 30 min. These findings deepen the understanding of COF materials and promise avenues for refining COF-based adsorption strategies.

Occurrence of bisphenol A analogues in the aquatic environment and their behaviors and toxicity effects in plants

Continuous technological and economic development has led to the extensive use of bisphenol A analogues (BPs) in products, leading to their release to aquatic environments and posing threats to aquatic plants. However, few papers have systemically reviewed the interactions between BPs and aquatic plants. This review comprehensively summarizes the properties, occurrence, fate, and hazardous influences of BPs on aquatic plants. BPs have been widely detected in the global aquatic environment, with concentrations generally ranging from a lower range of ng/L or ng/g to an upper range of μg/L or μg/g in surface water, groundwater, seawater, and sediments. Aquatic plants effectively uptake and translocate BPs, and metabolize them into new compounds. Meanwhile, BPs exposures have diverse toxic effects on the growth, photosynthesis, antioxidant, phytohormones, and structural integrity of aquatic plants. High-throughput omics assays provide significant evidence showing how BPs disturb gene transcription, proteins, and metabolism in plants. This review highlights the need for increased attention on the effects of emerging BPA alternatives, joint treatment, long-term exposure with environmental relevant doses, and potential hazards posed by ingesting polluted plants.

Environmental impact and source-controlled approaches for emerging micropollutants: Current status and future prospects

Emerging micropollutants, originating from diverse sources, including pharmaceutical, pesticides, and industrial effluents, are a serious environmental concern. Their presence in natural water bodies has negative effects on ecosystems and human health. To address this issue, the importance of a source-controlled approach has grown, highlighting the use of advanced technologies such as oxidation processes, membrane filtration, and adsorption to prevent micropollutants from entering the environment. Therefore, this review provides a comprehensive overview of emerging micropollutants, their analytical detection methods, and their environmental impacts, with a focus on aquatic ecosystems, human health, and terrestrial environments. It also highlights the importance of using a source-controlled approach and provides insights into the benefits and drawbacks of this strategy. The primary micropollutants identified in this review were erythromycin, ibuprofen, and triclocarban, originating from the pharmaceutical industries for their use as antibiotics, analgesic, and antibacterial drugs. The primary analytical methods used for detection involved hybrid techniques that integrate chromatography with spectroscopy. Thus, this review emphasizes the source-controlled approach's benefits and drawbacks, focusing on emerging micropollutants, their detection, and impacts on ecosystems and health.

DbGTi protein attenuates chromium (VI)-induced oxidative stress via activation of the Nrf2/HO-1 signalling pathway in zebrafish (Danio rerio) larval model

Hexavalent chromium (Cr (VI)) contamination poses a significant threat to environmental and human health due to its ability to induce oxidative stress. Conventional strategies to counter Cr (VI)-induced oxidative stress, like antioxidants and chelating agents, face efficacy limitations and adverse effects. The present study is intended to counteract the limitations of conventional strategies by introducing a trypsin inhibitor isolated from Dioscorea bulbifera L. tubers, known as DbGTi protein, against Cr (VI)-induced developmental toxicity and oxidative stress. Through a comprehensive array of biochemical assays, behavioural tests, and gene expression analyses, this study interprets the underlying mechanisms of the DbGTi protein. Results demonstrated that the DbGTi protein effectively restored antioxidant defense systems, including superoxide dismutase (SOD), catalase (CAT), glutathione (GSH), glutathione S-transferase (GST), and glutathione peroxidase (GTPx), thereby mitigating cellular damage, reducing cell death, and enhancing neuro-biomarkers. qRT-PCR analysis of mRNA expression profiling revealed the upregulation of genes associated with antioxidant defense (sod, cat, gpx) and defense pathway (nrf2, hmox-1a), further highlighting the protective effects of DbGTi protein against Cr (VI)-induced oxidative stress.

Nontarget analysis and characterization of p-phenylenediamine-quinones and -phenols in tire rubbers by LC-HRMS and chemical species-specific algorithm

BACKGROUND

N,N'-disubstituted p-phenylenediamine-quinones (PPDQs) are oxidization derivatives of p-phenylenediamines (PPDs) and have raised extensive concerns recently, due to their toxicities and prevalence in the environment, particularly in water environment. PPDQs are derived from tire rubbers, in which other PPD oxidization products besides reported PPDQs may also exist, e.g., unknown PPDQs and PPD-phenols (PPDPs).

RESULTS

This study implemented nontarget analysis and profiling for PPDQ/Ps in aged tire rubbers using liquid chromatography-high-resolution mass spectrometry and a species-specific algorithm. The algorithm took into account the ionization behaviors of PPDQ/Ps in both positive and negative electrospray ionization, and their specific carbon isotopologue distributions. A total of 47 formulas of PPDQ/Ps were found and elucidated with tentative or accurate structures, including 25 PPDQs, 18 PPDPs and 4 PPD-hydroxy-quinones (PPDHQs). The semiquantified total concentrations of PPDQ/Ps were 14.08-30.62 μg/g, and the concentrations followed the order as: PPDPs (6.48-17.39) > PPDQs (5.86-12.14) > PPDHQs (0.16-1.35 μg/g).

SIGNIFICANCE

The high concentrations and potential toxicities indicate that these PPDQ/Ps could seriously threaten the eco-environment, as they may finally enter the environment, accordingly requiring further investigation. The analysis strategy and data-processing algorithm can be extended to nontarget analysis for other zwitterionic pollutants, and the analysis results provide new understandings on the environmental occurrence of PPDQ/Ps from source and overall perspectives.

Solar Cell Enhancement from Supercritical CO2 Dye Surface Modification of Mesoporous TiO2 Photoanodes

In recent years, in an effort to reach Net Zero Emissions, there has been growing interest by various academic and industry communities to develop chemicals and industrial processes that are circular, sustainable and green. We report the rapid, simple and effective surface modification of a porous metal oxide with organic dyes using supercritical carbon dioxide (scCO2). Titanium dioxide (TiO2) photoanodes were coated in very short times, under mild conditions and the excess dye recovered afterwards for reuse. The process obviates the need for conventional toxic solvents, the generation of unwanted waste streams, and more importantly, we see an unexpected device performance enhancement of 212 and 163 % for TerCOOTMS, 2 a and TerCN/COOTBDMS, 4 dyes, respectively, when compared to the conventional solvent deposition method.

Integrated Transfer Learning and Multitask Learning Strategies to Construct Graph Neural Network Models for Predicting Bioaccumulation Parameters of Chemicals

Accurate prediction of parameters related to the environmental exposure of chemicals is crucial for the sound management of chemicals. However, the lack of large data sets for training models may result in poor prediction accuracy and robustness. Herein, integrated transfer learning (TL) and multitask learning (MTL) was proposed for constructing a graph neural network (GNN) model (abbreviated as TL-MTL-GNN model) using n-octanol/water partition coefficients as a source domain. The TL-MTL-GNN model was trained to predict three bioaccumulation parameters based on enlarged data sets that cover 2496 compounds with at least one bioaccumulation parameter. Results show that the TL-MTL-GNN model outperformed single-task GNN models with and without the TL, as well as conventional machine learning models trained with molecular descriptors or fingerprints. Applicability domains were characterized by a state-of-the-art structure-activity landscape-based (abbreviated as ADSAL) methodology. The TL-MTL-GNN model coupled with the optimal ADSAL was employed to predict bioaccumulation parameters for around 60,000 chemicals, with more than 13,000 compounds identified as bioaccumulative chemicals. The high predictive accuracy and robustness of the TL-MTL-GNN model demonstrate the feasibility of integrating the TL and MTL strategy in modeling small-sized data sets. The strategy holds significant potential for addressing small data challenges in modeling environmental chemicals.

Transforming contaminant ligands at water-solid interfaces via trivalent metal coordination

In environmental matrices, the migration and distribution of contaminants at water-solid interfaces play a crucial role in their capture or dissemination. Scientists working in environmental remediation and wastewater treatment are increasingly aware of metal-contaminant coordination; however, interfacial behaviors remain underexplored. Here, we show that trivalent metal ions (e.g. Al3+ and Fe3+) mediate the migration of pollutant ligands (e.g. tetracycline (TC) and ofloxacin) to the organic solid interface. In the absence of Al3+, humic acid (HA) colloids (50 mg/L) capture 26.1 % of the TC in water (initial concentration: 10 mg/L) via weak intermolecular interactions (binding energy: -5.71 kcal/mol). Adding Al3+ (2.5 mg/L) significantly enhances the binding of TC to an impressive 94.2 % via Al3+ mediated coordination (binding energy: -84.89 kcal/mol). The significant increase in binding energy results in superior interfacial immobilization. However, excess free Al3+ competes for TC binding via direct binary coordination, as confirmed based on the unique fluorescence of Al3+-TC complexes. Density functional theory calculations reveal the intricate process of HA-Al3+ binding via carboxyl and phenolic hydroxyl sites. The HA-Al3+ flocs then leverage the remaining coordination capacity of Al3+ to chelate with TC. As well as providing insights into the pivotal role of metal ion on the self-purification of natural water bodies, our findings on the interfacial behavior of metal-contaminant coordination will propel coagulation technology to the capture of microscale pollutants.

Integration of Nontarget Screening and QSPR Models to Identify Novel Organophosphate Esters of High Priority in Aquatic Environment

With the development of large numbers of novel organophosphate esters (OPEs) alternatives, it is imperative to screen and identify those with high priority. In this study, surface water, biofilms, and freshwater snails were collected from the flow-in rivers of Taihu Lake Basin, China. Screened by target, suspect, and nontarget analysis, 11 traditional and 14 novel OPEs were identified, of which 5 OPEs were first discovered in Taihu Lake Basin. The OPE concentrations in surface water ranged from 196 to 2568 ng/L, with the primary homologue tris(2,4-ditert-butylphenyl) phosphate (TDtBPP) being newly identified, which was likely derived from the transformation of tris(2,4-ditert-butylphenyl) phosphite. The majority of the newly identified OPEs displayed substantially higher bioaccumulation and biomagnification potentials in the biofilm-snail food chain than the traditional ones. Quantitative structure-property relationship models revealed both hydrophobicity and polarity influenced the bioaccumulation and biomagnification of the OPEs, while electrostatic attraction also had a contribution to the bioaccumulation in the biofilm. TDtBPP was determined as the utmost priority by toxicological priority index scheme, which integrated concentration, bioaccumulation, biomagnification, acute toxicity, and endocrine disrupting potential of the identified OPEs. These findings provide novel insights into the behaviors of OPEs and scientific bases for better management of high-risk pollutants in aquatic ecosystem.

Insight into the molecular recognition of human and polar bear pregnane X receptor by three organic pollutants using molecular docking and molecular dynamics simulations

Pregnane X receptor (PXR) is a heterologous biosensor that is involved in the metabolic pathway of environmental pollutants, regulating the transcription of genes involved in biotransformation. There are significant differences in the selectivity and specificity of organic pollutants (OPs) toward polar bear PXR (pbPXR) and human PXR (hPXR), but the detailed dynamical characteristics of their interactions are unclear. Homology Modeling, molecular docking, molecular dynamics simulation, and free energy calculation were used to analyze the recognition of pbPXR and hPXR by three OPs: BPA, chlordane and toxaphene. Comparing interaction patterns along with binding free energy of pbPXR and hPXR with these three OPs revealed that although pbPXR and hPXR interact similar with these three OPs, these OPs have different effects on the internal dynamics of pbPXR and hPXR. This results in significant alterations in the interaction of key residues near Leu209, Met243, Phe288, Met323, and His407 with OPs, thereby influencing their binding energy. Non-polar interactions, especially van der Waals interactions, were found to be the dominating factors in interacting of these OPs with PXRs. The region surrounding these key residues facilitates hydrophobic contacts with PXR, which are crucial for the selective activation of PXRs in different species by these three OPs. These findings are of significant guidance in understanding the impacts of environmental endocrine disruptors on different organisms.

High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage

In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

Highly sensitive response to the toxicity of environmental chemicals in transparent casper zebrafish

The response sensitivity to toxic substances is the most concerned performance of animal model in chemical risk assessment. Casper (mitfaw2/w2;mpv17a9/a9), a transparent zebrafish mutant, is a useful in vivo model for toxicological assessment. However, the ability of casper to respond to the toxicity of exogenous chemicals is unknown. In this study, zebrafish embryos were exposed to five environmental chemicals, chlorpyrifos, lindane, α-endosulfan, bisphenol A, tetrabromobisphenol A (TBBPA), and an antiepileptic drug valproic acid. The half-lethal concentration (LC50) values of these chemicals in casper embryos were 62-87 % of that in the wild-type. After TBBPA exposure, the occurrence of developmental defects in the posterior blood island of casper embryos was increased by 67-77 % in relative to the wild-type, and the half-maximal effective concentration (EC50) in casper was 73 % of that in the wild-type. Moreover, the casper genetic background significantly increased the hyperlocomotion caused by chlorpyrifos and lindane exposure compared with the wild-type. These results demonstrated that casper had greater susceptibility to toxicity than wild-type zebrafish in acute toxicity, developmental toxicity and neurobehavioral toxicity assessments. Our data will inform future toxicological studies in casper and accelerate the development of efficient approaches and strategies for toxicity assessment via the use of casper.

Contamination Profiles of Selected Pollutants in Procambarus clarkii Non-Edible Portions Highlight Their Potential Exploitation Applications

Properly managing aquatic organisms is crucial, including protecting endemic species and controlling invasive species. From a circular economy perspective, the sustainable use of aquatic species as a source of bioactive molecules is an area that is increasingly being explored. This includes the use of non-edible portions of seafood, which could pose considerable risks to the environment due to current methods of disposal. Therefore, it is of paramount importance to ensure that the exploitation of these resources does not result in the transfer of pollutants to the final product. This study analyzed two types of non-edible parts from the crayfish Procambarus clarkii: the abdominal portion of the exoskeleton (AbE) and the whole exoskeleton (WE), including the cephalothorax. These portions could potentially be utilized in the context of eradication activities regulated by local authorities. A screening analysis of four classes of pollutants, including pesticides, per- and polyfluoroalkyl substances (PFAS), phthalic acid esters (PAEs), and trace elements (TEs), was performed. The only analytes detected were TEs, and significant differences in the contamination profile were found between AbE and WE. Nevertheless, the levels recorded were comparable to or lower than those reported in the literature and below the maximum levels allowed in the current European legislation for food, suggesting that their potential use is legally permitted. In terms of scalability, the utilization of the entire non-edible P. clarkii portion would represent a sustainable solution for the reuse of waste products.

Occurrence and Distribution of Antibacterial Quaternary Ammonium Compounds in Chinese Estuaries Revealed by Machine Learning-Assisted Mass Spectrometric Analysis

Antimicrobial resistance (AMR) undermines the United Nations Sustainable Development Goals of good health and well-being. Antibiotics are known to exacerbate AMR, but nonantibiotic antimicrobials, such as quaternary ammonium compounds (QACs), are now emerging as another significant driver of AMR. However, assessing the AMR risks of QACs in complex environmental matrices remains challenging due to the ambiguity in their chemical structures and antibacterial activity. By machine learning prediction and high-resolution mass spectrometric analysis, a list of antibacterial QACs (n = 856) from industrial chemical inventories is compiled, and it leads to the identification of 50 structurally diverse antibacterial QACs in sediments, including traditional hydrocarbon-based compounds and new subclasses that bear additional functional groups, such as choline, ester, betaine, aryl ether, and pyridine. Urban wastewater, aquaculture, and hospital discharges are the main factors influencing QAC distribution patterns in estuarine sediments. Toxic unit calculations and metagenomic analysis revealed that these QACs can influence antibiotic resistance genes (particularly sulfonamide resistance genes) through cross- and coresistances. The potential to influence the AMR is related to their environmental persistence. These results suggest that controlling the source, preventing the co-use of QACs and sulfonamides, and prioritizing control of highly persistent molecules will lead to global stewardship and sustainable use of QACs.

Environment consistently impact on aquaculture: The predominant source of residual pollutants in cultured Chinese mitten crab (Eriocheir sinensis) across China

Advancements in monitoring and operation of aquaculture environments has minimized the concentrations of some residual pollutants in cultured aquatic products. However, currently most aquatic products are "farmed", and relationships among residual pollutants in tissues of crabs were still unclear. In this study, 64 typical pollutants, including 25 antibiotics, 15 metal, 23 organochlorine pesticides, and one dioxin-like compound inducing hydrocarbon-receptor (AHR) activity were measured in Chinese mitten crab (Eriocheir Sinensis) risks of consumption assessed and ranked. The superposition of properties including severity and relative potency of effects and parameters describing persistence and exposure along with rates of usage and identification of groups most likely to be exposed were assessed in combination to rank likelihood of dietary exposure and probabilities of adverse effects for each contaminant. The results indicated that the total scores per pollutants found that Cadmium (Cd), Heptachlor epoxide (HEPE), dioxin TEQ exhibited the greatest scores and explained the severity of dietary risk, while source analysis found that the three main pollutants resulted from the ambient environment and are not due to specific aquaculture processes. In summary, environment is still the predominant source of residual pollutants in cultured Chinese mitten crab across China.

Nontarget Discovery of Per- and Polyfluoroalkyl Sulfonyl Halides in Soils by Integration of Derivatization and Specific Fragment-Based Liquid Chromatography-High Resolution Mass Spectrometry Screening

Though long recognized as synthetic precursors to other poly- and perfluoroalkyl substances (PFASs), most poly- and perfluoroalkyl sulfonyl halides (PASXs) cannot be directly measured and have generally received minimal attention. Inspired by the redox reaction between sulfonyl halide groups and p-toluenethiol in organic chemistry, we developed a novel nontarget analysis strategy for PASXs by intergrating derivatization and specific fragment-based liquid chromatography-high resolution mass spectrometry screening for m/z 82.961 [SO2F-] and m/z 95.934 [S2O2-]. By using this strategy, we discovered 11 PASXs, namely, perfluoroalkyl sulfonyl fluorides (5), polyfluoroalkyl sulfonyl fluorides (2), unsaturated perfluoroalkyl sulfonyl fluoride (1), and perfluoroalkyl sulfonyl chlorides (3) in soil samples collected from an abandoned fluorochemical manufacturing park. These average ∑PASXs concentrations were 1120 μg kg-1 (range: 9.7-9860 μg kg-1), which were very likely to be the key intermediates and undesired byproducts of electrochemical fluorination processes. Spatial variation in the mass ratio of ∑PASXs to ∑PFSAs (range: 0.7-795%) also indicates their different transportation pathways. More importantly, the decline of PASXs and increase of perfluoroalkyl sulfonates (when compared to a prior study at this site) suggest the continued hydrolysis of PASXs and the relatively fast environmental transformation rates in the abandoned fluorochemical park soils. Overall, these findings demonstrated the utility of a novel nontarget analysis strategy, which may change most PASXs from inferred precursors to measured intermediates and further could be adapted for structures, distribution, and transformation studies of PFASXs in other matrices.

High-Efficiency Effect-Directed Analysis Leveraging Five High Level Advancements: A Critical Review

Organic contaminants are ubiquitous in the environment, with mounting evidence unequivocally connecting them to aquatic toxicity, illness, and increased mortality, underscoring their substantial impacts on ecological security and environmental health. The intricate composition of sample mixtures and uncertain physicochemical features of potential toxic substances pose challenges to identify key toxicants in environmental samples. Effect-directed analysis (EDA), establishing a connection between key toxicants found in environmental samples and associated hazards, enables the identification of toxicants that can streamline research efforts and inform management action. Nevertheless, the advancement of EDA is constrained by the following factors: inadequate extraction and fractionation of environmental samples, limited bioassay endpoints and unknown linkage to higher order impacts, limited coverage of chemical analysis (i.e., high-resolution mass spectrometry, HRMS), and lacking effective linkage between bioassays and chemical analysis. This review proposes five key advancements to enhance the efficiency of EDA in addressing these challenges: (1) multiple adsorbents for comprehensive coverage of chemical extraction, (2) high-resolution microfractionation and multidimensional fractionation for refined fractionation, (3) robust in vivo/vitro bioassays and omics, (4) high-performance configurations for HRMS analysis, and (5) chemical-, data-, and knowledge-driven approaches for streamlined toxicant identification and validation. We envision that future EDA will integrate big data and artificial intelligence based on the development of quantitative omics, cutting-edge multidimensional microfractionation, and ultraperformance MS to identify environmental hazard factors, serving for broader environmental governance.

Positive profile of natural small molecule organic matters on emerging antivirus pharmaceutical elimination in advance reduction process: A deep dive into the photosensitive mechanism of triplet excited state compounds

Natural small molecular organic matter (NSOM), ubiquitous in natural waters and distinct from humic acid or fulvic acid, is a special type of dissolved organic matter (DOM) which is characterized as strong photosensitivity and simple molecular structure. However, little study had been directed on the role of NSOM in eliminating emerging contaminants in advanced reduction process (ARP). This study took three small molecular isomeric organic acids (p-hydroxybenzoic acid, pHBA; salicylic acid, SA; m-hydroxybenzoic acid, mHBA) as the representative substances of NSOM to explore these mechanisms on promoting Ribavirin (RBV, an anti COVID-19 medicine) degradation in ultraviolet activated sulfite (UV/Sulfite) process. The results demonstrated that the observed degradation rate constant of RBV (kobs-RBV) was 7.56 × 10-6 s-1 in UV/Sulfite process, indicating that hydrated electron (eaq-) from UV/Sulfite process could not effectively degrade RBV, while it increased by 178 and 38 times when pHBA and SA were introduced into UV/Sulfite process respectively, suggesting that pHBA and SA strongly promoted RBV degradation while mHBA had no promotion on RBV abatement in UV/Sulfite process. Transient absorption spectra and reactive intermediates scavenging experiment indicated that the triplet excited state pHBA and SA (3pHBA* and 3SA*) contributed to the degradation of RBV through non-radical process. Notably, eaq- played the role of key initiator in transforming pHBA and SA into their triplet states. The difference of kobs-RBV in UV/Sulfite/pHBA and UV/Sulfite/SA process was attributed to different generation pathways of 3pHBA* and 3SA* (high molar absorptivity at the wavelength of 254 nm and photosensitive cycle, respectively) and their second order rate constants towards RBV (kRBV-3pHBA* = 8.60 × 108 M-1 s-1 and kRBV-3SA* = 6.81 × 107 M-1 s-1). mHBA could not degrade RBV for its lack of intramolecular hydrogen bond and low molar absorptivity at 254 nm to abundantly transform into its triplet state. kobs-RBV increased as pH increased from 5.0 to 11.0 in UV/Sulfite/SA process, due to the high yield of eaq- in alkaline condition which promoted the generation of 3SA* and the stable of the absorbance of SA at 254 nm. By contrast, kobs-RBV underwent a process of first increasing and then decreasing in UV/Sulfite/pHBA process as the increase of pH, and its highest value achieved in a neutral condition. This lied in the exposure of eaq- increased as the increase of pH which promoted the generation of 3pHBA*, while the molar absorptivity of pHBA at 254 nm decreased as the increase of pH in an alkaline condition which inhibited the yield of 3pHBA*. The RBV degradation pathways and products toxicity assessment indicated that UV/Sulfite/pHBA had better detoxification performance on RBV than UV/Sulfite/SA process. This study disclosed a novel mechanism of emerging contaminants abatement through non-radical process in NSOM mediated ARP, and provide a wide insight into positive profile of DOM in water treatment process, instead of only taking DOM as a quencher of reactive intermediates.

Exploring Prenatal Exposure to Halogenated Compounds and Its Relationship with Birth Outcomes Using Nontarget Analysis

Halogenated organic compounds (HOCs) are a class of contaminants showing high toxicity, low biodegradability, and high bioaccumulation potential, especially chlorinated and brominated HOCs (Cl/Br-HOCs). Knowledge gaps exist on whether novel Cl/Br-HOCs could penetrate the placental barrier and cause adverse birth outcomes. Herein, 326 cord blood samples were collected in a hospital in Jinan, Shandong Province from February 2017 to January 2022, and 44 Cl/Br-HOCs were identified with communicating confidence level above 4 based on a nontarget approach, covering veterinary drugs, pesticides, and their transformation products, pharmaceutical and personal care products, disinfection byproducts, and so on. To our knowledge, the presence of closantel, bromoxynil, 4-hydroxy-2,5,6-trichloroisophthalonitrile, 2,6-dibromo-4-nitrophenol, and related components in cord blood samples was reported for the first time. Both multiple linear regression (MLR) and Bayesian kernel machine regression (BKMR) models were applied to evaluate the relationships of newborn birth outcomes (birth weight, length, and ponderal index) with individual Cl/Br-HOC and Cl/Br-HOCs mixture exposure, respectively. A significantly negative association was observed between pentachlorophenol exposure and newborn birth length, but the significance vanished after the false discovery rate correction. The BKMR analysis showed that Cl/Br-HOCs mixture exposure was significantly associated with reduced newborn birth length, indicating higher risks of fetal growth restriction. Our findings offer an overview of Cl/Br-HOCs exposome during the early life stage and enhance the understanding of its exposure risks.

Occurrence and Ecological Risk of Alkylamine Triazines in Chinese Estuarine Sediments: An Emerging Class of Persistent, Mobile, and Toxic Substances

Identifying persistent, mobile, and toxic (PMT) substances from synthetic chemicals is critical for chemical management and ecological risk assessment. Inspired by the triazine analogues (e.g., atrazine and melamine) in the original European Union's list of PMT substances, the occurrence and compositions of alkylamine triazines (AATs) in the estuarine sediments of main rivers along the eastern coast of China were comprehensively explored by an integrated strategy of target, suspect, and nontarget screening analysis. A total of 44 AATs were identified, of which 23 were confirmed by comparison with authentic standards. Among the remaining tentatively identified analogues, 18 were emerging pollutants not previously reported in the environment. Tri- and di-AATs were the dominant analogues, and varied geographic distributions of AATs were apparent in the investigated regions. Toxic unit calculations indicated that there were acute and chronic risks to algae from AATs on a large geographical scale, with the antifouling biocide cybutryne as a key driver. The assessment of physicochemical properties further revealed that more than half of the AATs could be categorized as potential PMT and very persistent and very mobile substances at the screening level. These results highlight that AATs are a class of PMT substances posing high ecological impacts on the aquatic environment and therefore require more attention.

Fragmentation Pattern-Based Screening Strategy Combining Diagnostic Ion and Neutral Loss Uncovered Novel para-Phenylenediamine Quinone Contaminants in the Environment

Identifying transformed emerging contaminants in complex environmental compartments is a challenging but meaningful task. Substituted para-phenylenediamine quinones (PPD-quinones) are emerging contaminants originating from rubber antioxidants and have been proven to be toxic to the aquatic species, especially salmonids. The emergence of multiple PPD-quinones in various environmental matrices and evidence of their specific hazards underscore the need to understand their environmental occurrences. Here, we introduce a fragmentation pattern-based nontargeted screening strategy combining full MS/All ion fragmentation/neutral loss-ddMS2 scans to identify potential unknown PPD-quinones in different environmental matrices. Using diagnostic fragments of m/z 170.0600, 139.0502, and characteristic neutral losses of 199.0633, 138.0429 Da, six known and three novel PPD-quinones were recognized in air particulates, surface soil, and tire tissue. Their specific structures were confirmed, and their environmental concentration and composition profiles were clarified with self-synthesized standards. N-(1-methylheptyl)-N'-phenyl-1,4-benzenediamine quinone (8PPD-Q) and N,N'-di(1,3-dimethylbutyl)-p-phenylenediamine quinone (66PD-Q) were identified and quantified for the first time, with their median concentrations found to be 0.02-0.21 μg·g-1 in tire tissue, 0.40-2.76 pg·m-3 in air particles, and 0.23-1.02 ng·g-1 in surface soil. This work provides new evidence for the presence of unknown PPD-quinones in the environment, showcasing a potential strategy for screening emerging transformed contaminants in the environment.