Characterization of ecotoxicological risks from unintentional mixture exposures calculated from European freshwater monitoring data: Forwarding prospective chemical risk management

Characterizing Freshwater Ecotoxicity of More Than 9000 Chemicals by Combining Different Levels of Available Measured Test Data with In Silico Predictions

Ecotoxicological impacts of chemicals released into the environment are characterized by combining fate, exposure, and effects. For characterizing effects, species sensitivity distributions (SSDs) estimate toxic pressures of chemicals as the potentially affected fraction of species. Life cycle assessment (LCA) uses SSDs to identify products with lowest ecotoxicological impacts. To reflect ambient concentrations, the Global Life Cycle Impact Assessment Method (GLAM) ecotoxicity task force recently recommended deriving SSDs for LCA based on chronic EC10s (10% effect concentration, for a life-history trait) and using the 20th percentile of an EC10-based SSD as a working point. However, because we lacked measured effect concentrations, impacts of only few chemicals were assessed, underlining data limitations for decision support. The aims of this paper were therefore to derive and validate freshwater SSDs by combining measured effect concentrations with in silico methods. Freshwater effect factors (EFs) and uncertainty estimates for use in GLAM-consistent life cycle impact assessment were then derived by combining three elements: (1) using intraspecies extrapolating effect data to estimate EC10s, (2) using interspecies quantitative structure-activity relationships, or (3) assuming a constant slope of 0.7 to derive SSDs. Species sensitivity distributions, associated EFs, and EF confidence intervals for 9862 chemicals, including data-poor ones, were estimated based on these elements. Intraspecies extrapolations and the fixed slope approach were most often applied. The resulting EFs were consistent with EFs derived from SSD-EC50 models, implying a similar chemical ecotoxicity rank order and method robustness. Our approach is an important step toward considering the potential ecotoxic impacts of chemicals currently neglected in assessment frameworks due to limited test data. Environ Toxicol Chem 2024;43:1914-1927. © 2024 The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Ecological implications and drivers of emerging contaminants in Dongting Lake of Yangtze River Basin, China: A multi-substance risk analysis

Emerging contaminants (ECs) are increasingly recognized as a global threat to biodiversity and ecosystem health. However, the cumulative risks posed by ECs to aquatic organisms and ecosystems, as well as the influence of anthropogenic activities and natural factors on these risks, remain poorly understood. This study assessed the mixed risks of ECs in Dongting Lake, a Ramsar Convention-classified Typically Changing Wetland, to elucidate the major EC classes, key risk drivers, and magnitude of anthropogenic and natural impacts. Results revealed that ECs pose non-negligible acute (30% probability) and chronic (70% probability) mixed risks to aquatic organisms in the freshwater lake ecosystem, with imidacloprid identified as the primary pollutant stressor. Redundancy analysis (RDA) and structural equation modeling (SEM) indicated that cropland and precipitation were major drivers of EC contamination levels and ecological risk. Cropland was positively associated with EC concentrations, while precipitation exhibited a dilution effect. These findings provide critical insights into the ecological risk status and key risk drivers in a typical freshwater lake ecosystem, offering data-driven support for the control and management of ECs in China.

Assessment of the impact of chemical pollution on endangered migratory fish in two major rivers of France, including spawning grounds

Water pollution is a one of the most contributors to aquatic biodiversity decline. Consequently, ecological risk assessment methods have been developed to investigate the effects of existing stresses on the environment, including the toxic effects of chemicals. One of the existing approaches to quantify toxic risks is called "Potentially Affected Fraction of species" (PAF), which estimates the potential loss of species within a group of species studied. In this study, the PAF method was applied to the Garonne catchment (southwest France) due to the limited information available on the involvement of water pollution in the decline of diadromous fish populations. This approach was used to quantify the potential toxic risk associated with chemical contamination of water for fish species. The objectives were to quantify this risk (1) in the Garonne and Dordogne rivers and (2) in the spawning grounds of two endangered anadromous fish species: the allis shad and the European sturgeon during the development period of their early life stages. Environmental pollution data was provided for 21 sites within the Garonne catchment between 2007 and 2022, and toxicity data was obtained specifically from freshwater toxicity tests on fish species. Then, for each site and each year, the potential toxic risk for a single substance (ssPAF) and for a mixture of substances (msPAF) was calculated and classified as high (>5 %), moderate (>1 % and < 5 %) or low (<1 %). Potential toxic risks were mostly moderate and mainly associated with: metals > other industrial pollutants and hygiene and care products > agrochemicals. In summary, this study highlights the probable involvement of water contamination on the decline, fate and restoration of diadromous fish populations in the Garonne catchment, focusing notably on the toxic effects on early life stages, a previously understudied topic.

Handling concentration data below the analytical limit in environmental mixture risk assessment: A case-study on pesticide river monitoring

Aquatic organisms are exposed to ever-changing complex mixtures of chemicals throughout their lifetime. Component-Based Mixture Risk Assessment (CBMRA) is a well-established methodology for water contaminant-mixture management, the use of which is growing due to improved access to reference ecotoxicity data and extensive monitoring datasets. It enables the translation of measured exposure concentrations of chemicals into biological effect values, and thus to quantitatively estimate the risk of the whole water sample (i.e., as a mixture). However, many factors can bias the final risk decision by impacting the risk metric components; thus, a careful design of the CBMRA is needed, taking into primary consideration the specific features of the dataset and mixture risk assessment assignments. This study systematically addressed the effects of the most common approaches used for handling the concentrations of chemicals below the limit of detection/quantification (LOD/LOQ) in CBMRA. The main results included: i) an informed CBMRA procedure that enables the tracking of the risk decisions triggered by substances below LOD/LOQ, ii) a conceptual map and guidance criteria to support the selection of the most suitable approach for specific scenarios and related interpretation; iii) a guided implementation of the informed CBMRA on dataset of pesticide concentrations in Italian rivers in 2020 (702,097 records).

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.

Assessment of the contribution of surfactants to mixture toxicity in French surface waters

Surfactants are widely used 'down-the-drain' chemicals with the potential to occur at high concentrations in local water bodies and to be part of unintentional environmental mixtures. Recently, increased regulatory focus has been placed on the impacts of complex mixtures in aquatic environments and the substances that are likely to drive mixture risk. This study assessed the contribution of surfactants to the total mixture pressure in freshwater ecosystems. Environmental concentrations, collated from existing French monitoring data, were combined with estimated ecotoxicological thresholds to calculate hazard quotients (HQ) for each substance, and hazard indices (HI) for each mixture. Two scenarios were investigated to correct for concentrations below the limit of quantification (LOQ) in the dataset. The first (best-case) scenario assumed all values Collapse

Key Words

• Aquatic
• Complex mixtures
• Concentration addition
• Environmental monitoring
• Risk assessment
• Surfactants

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Affiliation(s)

Nathalie Briels ARCHE Consulting, Liefkensstraat 35d, 9032 Gent (Wondelgem), Belgium
Charlotte Nys ARCHE Consulting, Liefkensstraat 35d, 9032 Gent (Wondelgem), Belgium
Karel P J Viaene ARCHE Consulting, Liefkensstraat 35d, 9032 Gent (Wondelgem), Belgium
Frederik Verdonck ARCHE Consulting, Liefkensstraat 35d, 9032 Gent (Wondelgem), Belgium
Erin M Maloney Shell Global Solutions International B.V., Carel van Bylandtlaan 16, 2596 HR Den Haag, the Netherlands
James Dawick Innospec Limited, Innospec Manufacturing Park, Oil G Sites Road Ellesmere Port, Cheshire CH65 4EY, UK
Chiara Maria Vitale Procter & Gamble, Brussels Innovation Centre, Temselaan 100, B-1853 Strombeek-Bever, Belgium
Diederik Schowanek Procter & Gamble, Brussels Innovation Centre, Temselaan 100, B-1853 Strombeek-Bever, Belgium.

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Predicting Environmental Risks of Pharmaceuticals from Wholesale Data: An Example from Norway

Environmental risk assessment (ERA) of pharmaceuticals relies on available measured environmental concentrations, but often such data are sparse. Predicted environmental concentrations (PECs), calculated from sales weights, are an attractive alternative but often cover only prescription sales. We aimed to rank, by environmental risk in Norway, approximately 200 active pharmaceutical ingredients (APIs) over 2016-2019, based on sales PECs. To assess the added value of wholesale and veterinary data, we compared exposure and risk predictions with and without these additional sources. Finally, we aimed to characterize the persistence, mobility, and bioaccumulation of these APIs. We compared our PECs to available Norwegian measurements, then, using public predicted-no-effect concentrations, we calculated risk quotients (RQs) and appended experimental and predicted persistence and bioaccumulation. Our approach overestimated environmental concentrations compared with measurements for 18 of 20 APIs with comparable predictions and measurements. Seventeen APIs had mean RQs >1, indicating potential risk, while the mean RQ was 2.05 and the median 0.001, driven by sex hormones, antibiotics, the antineoplastic abiraterone, and common painkillers. Some high-risk APIs were also potentially persistent or bioaccumulative (e.g., levonorgestrel [RQ = 220] and ciprofloxacin [RQ = 56]), raising the possibility of impacts beyond their RQs. Exposure and risk were also calculated with and without over-the-counter sales, showing that prescriptions explained 70% of PEC magnitude. Likewise, human sales, compared with veterinary, explained 85%. Sales PECs provide an efficient option for ERA, designed to overestimate compared with analytical techniques and potentially held back by limited data availability and an inability to quantify uncertainty but, nevertheless, an ideal initial approach for identification and ranking of risks. Environ Toxicol Chem 2023;42:2253-2270. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Priority control sequence of 34 typical pollutants in effluents of Chinese wastewater treatment plants

The identification of the priority control sequence of pollutants in effluents of wastewater treatment plants (WWTPs) has important implications for the management of water quality. This study chose 34 typical pollutants based on their representativeness and detection rates in municipal wastewater. The occurrence frequency and concentration of these pollutants in 168 Chinese WWTP effluents were measured at the national level. The data on in vitro toxicity (67 assays) and in vivo toxicity (216 species) for target pollutants were obtained from the public toxicity database and our experimental data. An environmental health prioritization index (EHPi) method was proposed to integrate the occurrence frequency, concentration, removal rate, and in vitro and in vivo toxicity to determine the priority control sequence of target pollutants. Ethynyl estradiol, 17β-estradiol, estrone, diclofenac, and atrazine were the top 5 pollutants identified by the EHPi score. Several pollutants with high EHPi scores showed spatial differences. Besides the EHPi method which was from the single pollutant perspective, the combined toxicity of pollutants (300 pairs of binary combinations) was also measured based on in vitro toxicity assays to evaluate the key pollutants from the pollutant-pollutant interacting perspective. The pollutants (such as ofloxacin and acetaminophen) that could have significant synergetic effects with many other pollutants are worthy of prior attention. This study shed new light on the identification of the priority control sequence of pollutants in WWTP effluents. The results provide meaningful data for the effective management and control of wastewater water quality.

Chemical Mixtures and Multiple Stressors: Same but Different?

Ecosystems are strongly influenced by multiple anthropogenic stressors, including a wide range of chemicals and their mixtures. Studies on the effects of multiple stressors have largely focussed on nonchemical stressors, whereas studies on chemical mixtures have largely ignored other stressors. However, both research areas face similar challenges and require similar tools and methods to predict the joint effects of chemicals or nonchemical stressors, and frameworks to integrate multiple chemical and nonchemical stressors are missing. We provide an overview of the research paradigms, tools, and methods commonly used in multiple stressor and chemical mixture research and discuss potential domains of cross-fertilization and joint challenges. First, we compare the general paradigms of ecotoxicology and (applied) ecology to explain the historical divide. Subsequently, we compare methods and approaches for the identification of interactions, stressor characterization, and designing experiments. We suggest that both multiple stressor and chemical mixture research are too focused on interactions and would benefit from integration regarding null model selection. Stressor characterization is typically more costly for chemical mixtures. While for chemical mixtures comprehensive classification systems at suborganismal level have been developed, recent classification systems for multiple stressors account for environmental context. Both research areas suffer from rather simplified experimental designs that focus on only a limited number of stressors, chemicals, and treatments. We discuss concepts that can guide more realistic designs capturing spatiotemporal stressor dynamics. We suggest that process-based and data-driven models are particularly promising to tackle the challenge of prediction of effects of chemical mixtures and nonchemical stressors on (meta-)communities and (meta-)food webs. We propose a framework to integrate the assessment of effects for multiple stressors and chemical mixtures. Environ Toxicol Chem 2023;42:1915-1936. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

A data-derived reference mixture representative of European wastewater treatment plant effluents to complement mixture assessment

Aquatic environments are polluted with a multitude of organic micropollutants, which challenges risk assessment due the complexity and diversity of pollutant mixtures. The recognition that certain source-specific background pollution occurs ubiquitously in the aquatic environment might be one way forward to approach mixture risk assessment. To investigate this hypothesis, we prepared one typical and representative WWTP effluent mixture of organic micropollutants (EWERBmix) comprised of 81 compounds selected according to their high frequency of occurrence and toxic potential. Toxicological relevant effects of this reference mixture were measured in eight organism- and cell-based bioassays and compared with predicted mixture effects, which were calculated based on effect data of single chemicals retrieved from literature or different databases, and via quantitative structure-activity relationships (QSARs). The results show that the EWERBmix supports the identification of substances which should be considered in future monitoring efforts. It provides measures to estimate wastewater background concentrations in rivers under consideration of respective dilution factors, and to assess the extent of mixture risks to be expected from European WWTP effluents. The EWERBmix presents a reasonable proxy for regulatory authorities to develop and implement assessment approaches and regulatory measures to address mixture risks. The highlighted data gaps should be considered for prioritization of effect testing of most prevalent and relevant individual organic micropollutants of WWTP effluent background pollution. The here provided approach and EWERBmix are available for authorities and scientists for further investigations. The approach presented can furthermore serve as a roadmap guiding the development of archetypic background mixtures for other sources, geographical settings and chemical compounds, e.g. inorganic pollutants.

Deep mining of reported emerging contaminants in China's surface water in the past decade: Exposure, ecological effects and risk assessment

The identification and management of high-risk contaminants have raised great concern from governments. Facing the growing amount of data on the occurrence of emerging contaminants (ECs) in surface water, a deep mining and quality control strategy was developed to integrate data on all reported ECs in Chinese surface water over the past decade, and an exposure and effect database was further built. In addition, multilevel risk characterization was carried out to prioritize high-risk areas, contaminants and endpoints. A total of 1038 ECs, mainly pharmaceutical and personal care products (PPCPs) and industrial chemicals, were curated, with concentrations ranging from 0.02 pg/L to 533 µg/L. For individual risk, all the provinces had acceptable risks except for Henan, which was characterized with a medium chronic risk. Nine ECs, including 4-nonylphenol and estrone, dominated individual risks. Conversely, for multisubstance risk, 76.20% and 73.87% of aquatic organisms were affected acutely and chronically at the national level, with acute and chronic risks exceeding the safety threshold of 5% in 11 and 19 provinces, respectively. Nineteen ECs, including sitosterol and chyfluthrin, dominated the multisubstance risk. In addition, 9 MoAs mainly inducing electron transfer inhibition, neurotoxicity and narcosis toxicity are high-risk endpoints. The study revealed the ecological risk status and key risk entities of Chinese surface waters, which provided the latest data to support the control of ECs in China.

Risk from unintentional environmental mixtures in EU surface waters is dominated by a limited number of substances

Unintentional environmental mixtures happen when multiple chemicals co-occur in the environment. A generic mixture assessment factor (MAF), has been proposed to account for this. The MAF is a number by which safe exposure levels for single chemicals are divided to ensure protection against combined exposures to multiple chemicals. Two key elements to judge the appropriateness of a generic MAF are (1) defining the scope of mixtures that need to be addressed by a MAF (i.e.: simple mixtures vs complex mixtures), and (2) the existence of common risk drivers across large spatial scales. Simple mixtures with one to three risk drivers can easily be addressed by chemical-by-chemical regulatory action. Our work provides evidence on the prevalence and complexity of cumulative risk in EU freshwaters based on chemical monitoring data from one of the largest databases in the EU. With 334 chemicals being monitored, low complexity mixtures (one to 3 three risk drivers) dominated. After excluding metals, only 15 out of 307 chemicals (5 %) were most frequent chemical risk drivers. When these 15 chemicals were excluded from the analysis, 95 % of all monitoring site - year combinations did not pose a concern for cumulative risk. Most of these 15 chemicals are already banned or listed in various priority lists, showing that current regulatory frameworks were effective in identifying drivers of single chemical and cumulative risk. Although the monitoring data do not represent the entirety of environmental mixtures in the EU, the observed patterns of (1) limited prevalence of truly complex mixtures, and (2) limited number of overall risk drivers, argue against the need for implementing a generic MAF as a regulatory tool to address risk from unintentional mixtures in EU freshwaters.

Petroleum refinery effluent contribution to chemical mixture toxic pressure in the environment

Petroleum refinery effluents (PRE) are wastewaters from industries associated with oil refining. Within Europe, PREs are regulated through local discharge permits and receive substantial treatment before emission. After treatment, PREs can still contain low levels of various pollutants potentially toxic to organisms. Earlier work, including whole-effluent toxicity assessments, has shown that the toxicity of permitted PREs is often limited. However, the extent to which PREs contribute to chemical pollution already present in the receiving environment is unknown. Therefore, our study aimed to assess the contribution of PREs to mixture toxic pressure in the environment, using the multi-substance potentially affected fraction of species (msPAF) as an indicator. Based on measured chemical concentrations, compiled species sensitivity distributions (SSD) and a mechanistic solubility model, msPAF levels were estimated for undiluted effluents at discharge points and diluted effluents downstream in receiving waters. Median msPAF-chronic and msPAF-acute levels of PREs at discharge points were 74% (P50) and 40% (P95), respectively. The calculated msPAF levels were reduced substantially to <5% downstream for most effluents (82%), indicating low to negligible toxicity of PREs in receiving environments beyond the initial mixing zone. Regardless of differences in endpoints and locations, hydrocarbons (mainly total petroleum hydrocarbons) and inorganics (mainly ammonia) explained at least 85% of the mixture toxic pressure. The msPAF levels of PREs were on average 2.5-4.5 orders of magnitude lower than msPAF levels derived from background pollution levels, suggesting that PREs were minor contributors to the toxic pressure in the environment. This study presents a generic methodology for quantifying the potential toxic pressure of PREs in the environment, identifying hotspots where more effective wastewater treatment could be needed. We explicitly discuss the uncertainties for further refinement and development of the method.

Ecotoxicity characterization of chemicals: Global recommendations and implementation in USEtox

Chemicals emitted to the environment affect ecosystem health from local to global scale, and reducing chemical impacts has become an important element of European and global sustainability efforts. The present work advances ecotoxicity characterization of chemicals in life cycle impact assessment by proposing recommendations resulting from international expert workshops and work conducted under the umbrella of the UNEP-SETAC Life Cycle Initiative in the GLAM project (Global guidance on environmental life cycle impact assessment indicators). We include specific recommendations for broadening the assessment scope through proposing to introduce additional environmental compartments beyond freshwater and related ecotoxicity indicators, as well as for adapting the ecotoxicity effect modelling approach to better reflect environmentally relevant exposure levels and including to a larger extent chronic test data. As result, we (1) propose a consistent mathematical framework for calculating freshwater ecotoxicity characterization factors and their underlying fate, exposure and effect parameters; (2) implement the framework into the USEtox scientific consensus model; (3) calculate characterization factors for chemicals reported in an inventory of a life cycle assessment case study on rice production and consumption; and (4) investigate the influence of effect data selection criteria on resulting indicator scores. Our results highlight the need for careful interpretation of life cycle assessment impact scores in light of robustness of underlying species sensitivity distributions. Next steps are to apply the recommended characterization framework in additional case studies, and to adapt it to soil, sediment and the marine environment. Our framework is applicable for evaluating chemicals in life cycle assessment, chemical and environmental footprinting, chemical substitution, risk screening, chemical prioritization, and comparison with environmental sustainability targets.

Proportional contributions to organic chemical mixture effects in groundwater and surface water

Semi-quantitative GC-MS and LC-MS measurements of organic chemicals in groundwater and surface waters were used to assess the overall magnitude and contribution of the most important substances to calculated mixture hazard. Here we use GC-MS and LC-MS measurements taken from two separate national monitoring programs for groundwater and surface water in England, in combination with chronic species sensitivity distribution (SSD) HC50 values published by Posthuma et al. (2019, Environ. Toxicol. Chem, 38, 905-917) to calculate individual substance hazard quotients and mixture effects using a concentration addition approach. The mixture analysis indicated that, as anticipated, there was an increased hazard from the presence of a cocktail of substances at sites compared to the hazard for any single chemical. The magnitude of the difference between the hazard attributed to the most important chemical and the overall mixture effect, however, was not large. Thus, the most toxic chemical contributed ≥ 20% of the calculated mixture effect in >99% of all measured groundwater and surface water samples. On the basis of this analysis, a 5 fold assessment factor placed on the risk identified for any single chemical would offer a high degree of in cases where implementation of a full mixture analysis was not possible. This finding is consistent with previous work that has assessed chemical mixture effects within field monitoring programs and as such provides essential underpinning for future policy and management decisions on how to effectively and proportionately manage mixture risks.