Unraveling longitudinal pollution patterns of organic micropollutants in a river by non-target screening and cluster analysis

Preliminary dataset of emerging contaminants in surface water, bottom water, porewater, and sediment: Urban and aquaculture impacts in Coliumo bay and Caucahue Channel in the central and southern coast of Chile

Synthetic organic chemicals, including pesticides, pharmaceuticals, and industrial compounds, pose a growing threat to marine ecosystems. Despite their potential impact, data on the co-occurrence of these contaminants in multiple compartments, including surface water, bottom water, porewater, and sediment in the marine environment remains limited. Such information is critical for assessing coastal chemical status, establishing environmental quality benchmarks, and conducting comprehensive environmental risk assessments. In this study, we describe a multifaceted monitoring campaign targeting pesticides, pharmaceuticals, surfactants, additives, and plasticizers among other synthetic chemicals in four sampling sites. One site was located in the small Coliumo bay affected by urban settlements and tourism in central-south and additionally, we sampled three sites, Caucahue Channel, affected by urban settlements and salmon farming in northern Patagonia in Chile. Surface water, bottom water, porewater, and adjacent sediment samples were collected for target screening analysis in LC- and GC-HRMS platforms. Our results show the detection of up to 83 chemicals in surface water, 71 in bottom water, 101 in porewater, and 244 in sediments. To enhance data utility and reuse potential, we provide valuable information on the mode of action and molecular targets of the identified chemicals. This comprehensive dataset contributes to defining pollution fingerprints in coastal areas of the Global South, including remote regions in Patagonia. It serves as a critical resource for future research including marine chemical risk assessment, policymaking, and the advancement of environmental protection in these regions.

Occurrence, removal and risk assessment of chemicals of emerging concern in selected rivers and wastewater treatment plants in western Kenya

Water resources play a crucial role in sustaining life on earth yet chemicals of emerging concern (CECs) arising from extensive human applications are an increasing threat towards their existence. In this study, we examined the occurrence, removal and potential risk of CECs found in rivers and wastewater treatment plants (WWTPs) in western Kenya. Samples were prepared by solid-phase extraction and analysed using high performance liquid chromatography-mass spectrometry with a target list of 785 compounds. Out of these, 333 and 352 (influent 322, effluent 265) compounds were quantified in rivers and wastewater respectively, with pharmaceuticals, industrial compounds, and pesticides being frequently detected in both rivers and WWTPs. Compounds with highest concentrations included saccharin (9.9 μg/L), metformin (7.5 μg/L), and oxypurinol (6.5 μg/L) in rivers whereas caffeine (280 μg/L), deoxycholic acid (179 μg/L), 2-oxindole (10.9 μg/L) and ibuprofen (8.1 μg/L) were found at high concentrations in WWTPs. Based on the types of crops grown, samples from maize growing regions recorded the highest number of pesticides (75) which coincided with the spraying season. The WWTP showed the capacity to eliminate some compounds although the removal efficiencies varied greatly with 204 compounds exhibiting an average removal efficiency exceeding 50 %. Based on the risk assessment, crustaceans had the highest potential risk for toxicity with toxic unit (TU) values up to 5.4 driven primarily by diazinon and dichlorvos followed by algae (TU up to 0.07) and fish (TU up to 0.01) in rivers. A similar trend was observed in WWTP with diazinon (TU up to 5.5), diuron (TU up to 0.07) and carbendazim (TU up to 0.006) driving the risk for crustaceans, algae and fish respectively. These findings highlight the significance of surface water and WWTPs as sources and sinks of CECs in the environment translating to potential risks on aquatic organisms and humans.

One like all? Behavioral response range of native and invasive amphipods to neonicotinoid exposure

Native and invasive species often occupy similar ecological niches and environments where they face comparable risks from chemical exposure. Sometimes, invasive species are phylogenetically related to native species, e.g. they may come from the same family and have potentially similar sensitivities to environmental stressors due to phylogenetic conservatism and ecological similarity. However, empirical studies that aim to understand the nuanced impacts of chemicals on the full range of closely related species are rare, yet they would help to comprehend patterns of current biodiversity loss and species turnover. Behavioral sublethal endpoints are of increasing ecotoxicological interest. Therefore, we investigated behavioral responses (i.e., change in movement behavior) of the four dominant amphipod species in the Rhine-Main area (central Germany) when exposed to the neonicotinoid thiacloprid. Moreover, beyond species-specific behavioral responses, ecological interactions (e.g. parasitation with Acanthocephala) play a crucial role in shaping behavior, and we have considered these infections in our analysis. Our findings revealed distinct baseline behaviors and species-specific responses to thiacloprid exposure. Notably, Gammarus fossarum exhibited biphasic behavioral changes with hyperactivity at low concentrations that decreased at higher concentrations. Whereas Gammarus pulex, Gammarus roeselii and the invasive species Dikerogammarus villosus, showed no or weaker behavioral responses. This may partly explain why G. fossarum disappears in chemically polluted regions while the other species persist there to a certain degree. But it also shows that potential pre-exposure in the habitat may influence behavioral responses of the other amphipod species, because habituation occurs, and potential hyperactivity would be harmful to individuals in the habitat. The observed responses were further influenced by acanthocephalan parasites, which altered baseline behavior in G. roeselii and enhanced the behavioral response to thiacloprid exposure. Our results underscore the intricate and diverse nature of responses among closely related amphipod species, highlighting their unique vulnerabilities in anthropogenically impacted freshwater ecosystems.

Handling of problematic ion chromatograms with the Automated Target Screening (ATS) workflow for unsupervised analysis of high-resolution mass spectrometry data

Liquid chromatography (LC) or gas chromatography (GC) coupled to high-resolution mass spectrometry (HRMS) is a versatile analytical method for the analysis of thousands of chemical pollutants that can be found in environmental and biological samples. While the tools for handling such complex datasets have improved, there are still no fully automated workflows for targeted screening analysis. Here we present an R-based workflow that is able to cope with challenging data like noisy ion chromatograms, retention time shifts, and multiple peak patterns. The workflow can be applied to batches of HRMS data recorded after GC with electron ionization (GC-EI) and LC coupled to electrospray ionization in both negative and positive mode (LC-ESIneg/LC-ESIpos) to perform peak annotation and quantitation fully unsupervised. We used Orbitrap HRMS data of surface water extracts to compare the Automated Target Screening (ATS) workflow with data evaluations performed with the vendor software TraceFinder and the established semi-automated analysis workflow in the MZmine software. The ATS approach increased the overall evaluation performance of the peak annotation compared to the established MZmine module without the need for any post-hoc corrections. The overall accuracy increased from 0.80 to 0.86 (LC-ESIpos), from 0.77 to 0.83 (LC-ESIneg), and from 0.67 to 0.76 (GC-EI). The mean average percentage errors for quantification of ATS were around 30% compared to the manual quantification with TraceFinder. The ATS workflow enables time-efficient analysis of GC- and LC-HRMS data and accelerates and improves the applicability of target screening in studies with a large number of analytes and sample sizes without the need for manual intervention.

Evaluation of GC-EI&CI-TOFMS for Nontarget Analysis of Industrial Wastewater Using Hydrophilic-Lipophilic-Balanced SPME

The evaluation of nontarget analysis (NTA) techniques for the monitoring of wastewater is important as wastewater is an anthropogenic pollution source for aquatic ecosystems and a threat to human and environmental health. This study presents the proof-of-concept NTA of industrial wastewater samples. A prototype hydrophilic-lipophilic-balanced (HLB) SPME and gas chromatography interfaced with time-of-flight high-resolution mass spectrometry (GC-TOFMS) with electron ionization (EI) and chemical ionization (CI) in parallel are employed. The HLB-SPME consists of a poly(divinylbenzene-co-N-vinylpyrrolidone) structure, allowing the extraction of hydrophilic as well as lipophilic substances. As the combination of parallel CI and EI data provides a comprehensive data set as a unique feature, this study is strongly focused on the compound identification procedure and confidence reporting of exemplary substances. Furthermore, the use of three different CI reagent ions, including [N2H]+/[N4H]+, [H3O]+, and [NH4]+, enables a broad range of analytes to be ionized in terms of selectivity and softness. The complementary information provided by EI and CI data allows a level 3 identification or higher in 69% of cases. The polarity coverage based on the physicochemical properties of the analytes (such as volatility, water solubility, hydrophilicity, and lipophilicity) was visualized by using Henry's law and octanol-water partitioning constants. In conclusion, the presented approach is shown to be valuable for water analysis and allows enhanced and accelerated compound identification compared to utilizing only one type of ionization.

Spatial and temporal variability of micropollutants within a wastewater catchment system

Treated wastewater effluent is a major contributor to concentrations of many anthropogenic chemicals in the environment. Examining patterns of these compounds measured from different catchment areas comprising the influent to a wastewater treatment plant, across many months, may reveal patterns in compound sources and seasonality helpful to management efforts. This study considers a wastewater catchment system that was sampled at six sub-catchment sites plus the treatment plant influent and effluent at seven time points spanning nine months. Wastewater samples were analyzed with LC-QTOF-MS using positive electrospray ionization and GC-QTOF-MS using negative chemical ionization and electron ionization. MS data were screened against spectral libraries to identify micropollutants. As expected, multiple classes of chemicals were represented, including pharmaceuticals, plasticizers, personal care products, and flame retardants. Patterns in the compounds seen at different sampling sites and dates reflect the varying uses and down-the-drain routes that influence micropollutant loading in sewer systems. Patterns in examined compounds revealed little spatial variation, and greater temporal variation. For example, the greatest loads of DEET were found to occur in the summer months. Additionally, groups of compounds exhibited strong correlation with each other, which could be indicative of similar down-the-drain routes (such as a group intercorrelated chemicals that are components of cleaning products) or the influence of similar physicochemical processes within the sewer system. This study contributes to the understanding of dynamics of micropollutants in sewer systems.

Unraveling the chemical fingerprint of the Miami River sources: Insights from high-resolution mass spectrometry and nontarget analysis

This study investigated the chemical composition of waters in the heavily urbanized and historically polluted Miami River, Florida. The goal was to assess the different water sources and anthropogenic influence in this managed area using nontarget analysis (NTA) combined with high-resolution mass spectrometry (HRMS). Surface water samples were collected from 10 sites during five sampling events in the wet season of 2021 and 2022. The HRMS data was processed using Compound Discoverer™ version 3.3, and the results were analyzed using techniques including Principal Component Analysis and Kendrick Mass Defect plots. Results showed a gradient change in the chemical composition from the Everglades to Biscayne Bay endmembers. The Seybold Canal, an adjacent canal, was consistently identified as a unique source of contaminants, contributing its own specific set of tracers. Increased presence and intensity of organic contaminants along the waterway was observed, indicating significant anthropogenic influence in the area. The NTA and post-processing were evaluated for reproducibility, demonstrating robustness with a 71.2% average reproducibility for compounds detected in 3 out of 5 sampling trips. A detection frequency of 80% (4 out of 5) was the set criterion for detected compounds suggested as tracers. To prioritize samples, hierarchical cluster analysis was employed, and potential tracers for each water source were determined. Tracers included natural products and agricultural herbicides and insecticides for the Everglades, anthropogenic contaminants for the Seybold Canal, and a lack of unique tracers for Biscayne Bay. Additionally, urban-influenced contaminants such as flame retardants, insect repellents, pharmaceuticals, and non-agricultural herbicides were identified along the river. This study highlights the impact of human activities on the Miami River and demonstrates the effectiveness of NTA in differentiating and tracking water sources. The results emphasize the importance of reproducibility in NTA and provide guidance on implementing monitoring strategies by prioritizing samples based on chemical compositions.

Curated mode-of-action data and effect concentrations for chemicals relevant for the aquatic environment

Chemicals in the aquatic environment can be harmful to organisms and ecosystems. Knowledge on effect concentrations as well as on mechanisms and modes of interaction with biological molecules and signaling pathways is necessary to perform chemical risk assessment and identify toxic compounds. To this end, we developed criteria and a pipeline for harvesting and summarizing effect concentrations from the US ECOTOX database for the three aquatic species groups algae, crustaceans, and fish and researched the modes of action of more than 3,300 environmentally relevant chemicals in literature and databases. We provide a curated dataset ready to be used for risk assessment based on monitoring data and the first comprehensive collection and categorization of modes of action of environmental chemicals. Authorities, regulators, and scientists can use this data for the grouping of chemicals, the establishment of meaningful assessment groups, and the development of in vitro and in silico approaches for chemical testing and assessment.

Non-target analysis for water characterization: wastewater treatment impact and selection of relevant features

Non-target analyses were conducted to characterize and compare the molecular profiles (UHPLC-HRMS fingerprint) of water samples from a wastewater treatment plant (WWTP). Inlet and outlet samples were collected from three campaigns spaced 6 months apart in order to highlight common trends. A significant impact of the treatment on the sample fingerprints was shown, with a 65-70% abatement of the number of features detected in the effluent, and more polar, smaller and less intense molecules found overall compared to those in WWTP influent waters. Multivariate analysis (PCA) associated with variations of the features between inlets and outlets showed that features appearing or increasing were correlated with effluents while those disappearing or decreasing were correlated with influents. Finally, effluent features considered as relevant to a potentially adverse effect on aqueous media (i.e. those which appeared or increased or slightly varied from the influent) were highlighted. Three hundred seventy-five features common with the 3 campaigns were thus selected and further characterized. For most of them, elementary composition was found to be C, H, N, O (42%) and C, H, N, O, P (18%). Considering the MS2 spectra and several reference MS2 databases, annotations were proposed for 35 of these relevant features. They include synthetic products, pharmaceuticals and metabolites.

Assessing background contamination of sample tubes used in human biomonitoring by non-targeted liquid chromatography-high resolution mass spectrometry

Controlling and minimising background contamination is crucial for maintaining a high quality of samples in human biomonitoring targeting organic chemicals. We assessed the contamination of three previous types and one newly introduced medical-grade type of sample tubes used for storing human body fluids at the German Environmental Specimen Bank. Aqueous extracts from these tubes were analysed by non-targeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) before and after a dedicated cleaning procedure. After peak detection using MZmine, Bayesian hypothesis testing was used to group peaks into those originating either from instrumental and laboratory background contamination, or actual tube contaminants, based on if their peak height was reduced, increased or not affected by the cleaning procedure. For all four tube types 80-90% of the 2475 peaks (1549 in positive and 926 in negative mode) were assigned to laboratory/instrumental background, which we have to consider as potential sample tube contaminants. Among the tube contaminants, results suggest a considerable difference in the contaminant peak inventory and the absolute level of contamination among the different sample tube types. The cleaning procedure did not affect the largest fraction of peaks (50-70%). For the medical grade tubes, the removal of contaminants by the cleaning procedure was strongest compared to the previous tubes, but in all cases a small fraction increased in intensity after cleaning, probably due to a release of oligomers or additives. The identified laboratory background contaminants were mainly semi-volatile polymer additives such as phthalates and phosphate esters. A few compounds could be assigned solely as tube-specific contaminants, such as N,N-dibutylformamide and several constituents of the oligomeric light stabiliser Tinuvin-622. A cleaning procedure before use is an effective way to standardise the used sample tubes and minimises the background contamination, and therefore increases sample quality and therewith analytical results.

A dataset of organic pollutants identified and quantified in recycled polyethylene pellets

Plastics are produced with a staggering array of chemical compounds, with many being known to possess hazardous properties, and others lacking comprehensive hazard data. Furthermore, non-intentionally added substances can contaminate plastics at various stages of their lifecycle, resulting in recycled materials containing an unknown number of chemical compounds at unknown concentrations. While some national and regional regulations exist for permissible concentrations of hazardous chemicals in specific plastic products, less than 1 % of plastics chemicals are subject to international regulation [1]. There are currently no policies mandating transparent reporting of chemicals throughout the plastics value chain or comprehensive monitoring of chemicals in recycled materials. The dataset presented here provides the chemical analysis of 28 samples of recycled High-Density Polyethylene (HDPE) pellets obtained from various regions of the Global South, along with a reference sample of virgin HDPE. The analysis comprises both Target and Non-Targeted Screening approaches, employing Liquid Chromatography-High-Resolution Mass Spectrometry (LC-HRMS) and Gas Chromatography-High-Resolution Mass Spectrometry (GC-HRMS). In total, 491 organic compounds were detected and quantified, with an additional 170 compounds tentatively annotated. These compounds span various classes, including pesticides, pharmaceuticals, industrial chemicals, plastic additives. The results highlight the prevalence of certain chemicals, such as N-ethyl-o-Toluesulfonamide, commonly used in HDPE processing, found in high concentrations. The paper provides a dataset advancing knowledge of the complex chemical composition associated with recycled plastics.

Water quality variation and driving factors quantitatively evaluation of urban lakes during quick socioeconomic development

Rapid urbanisation has caused a significant impact on the ecological environment of urban lakes in the world. To maintain the harmonious development of urban progress and water quality, it is essential to evaluate water quality variation and explore the driving factors quantitatively. A comprehensive evaluation method with cluster analysis and Kriging interpolation was used to explore the spatiotemporal variation in a typical urban lake in China, Chaohu Lake, from 2011 to 2020. The correlation between water quality and socioeconomic factors was evaluated by Pearson correlation analysis. Results indicated that: total phosphorus (TP) and total nitrogen (TN) were the key pollution parameters of Chaohu Lake. The pollution situation was gradually improving, however, and the improvement in chemical oxygen demand (COD) is more evident due to anthropogenic control. The spatial heterogeneity of water quality in Chaohu Lake is remarkable, and the water quality is poor in the west but better in the east. Natural attributes of lakes and external load were the main reasons for the spatial heterogeneity. The western residential areas of Chaohu Lake Basin (CLB) are concentrated, and a large amount of industrial and domestic sewage exacerbates water pollution in the west of tributaries. In contrast, the implementation of water environmental governance policies in recent years has alleviated water pollution. From 2011 to 2020, water quality has improved by 23%-35% in the west and 7%-14% in the east. This study provided a framework for quantitatively assessing water quality variation and its driving forces in urban lakes.

Dataset comprising pesticides, pharmaceuticals and personal care products, and industrial chemicals detected in streams and rivers of Central Chile

Chemical pollution caused by synthetic organic chemicals at low concentrations in the environment poses a growing threat to the ecological status of aquatic ecosystems. These chemicals are regularly released into surface waters through both treated and untreated effluents from wastewater treatment plants (WWTPs), agricultural runoff, and industrial discharges. Consequently, they accumulate in surface waters, distribute amongst environmental compartments according to their physicochemical properties, and cause adverse effects on aquatic organisms. Unfortunately, there is a lack of data regarding the occurrence of synthetic organic chemicals, henceforth micropollutants, in South American freshwater ecosystems, especially in Chile. To address this research gap, we present a comprehensive dataset comprising concentrations of 153 emerging chemicals, including pesticides, pharmaceutical and personal care products (PPCPs), surfactants, and industrial chemicals. These chemicals were found to co-occur in surface waters within Central Chile, specifically in the River Aconcagua Basin. Our sampling strategy involved collecting surface water samples from streams and rivers with diverse land uses, such as agriculture, urban areas, and natural reserves. For sample extraction, we employed an on-site large-volume solid phase extraction (LVSPE) device. The resulting environmental extracts were then subjected to wide-scope chemical target screening using gas chromatography and liquid chromatography high-resolution mass spectrometry (GC- and LC-HRMS). The dataset we present holds significant value in assessing the chemical status of water bodies. It enables comparative analysis of pollution fingerprints associated with emerging chemicals across different freshwater systems. Moreover, the data can be reused for environmental risk assessment studies. Its utilisation will contribute to a better understanding of the impact and extent of chemical pollution in aquatic ecosystems, facilitating the development of effective mitigation strategies.

Antibiotic resistance indicator genes in biofilm and planktonic microbial communities after wastewater discharge

The spread of bacteria with antibiotic resistance genes (ARGs) in aquatic ecosystems is of growing concern as this can pose a risk of transmission to humans and animals. While the impact of wastewater treatment plant (WWTP) effluent on ARG abundance in surface waters has been studied extensively, less is known about the fate of ARGs in biofilms. The proximity and dense growth of microorganisms in combination with the accumulation of higher antibiotic concentrations in biofilms might render biofilms a reservoir for ARGs. Seasonal parameters such as water temperature, precipitation, and antibiotic concentrations should be considered as well, as they may further influence the fate of ARGs in aquatic ecosystems. Here we investigated the effect of WWTP effluent on the abundance of the sulfonamide resistance genes sul1 and sul2, and the integrase gene intI1 in biofilm and surface water compartments of a river in Germany with a gradient of anthropogenic impact using quantitative PCR. Furthermore, we analyzed the bacterial community structure in both compartments via 16S rRNA gene amplicon sequencing, following the river downstream. Additionally, conventional water parameters and sulfonamide concentrations were measured, and seasonal aspects were considered by comparing the fate of ARGs and bacterial community diversity in the surface water compartment between the summer and winter season. Our results show that biofilm compartments near the WWTP had a higher relative abundance of ARGs (up to 4.7%) than surface waters (<2.8%). Sulfonamide resistance genes were more persistent further downstream (>10 km) of the WWTP in the hot and dry summer season than in winter. This finding is likely a consequence of the higher proportion of wastewater and thus wastewater-derived microorganisms in the river during summer periods. We observed distinct bacterial communities and ARG abundance between the biofilm and surface water compartment, but even greater variations when considering seasonal and spatiotemporal parameters. This underscores the need to consider seasonal aspects when studying the fate of ARGs in aquatic ecosystems.

Bioanalytical and chemical characterization of organic micropollutant mixtures in long-term exposed passive samplers from the Joint Danube Survey 4: Setting a baseline for water quality monitoring

Monitoring methodologies reflecting the long-term quality and contamination of surface waters are needed to obtain a representative picture of pollution and identify risk drivers. This study sets a baseline for characterizing chemical pollution in the Danube River using an innovative approach, combining continuous three-months use of passive sampling technology with comprehensive chemical (747 chemicals) and bioanalytical (seven in vitro bioassays) assessment during the Joint Danube Survey (JDS4). This is one of the world's largest investigative surface-water monitoring efforts in the longest river in the European Union, which water after riverbank filtration is broadly used for drinking water production. Two types of passive samplers, silicone rubber (SR) sheets for hydrophobic compounds and AttractSPETM HLB disks for hydrophilic compounds, were deployed at nine sites for approximately 100 days. The Danube River pollution was dominated by industrial compounds in SR samplers and by industrial compounds together with pharmaceuticals and personal care products in HLB samplers. Comparison of the Estimated Environmental Concentrations with Predicted No-Effect Concentrations revealed that at the studied sites, at least one (SR) and 4-7 (HLB) compound(s) exceeded the risk quotient of 1. We also detected AhR-mediated activity, oxidative stress response, peroxisome proliferator-activated receptor gamma-mediated activity, estrogenic, androgenic, and anti-androgenic activities using in vitro bioassays. A significant portion of the AhR-mediated and estrogenic activities could be explained by detected analytes at several sites, while for the other bioassays and other sites, much of the activity remained unexplained. The effect-based trigger values for estrogenic and anti-androgenic activities were exceeded at some sites. The identified drivers of mixture in vitro effects deserve further attention in ecotoxicological and environmental pollution research. This novel approach using long-term passive sampling provides a representative benchmark of pollution and effect potentials of chemical mixtures for future water quality monitoring of the Danube River and other large water bodies.

Delivering on sustainable development goals in wastewater reuse for agriculture: Initial prioritization of emerging pollutants in the Tula Valley, Mexico

Wastewater reuse for agricultural irrigation is a widespread beneficial practice, in line with the sustainable development goals. However, contaminants of emerging concern (CECs) present in wastewater, such as pharmaceuticals, pose an environmental risk. The Tula Valley in Mexico is one of the world's largest agricultural areas reusing wastewater for agriculture. However, no untargeted CEC monitoring has been undertaken there, limiting the information available to prioritise local environmental risk assessment. Furthermore, CEC environmental presence in the Global South remains understudied, compared to the Global North. There is a risk that current research efforts focus on CECs predominantly found in the Global North, leading to strategies that may not be appropriate for the Global South where the pollution profile may be different. To address these knowledge gaps, a sampling campaign at five key sites in the Tula Valley was undertaken and samples analysed using multi-residue targeted and untargeted liquid chromatography mass spectrometry methods. Using the targeted data, ten CECs were found to be of environmental risk for at least one sampling site: 4‑tert-octylphenol, acetaminophen, bezafibrate, diclofenac, erythromycin, levonorgestrel, simvastatin, sulfamethoxazole, trimethoprim and tramadol as well as total estrogenicity (combination of three steroid hormones). Six of these have not been previously quantified in the Tula Valley. Over one hundred pollutants never previously measured in the area were identified through untargeted analysis supported by library spectrum match. Examples include diclofenac and carbamazepine metabolites and area-specific pollutants such as the herbicide fomesafen. This research contributes to characterising the presence of CECs in the Global South, as well as providing site-specific data for the Tula Valley.

Nontarget Analysis of Polluted Surface Waters in Bangladesh Using Open Science Workflows

Nontarget mass spectrometry has great potential to reveal patterns of water contamination globally through community science, but few studies are conducted in low-income countries, nor with open-source workflows, and few datasets are FAIR (Findable, Accessible, Interoperable, Reusable). Water was collected from urban and rural rivers around Dhaka, Bangladesh, and analyzed by liquid chromatography high-resolution mass spectrometry in four ionization modes (electrospray ionization ±, atmospheric pressure chemical ionization ±) with data-independent MS2 acquisition. The acquisition strategy was complementary: 19,427 and 7365 features were unique to ESI and APCI, respectively. The complexity of water pollution was revealed by >26,000 unique molecular features resolved by MS-DIAL, among which >20,000 correlated with urban sources in Dhaka. A major wastewater treatment plant was not a dominant pollution source, consistent with major contributions from uncontrolled urban drainage, a result that encourages development of further wastewater infrastructures. Matching of deconvoluted MS2 spectra to public libraries resulted in 62 confident annotations (i.e., Level 1-2a) and allowed semiquantification of 42 analytes including pharmaceuticals, pesticides, and personal care products. In silico structure prediction for the top 100 unknown molecular features associated with an urban source allowed 15 additional chemicals of anthropogenic origin to be annotated (i.e., Level 3). The authentic MS2 spectra were uploaded to MassBank Europe, mass spectral data were openly shared on the MassIVE repository, a tool (i.e., MASST) that could be used for community science environmental surveillance was demonstrated, and current limitations were discussed.

Contamination Pattern and Risk Assessment of Polar Compounds in Snow Melt: An Integrative Proxy of Road Runoffs

To assess the contamination and potential risk of snow melt with polar compounds, road and background snow was sampled during a melting event at 23 sites at the city of Leipzig and screened for 489 chemicals using liquid chromatography high-resolution mass spectrometry with target screening. Additionally, six 24 h composite samples were taken from the influent and effluent of the Leipzig wastewater treatment plant (WWTP) during the snow melt event. 207 compounds were at least detected once (concentrations between 0.80 ng/L and 75 μg/L). Consistent patterns of traffic-related compounds dominated the chemical profile (58 compounds in concentrations from 1.3 ng/L to 75 μg/L) and among them were 2-benzothiazole sulfonic acid and 1-cyclohexyl-3-phenylurea from tire wear and denatonium used as a bittern in vehicle fluids. Besides, the analysis unveiled the presence of the rubber additive 6-PPD and its transformation product N-(1.3-dimethylbutyl)-N'-phenyl-p-phenylenediamine quinone (6-PPDQ) at concentrations known to cause acute toxicity in sensitive fish species. The analysis also detected 149 other compounds such as food additives, pharmaceuticals, and pesticides. Several biocides were identified as major risk contributors, with a more site-specific occurrence, to acute toxic risks to algae (five samples) and invertebrates (six samples). Ametryn, flumioxazin, and 1,2-cyclohexane dicarboxylic acid diisononyl ester are the main compounds contributing to toxic risk for algae, while etofenprox and bendiocarb are found as the main contributors for crustacean risk. Correlations between concentrations in the WWTP influent and flow rate allowed us to discriminate compounds with snow melt and urban runoff as major sources from other compounds with other dominant sources. Removal rates in the WWTP showed that some traffic-related compounds were largely eliminated (removal rate higher than 80%) during wastewater treatment and among them was 6-PPDQ, while others persisted in the WWTP.

Screening of hazardous groundwater pollutants responsible for microbial ecological consequences by integrated nontargeted analysis and high-throughput sequencing technologies

Organic contaminants, especially hydrophobic organic contaminants (HOCs), pose potential ecological threats even at environmental concentrations. Characterization of HOC profiles and identification of key environmental stressors are vital but still challenging in groundwater quality management. In this study, a strategy for identifying the key environmental stressors among HOCs in groundwater based on integrated chemical monitoring technologies and microbial ecology analysis methods was proposed and applied to typical groundwater samples. Specifically, the characteristics of HOCs were systematically analyzed based on nontargeted and targeted approaches, and microbial community assembly and specific biomarker analysis were combined to determine the major ecological processes and key environmental stressors. The results showed that a total of 234 HOCs were detected in groundwater collected from Tongzhou, Beijing; among them, phthalate esters (PAEs) were screened out as key environmental stressors, considering that they made relatively higher microbial ecology contributions. Furthermore, their influences on the structure and function of the groundwater microbial community were evaluated by adopting high-throughput sequencing and bioinformatics analysis technologies. These findings confirmed PAEs as vital determinants driving microbial assembly, shifting community structure, and regulating community function in groundwater; in addition, the findings validated the feasibility and suitability of the proposed strategy.

The fate of sulfonamide resistance genes and anthropogenic pollution marker intI1 after discharge of wastewater into a pristine river stream

Introduction

Currently there are sparse regulations regarding the discharge of antibiotics from wastewater treatment plants (WWTP) into river systems, making surface waters a latent reservoir for antibiotics and antibiotic resistance genes (ARGs). To better understand factors that influence the fate of ARGs in the environment and to foster surveillance of antibiotic resistance spreading in such habitats, several indicator genes have been proposed, including the integrase gene intI1 and the sulfonamide resistance genes sul1 and sul2.

Methods

Here we used quantitative PCR and long-read nanopore sequencing to monitor the abundance of these indicator genes and ARGs present as class 1 integron gene cassettes in a river system from pristine source to WWTP-impacted water. ARG abundance was compared with the dynamics of the microbial communities determined via 16S rRNA gene amplicon sequencing, conventional water parameters and the concentration of sulfamethoxazole (SMX), sulfamethazine (SMZ) and sulfadiazine (SDZ).

Results

Our results show that WWTP effluent was the principal source of all three sulfonamides with highest concentrations for SMX (median 8.6 ng/l), and of the indicator genes sul1, sul2 and intI1 with median relative abundance to 16S rRNA gene of 0.55, 0.77 and 0.65%, respectively. Downstream from the WWTP, water quality improved constantly, including lower sulfonamide concentrations, decreasing abundances of sul1 and sul2 and lower numbers and diversity of ARGs in the class 1 integron. The riverine microbial community partially recovered after receiving WWTP effluent, which was consolidated by a microbiome recovery model. Surprisingly, the relative abundance of intI1 increased 3-fold over 13 km of the river stretch, suggesting an internal gene multiplication.

Discussion

We found no evidence that low amounts of sulfonamides in the aquatic environment stimulate the maintenance or even spread of corresponding ARGs. Nevertheless, class 1 integrons carrying various ARGs were still present 13 km downstream from the WWTP. Therefore, limiting the release of ARG-harboring microorganisms may be more crucial for restricting the environmental spread of antimicrobial resistance than attenuating ng/L concentrations of antibiotics.

Batch correction methods for nontarget chemical analysis data: application to a municipal wastewater collection system

Nontarget chemical analysis using high-resolution mass spectrometry has increasingly been used to discern spatial patterns and temporal trends in anthropogenic chemical abundance in natural and engineered systems. A critical experimental design consideration in such applications, especially those monitoring complex matrices over long time periods, is a choice between analyzing samples in multiple batches as they are collected, or in one batch after all samples have been processed. While datasets acquired in multiple analytical batches can include the effects of instrumental variability over time, datasets acquired in a single batch risk compound degradation during sample storage. To assess the influence of batch effects on the analysis and interpretation of nontarget data, this study examined a set of 56 samples collected from a municipal wastewater system over 7 months. Each month's samples included 6 from sites within the collection system, one combined influent, and one treated effluent sample. Samples were analyzed using liquid chromatography high-resolution mass spectrometry in positive electrospray ionization mode in multiple batches as the samples were collected and in a single batch at the conclusion of the study. Data were aligned and normalized using internal standard scaling and ComBat, an empirical Bayes method developed for estimating and removing batch effects in microarrays. As judged by multiple lines of evidence, including comparing principal variance component analysis between single and multi-batch datasets and through patterns in principal components and hierarchical clustering analyses, ComBat appeared to significantly reduce the influence of batch effects. For this reason, we recommend the use of more, small batches with an appropriate batch correction step rather than acquisition in one large batch.

Spatial and temporal variations in anti-androgenic activity and environmental risk in a small river

The biological effects of multiple compounds have been widely investigated in aquatic environments. However, investigations of spatial and temporal variations in biological effects are rarely performed because they are time-consuming and labor-intensive. In this study, the variability of the anti-androgen, receptor-mediated activity of surface water samples was observed over 3 years using in vitro bioassays. Large-volume water samples were collected at one site upstream (Wer site) and two sites downstream (Sil and Nien sites) of a wastewater treatment plant (WWTP) outfall in the Holtemme River. Anti-AR activity was persistently present in all surface water samples over the three years. Large spatial variations in anti-androgenic activity were observed, with the lowest activity at the Wer site (mean concentration of 9.5 ± 7.2 μg flutamide equivalents/L) and the highest activity at the Sil site (mean concentration of 31.1 ± 12.0 μg flutamide equivalents/L) directly influenced by WWTP effluents. On the temporal scale, no distinct trend for anti-AR activity was observed among the seasons in all three years. The anti-androgenic activity at the upstream Wer site showed a decreasing trend from 2014 to 2016, indicating improved water quality. A novel bioanalytical-equivalent-based risk assessment method considering the frequency of risk occurrence was developed and then utilized to assess the environmental risk of anti-androgenic activity in the Holtemme River. The results revealed that the highest risk was present at the Sil site, while the risk was considerably reduced at the Nien site. The risk at the upstream Wer site was the lowest.

Combining Passive Sampling with Suspect and Nontarget Screening to Characterize Organic Micropollutants in Streams Draining Mixed-Use Watersheds

Organic micropollutants (OMPs) represent an anthropogenic stressor on stream ecosystems. In this work, we combined passive sampling with suspect and nontarget screening enabled by liquid chromatography-high-resolution mass spectrometry to characterize complex mixtures of OMPs in streams draining mixed-use watersheds. Suspect screening identified 122 unique OMPs for target quantification in polar organic chemical integrative samplers (POCIS) and grab samples collected from 20 stream sites in upstate New York over two sampling seasons. Hierarchical clustering established the co-occurrence profiles of OMPs in connection with watershed attributes indicative of anthropogenic influences. Nontarget screening leveraging the time-integrative nature of POCIS and the cross-site variability in watershed attributes prioritized and confirmed 11 additional compounds that were ubiquitously present in monitored streams. Field sampling rates for 37 OMPs that simultaneously occurred in POCIS and grab samples spanned the range of 0.02 to 0.22 L/d with a median value of 0.07 L/d. Comparative analyses of the daily average loads, cumulative exposure-activity ratios, and multi-substance potentially affected fractions supported the feasibility of complementing grab sampling with POCIS for OMP load estimation and screening-level risk assessments. Overall, this work demonstrated a multi-watershed sampling and screening approach that can be adapted to assess OMP contamination in streams across landscapes.

Scientific concepts and methods for moving persistence assessments into the 21st century

The evaluation of a chemical substance's persistence is key to understanding its environmental fate, exposure concentration, and, ultimately, environmental risk. Traditional biodegradation test methods were developed many years ago for soluble, nonvolatile, single-constituent test substances, which do not represent the wide range of manufactured chemical substances. In addition, the Organisation for Economic Co-operation and Development (OECD) screening and simulation test methods do not fully reflect the environmental conditions into which substances are released and, therefore, estimates of chemical degradation half-lives can be very uncertain and may misrepresent real environmental processes. In this paper, we address the challenges and limitations facing current test methods and the scientific advances that are helping to both understand and provide solutions to them. Some of these advancements include the following: (1) robust methods that provide a deeper understanding of microbial composition, diversity, and abundance to ensure consistency and/or interpret variability between tests; (2) benchmarking tools and reference substances that aid in persistence evaluations through comparison against substances with well-quantified degradation profiles; (3) analytical methods that allow quantification for parent and metabolites at environmentally relevant concentrations, and inform on test substance bioavailability, biochemical pathways, rates of primary versus overall degradation, and rates of metabolite formation and decay; (4) modeling tools that predict the likelihood of microbial biotransformation, as well as biochemical pathways; and (5) modeling approaches that allow for derivation of more generally applicable biotransformation rate constants, by accounting for physical and/or chemical processes and test system design when evaluating test data. We also identify that, while such advancements could improve the certainty and accuracy of persistence assessments, the mechanisms and processes by which they are translated into regulatory practice and development of new OECD test guidelines need improving and accelerating. Where uncertainty remains, holistic weight of evidence approaches may be required to accurately assess the persistence of chemicals. Integr Environ Assess Manag 2022;18:1454-1487. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Cumulative Risk Meets Inter-Individual Variability: Probabilistic Concentration Addition of Complex Mixture Exposures in a Population-Based Human In Vitro Model

Although humans are continuously exposed to complex chemical mixtures in the environment, it has been extremely challenging to investigate the resulting cumulative risks and impacts. Recent studies proposed the use of “new approach methods,” in particular in vitro assays, for hazard and dose−response evaluation of mixtures. We previously found, using five human cell-based assays, that concentration addition (CA), the usual default approach to calculate cumulative risk, is mostly accurate to within an order of magnitude. Here, we extend these findings to further investigate how cell-based data can be used to quantify inter-individual variability in CA. Utilizing data from testing 42 Superfund priority chemicals separately and in 8 defined mixtures in a human cell-based population-wide in vitro model, we applied CA to predict effective concentrations for cytotoxicity for each individual, for “typical” (median) and “sensitive” (first percentile) members of the population, and for the median-to-sensitive individual ratio (defined as the toxicodynamic variability factor, TDVF). We quantified the accuracy of CA with the Loewe Additivity Index (LAI). We found that LAI varies more between different mixtures than between different individuals, and that predictions of the population median are generally more accurate than predictions for the “sensitive” individual or the TDVF. Moreover, LAI values were generally <1, indicating that the mixtures were more potent than predicted by CA. Together with our previous studies, we posit that new approach methods data from human cell-based in vitro assays, including multiple phenotypes in diverse cell types and studies in a population-wide model, can fill critical data gaps in cumulative risk assessment, but more sophisticated models of in vitro mixture additivity and bioavailability may be needed. In the meantime, because simple CA models may underestimate potency by an order of magnitude or more, either whole-mixture testing in vitro or, alternatively, more stringent benchmarks of cumulative risk indices (e.g., lower hazard index) may be needed to ensure public health protection.

Complex chemical cocktail, containing insecticides diazinon and permethrin, drives acute toxicity to crustaceans in mountain lakes

Mountain lakes have long been perceived as pristine environments. However, atmospheric deposition of persistent organic pollutants (POPs) have been shown to expose these sensitive ecosystems to chemical pollution. Little is known on how this pollution impacts aquatic ecosystems at high altitudes. We combined passive sampling with liquid and gas chromatography high resolution mass spectrometry (LC- and GC-HRMS) to screen the water of eight lakes in three different regions of the French Pyrenees. In total, we screened for 479 organic chemicals including POPs, polycyclic aromatic hydrocarbons (PAHs), legacy and current-use pesticides, biocides, and musk fragrances. We detected a complex cocktail of 151 individual chemicals and used their toxic unit summation (ΣTU) to assess toxicity for crustaceans and algae. While risks for algae never reached chronic risks, this was always the case for crustaceans. Acute toxic risk thresholds for crustaceans were even exceeded in several of our sites. At sites with acute toxic risk levels (> 0.1 ΣTU) crustaceans were completely absent or showed a low abundance. We conclude that crustaceans were at least partly impacted by the high toxic risks driven by the insecticides diazinon and permethrin. These drugs are widely used to protect livestock from blue tongue disease transmitted by sucking insects, suggesting free roaming livestock as local source. Our results provide important evidence on toxic chemical pollution in relatively remote mountain areas, with important consequences for aquatic mountain ecosystems.

From data to reliable conclusions: Identification and comparison of persistent micropollutants and transformation products in 37 wastewater samples by non-target screening prioritization

In this study, micropollutants in wastewater effluents were prioritized by monitoring the composition of influent and effluent wastewater by liquid chromatography - high-resolution mass spectrometry (LCHRMS) non-target screening (NTS) analysis. The study shows how important data pre-processing and filtering of raw data is to produce reliable NTS data for comparison of compounds between many samples (37 wastewater samples) analyzed at different times. Triplicate injections were critical for reducing the number of false-positive detections. Intensity drift corrections within and between batches analyzed months apart made peak intensities comparable across samples. Adjustment of the feature detection threshold was shown to be important, due to large intensity variations for low abundance compounds across batches. When the threshold correction cut-offs, or the filtering of relevant compounds by the occurrence frequency, were too stringent, a high number of false positive transformation products (TPs) were reported. We also showed that matrix effect correction by internal standards can over- or under-correct the intensity for unknown compounds, thus the TIC matrix effect correction was shown as an additional tool for a retention time dependent matrix effect correction. After these preprocessing and filtering steps, we identified 78 prioritized compounds, of which 36 were persistent compounds, defined as compounds with a reduction in peak intensity between influent and effluent wastewater <50%, and 13 compounds were defined as TPs because they occurred solely in the effluent samples. Some examples of persistent compounds are 1,3-diphenylguanidine, amisulpride and the human metabolites from losartan, verapamil and methadone. To our knowledge, nine of the identified TPs have not been previously described in effluent wastewater. The TPs were derived from metoprolol, fexofenadine, DEET and losartan. The screening of all identified compounds in effluent samples from eight wastewater treatment plants (WWTPs) showed that potential drugs of abuse, anti-psychotic and anti-depressant drugs were predominant in the capital city region, whereas the anti-epileptic agents and agricultural pesticides were dominant in more rural areas.

A risk based assessment approach for chemical mixtures from wastewater treatment plant effluents

In this study, 56 effluent samples from 52 European wastewater treatment plants (WWTPs) were investigated for the occurrence of 499 emerging chemicals (ECs) and their associated potential risks to the environment. The two main objectives were (i) to extend our knowledge on chemicals occurring in treated wastewater, and (ii) to identify and prioritize compounds of concern based on three different risk assessment approaches for the identification of consensus mixture risk drivers of concern. Approaches include (i) PNEC and EQS-based regulatory risk quotients (RQs), (ii) species sensitivity distribution (SSD)-based hazard units (HUs) and (iii) toxic units (TUs) for three biological quality elements (BQEs) algae, crustacean, and fish. For this purpose, solid-phase extracts were analysed with wide-scope chemical target screening via liquid chromatography high-resolution mass spectrometry (LC-HRMS), resulting in 366 detected compounds, with concentrations ranging from < 1 ng/L to > 100 µg/L. The detected chemicals were categorized with respect to critical information relevant for risk assessment and management prioritization including: (1) frequency of occurrence, (2) measured concentrations, (3) use groups, (4) persistence & bioaccumulation, and (5) modes of action. A comprehensive assessment using RQ, HU and TU indicated exceedance of risk thresholds for the majority of effluents with RQ being the most sensitive metric. In total, 299 out of the 366 compounds were identified as mixture risk contributors in one of the approaches, while 32 chemicals were established as consensus mixture risk contributors of high concern, including a high percentage (66%) of pesticides and biocides. For samples which have passed an advanced treatment using ozonation or activated carbon (AC), consistently much lower risks were estimated.

Identifying congeners and transformation products of organic contaminants within complex chemical mixtures in impacted surface waters with a top-down non-targeted screening workflow

Over 350,000 compounds are registered for production and use including a high number of congeners found in complex chemical mixtures (CCMs). With such a high number of chemicals being released in the environment and degraded into transformation products (TPs), the challenge of identifying contaminants by non-targeted screening (NTS) is massive. "Bottom-up" studies, where compounds are subjected to conditions simulating environmental degradation to identify new TPs, are time consuming and cannot be relied upon to study the TPs of hundreds of thousands of compounds. Therefore, the development of "top-down" workflows, where the structural elucidation of unknown compounds is carried directly on the sample, is of interest. In this study, a top-down NTS workflow was developed using molecular networking and clustering (MNC). A total of 438 compounds were identified including 176 congeners of consumer product additives and 106 TPs. Reference standards were used to confirm the identification of 53 contaminants among them lesser-known pharmaceuticals (aliskiren, sitagliptin) and consumer product additives (lauramidopropyl betaine, 2,2,4-trimethyl-1,2-dihydroquinoline). The MNC tools allowed to group similar TPs and congeners together. As such, several previously unknown TPs of pesticides (metolachlor) and pharmaceuticals (gliclazide, irbesartan) were identified as tentative candidates or probable structures. Moreover, some congeners that had no entry on global repositories (PubChem, ChemSpider) were identified as probable structures. The workflow worked efficiently with oligomers containing ethylene oxide moieties, and with TPs structurally related to their parent compounds. The top-down approach shown in this study addresses several issues with the identification of congeners of industrial compounds from CCMs. Furthermore, it allows elucidating the structure of TPs directly from samples without relying on bottom-up studies under conditions discussed herein. The top-down workflow and the MNC tools show great potential for data mining and retrospective analysis of previous NTS studies.

Large-scale assessment of organic contaminant emissions from chemical and pharmaceutical manufacturing into Swiss surface waters

This study presents a nation-wide assessment of the influence of chemical and pharmaceutical manufacturing (CPM) wastewaters on synthetic organic contaminant (SOC) emissions to Swiss surface waters. Geographic Information System (GIS) based analysis of the presence of CPM in wastewater treatment plant (WWTP) catchments revealed wide distribution of this industrial sector across Switzerland, suggesting that one-third of the 718 Swiss WWTPs may be influenced by CPM wastewaters. To reflect the diversity of this type of wastewaters, we investigated the effluents of 11 WWTPs of diverse sizes and technologies, which treated 0-100% wastewater from a variety of CPM activities. In an extensive sampling campaign, we collected temporally high resolved (i.e., daily) samples for 2-3 months to capture the dynamics of CPM discharges. The > 850 samples were then measured with liquid chromatography high-resolution mass spectrometry (LC-HRMS). Non-target characterization of the LC-HRMS time series datasets revealed that CPM wastewaters left a highly variable and site-specific signature in the effluents of the WWTPs. Particularly, compared to WWTPs with purely domestic input, a larger variety of substances (up to 15 times more compounds) with higher maximum concentrations (1-2 orders of magnitude) and more uncommon substances were found in CPM-influenced effluents. Moreover, in the latter, highly fluctuating discharges often contributed to a substantial fraction of the overall emissions. The largely varying characteristics of CPM discharges between different facilities were primarily related to the type of activities at the industries (i.e., production versus processing of chemicals) as well as to the pre-treatment and storage of CPM wastewaters. Eventually, for one WWTP, LC-HRMS time series were correlated with ecotoxicity time series obtained from bioassays and major toxic components could be identified. Overall, in view of their potential relevance to water quality, a strong focus on SOC discharges from CPM is essential, including the design of situation-specific monitoring, as well as risk assessment and mitigation strategies that consider the variability of industrial emissions.

Reduced genetic diversity of freshwater amphipods in rivers with increased levels of anthropogenic organic micropollutants

Anthropogenic chemicals in freshwater environments contribute majorly to ecosystem degradation and biodiversity decline. In particular anthropogenic organic micropollutants (AOM), a diverse group of compounds, including pesticides, pharmaceuticals, and industrial chemicals, can significantly impact freshwater organisms. AOM were found to impact genetic diversity of freshwater species; however, to which degree AOM cause changes in population genetic structure and allelic richness of freshwater macroinvertebrates remains poorly understood. Here, the impact of AOM on genetic diversity of the common amphipod Gammarus pulex (Linnaeus, 1758) (clade E) was investigated on a regional scale. The site‐specific AOM levels and their toxic potentials were determined in water and G. pulex tissue sample extracts for 34 sites along six rivers in central Germany impacted by wastewater effluents and agricultural run‐off. Population genetic parameters were determined for G. pulex from the sampling sites by genotyping 16 microsatellite loci. Genetic differentiation among G. pulex from the studied rivers was found to be associated with geographic distance between sites and to differences in site‐specific concentrations of AOM. The genetic diversity parameters of G. pulex were found to be related to the site‐specific AOM levels. Allelic richness was significantly negatively correlated with levels of AOM in G. pulex tissue (p < 0.003) and was reduced by up to 22% at sites with increased levels of AOM, despite a positive relationship of allelic richness and the presence of waste‐water effluent. In addition, the inbreeding coefficient of G. pulex from sites with toxic AOM levels was up to 2.5 times higher than that of G. pulex from more pristine sites. These results indicate that AOM levels commonly found in European rivers significantly contribute to changes in the genetic diversity of an ecologically relevant indicator species.

A Multi-Dimensional Investigation on Water Quality of Urban Rivers with Emphasis on Implications for the Optimization of Monitoring Strategy

Water quality monitoring (WQM) of urban rivers has been a reliable method to supervise the urban water environment. Indiscriminate WQM strategies can hardly emphasize the concerning pollution and usually require high costs of money, time, and manpower. To tackle these issues, this work carried out a multi-dimensional study (large spatial scale, multiple monitoring parameters, and long time scale) on the water quality of two urban rivers in Jiujiang City, China, which can provide indicative information for the optimization of WQM. Of note, the spatial distribution of NH3-N concentration varied significantly both in terms of the two different rivers as well as the different sections (i.e., much higher in the northern section), with a maximal difference, on average greater, than five times. Statistical methods and machine learning algorithms were applied to optimize the monitoring objects, parameters, and frequency. The sharp decrease in water quality of adjacent sections was identified by Analytical Hierarchy Process of water quality assessment indexes. After correlation analysis, principal component analysis, and cluster analysis, the various WQM parameters could be divided into three principal components and four clusters. With the machine learning algorithm of Random Forest, the relation between concentration of pollutants and rainfall depth was fitted using quadratic functions (calculated Pearson correlation coefficients ≥ 0.89), which could help predict the pollution after precipitation and further determine the appropriate WQM frequency. Generally, this work provides a novel thought for efficient, smart, and low-cost water quality investigation and monitoring strategy determination, which contributes to the construction of smart water systems and sustainable water source management.

Demonstration of an aggregated biomarker response approach to assess the impact of point and diffuse contaminant sources in feral fish in a small river case study

The assessment of the exposure of aquatic wildlife to complex environmental mixtures of chemicals originating from both point and diffuse sources and evaluating the potential impact thereof constitutes a significant step towards mitigating toxic pressure and the improvement of ecological status. In the current proof-of-concept study, we demonstrate the potential of a novel Aggregated Biomarker Response (ABR) approach involving a comprehensive set of biomarkers to identify complex exposure and impacts on wild brown trout (Salmo trutta fario). Our scenario used a small lowland river in Germany (Holtemme river in the Elbe river catchment) impacted by two wastewater treatment plants (WWTP) and diffuse agricultural runoff as a case study. The trout were collected along a pollution gradient (characterised in a parallel study) in the river. Compared to fish from the reference site upstream of the first WWTP, the trout collected downstream of the WWTPs showed a significant increase in micronucleus formation, phase I and II enzyme activities, and oxidative stress parameters in agreement with increasing exposure to various chemicals. By integrating single biomarker responses into an aggregated biomarker response, the two WWTPs' contribution to the observed toxicity could be clearly differentiated. The ABR results were supported by chemical analyses and whole transcriptome data, which revealed alterations of steroid biosynthesis and associated pathways, including an anti-androgenic effect, as some of the key drivers of the observed toxicity. Overall, this combined approach of in situ biomarker responses complemented with molecular pathway analysis allowed for a comprehensive ecotoxicological assessment of fish along the river. This study provides evidence for specific hazard potentials caused by mixtures of agricultural and WWTP derived chemicals at sublethal concentrations. Using aggregated biomarker responses combined with chemical analyses enabled an evidence-based ranking of sites with different degrees of pollution according to toxic stress and observed effects.

Coupling Suspect and Nontarget Screening with Mass Balance Modeling to Characterize Organic Micropollutants in the Onondaga Lake-Three Rivers System

Characterizing the occurrence, sources, and fate of organic micropollutants (OMPs) in lake-river systems serves as an important foundation for constraining the potential impacts of OMPs on the ecosystem functions of these critical landscape features. In this work, we combined suspect and nontarget screening with mass balance modeling to investigate OMP contamination in the Onondaga Lake-Three Rivers system of New York. Suspect and nontarget screening enabled by liquid chromatography-high-resolution mass spectrometry led to the confirmation and quantification of 105 OMPs in water samples collected throughout the lake-river system, which were grouped by their concentration patterns into wastewater-derived and mixed-source clusters via hierarchical cluster analysis. Four of these OMPs (i.e., galaxolidone, diphenylphosphinic acid, N-butylbenzenesulfonamide, and triisopropanolamine) were prioritized and identified by nontarget screening based on their characteristic vertical distribution patterns during thermal stratification in Onondaga Lake. Mass balance modeling performed using the concentration and discharge data highlighted the export of OMPs from Onondaga Lake to the Three Rivers as a major contributor to the OMP budget in this lake-river system. Overall, this work demonstrated the utility of an integrated screening and modeling framework that can be adapted for OMP characterization, fate assessment, and load apportionment in similar surface water systems.

Exploring personal chemical exposures in China with wearable air pollutant monitors: A repeated-measure study in healthy older adults in Jinan, China

The health impact of airborne contaminants has been challenging to assess due to current limitations in measurement technologies. The emergence of wearable passive samplers coupled with high resolution mass spectrometry (HR-MS) chemical analysis has enabled comprehensive characterization of personal exposures. We conducted a repeated-measure study among 84 older adults in Jinan, China, as part of the Biomarkers for Air Pollutants Exposure (China BAPE) study. Study objectives were: 1) to characterize the occurrence, magnitude, and distribution of personal exposure to airborne contaminants; 2) to evaluate the temporal variation of chemical exposures across the study population; and 3) to identify behavioral and environmental factors that influence the observed variance in chemical exposures. The FreshAir wristband was worn by participants for three consecutive days each month from September 2018 to January 2019 and collected with paired time-activity logs. Passive air samplers were also deployed in parallel at a local outdoor air monitoring station. Spearman's Rho trend test and trajectory cluster analysis were used to identify exposure trends and variation patterns, respectively. Out of the 70 airborne compounds of potential concern screened, 26 compounds from 10 chemical classes were found to be above detection thresholds across >70% of the study population. Personal exposures were predominantly characterized by nine polycyclic aromatic hydrocarbons (PAHs), four phthalates, three nitroaromatics, and two volatile organic compounds (VOCs). Phthalate personal exposures were positively correlated with outdoor temperatures while the inverse relationship was observed for certain PAHs (p < 0.05). Specifically, dimethyl phthalate (r_s = 0.31) decreased as temperatures declined, while nitrobenzene (r_s = -0.35) and naphthalene (r_s = -0.40) increased as temperatures decreased. Compared to levels measured at the outdoor air monitoring site, personal exposure of phthalates was elevated (p < 0.05) and hexachlorobutadiene was lower across participants (p < 0.01). Personal exposure of these chemicals was further found to be weakly associated with daily duration participants spent outdoors. Individuals formed distinct clusters based on trajectories of chemical exposures across the sampling period (September to January), potentially suggestive of distinct emission sources. In conclusion, we demonstrate the feasibility of characterizing the occurrence and magnitude of personal exposure to airborne chemical contaminants using passive wristband samplers. The temporal variability of these personal exposure profiles was highlighted and with distinct trends identified across different groups of individuals. Future studies will integrate this data with other omics datasets collected from this population of Chinese older adults to investigate associations between exposure profiles and health relevant biomarkers, to provide evidence in feasibility of disease prevention through environmental improvements.

Sources and Fate of the Antiandrogenic Fluorescent Dye 4-Methyl-7-Diethylaminocoumarin in Small River Systems

Recently, the potent antiandrogen 4-methyl-7-diethylaminocoumarin (C47) and its potential transformation products 4-methyl-7-ethylaminocoumarin (C47T1) and 4-methyl-7-aminocoumarin (C47T2) were identified as novel environmental contaminants. We assessed for the first time the sources, distribution, and fate of these compounds in aquatic systems using the Holtemme River (Saxony-Anhalt, Germany), which is a hotspot for these contaminants. To this end, wastewater-treatment plant (WWTP) influent and effluent samples, surface water samples over 3 years, and the longitudinal profiles in water, sediment, and gammarids were analyzed. From the longitudinal profile of the river stretch, the WWTP of Silstedt was identified as the sole point source for these compounds in the River Holtemme, and exposure concentrations in the low micrograms per liter range could be recorded continuously over 3 years. Analysis of WWTP influent and effluent showed a transformation of approximately half of the C47 into C47T1 and C47T2 but no complete removal. A further attenuation of the three coumarins after discharge into the river could be largely attributed to dilution, while transformation was only approximately 20%, thus suggesting a significant persistence in aquatic systems. Experimentally derived partitioning coefficients between water and sediment organic carbon exceeded those predicted using the OPERA quantitative structure-activity relationship tools and polyparameter linear free-energy relationships by up to 93-fold, suggesting cation binding as a significant factor for their sorption behavior. Near-equilibrium conditions between water and sediment were not observed close to the emitting WWTP but farther downstream in the river. Experimental and predicted bioaccumulation factors for gammarids were closely matching, and the concentrations in field-sampled gammarids were close to steady state with exposure concentrations in the water phase of the river. Environ Toxicol Chem 2021;40:3078-3091. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Non-target trend analysis for the identification of transformation products during ozonation experiments of citalopram and four of its biodegradation products

During ozonation in wastewater treatment plants, ozone reacts with emerging pollutants, which are partially removed through the secondary treatment, as long as, with their biotransformation products, triggering the formation of ozonation transformation products (TPs). Although the transformation of parent compounds (PCs) and their metabolites has been reported in the literature, the probable transformation of biotransformation products has not been investigated so far. This study evaluates the fate of citalopram (CTR) and four of its biotransformation products (DESCTR, CTRAM, CTRAC and CTROXO) during ozonation experiments. A Gaussian curve-based trend analysis was performed for the first time for the automated detection of TPs in ozone concentrations ranging from 0.06 to 12 mg/L. In total 46 ozonation TPs were detected; 7 TPs of CTR, 10 of DESCTR, 9 of CTRAM, 12 of CTRAC and 8 of CTROXO and were structurally elucidated based on their high resolution tandem mass spectra interpretation and tandem mass spectra similarity with the respective PC. Results have demonstrated that the examined compounds follow common transformation pathways in reaction with ozone and that common TPs were formed through the ozonation of different structurally-alike compounds. Moreover, the toxicity of the identified TPs was predicted with an in-house risk assessment program.

Development and Application of Liquid Chromatographic Retention Time Indices in HRMS-Based Suspect and Nontarget Screening

There is an increasing need for comparable and harmonized retention times (t_R) in liquid chromatography (LC) among different laboratories, to provide supplementary evidence for the identity of compounds in high-resolution mass spectrometry (HRMS)-based suspect and nontarget screening investigations. In this study, a rigorously tested, flexible, and less system-dependent unified retention time index (RTI) approach for LC is presented, based on the calibration of the elution pattern. Two sets of 18 calibrants were selected for each of ESI+ and ESI-based on the maximum overlap with the retention times and chemical similarity indices from a total set of 2123 compounds. The resulting calibration set, with RTI set to range between 1 and 1000, was proposed as the most appropriate RTI system after rigorous evaluation, coordinated by the NORMAN network. The validation of the proposed RTI system was done externally on different instrumentation and LC conditions. The RTI can also be used to check the reproducibility and quality of LC conditions. Two quantitative structure-retention relationship (QSRR)-based models were built based on the developed RTI systems, which assist in the removal of false-positive annotations. The applicability domains of the QSRR models allowed completing the identification process with higher confidence for substances within the domain, while indicating those substances for which results should be treated with caution. The proposed RTI system was used to improve confidence in suspect and nontarget screening and increase the comparability between laboratories as demonstrated for two examples. All RTI-related calculations can be performed online at http://rti.chem.uoa.gr/.

Disentangling multiple chemical and non-chemical stressors in a lotic ecosystem using a longitudinal approach

Meeting ecological and water quality standards in lotic ecosystems is often failed due to multiple stressors. However, disentangling stressor effects and identifying relevant stressor-effect-relationships in complex environmental settings remain major challenges. By combining state-of-the-art methods from ecotoxicology and aquatic ecosystem analysis, we aimed here to disentangle the effects of multiple chemical and non-chemical stressors along a longitudinal land use gradient in a third-order river in Germany. We distinguished and evaluated four dominant stressor categories along this gradient: (1) Hydromorphological alterations: Flow diversity and substrate diversity correlated with the EU-Water Framework Directive based indicators for the quality element macroinvertebrates, which deteriorated at the transition from near-natural reference sites to urban sites. (2) Elevated nutrient levels and eutrophication: Low to moderate nutrient concentrations together with complete canopy cover at the reference sites correlated with low densities of benthic algae (biofilms). We found no more systematic relation of algal density with nutrient concentrations at the downstream sites, suggesting that limiting concentrations are exceeded already at moderate nutrient concentrations and reduced shading by riparian vegetation. (3) Elevated organic matter levels: Wastewater treatment plants (WWTP) and stormwater drainage systems were the primary sources of bioavailable dissolved organic carbon. Consequently, planktonic bacterial production and especially extracellular enzyme activity increased downstream of those effluents showing local peaks. (4) Micropollutants and toxicity-related stress: WWTPs were the predominant source of toxic stress, resulting in a rapid increase of the toxicity for invertebrates and algae with only one order of magnitude below the acute toxic levels. This toxicity correlates negatively with the contribution of invertebrate species being sensitive towards pesticides (SPEAR_pesticides index), probably contributing to the loss of biodiversity recorded in response to WWTP effluents. Our longitudinal approach highlights the potential of coordinated community efforts in supplementing established monitoring methods to tackle the complex phenomenon of multiple stress.

Suspect and non-target screening: the last frontier in environmental analysis

Suspect and non-target screening (SNTS) techniques are arising as new analytical strategies useful to disentangle the environmental occurrence of the thousands of exogenous chemicals present in our ecosystems. The unbiased discovery of the wide number of substances present over environmental analysis needs to find a consensus with powerful technical and computational requirements, as well as with the time-consuming unequivocal identification of discovered analytes. Within these boundaries, the potential applications of SNTS include the studies of environmental pollution in aquatic, atmospheric, solid and biological samples, the assessment of new compounds, transformation products and metabolites, contaminant prioritization, bioremediation or soil/water treatment evaluation, and retrospective data analysis, among many others. In this review, we evaluate the state of the art of SNTS techniques going over the normalized workflow from sampling and sample treatment to instrumental analysis, data processing and a brief review of the more recent applications of SNTS in environmental occurrence and exposure to xenobiotics. The main issues related to harmonization and knowledge gaps are critically evaluated and the challenges of their implementation are assessed in order to ensure a proper use of these promising techniques in the near future.

Clustering Longitudinal Blood Pressure Trajectories to Examine Heterogeneity in Outcomes Among Preeclampsia Cases and Controls

[Figure: see text].

Symbolic Aggregate Approximation Improves Gap Filling in High-Resolution Mass Spectrometry Data Processing

Nontargeted mass spectrometry (MS) is widely used in life sciences and environmental chemistry to investigate large sets of samples. A major problem for larger-scale MS studies is data gaps or missing values in aligned data sets. The main causes for these data gaps are the absence of the compound from the sample, issues related to chromatography or mass spectrometry (for example, broad peaks, early eluting peaks, ion suppression, low ionization efficiency), and issues related to software (mainly limitations of peak detection algorithms). While those algorithms are heuristic by necessity and should be used with strict settings to minimize the number of false positive and negative peaks in a data set, gap filling may be used to reduce missing data in single samples remaining after peak detection. In this study, we present a new gap filling algorithm. The method is based on the symbolic aggregation approximation (SAX) algorithm that was developed for the evaluation and classification of time series in data mining studies. We adopted SAX for liquid chromatography high-resolution MS nontarget screening to support the detection of missing peaks in aligned mass spectral data sets. The SAX-based algorithm improves the detection efficiency considerably compared to existing gap filling methods including the Peak Finder algorithm provided in MZmine.

A Data Set of 255,000 Randomly Selected and Manually Classified Extracted Ion Chromatograms for Evaluation of Peak Detection Methods

Non-targeted mass spectrometry (MS) has become an important method over recent years in the fields of metabolomics and environmental research. While more and more algorithms and workflows become available to process a large number of non-targeted data sets, there still exist few manually evaluated universal test data sets for refining and evaluating these methods. The first step of non-targeted screening, peak detection and refinement of it is arguably the most important step for non-targeted screening. However, the absence of a model data set makes it harder for researchers to evaluate peak detection methods. In this Data Descriptor, we provide a manually checked data set consisting of 255,000 EICs (5000 peaks randomly sampled from across 51 samples) for the evaluation on peak detection and gap-filling algorithms. The data set was created from a previous real-world study, of which a subset was used to extract and manually classify ion chromatograms by three mass spectrometry experts. The data set consists of the converted mass spectrometry files, intermediate processing files and the central file containing a table with all important information for the classified peaks.