Non-target analysis of Danish wastewater treatment plant effluent: Statistical analysis of chemical fingerprinting as a step toward a future monitoring tool

In an attempt to discover and characterize the plethora of xenobiotic substances, this study investigates chemical compounds released into the environment with wastewater effluents. A novel non-targeted screening methodology based on ultra-high resolution Orbitrap mass spectrometry and nanoflow ultra-high performance liquid chromatography together with a newly optimized data-processing pipeline were applied to effluent samples from two state-of-the-art and one small wastewater treatment facility. In total, 785 molecular structures were obtained, of which 38 were identified as single compounds, while 480 structures were identified at a putative level. Most of these substances were therapeutics and drugs, present as parent compounds and metabolites. Using R packages Phyloseq and MetacodeR, originally developed for bioinformatics, significant differences in xenobiotic presence in the wastewater effluents between the three sites were demonstrated.

Deep Learning Bridged Bioactivity, Structure, and GC-HRMS-Readable Evidence to Decipher Nontarget Toxicants in Sediments

Identifying causative toxicants in mixtures is critical, but this task is challenging when mixtures contain multiple chemical classes. Effect-based methods are used to complement chemical analyses to identify toxicants, yet conventional bioassays typically rely on an apical and/or single endpoint, providing limited diagnostic potential to guide chemical prioritization. We proposed an event-driven taxonomy framework for mixture risk assessment that relied on high-throughput screening bioassays and toxicant identification integrated by deep learning. In this work, the framework was evaluated using chemical mixtures in sediments eliciting aryl-hydrocarbon receptor activation and oxidative stress response. Mixture prediction using target analysis explained <10% of observed sediment bioactivity. To identify additional contaminants, two deep learning models were developed to predict fingerprints of a pool of bioactive substances (event driver fingerprint, EDFP) and convert these candidates to MS-readable information (event driver ion, EDION) for nontarget analysis. Two libraries with 121 and 118 fingerprints were established, and 247 bioactive compounds were identified at confidence level 2 or 3 in sediment extract using GC-qToF-MS. Among them, 12 toxicants were analytically confirmed using reference standards. Collectively, we present a "bioactivity-signature-toxicant" strategy to deconvolute mixtures and to connect patchy data sets and guide nontarget analysis for diverse chemicals that elicit the same bioactivity.

Water temperature governs organophosphate ester dynamics in the aquatic food chain of Poyang Lake

Organophosphate esters (OPEs) are increasingly recognized as pervasive environmental contaminants, primarily from their extensive application in flame retardants and plasticizers. Despite their widespread presence, the intricacies of OPE bioaccumulation within aquatic ecosystems remain poorly understood, particularly the environmental determinants influencing their distribution and the bioaccumulation dynamics across aquatic food chains. Here we show that water temperature plays a crucial role in modulating the dispersion of OPE in the aquatic environment of Poyang Lake. We quantified OPE concentrations across various matrices, uncovering levels ranging from 0.198 to 912.622 ng L-1 in water, 0.013-493.36 ng per g dry weight (dw) in sediment, 0.026-41.92 ng per g wet weight (ww) in plankton, 0.13-2100.72 ng per g dw in benthic invertebrates, and 0.31-3956.49 ng per g dw in wild fish, highlighting a pronounced bioaccumulation gradient. Notably, the intestines emerged as the principal site for OPE absorption, displaying the highest concentrations among the seven tissues examined. Among the various OPEs, tris(chloroethyl) phosphate was distinguished by its significant bioaccumulation potential within the aquatic food web, suggesting a need for heightened scrutiny. The propensity for OPE accumulation was markedly higher in benthic invertebrates than wild fish, indicating a differential vulnerability within aquatic biota. This study lays a foundational basis for the risk assessment of OPEs as emerging contaminants and underscores the imperative to prioritize the examination of bioaccumulation effects, particularly in benthic invertebrates, to inform future environmental safeguarding strategies.

Unravelling structural features of small molecules for photochemical transformation of environmental contaminants

Small molecules, including natural metabolites, organic matter decomposition products, and engineered oxidation byproducts, are widespread in aquatic environment. However, the limited understanding of the photochemical interactions of these small molecules with water pollutants hampers the development of effective environmental protection strategies. This study explores the structural features governing the photochemical transformation of toxic oxyanions by α- and β-dicarbonyl compounds. By integrating experimental observations with quantum chemical calculations, a robust correlation network was constructed. The correlation network reveals that the reactivity of small organic molecules with oxyanions could be quantitively predicted by their intrinsic properties, such as electronic transition energy, bond dissociation energy, molecular softness, molecular orbital gap, atomic charge, and molecular surface local ionization energy. This network maps the relationship between the molecular architecture of chemicals and their photochemical behaviors. This perspective offers fresh insights into the photochemical behaviors of small molecules in diverse environmental and chemical contexts and are helpful for developing advanced water treatment strategies toward a sustainable future.

Copper induces cytotoxicity in freshwater bivalve Anodonta woodiana hemocytes

Hemocytes of freshwater bivalves are an important target model for evaluating copper (Cu) toxicity in vitro, with excess Cu causing adverse responses in these organisms. Despite this, the mechanisms underlying cytotoxicity remain poorly understood. The freshwater bivalve Anodonta woodiana, employed as a model organism in freshwater environments, was utilized in this study. Hemocytes of A. woodiana were exposed to various aqueous Cu treatments (0.001, 0.01, 0.1, 1, and 10 mg/L), and a control group (no Cu added) for 3 h to investigate the cytotoxic mechanisms of Cu. The results showed a significant increase in the production of reactive oxygen species in hemocytes of all Cu exposed groups compared to the control (p < 0.05). Remarkably, Cu treatments disrupted the cellular membrane (p < 0.05) but did not induce significant changes in the stability of the lysosomal membrane. Cu targeted the mitochondria, leading to a reduction in mitochondrial membrane potential. Additionally, all Cu treatments significantly increased the degree of DNA damage (p < 0.05). Cellular damage and a significant decline in cell viability were observed when the Cu exposure concentration reached 0.1, 1, and 10 mg/L (p < 0.05). Our study provides new insights into the cytotoxicity mechanisms triggered by Cu in hemocytes of the freshwater bivalve A. woodiana, even under environmentally relevant conditions of 0.01 mg/L exposure.

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.

The effect of information about hazardous chemicals in consumer products on behaviour - A systematic review

Exposure to hazardous chemicals in consumer products poses significant risks to personal health and the environment, and the combined effects may be negative even if each individual exposure is low. This necessitates informed and effective policies for risk reduction. This systematic review aims to identify and analyse existing evidence on how consumer preferences, product use, and product disposal are affected by information on harmful chemicals in consumer products and by price interventions. The review is conducted according to the PRISMA 2020 guidelines, synthesises forty-eight scientific articles on the relationship between information and consumer responses. No corresponding studies on the effects of price interventions were found. A large share of the identified articles focused on household chemicals, where warning labels are common, while less has been published on "everyday products" where the presence of hazardous chemicals is less clear to consumers. Effects of information on hazardous chemicals on consumer behaviour are highly contextual and dependent on the type of product, consumer behaviour and what kind of label is used. Warning symbols are effective in communicating a general warning of a potential danger, although consumers often misinterpret specifics regarding the exact nature of that danger or what means should be taken to minimise it. Informational texts are more informative but are also often missed or quickly forgotten. Consumer willingness to pay for safer products is generally positive but low. Additional research on how consumers react to information and price signals on chemical hazards is needed to improve policy design.

Which distribution to choose for deriving a species sensitivity distribution? Implications from analysis of acute and chronic ecotoxicity data

Species sensitivity distributions (SSDs) estimated by fitting a statistical distribution to ecotoxicity data are indispensable tools used to derive the hazardous concentration for 5 % of species (HC5) and thereby a predicted no-effect concentration in environmental risk assessment. Whereas various statistical distributions are available for SSD estimation, the fundamental question of which statistical distribution should be used has received limited systematic analysis. We aimed to address this knowledge gap by applying four frequently used statistical distributions (log-normal, log-logistic, Burr type III, and Weibull distributions) to acute and chronic SSD estimation using aquatic toxicity data for 191 and 31 chemicals, respectively. Based on the differences in the corrected Akaike's information criterion (AICc) as well as visual inspection of the fitting of the lower tails of SSD curves, the log-normal SSD was generally better or equally good for the majority of chemicals examined. Together with the fact that the ratios of HC5 values of other alternative SSDs to those of log-normal SSDs generally fell within the range 0.1-10, our findings indicate that the log-normal distribution can be a reasonable first candidate for SSD derivation, which does not contest the existing widespread use of log-normal SSDs.

Effect-directed analysis of androgenic compounds from sewage sludges in China

The safety of municipal sewage sludge has raised great concerns because of the accumulation of large-scale endocrine disrupting chemicals in the sludge during wastewater treatment. The presence of contaminants in sludge can cause secondary pollution owing to inappropriate disposal mechanisms, posing potential risks to the environment and human health. Effect-directed analysis (EDA), involving an androgen receptor (AR) reporter gene bioassay, fractionation, and suspect and nontarget chemical analysis, were applied to identify causal AR agonists in sludge; 20 of the 30 sludge extracts exhibited significant androgenic activity. Among these, the extracts from Yinchuan, Kunming, and Shijiazhuang, which held the most polluted AR agonistic activities were prepared for extensive EDA, with the dihydrotestosterone (DHT)-equivalency of 2.5 - 4.5 ng DHT/g of sludge. Seven androgens, namely boldione, androstenedione, testosterone, megestrol, progesterone, and testosterone isocaproate, were identified in these strongest sludges together, along with testosterone cypionate, first reported in sludge media. These identified androgens together accounted for 55 %, 87 %, and 52 % of the effects on the sludge from Yinchuan, Shijiazhuang, and Kunming, respectively. This study elucidates the causative androgenic compounds in sewage sludge and provides a valuable reference for monitoring and managing androgens in wastewater treatment.

Electrophilicity Modulation for Sub-ppm Visualization and Discrimination of EDA

Precise and timely recognition of hazardous chemical substances is of great significance for safeguarding human health, ecological environment, public security, etc., especially crucial for adopting appropriate disposition measures. Up to now, there remains a practical challenge to sensitively detect and differentiate organic amines with similar chemical structures with intuitive analysis outcomes. Here, a unique optical probe with two electrophilic recognition sites for rapid and ultra-sensitive ratiometric fluorescence detection of ethylenediamine (EDA) is presented, while producing distinct fluorescence signals to its structural analog. The probe exhibits ppb/nmol level sensitivity to liquidous and gaseous EDA, specific recognition toward EDA without disturbance to up to 28 potential interferents, as well as rapid fluorescence response within 0.2 s. By further combining the portable sensing chip with the convolutional algorithm endowed with image processing, this work cracked the problem of precisely discriminating the target and non-targets at extremely low concentrations.

CRISPR/Cas12a-Amplified Aptamer Switch Microplate Assay for Small Molecules

The presence of small molecule contaminants such as mycotoxins and heavy metals in foods and the environment causes a serious threat to human health and huge economic losses. The development of simple, rapid, sensitive, and on-site methods for small molecule pollutant detection is highly demanded. Here, combining the advantages of structure-switchable aptamer-mediated signal conversion and CRISPR/Cas12a-based signal amplification, we developed a CRISPR/Cas12a-amplified aptamer switch assay on a microplate for sensitive small molecule detection. In this assay, a short DNA strand complementary to the aptamer (cDNA) is immobilized on a microplate, which can capture the aptamer-linked active DNA probe (Apt-acDNA) in the sample solution when the target is absent. With the addition of the Cas12a reporter system, the captured Apt-acDNA probes activate Cas12a to indiscriminately cleave fluorescent DNA substrates, producing a high fluorescence signal. When the target is present, the Apt-acDNA probe specifically binds to the target rather than hybridizing with cDNA on the microplate, and the fluorescence signal is reduced. The analytical performance of our method was demonstrated by the detection of two highly toxic pollutants, aflatoxin B1 (AFB1) and cadmium ion (Cd2+), as examples. The assay exhibited good selectivity and high sensitivity, with detection limits of 31 pM AFB1 and 3.9 nM Cd2+. It also allowed the detection of targets in the actual sample matrix. With the general signal conversion strategy, this method can be used to detect other targets by simply changing the aptamer and cDNA, showing potential practical applications in broad fields.

Prediction of HC5s for phthalate esters by use of the QSAR-ICE model and ecological risk assessment in Chinese surface waters

Due to their endocrine-disrupting effects and the risks posed in surface waters, in particular by chronic low-dose exposure to aquatic organisms, phthalate esters (PAEs) have received significant attention. However, most assessments of risks posed by PAEs were performed at a selection level, and thus limited by empirical data on toxic effects and potencies. A quantitative structure activity relationship (QSAR) and interspecies correlation estimation (ICE) model was constructed to estimate hazardous concentrations (HCs) of selected PAEs to aquatic organisms, then they were used to conduct a multiple-level environmental risk assessment for PAEs in surface waters of China. Values of hazardous concentration for 5% of species (HC5s), based on acute lethality, estimated by use of the QSAR-ICE model were within 1.25-fold of HC5 values derived from empirical data on toxic potency, indicating that the QSAR-ICE model predicts the toxicity of these three PAEs with sufficient accuracy. The five selected PAEs may be commonly measured in China surface waters at concentrations between ng/L and μg/L. Risk quotients according to median concentrations of the five PAEs ranged from 3.24 for di(2-ethylhexhyl) phthalate (DEHP) to 4.10 × 10-3 for dimethyl phthalate (DMP). DEHP and dibutyl phthalate (DBP) had risks to the most vulnerable aquatic biota, with the frequency of exceedances of the predicted no-effect concentration (PNECs) of 75.5% and 38.0%, respectively. DEHP and DBP were identified as having "high" or "moderate" risks. Results of the joint probability curves (JPC) method indicated DEHP posed "intermediate" risk to freshwater species with a maximum risk product of 5.98%. The multiple level system introduced in this study can be used to prioritize chemicals and other new pollutant in the aquatic ecological.

Predicting macroinvertebrate average score per taxon (ASPT) at water quality monitoring sites in Japanese rivers

Biomonitoring with bioindicators such as river macroinvertebrates is fundamental for assessing the status of freshwater ecosystems. In Japan, water quality and biomonitoring surveys are conducted separately, leading to a lack of nationwide information on their relationships and the biological status of water quality monitoring (WQM) sites. To understand the biological status of WQM sites across Japan, we developed a multiple linear regression model to estimate the average score per taxon (ASPT) using river macroinvertebrate data surveyed at a total of 237 "aligned" sites based on the co-occurrence of biomonitoring and WQM sites. The resulting regression model with eight predictors, such as biological oxygen demand, the proportion of urban areas in the catchment, could predict ASPT with reasonable accuracy (e.g., an error of ±1 for 96% of the aligned data). Using this model, we estimated ASPT values at 2925 WQM sites in rivers nationwide, categorizing them into four levels of river environment quality: "very good" (29% of WQM sites), "good" (50%), "fairly good" (14%), and "not good" (8%). Furthermore, we observed statistically significant correlations (p < 0.05; 0.4 ≤ r ≤ 0.7) between ASPT and all eight macroinvertebrate metrics examined, such as mayfly and stonefly richness, providing ecological implications of changes in ASPT.

Chemical-toxicological insights and process comparison for estrogenic activity mitigation in municipal wastewater treatment plants

Efforts in water ecosystem conservation require an understanding of causative factors and removal efficacies associated with mixture toxicity during wastewater treatment. This study conducts a comprehensive investigation into the interplay between wastewater estrogenic activity and 30 estrogen-like endocrine disrupting chemicals (EEDCs) across 12 municipal wastewater treatment plants (WWTPs) spanning four seasons in China. Results reveal substantial estrogenic activity in all WWTPs and potential endocrine-disrupting risks in over 37.5 % of final effluent samples, with heightened effects during colder seasons. While phthalates are the predominant EEDCs (concentrations ranging from 86.39 %) for both estrogenic activity and major EEDCs (phthalates and estrogens), with the secondary and tertiary treatment segments contributing 88.59 ± 8.12 % and 11.41 ± 8.12 %, respectively. Among various secondary treatment processes, the anaerobic/anoxic/oxic-membrane bioreactor (A/A/O-MBR) excels in removing both estrogenic activity and EEDCs. In tertiary treatment, removal efficiencies increase with the inclusion of components involving physical, chemical, and biological removal principles. Furthermore, correlation and multiple liner regression analysis establish a significant (p < 0.05) positive association between solid retention time (SRT) and removal efficiencies of estrogenic activity and EEDCs within WWTPs. This study provides valuable insights from the perspective of prioritizing key pollutants, the necessity of integrating more efficient secondary and tertiary treatment processes, along with adjustments to operational parameters like SRT, to mitigate estrogenic activity in municipal WWTPs. This contribution aids in managing endocrine-disrupting risks in wastewater as part of ecological conservation efforts.

Innovative analytical methodologies for characterizing chemical exposure with a view to next-generation risk assessment

The chemical burden on the environment and human population is increasing. Consequently, regulatory risk assessment must keep pace to manage, reduce, and prevent adverse impacts on human and environmental health associated with hazardous chemicals. Surveillance of chemicals of known, emerging, or potential future concern, entering the environment-food-human continuum is needed to document the reality of risks posed by chemicals on ecosystem and human health from a one health perspective, feed into early warning systems and support public policies for exposure mitigation provisions and safe and sustainable by design strategies. The use of less-conventional sampling strategies and integration of full-scan, high-resolution mass spectrometry and effect-directed analysis in environmental and human monitoring programmes have the potential to enhance the screening and identification of a wider range of chemicals of known, emerging or potential future concern. Here, we outline the key needs and recommendations identified within the European Partnership for Assessment of Risks from Chemicals (PARC) project for leveraging these innovative methodologies to support the development of next-generation chemical risk assessment.

A critical and comprehensive review of the current status of 17β-estradiol hormone remediation through adsorption technology

Even at low concentrations, steroid hormones pose a significant threat to ecosystem health and are classified as micropollutants. Among these, 17β-estradiol (molecular formula: C18H24O2; pKa = 10.46; Log Kow = 4.01; solubility in water = 3.90 mg L-1 at 27 °C; molecular weight: 272.4 g mol-1) is extensively studied as an endocrine disruptor due to its release through natural pathways and widespread use in conventional medicine. 17β-estradiol (E2) is emitted by various sources, such as animal and human excretions, hospital and veterinary clinic effluents, and treatment plants. In aquatic biota, it can cause issues ranging from the feminization of males to inhibiting plant growth. This review aims to identify technologies for remediating E2 in water, revealing that materials like graphene oxides, nanocomposites, and carbonaceous materials are commonly used for adsorption. The pH of the medium, especially in acidic to neutral conditions, affects efficiency, and ambient temperature (298 K) supports the process. The Langmuir and Freundlich models aptly describe isothermal studies, with interactions being of a low-energy, physical nature. Adsorption faces limitations when other ions coexist in the solution. Hybrid treatments exhibit high removal efficiency. To mitigate global E2 pollution, establishing national and international standards with detailed guidelines for advanced treatment systems is crucial. Despite significant advancements in optimizing technologies by the scientific community, there remains a considerable gap in their societal application, primarily due to economic and sustainable factors. Therefore, further studies are necessary, including conducting batch experiments with these adsorbents for large-scale treatment along with economic analyses of the production process.

(Non)targeted Chemical Analysis and Risk Assessment of Organic Contaminants in Darkibor Kale Grown at Rural and Urban Farms

This study investigated the presence and human hazards associated with pesticides and other anthropogenic chemicals identified in kale grown in urban and rural environments. Pesticides and related compounds (i.e., surfactants and metabolites) in kale samples were evaluated using a nontargeted data acquisition for targeted analysis method which utilized a pesticide mixture containing >1,000 compounds for suspect screening and quantification. We modeled population-level exposures and assessed noncancer hazards to DEET, piperonyl butoxide, prometon, secbumeton, terbumeton, and spinosyn A using nationally representative estimates of kale consumption across life stages in the US. Our findings indicate even sensitive populations (e.g., pregnant women and children) are not likely to experience hazards from these select compounds were they to consume kale from this study. However, a strictly nontargeted chemical analytical approach identified a total of 1,822 features across all samples, and principal component analysis revealed that the kale chemical composition may have been impacted by agricultural growing practices and environmental factors. Confidence level 2 compounds that were ≥5 times more abundant in the urban samples than in rural samples (p < 0.05) included chemicals categorized as "flavoring and nutrients" and "surfactants" in the EPA's Chemicals and Products Database. Using the US-EPA's Cheminformatics Hazard Module, we identified that many of the nontarget compounds have predicted toxicity scores of "very high" for several end points related to human health. These aspects would have been overlooked using traditional targeted analysis methods, although more information is needed to ascertain whether the compounds identified through nontargeted analysis are of environmental or human health concern. As such, our approach enabled the identification of potentially hazardous compounds that, based on their hazard assessment score, merit follow-up investigations.

Predicting the Metal Mixture Toxicity with a Toxicokinetic-Toxicodynamic Model Considering the Time-Dependent Adverse Outcome Pathways

Chemicals mainly exist in ecosystems as mixtures, and understanding and predicting their effects are major challenges in ecotoxicology. While the adverse outcome pathway (AOP) and toxicokinetic-toxicodynamic (TK-TD) models show promise as mechanistic approaches in chemical risk assessment, there is still a lack of methodology to incorporate the AOP into a TK-TD model. Here, we describe a novel approach that integrates the AOP and TK-TD models to predict mixture toxicity using metal mixtures (specifically Cd-Cu) as a case study. We preliminarily constructed an AOP of the metal mixture through temporal transcriptome analysis together with confirmatory bioassays. The AOP revealed that prolonged exposure time activated more key events and adverse outcomes, indicating different modes of action over time. We selected a potential key event as a proxy for damage and used it as a measurable parameter to replace the theoretical parameter (scaled damage) in the TK-TD model. This refined model, which connects molecular responses to organism outcomes, effectively predicts Cd-Cu mixture toxicity over time and can be extended to other metal mixtures and even multicomponent mixtures. Overall, our results contribute to a better understanding of metal mixture toxicity and provide insights for integrating the AOP and TK-TD models to improve risk assessment for chemical mixtures.

Comprehensive characterization and prioritization of halogenated organic compounds in fish and their implications for exposure

Fish are an important pollution indicator for biomonitoring of halogenated organic compounds (HOCs) in aquatic environments, and HOCs in fish may pose health threats to consumers. This study performed nontarget and comprehensive analyses of HOCs in fish from an e-waste recycling zone by gas chromatography-high-resolution mass spectrometry, and further prioritized their human exposure risks. A total of 1652 formulas of HOCs were found in the fish, of which 1222, 117, and 313 were organochlorines, organobromines, and organochlorine-bromines, respectively. The total concentrations of HOCs were 15.4-18.7 μg/g (wet weight), and organobromines were the predominant (14.1-16.8 μg/g). Of the HOCs, 41 % were elucidated with tentative structures and divided into 13 groups. The estimated total daily exposures of HOCs via dietary consumption of the fish for local adult residents were 3082-3744 ng/kg bw/day. The total exposures were dominated by several groups of HOCs with the following contribution order: polyhalogenated biphenyls and their derivatives > polyhalogenated diphenyl ethers > halo- (H-)alkanes/olefines > H-benzenes > H-dioxins > H-polycyclic aromatic hydrocarbons > H-phenols. The comprehensive characterization and prioritization results provide an overview of the species and distributions of HOCs in edible fish, and propose an inventory of crucial HOCs associated with high exposure risks.

Spatial variation in the sensitivity of freshwater macroinvertebrate assemblages to chemical stressors

Assessing spatial variation in the chemical sensitivity of natural assemblages will enhance ecological relevance and reduce uncertainty in ecological risk assessments and the derivation of environmental quality standards (EQSs). However, the majority of species in natural communities have not undergone toxicity testing for any chemical, which poses a major challenge when assessing their sensitivity. We investigated spatial variation and patterns in the sensitivity of 4084 freshwater macroinvertebrate assemblages across England to 5 general-acting chemicals (heavy metals) and 13 specifically acting chemicals (insecticides) using a novel hierarchical species sensitivity distribution method based on taxonomic relatedness. Furthermore, we explored how river typology relates to spatial variation in assemblage sensitivity to chemicals and the potential impacts of such variation on current EQSs. Our findings revealed that, whereas assemblages with similar taxonomic compositions exhibit comparable sensitivity distributions, assemblages with different taxonomic compositions could have very similar or very different sensitivity distributions. The variation in assemblage sensitivity was greater for specifically acting chemicals than for general-acting chemicals and exhibited spatial clustering patterns. These spatial clustering patterns varied depending on the chemical, and the regions where assemblages were most sensitive to metals were generally not the same as the regions where assemblages were most sensitive to insecticides. Spatial variation in assemblage sensitivity was related to river typology with sensitive assemblages being more common than expected in lowland calcareous (or mixed geology) rivers within very small to small catchments. Comparing spatial variation in assemblage-specific chemical sensitivity to EQSs, we found that the operational EQSs in England would protect most study assemblages (i.e., > 99.5 %), although a small proportion of assemblages may face potential risks associated with azinphos-methyl, copper, and malathion. In many cases the EQSs were very precautionary, potentially requiring expensive control measures or restricting beneficial chemical use with no additional environmental benefit. The development of spatially defined EQSs, possibly based on river types, could be developed to target areas that require the highest level of protection and thus strike a balance between the benefits of chemical use and environmental protection.

CPBA-CLIM: An entity-relation extraction model for ontology-based knowledge graph construction in hazardous chemical incident management

In recent years, hazardous chemical incidents have occurred frequently, resulting in significant human casualties, property damage, and environmental pollution due to human or natural factors. Accurately mining the lessons learned from accumulating incident reports and constructing the knowledge graph for hazardous chemical incident management can assist managers in identifying patterns and analyzing common attributes, thereby preventing the recurrence of similar incidents. This article addresses the challenges of dispersed textual information, specialized vocabulary, and data formats in hazardous chemical incidents. We propose a novel entity-relation extraction model called CPBA-CLIM (content-position-based attention-cross-label intersect matching) to provide an accurate data foundation for constructing the hazardous chemical incident knowledge graph. The content-position-based attention module, based on content-position attention, incorporates contextual semantic information into the combined encoding of bidirectional encoder representations from the transformer's content and position to obtain dynamic word vectors that align with the thematic context of the text. Additionally, the cross-label intersect matching strategy evaluates the rationality of entity-relation interactions in sets containing potential overlaps, reducing the impact of entity-relation overlap on triplet extraction accuracy. Comparative experimental results on public datasets demonstrate the model's outstanding performance in overlapping triplets. Qualitative experiments on a self-constructed dataset integrate our model with ontology construction techniques, successfully establishing a knowledge graph for managing hazardous chemical incidents. This research effectively enhances the degree of automation and efficiency in knowledge graph construction, thus offering support and decision-making foundations for hazardous chemical safety management.

Sources of the Elevating Polycyclic Aromatic Hydrocarbon Pollution in the Western South China Sea and Its Environmental Implications

The environmental implications of polycyclic aromatic hydrocarbons (PAHs) caused by the vigorous development of offshore oil exploitation and shipping on the marine ecosystem are unclear. In this study, the PAH concentrations were systematically characterized in multiple environmental media (i.e., atmosphere, rainwater, seawater, and deep-sea sediments) in the western South China Sea (WSCS) for the first time to determine whether PAH pollution increased. The average ∑15PAHs (total concentration of 15 US EPA priority controlled PAHs excluding naphthalene) in the water of WSCS has increased and is higher than the majority of the oceans worldwide due to the synergistic influence of offshore oil extraction, shipping, and river input. The systematic model comparison confirms that the Ksoot-air model can more accurately reflect the gas-particle partitioning of PAHs in the atmosphere of the WSCS. We also found that the vertical migration of the elevating PAHs is accelerated by particulate matter, driving the migration of atmospheric PAHs to the ocean through dry and wet deposition, with 16% being contributed by the particle phase. The particulate matter sinking alters the PAH distribution in the water column and generates variation in source apportionment, while the contribution of PAHs loaded on them (>20%) to the total PAH reserves cannot be ignored as before. Hence, the ecological threat of PAHs increases by the oil drilling and shipping industry, and the driving force of particulate matter deserves continuous attention.

Rapid sensitive fluorescence detection of cadmium (II) with pyrene excimer switching aptasensor

Heavy metal cadmium (II) contamination often occurs, causing great health risk to human due to high toxicity of cadmium (II). Rapid, sensitive and simple detection of cadmium (II) are of great importance in environmental monitoring. Taking advantage of aptamer in specific recognition, easy modification, and capability of binding-induced structure change, here we reported a simple fluorescent sensor with rapid and sensitive response for Cd²⁺ using aptamer pyrene excimer switch. The aptamer was labeled with dual pyrene molecules at two ends of the sequence. The binding of Cd²⁺ to this aptamer probe brought the pyrene labels into close proximity and enhanced formation of a pyrene excimer, which generated increased fluorescence at 485 nm. By measuring the fluorescence of pyrene excimer, we achieved detection of Cd²⁺ with this aptasensor. Under the optimum experimental conditions, the detection limit of Cd²⁺ reached nanomolar levels. This method was selective and allowed for the detection of Cd²⁺ in tap water. This fluorescence aptasensor is promising for rapid detection of Cd²⁺ in broad applications.

Combining chemical, bioanalytical and predictive tools to assess persistence, seasonality, and sporadic releases of organic micropollutants within the urban water cycle

Using a novel liquid chromatography-tandem mass spectrometry method with large volume direct injection and quantitation via isotope dilution, we evaluated the presence of 55 organic micropollutants in wastewater effluents, and locations within the Bow River and Elbow River watersheds in and around the city of Calgary, Alberta, Canada. In addition to establishing baseline micropollutant data for water utility operations, our study aimed to enhance our understanding of micropollutant behavior in the urban water cycle, assess the contributions of three wastewater treatment plants (WWTPs) to downstream receiving waters, explain the potential causes of total estrogenicity measured using the yeast-estrogen screen assay (YES), and prioritize a subset of substances for continuous monitoring. With data spanning 48 months and 95 river km, our results indicate the extensive persistence of metformin (antidiabetic), seasonality of N,N‑diethyl-m-toluamide (DEET, insect repellant), O-desmethylvenlafaxine (antidepressant metabolite), and sulfamethoxazole (antibiotic) in source waters, and sporadic detections of a well-known perfluoroalkyl substance (PFOA). The seasonality of pharmaceuticals at the sentinel downstream monitoring site appeared to coincide with river dilution while that of DEET was likely attributable to peak usage during the warmer months. Steroidal estrogens were rarely detected in wastewater effluents although total estrogenicity via YES was evident, suggesting the presence of less potent but more abundant non-steroidal estrogens (e.g., flame retardants, bisphenols, and phthalates). A conservative mass balance analysis suggests that the largest WWTP (serving a population of >1 million) consistently contributed the highest load of micropollutants, with the exception of metformin, which appeared to be influenced by a smaller WWTP (serving 115,000) that operates a different activated sludge process. We consider metformin, sucralose, diclofenac, and venlafaxine as more effective conservative tracers of wastewater pollution due to their notably higher concentrations and persistence in the Bow River compared to carbamazepine and caffeine, respectively. Finally, hierarchical clustering revealed a close association between E. coli and caffeine, supporting the use of caffeine as an indicator of short-term, untreated anthropogenic inputs. Overall, this study yields valuable insights on the presence, behavior, and sources of organic micropollutants in the urban water cycle and identifies indicators of anthropogenic impacts that are useful for prioritizing future monitoring campaigns in Calgary and elsewhere.

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

Exposure to environmental organic pollutants has triggered significant ecological impacts and adverse health outcomes, which have been received substantial and increasing attention. The contribution of unidentified chemical components is considered as the most significant knowledge gap in understanding the combined effects of pollutant mixtures. To address this issue, remarkable analytical breakthroughs have recently been made. In this review, the basic principles on recognition of environmental organic pollutants are overviewed. Complementary analytical methodologies (i.e., quantitative structure-activity relationship prediction, mass spectrometric nontarget screening, and effect-directed analysis) and experimental platforms are briefly described. The stages of technique development and/or essential parts of the analytical workflow for each of the methodologies are then reviewed. Finally, plausible technique paths and applications of the future nontarget screening methods, interdisciplinary techniques for achieving toxicant identification, and burgeoning strategies on risk assessment of chemical cocktails are discussed.

Co-generation of hydroxyl and sulfate radicals via homogeneous and heterogeneous bi-catalysis with the EO-PS-EF tri-coupling system for efficient removal of refractory organic pollutants

Advanced oxidation processes are commonly considered one of the most effective techniques to degrade refractory organic pollutants, but the limitation of a single process usually makes it insufficient to achieve the desired treatment. This work introduces, for the first time, a highly-efficient coupled advanced oxidation process, namely Electro-Oxidation-Persulfate-Electro-Fenton (EO-PS-EF). Leveraging the EO-PS-EF tri-coupling system, diverse contaminants can be highly efficiently removed with the help of reactive hydroxyl and sulfate radicals generated via homogeneous and heterogeneous bi-catalysis, as certified by radical quenching and electron spin resonance. Concerning degradation of tetracycline (TC), the EO-PS-EF system witnessed a fast pseudo-first-order reaction kinetic constant of 2.54 × 10-3 s-1, ten times that of a single EO system and three-to-four times that of a binary system (EO-PS or EO-EF). In addition, critical parameters (e.g., electrolyte, pH and temperature) are systematically investigated. Surprisingly, after 100 repetitive trials TC removal can still reach 100% within 30 min and no apparent morphological changes to electrode materials were observed, demonstrating its long-term stability. Finally, its universality was demonstrated with effective degradation of diverse refractory contaminants (i.e., antibiotics, dyes and pesticides).

Data driven toxicity assessment of organic chemicals against Gammarus species using QSAR approach

Nowadays, organic chemicals play an essential role in almost all walks of life and have become indispensable to modern society. However, the continually synthesized chemicals and the numerous potential adverse endpoints against living organisms increasingly promote the regulators regarding the computational approach as a crucial supplement and an alternative to the traditional animal tests in chemical risk assessment. In this present research, we evaluated the ecotoxicity of chemicals against four typical Gammarus species, which constituted a critical element in detritus cycle and also the recommended species for water monitoring. We first screened the molecular descriptors based on the Genetic Algorithm and then developed the Quantitative Structure-Activity Relationship models using the Multiple Linear Regression method. The statistical results from various validation metrics suggested that the obtained models were internally robust and externally predictive. The application domain analysis based on the leverage approach and standardized residual method demonstrated the broad application range of each model. The interpretation of molecular descriptors in each model suggested that the chemicals with higher polarity and hydrophilicity tend to be less toxic, whereas the lipophilic moieties would enhance the chemical toxicity. Meanwhile, the other selected descriptors, such as Chi-cluster, heterocyclic, and distance matrix descriptors, manifested that the chemical toxicity was also affected by molecular branching, connectivity, electrotopological state, and other various properties. In summary, the present work proposed well-performed QSAR models and clarified the possible toxic mechanism of chemicals against Gammarus species. The obtained models could help predict the toxicity data and conduct a preliminary risk assessment, thus guiding the subsequent animal tests and reducing the assessment cost.

Machine learning-assisted data filtering and QSAR models for prediction of chemical acute toxicity on rat and mouse

Machine learning (ML) methods provide a new opportunity to build quantitative structure-activity relationship (QSAR) models for predicting chemicals' toxicity based on large toxicity data sets, but they are limited in insufficient model robustness due to poor data set quality for chemicals with certain structures. To address this issue and improve model robustness, we built a large data set on rat oral acute toxicity for thousands of chemicals, then used ML to filter chemicals favorable for regression models (CFRM). In comparison to chemicals not favorable for regression models (CNRM), CFRM accounted for 67% of chemicals in the original data set, and had a higher structural similarity and a smaller toxicity distribution in 2-4 log₁₀ (mg/kg). The performance of established regression models for CFRM was greatly improved, with root-mean-square deviations (RMSE) in the range of 0.45-0.48 log₁₀ (mg/kg). Classification models were built for CNRM using all chemicals in the original data set, and the area under receiver operating characteristic (AUROC) reached 0.75-0.76. The proposed strategy was successfully applied to a mouse oral acute data set, yielding RMSE and AUROC in the range of 0.36-0.38 log₁₀ (mg/kg) and 0.79, respectively.

Linear alkylbenzene sulfonate threats to surface waters at the national scale: A neglected traditional pollutant

Freshwater biodiversity and ecosystem services might decline due to exposure to chemicals. However, researchers have devoted much attention to the potential risks of emerging contaminants, while placing less effort on historical pollutants, such as the surfactant, linear-alkylbenzene-sulfonate (LAS), which is a major component of widely used synthetic detergents worldwide. In this study, a multilevel risk assessment approach was used to assess risks posed by LAS to aquatic organisms, on a wide spatial scale, based on various assessment endpoints. Additionally, bottom-up approaches were used to assess contributions of LAS source discharges to aquatic environments. Concentrations of LAS in surface waters of China ranged from less than the limit of detection to 14,200 μg/L. The predicted no effect concentration (PNEC) based on adverse effects on reproduction is 15 μg/L, which is slightly less than the PNEC based on other endpoints. 99% of surface waters in Chaohu Lake and the Hai River (Ch: Haihe) were predicted to pose a risk to growth of aquatic organisms, with a protection threshold of 5% of species (HC₅). Discharges of LAS were estimated using activity data and emission factors for 280 major cities in the basin. Rural domestic sources were the main source of LAS to surface waters. These outcomes provided a process for developing comprehensive management and control approaches to help researchers and policymakers effectively manage water resources affected by increasing concentrations of LAS.

Machine Learning Model for Screening Thyroid Stimulating Hormone Receptor Agonists Based on Updated Datasets and Improved Applicability Domain Metrics

Machine learning (ML) models for screening endocrine-disrupting chemicals (EDCs), such as thyroid stimulating hormone receptor (TSHR) agonists, are essential for sound management of chemicals. Previous models for screening TSHR agonists were built on imbalanced datasets and lacked applicability domain (AD) characterization essential for regulatory application. Herein, an updated TSHR agonist dataset was built, for which the ratio of active to inactive compounds greatly increased to 1:2.6, and chemical spaces of structure-activity landscapes (SALs) were enhanced. Resulting models based on 7 molecular representations and 4 ML algorithms were proven to outperform previous ones. Weighted similarity density (ρ_s) and weighted inconsistency of activities (I_A) were proposed to characterize the SALs, and a state-of-the-art AD characterization methodology AD_SAL{ρ_s, I_A} was established. An optimal classifier developed with PubChem fingerprints and the random forest algorithm, coupled with AD_SAL{ρ_s ≥ 0.15, I_A ≤ 0.65}, exhibited good performance on the validation set with the area under the receiver operating characteristic curve being 0.984 and balanced accuracy being 0.941 and identified 90 TSHR agonist classes that could not be found previously. The classifier together with the AD_SAL{ρ_s, I_A} may serve as efficient tools for screening EDCs, and the AD characterization methodology may be applied to other ML models.

Time-dependent effects of microplastics on soil bacteriome

Microplastic threats to biodiversity, health and ecological safety are adding to concern worldwide, but the real impacts on the functioning of organisms and ecosystems are obscure owing to their inert characteristics. Here we investigated the long-lasting ecological effects of six prevalent microplastic types: polyethylene (PE), polypropylene (PP), polyamide (PA), polystyrene (PS), polyethylene terephthalate (PET), and polyvinyl chloride (PVC) on soil bacteria at a 2 % (w/w) level. Due to the inertia and lack of available nitrogen of these microplastics, their effects on bacteriome tended to converge after one year and were strongly different from their short-term effects. The soil volumes around microplastics were very specific, in which the microplastic-adapted bacteria (e.g., some genera in Actinobacteria) were enriched but the phyla Bacteroidetes and Gemmatimonadetes declined, resulting in higher microbial nitrogen requirements and reduced organic carbon mineralization. The reshaped bacteriome was specialized in the genetic potential of xenobiotic and lipid metabolism as well as related oxidation, esterification, and hydrolysis processes, but excessive oxidative damage resulted in severe weakness in community genetic information processing. According to model predictions, microplastic effects are indirectly derived from nutrients and oxidative stress, and the effects on bacterial functions are stronger than on structure, posing a heavy risk to soil ecosystems.

Pharmaceuticals and personal care products (PPCPs) in surface water and fish from three Asian countries: Species-specific bioaccumulation and potential ecological risks

In Asian developing countries, undeveloped and ineffective sewer systems are causing surface water pollution by a lot of contaminants, especially pharmaceuticals and personal care products (PPCPs). Therefore, the risks for freshwater fauna need to be assessed. The present study aimed at: i) elucidating the contamination status; ii) evaluating the bioaccumulation; and iii) assessing the potential risks of PPCP residues in surface water and freshwater fish from three Asian countries. We measured 43 PPCPs in the plasma of several fish species as well as ambient water samples collected from India (Chennai and Bengaluru), Indonesia (Jakarta and Tangerang), and Vietnam (Hanoi and Hoa Binh). In addition, the validity of the existing fish blood-water partitioning model based solely on the lipophilicity of chemicals is assessed for ionizable and readily metabolizable PPCPs. When comparing bioaccumulation factors calculated from the PPCP concentrations measured in the fish and water (BAF_measured) with bioconcentration factors predicted from their pH-dependent octanol-water partition coefficient (BCF_predicted), close values (within an order of magnitude) were observed for 58-91 % of the detected compounds. Nevertheless, up to 110 times higher plasma BAF_measured than the BCF_predicted were found for the antihistamine chlorpheniramine in tilapia but not in other fish species. The plasma BAF_measured values of the compound were significantly different in the three fish species (tilapia > carp > catfish), possibly due to species-specific differences in toxicokinetics (e.g., plasma protein binding and hepatic metabolism). Results of potential risk evaluation based on the PPCP concentrations measured in the fish plasma suggested that chlorpheniramine, triclosan, haloperidol, triclocarban, diclofenac, and diphenhydramine can pose potential adverse effects on wild fish. Results of potential risk evaluation based on the PPCP concentrations measured in the surface water indicated high ecological risks of carbamazepine, sulfamethoxazole, erythromycin, and triclosan on Asian freshwater ecosystems.

N-doped porous bowl-like carbon with superhigh external surface area for ultrafast degradation of bisphenol A: Key role of site exposure degree

High-temperature nitrogen (N) doping boosts the activity of biochars for peroxymonosulfate (PMS) activation, but the N heat loss causes the unsatisfactory catalytic efficiency. Improving the surface area for obtaining the high exposure of N sites is a promising solution. Herein, a soft template-KHCO₃ etching strategy is used to synthesize the N-doped porous bowl-like carbon (NPBC) with ultrahigh external surface area (1610.8 m² g^-1). The bowl-like structure eliminates inert bulk interior and allows unobstructed mass transfer of reactants onto both outer and inner surfaces, while the large pore channels by KHCO₃ etching further improves the exposure degree of limited N sites. Although NPBC has only 0.43% N content, 93.1% of bisphenol A (BPA) is removed within 1 min through the electron-transfer pathway by fully utilizing the N active centers, and the kinetic rate constant (k) reaches 5.29 min^-1, exceeding reported values by 2-270 times. Moreover, the NPBC/PMS system possesses excellent applicability for various organics and conditions, effectively mineralizes BPA and reduces effluent biotoxicity. A quantitative index W representing N exposure degree is first proposed and shows high linearity with the k values of BPA degradation (R²=0.992, 0 <W<3750 m² g^-1%^-1), proving the critical role of W in determining catalytic efficiency.

Quantitative multi-species toxicity modeling: Does a multi-species, machine learning model provide better performance than a single-species model for the evaluation of acute aquatic toxicity by organic pollutants?

The toxicological profile of any chemical is defined by multiple endpoints and testing procedures, including representative test species from different trophic levels. While computer-aided methods play an increasingly important role in supporting ecotoxicology research and chemical hazard assessment, most of the recently developed machine learning models are directed towards a single, specific endpoint. To overcome this limitation and accelerate the process of identifying potentially hazardous environmental pollutants, we are introducing an effective approach for quantitative, multi-species modeling. The proposed approach is based on canonical correlation analysis that finds a pair(s) of uncorrelated, linear combinations of the original variables that best defines the overall variability within and between multiple biological responses and predictor variables. Its effectiveness was confirmed by the machine learning model for estimating acute toxicity of diverse organic pollutants in aquatic species from three trophic levels: algae (Pseudokirchneriella subcapitata), daphnia (Daphnia magna), and fish (Oryzias latipes). The multi-species model achieved a favorable predictive performance that were in line with predictive models derived for the aquatic organisms individually. The chemical bioavailability and reactivity parameters (n-octanol/water partition coefficient, chemical potential, and molecular size and volume) were important to accurately predict acute ecotoxicity to the three aquatic organisms. To facilitate the use of this approach, an open-source, Python-based script, named qMTM (quantitative Multi-species Toxicity Modeling) has been provided.

Fast evaluation of the safety of chemical reactions using cytotoxicity potentials and bio-Strips

We introduce new quantitative environmental metrics - "cytotoxicity potentials" - which can be used for the preliminary evaluation of the safety of chemical reactions from the viewpoint of the cytotoxicity of their components. We also elaborate the concept of bio-Profiles to be employed for fast estimation of the potential environmental dangers of chemical processes by (1) including the common cytotoxicity scale for all routes of synthesis of a particular product and (2) proposing a novel, more compact representation of the bio-Profiles themselves in the form of bio-Strips. These improvements allow direct comparisons of various synthetic routes for a particular target product, thus providing faster assessment of the reactions in question from the viewpoint of their "overall cytotoxicity". The advantages of these developments are illustrated by 36 routes of synthesizing 1,1'-biphenyl and 72 routes of synthesizing 4-methoxy-1,1'-biphenyl. The effect of incomplete conversion on bio-Strips and their metrics is also discussed. In addition, we address the impact of the selection of a particular cell line on the evaluation of the reaction safety by comparing the results obtained in three cell lines of various origins.

Formation and Inventory of Polychlorinated Dibenzo-p-dioxins and Dibenzofurans and Other Byproducts along Manufacturing Processes of Chlorobenzene and Chloroethylene

Chlorinated organic chemicals are produced and used extensively worldwide, and their risks to the biology and environment are of increasing concern. However, chlorinated byproducts [e.g., polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs)] formed during the commercial manufacturing processes and present in organochlorine products are rarely reported. The knowledge on the occurrences and fate of unintentional persistent organic chemicals in the manufacturing of organochlorine chemical is necessary for accurate assessment of the risks of commercial chemicals and their production. Here, PCDD/Fs were tracked throughout chlorobenzene and chloroethylene production processes (from raw materials to final products) by target analysis. Other byproducts that can further transform into PCDD/Fs were also identified by performing non-target screening. As a result, the PCDD/F concentrations were mostly the highest in bottom residues, and the octachlorinated congeners were dominant. Alkali/water washing stages may cause the formation of oxygen-containing byproducts including PCDD/Fs and acyl-containing compounds, so more attention should be paid to these stages. PCDD/Fs were of 0.17 and 0.21-1.2 ng/mL in monochlorobenzene and chloroethylene products, respectively. Annual PCDD/F emissions (17 g toxic equivalent in 2018) during chlorobenzene and chloroethylene production were estimated using PCDD/F emission factors. The results can contribute to the improvement of PCDD/F inventories for the analyzed commercial chemicals.

Energy Barriers for Steroid Hormone Transport in Nanofiltration

Nanofiltration (NF) membranes can retain micropollutants (MPs) to a large extent, even though adsorption into the membrane and gradual permeation result in breakthrough and incomplete removal. The permeation of MPs is investigated by examining the energy barriers (determined using the Arrhenius concept) for adsorption, intrapore diffusion, and permeation encountered by four different steroid hormones in tight and loose NF membranes. Results show that the energy barriers for steroid hormone transport in tight membrane are entropically dominated and underestimated because of the high steric exclusion at the pore entrance. In contrast, the loose NF membrane enables steroid hormones partitioning at the pore entrance, with a permeation energy barrier (from feed toward the permeate side) ranging between 96 and 116 kJ/mol. The contribution of adsorption and intrapore diffusion to the energy barrier for steroid hormone permeation reveals a significant role of intrapore diffusive transport on the obtained permeation energy barrier. Overall, the breakthrough phenomenon observed during the NF of MPs is facilitated by the low energy barrier for adsorption. Experimental evidence of such principles is relevant for understanding mechanisms and ultimately improving the selectivity of NF.

Human activities induce potential aquatic threats of micropollutants in Danjiangkou Reservoir, the largest artificial freshwater lake in Asia

Freshwater biodiversity and ecosystem services may decline because of toxicant input, and other environmental variables often co-occur with contaminants to jeopardize the freshwater ecosystem. In this study, Danjiangkou Reservoir (DJKR) in central China was selected as the target research area to investigate the impact of multiple categories of micropollutants coupled with other stressors on the reservoir ecosystem. A total of 140 samples were collected from 28 sites in DJKR, and 124 micropollutants, including pesticides, organophosphate esters (OPEs), psychoactive substances, antiviral drugs, and pharmaceutical and personal care products, were quantified. A total of 108 micropollutants were detected in the water samples, with sum concentrations ranging from 82.35 ng·L^-1 to 1436.57 ng·L^-1, and 71 of them had a detection frequency above 50 %, indicating the prevailing micropollutant contamination in the reservoir. The most severe pollution and risks were observed in the tributaries of DJKR. Pesticides (neonicotinoid and triazine) and OPEs were the major contributors to the ecological risk in the reservoir. Insecticides, herbicides, and OPEs accounted for the majority of the risks to fish, algae, and invertebrates, respectively. The determined priority pollutants should be paid increased attention. Environmental variables and human activities, such as human land use, induced the potential aquatic threats of micropollutants in DJKR. Results demonstrated that micropollutant pollution was one of the dominant pressures faced by aquatic organisms and human beings, and human activities played important roles as well.

Advancing exposure data analytics and repositories as part of the European Exposure Science Strategy 2020-2030

High-quality and comprehensive exposure-related data are critical for different decision contexts, including environmental and human health monitoring, and chemicals risk assessment and management. However, exposure-related data are currently scattered, frequently of unclear quality and structure, not readily accessible, and stored in various-partly overlapping-data repositories, leading to inefficient and ineffective data usage in Europe and globally. We propose strategic guidance for an integrated European exposure data production and management framework for use in science and policy, building on current and future data analysis and digitalization trends. We map the existing exposure data landscape to requirements for data analytics and repositories across European policies and regulations. We further identify needs and ways forward for improving data generation, sharing, and usage, and translate identified needs into an operational action plan for European and global advancement of exposure data for policies and regulations. Identified key areas of action are to develop consistent exposure data standards and terminology for data production and reporting, increase data transparency and availability, enhance data storage and related infrastructure, boost automation in data management, increase data integration, and advance tools for innovative data analysis. Improving and streamlining exposure data generation and uptake into science and policy is crucial for the European Chemicals Strategy for Sustainability and European Digital Strategy, in line with EU Data policies on data management and interoperability.

Renewing and improving the environmental risk assessment of chemicals

The processes underpinning the environmental risk assessment (ERA) of chemicals have not changed appreciably in the last 30 years. It is unclear how successful these processes are in protecting the environment from any adverse effects of chemicals. To ascertain if the current methodology can be improved, and if so, how, we invited experts to suggest how the current ERA process could be improved. They were not asked to select from a list of suggestions. The 36 experts made 109 suggestions for improvement, which could be grouped into 33 categories. The category that received the most support, from 12 experts, was to utilise a broader range of scientific information, including all up-to-date information, in ERAs. The second most popular category, supported by 10 experts, was the suggestion to regulate mixtures of chemicals; the current regulatory process involves chemical-by-chemical assessment. Two quite radical proposals were suggested. One was to replace the regulator with artificial intelligence. The other was to establish a new competent authority that would appoint groups of experts, each including representatives of the range of stakeholders, to decide which studies were required, commission those studies, then conduct the ERA based on the results of those studies. These two radical proposals, which the authors support strongly, are not necessarily mutually exclusive. We conclude that the present ERA process could be improved to better protect the environment from the myriad of chemicals in use.

Organophosphate esters cause thyroid dysfunction via multiple signaling pathways in zebrafish brain

Organophosphate esters (OPEs) are widespread in various environmental media, and can disrupt thyroid endocrine signaling pathways. Mechanisms by which OPEs disrupt thyroid hormone (TH) signal transduction are not fully understood. Here, we present in vivo-in vitro-in silico evidence establishing OPEs as environmental THs competitively entering the brain to inhibit growth of zebrafish via multiple signaling pathways. OPEs can bind to transthyretin (TTR) and thyroxine-binding globulin, thereby affecting the transport of TH in the blood, and to the brain by TTR through the blood-brain barrier. When GH3 cells were exposed to OPEs, cell proliferation was significantly inhibited given that OPEs are competitive inhibitors of TH. Cresyl diphenyl phosphate was shown to be an effective antagonist of TH. Chronic exposure to OPEs significantly inhibited the growth of zebrafish by interfering with thyroperoxidase and thyroglobulin to inhibit TH synthesis. Based on comparisons of modulations of gene expression with the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases, signaling pathways related to thyroid endocrine functions, such as receptor-ligand binding and regulation of hormone levels, were identified as being affected by exposure to OPEs. Effects were also associated with the biosynthesis and metabolism of lipids, and neuroactive ligand-receptor interactions. These findings provide a comprehensive understanding of the mechanisms by which OPEs disrupt thyroid pathways in zebrafish.

Ecotoxicological effects of the UV-filter 4-MBC on sperms and adults of the mussel Mytilus galloprovincialis

Present in an increasing number of products, UV-filters are continuously discharged into aquatic environments. Despite potential risks for inhabiting organisms are recognized, the effects of UV-filter 4-methylbenzylidenecamphor (4-MBC) on marine invertebrates are poorly investigated. By combining in vitro/in vivo exposures through a multi-biomarker approach on sperms and adults, the present study evaluated how 4-MBC affect the mussel species Mytilus galloprovincialis, providing ecologically relevant information on organisms' responses. From the obtained results, considering mortality as endpoint, sperms revealed a greater sensitivity (EC₅₀:347 μg/L) than adults (EC₅₀: not calculable). From an ecotoxicological perspective, this resulted in a derived threshold concentration (LOEC) of 100 μg/L and 72 μg/L, respectively. Effects at the cell/molecular level were provided by general redox-status imbalance and oxidative stress. Sperms showed functional and structural impairments, hyperactivation and DNA damage, while adults showed physiological, metabolic/energetic dysfunctions, DNA damage and activation of oxidative and biotransformation enzymes. High 4-MBC bioaccumulation was also observed in exposed mussels (BCFs:14.0-32.0 L/kg). These findings suggest that 4-MBC may impair fitness and survival of the broadcast spawning mussel M. galloprovincialis, affecting reproduction success and population growth.

Elucidating the Differences in Metal Toxicity by Quantitative Adverse Outcome Pathways

Numerous studies have reported that the toxicity differences among metals are widespread; however, little is known about the mechanism of differences in metal toxicity to aquatic organisms due to the lack of quantitative understanding of their adverse outcome pathway. Here, we investigated the effects of Cd and Cu on bioaccumulation, gene expression, physiological responses, and apical effects in zebrafish larvae. RNA sequencing was conducted to provide supplementary mechanistic information for the effects of Cd and Cu exposure. On this basis, we proposed a quantitative adverse outcome pathway (qAOP) suitable for metal risk assessment of aquatic organisms. Our work provides a mechanistic explanation for the differences in metal toxicity where the strong bioaccumulation of Cu enables the newly accumulated Cu to reach the threshold that causes different adverse effects faster than Cd in zebrafish larvae, resulting in a higher toxicity of Cu than that of Cd. Furthermore, we proposed a parameter C_IT/BCF (the ratio of internal threshold concentration and bioaccumulation factor) that helps to understand the toxicity differences by combining the information of bioaccumulation and internal threshold of adverse effects. This work demonstrated that qAOP is an effective quantitative tool for understanding the toxicity mechanism and highlight the importance of toxicokinetics and toxicodynamics at different biological levels in determining the metal toxicity.

Modeling and insights into the structural basis of chemical acute aquatic toxicity

It has become a top global regulatory priority to prevent and control pollution from the release of synthetic chemicals, which continues to affect the aquatic communities. In the past decades, computational tools were largely used to significantly reduce the budget and time cost of chemical acute aquatic toxicity assessment. But the structural basis of toxic compounds was rarely analyzed. In the present study, we collected 1438, 485 and 961 chemicals with acute toxicity data records for three representative aquatic species, including Tetrahymena pyriformis, Daphnia magna, and Fathead minnow, respectively. A series of artificial intelligence models were developed using OCHEM tools. For each aquatic toxicity endpoint, a consensus model was developed based on the top performed individual models. The consensus models provided good performance on external validation sets with total accuracy values 96.88 %, 90.63 %, and 84.90 % for Tetrahymena pyriformis toxicity (TPT), Daphnia magna toxicity (DMT), and Fathead minnow toxicity (FMT), respectively. The models can be freely accessed via https://ochem.eu/article/146910. Moreover, the analysis of physical-chemical properties suggested that several key molecular properties of aquatic toxic compounds were significantly different with those of non-toxic compounds. Thus, these descriptors may be associated to chemical acute aquatic toxicity, and may be useful for the understand of chemical aquatic toxicity. Besides, in this study, the structural alerts for aquatic toxicity were detected using f-score and frequency ratio analysis of predefined substructures. A total of 112, 58 and 33 structural alerts were identified responsible for TPT, DMT, and FMT, respectively. These structural alerts could provide useful information for the mechanisms of chemical aquatic toxicity and visual alerts for environmental assessment. All the structural alerts were integrated in the web-server SApredictor (www.sapredictor.cn).

Investigations On the Fish Acute Toxicity of Fragrance Ingredients Involving Chinese Fish Species and Zebrafish Embryos

While zebrafish (Danio rerio) have been accepted worldwide for evaluating chemical hazards to aquatic vertebrates, and in some countries it is mandated to generate fish toxicity data using native species, such as Chinese rare minnow (Gobiocypris rarus) in China. This represents an additional regulatory constraint that may cause redundant tests, additional animal uses, and higher costs. Previous studies showed that juvenile G. rarus was more sensitive than zebrafish juveniles and embryos to metals. To better understand the sensitivity of G. rarus to organic chemicals, we selected 29 fragrance ingredients belonging to various chemical classes and with differing physicochemical properties, for which good quality zebrafish acute toxicity data were available and tested them with juvenile G. rarus and embryo D. rerio using the Organisation of Economic Co-operation and Development test guidelines. Chemical toxicity distribution (CTD) and chemical ratio distribution (CRD) models were established to systematically compare the sensitivity between juveniles of G. rarus and D. rerio, as well as between D. rerio embryos and juveniles. The results of the CTD models showed that for tested chemicals, the sensitivity of juvenile G. rarus was similar to that of D. rerio juveniles and embryos. The CRD comparisons revealed that juvenile G. rarus was slightly less sensitive by a factor of ~2 than juvenile D. rerio to ingredients belonging to Verhaar class 3 and Ecological Structure Activity Relationship ester class, while comparable to other chemicals. These comparative experiments demonstrated that fish toxicity data with G. rarus can be submitted for use in chemical registrations outside China, which would avoid repeating animal tests using D. rerio. Meanwhile, the similar sensitivity of zebrafish juveniles and embryos to fragrance ingredients confirmed the suitability of replacing juveniles by zebrafish embryos. Environ Toxicol Chem 2022;41:2305-2317. © 2022 SETAC.

UV-filters in marine environments: a review of research trends, meta-analysis, and ecotoxicological impacts of 4-methylbenzylidene-camphor and benzophenone-3 on marine invertebrate communities

The potential adverse effects of UV-filter pollution in marine environments have been the focus of research in recent years. This systematic review aims to determine the extent of this emerging problem, both quantitatively and qualitatively, combining temporal and science mapping analyses to explore the development of the field of UV-filters in the marine environment (from 1990 to 2021), and to outline new research frontiers. The temporal trend analysis revealed an exponential growth of published studies over the last decade (70% since 2016), confirming the emerging role of this topic in environmental science. The meta-analysis determined that 4-methylbenzylidene-camphor (4-MBC) and benzophenone-3 (BP-3) are top-priority environmental pollutants due to their increasing usage and, in turn, a frequent occurrence in marine ecosystems. This meta-analysis determined the focus on these two contaminants for this review. A critical discussion of the applications, regulatory aspects, and environmental occurrences of these selected compounds was provided. The present study also focused on the most recent (2015-2021) field and laboratory studies investigating the ecotoxicological impacts of 4-MBC and BP-3 on marine invertebrates. This review highlights the need for more research efforts to fill the knowledge gaps on the realistic effects these compounds may have when considered individually, in combination, or as subsequent exposures. Overall, this review aims to establish guidelines for further studies to understand the effect of UV-filters on marine ecosystems and marine invertebrate communities.

A QSAR-ICE-SSD model prediction of the PNECs for alkylphenol substances and application in ecological risk assessment for rivers of a megacity

Alkylphenols (APs) are ubiquitous and generally present in higher residue levels in the environment. The present work focuses on the development of a set of in silico models to predict the aquatic toxicity of APs with incomplete/unknown toxicity data in aquatic environments. To achieve this, a QSAR-ICE-SSD model was constructed for aquatic organisms by combining quantitative structure-activity relationship (QSAR), interspecies correlation estimation (ICE), and species sensitivity distribution (SSD) models in order to obtain the hazardous concentrations (HCs) of selected APs. The research indicated that the keywords "alkylphenol" and "nonylphenol" were most commonly studied. The selected ICE models were robust (R2: 0.70-0.99; p-value < 0.01). All models had a high reliability cross- validation success rates (>75%), and the HC5 predicted with the QSAR-ICE-SSD model was 2-fold than that derived with measured experimental data. The HC5 values demonstrated nearly linear decreasing trend from 2-MP to 4-HTP, while the decreasing trend from 4-HTP to 4-DP became shallower, indicates that the toxicity of APs to aquatic organisms increases with the addition of alkyl carbon chain lengths. The ecological risks assessment (ERA) of APs revealed that aquatic organisms were at risk from exposure to 4-NP at most river stations (the highest risk quotient (RQ) = 1.51), with the highest relative risk associated with 2.9% of 4-NP detected in 82.9% of the sampling sites. The targeted APs posed potential ecological risks in the Yongding and Beiyun River according to the mixture ERA. The potential application of QSAR-ICE-SSD models could satisfy the immediate needs for HC5 derivations without the need for additional in vivo testing.

Can Chemical Toxicity in Saltwater Be Predicted from Toxicity in Freshwater? A Comprehensive Evaluation Using Species Sensitivity Distributions

Species sensitivity distributions (SSDs) play an important role in ecological risk assessment. Estimating SSDs requires toxicity data for many species, but reports on saltwater species are often limited compared to freshwater species. This limitation can constrain informed management of saltwater quality for the protection of marine ecosystems. We investigated the relationships between the parameters (i.e., mean and standard deviation [SD]) of freshwater and saltwater log-normal SSDs to determine how accurately saltwater toxicity could be estimated from freshwater toxicity test data. We estimated freshwater and saltwater SSDs for 104 chemicals with reported acute toxicity data for five or more species and compared their means, SDs, and hazardous concentrations for 5% of the species (HC5) derived from the acute SSDs. Standard major axis regression analyses generally showed that log-log relationships between freshwater and saltwater SSD means, SDs, and HC5 values were nearly 1:1. In addition, the ratios of freshwater-to-saltwater SSD means and HC5 values for most of the 104 chemicals fell within the range 0.1-10. Although such a strong correlation was not observed for SSD SDs (r²  < 0.5), differences between freshwater and saltwater SSD SDs were relatively small. These results indicate that saltwater acute SSDs can be reasonably estimated using freshwater acute SSDs. Because the differences of the means and SDs between freshwater and saltwater SSDs were larger when the number of test species used for SSD estimation was lower (i.e., five to seven species in the present study), obtaining toxicity data for an adequate number of species will be key to better approximation of a saltwater acute SSD from a freshwater acute SSD for a given chemical. Environ Toxicol Chem 2022;41:2021-2027. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.