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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., (© 2024 The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.)

How can data on the occurrence of pharmaceuticals and personal care products (PPCPs) in the environment and the quality of ecosystems exposed to PPCPs be used to determine whether current regulatory risk assessment schemes are effective? This is one of 20 "big questions" concerning PPCPs in the environment posed in a landmark review paper in 2012. Ten years later, we review the developments around this question, focusing on the first P in PPCPs, that is, pharmaceuticals, or more specifically the active ingredients included in them (active pharmaceutical ingredients, APIs). We illustrate how extensive data on both the occurrence of APIs and the ecotoxicological sensitivity of aquatic species to them can be used in a retrospective risk assessment. In the Netherlands, current regulatory risk assessment schemes offer insufficient protection against direct ecotoxicological effects from APIs: the toxic pressure exerted by the 39 APIs included in our study exceeds the policy-related protective threshold of 0.05 (the "95%-protection level") in at least 13% of sampled surface waters. In general, anti-inflammatory and antirheumatic products (e.g., diclofenac, ibuprofen) contributed most to the overall toxic pressure, followed by sex hormones and modulators of the genital system (e.g., ethinylestradiol) and psychoanaleptics (e.g., caffeine). We formulated three open questions for future research. The first relates to improving the availability and accessibility of good-quality ecotoxicity data on pharmaceuticals for the global scientific, regulatory, and general public. The second relates to the adaptation of regulatory risk assessment frameworks for developing regions of the world. The third relates to the integration of effect-based and ecological approaches into regulatory risk assessment practice. Environ Toxicol Chem 2024;43:611-622. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC., (© 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.)

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., (© 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.)

We describe a procedure to quantify emissions of chemicals for environmental protection, assessment, and management purposes. The procedure uses production and use volumes from registration dossiers and combines these with Specific Environmental Release Category data. The procedure was applied in a case study. Emission estimations were made for chemicals registered under the European Union chemicals regulations for industrial chemicals (Registration, Evaluation, Authorisation and Restriction of Chemicals [REACH]) and for the active ingredients of medicines and crop protection products. Emissions themselves cannot be validated. Instead, emission estimates were followed by multimedia fate modeling and mixture toxic pressure modeling to arrive at predicted environmental concentrations (PECs) and toxic pressures for a typical European water body at steady state, which were compared with other such data. The results show that screening-level assessments could be performed, and yielded estimates of emissions, PECs, and mixture toxic pressures of chemicals used in Europe. Steady-state PECs agreed fairly well with measured concentrations. The mixture toxic pressure at steady state suggests the presence of effects in aquatic species assemblages, whereby few compounds dominate the predicted impact. The study shows that our screening-level emission estimation procedure is sufficiently accurate and precise to serve as a basis for assessment of chemical pollution in aquatic ecosystems at the scale of river catchments. Given a recognized societal need to develop methods for realistic, cumulative exposures, the emission assessment procedure can assist in the prioritization of chemicals in safety policies (such as the European Union REACH regulation), where "possibility to be used safely" needs to be demonstrated, and environmental quality policies (such as the European Union Water Framework Directive), where "good environmental quality" needs to be reached. Environ Toxicol Chem 2020;39:1839-1851. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC., (© 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.)

Ecological risk assessments are hampered by limited availability of ecotoxicity data. The present study aimed to explore the possibility of deriving species sensitivity distribution (SSD) parameters for nontested compounds, based on simple physicochemical characteristics, known SSDs for data-rich compounds, and a quantitative structure-activity relationship (QSAR)-type approach. The median toxicity of a data-poor chemical for species assemblages significantly varies with values of the physicochemical descriptors, especially when based on high-quality SSD data (from either acute median effect concentrations or chronic no-observed-effect concentrations). Beyond exploratory uses, we discuss how the precision of QSAR-based SSDs can be improved to construct models that accurately predict the SSD parameters of data-poor chemicals. The current models show that the concept of QSAR-based SSDs supports screening-level evaluations of the potential ecotoxicity of compounds for which data are lacking. Environ Toxicol Chem 2019;38:2764-2770. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC., (© 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.)

The present study considers the collection and use of ecotoxicity data for risk assessment with species sensitivity distributions (SSDs) of chemical pollution in surface water, which are used to quantify the likelihood that critical effect levels are exceeded. This fits the European Water Framework Directive, which suggests using models to assess the likelihood that chemicals affect water quality for management prioritization. We derived SSDs based on chronic and acute ecotoxicity test data for 12 386 compounds. The log-normal SSDs are characterized by the median and the standard deviation of log-transformed ecotoxicity data and by a quality score. A case study illustrates the utility of SSDs for water quality assessment and management prioritization. We quantified the chronic and acute mixture toxic pressure of mixture exposures for >22 000 water bodies in Europe for 1760 chemicals for which we had both exposure and hazard data. The results show the likelihood of mixture exposures exceeding a negligible effect level and increasing species loss. The SSDs in the present study represent a versatile and comprehensive approach to prevent, assess, and manage chemical pollution problems. Environ Toxicol Chem 2019;38:905-917. © 2019 SETAC., (© 2019 SETAC.)

Ecosystem quality is an important area of protection in life cycle impact assessment (LCIA). Chemical pollution has adverse impacts on ecosystems on a global scale. To improve methods for assessing ecosystem impacts, the Life Cycle Initiative hosted by the United Nations Environment Programme established a task force to evaluate the state-of-the-science in modeling chemical exposure of organisms and the resulting ecotoxicological effects for use in LCIA. The outcome of the task force work will be global guidance and harmonization by recommending changes to the existing practice of exposure and effect modeling in ecotoxicity characterization. These changes will reflect the current science and ensure the stability of recommended practice. Recommendations must work within the needs of LCIA in terms of 1) operating on information from any inventory reporting chemical emissions with limited spatiotemporal information, 2) applying best estimates rather than conservative assumptions to ensure unbiased comparison with results for other impact categories, and 3) yielding results that are additive across substances and life cycle stages and that will allow a quantitative expression of damage to the exposed ecosystem. We describe the current framework and discuss research questions identified in a roadmap. Primary research questions relate to the approach toward ecotoxicological effect assessment, the need to clarify the method's scope and interpretation of its results, the need to consider additional environmental compartments and impact pathways, and the relevance of effect metrics other than the currently applied geometric mean of toxicity effect data across species. Because they often dominate ecotoxicity results in LCIA, we give metals a special focus, including consideration of their possible essentiality and changes in environmental bioavailability. We conclude with a summary of key questions along with preliminary recommendations to address them as well as open questions that require additional research efforts. Environ Toxicol Chem 2018;37:2955-2971. © 2018 SETAC., (© 2018 SETAC.)

Ecological risk assessment increasingly focuses on risks from chemical mixtures and multiple stressors because ecosystems are commonly exposed to a plethora of contaminants and nonchemical stressors. To simplify the task of assessing potential mixture effects, we explored 3 land use-related chemical emission scenarios. We applied a tiered methodology to judge the implications of the emissions of chemicals from agricultural practices, domestic discharges, and urban runoff in a quantitative model. The results showed land use-dependent mixture exposures, clearly discriminating downstream effects of land uses, with unique chemical "signatures" regarding composition, concentration, and temporal patterns. Associated risks were characterized in relation to the land-use scenarios. Comparisons to measured environmental concentrations and predicted impacts showed relatively good similarity. The results suggest that the land uses imply exceedances of regulatory protective environmental quality standards, varying over time in relation to rain events and associated flow and dilution variation. Higher-tier analyses using ecotoxicological effect criteria confirmed that species assemblages may be affected by exposures exceeding no-effect levels and that mixture exposure could be associated with predicted species loss under certain situations. The model outcomes can inform various types of prioritization to support risk management, including a ranking across land uses as a whole, a ranking on characteristics of exposure times and frequencies, and various rankings of the relative role of individual chemicals. Though all results are based on in silico assessments, the prospective land use-based approach applied in the present study yields useful insights for simplifying and assessing potential ecological risks of chemical mixtures and can therefore be useful for catchment-management decisions. Environ Toxicol Chem 2018;37:715-728. © 2017 The Authors. Environmental Toxicology Chemistry Published by Wiley Periodicals, Inc., (© 2017 The Authors. Environmental Toxicology Chemistry Published by Wiley Periodicals, Inc.)

Environmental risk assessment of chemical mixtures is challenging because of the multitude of possible combinations that may occur. Aquatic risk from chemical mixtures in an agricultural landscape was evaluated prospectively in 2 exposure scenario case studies: at field scale for a program of 13 plant-protection products applied annually for 20 yr and at a watershed scale for a mixed land-use scenario over 30 yr with 12 plant-protection products and 2 veterinary pharmaceuticals used for beef cattle. Risk quotients were calculated from regulatory exposure models with typical real-world use patterns and regulatory acceptable concentrations for individual chemicals. The results could differentiate situations when there was concern associated with single chemicals from those when concern was associated with a mixture (based on concentration addition) with no single chemical triggering concern. Potential mixture risk was identified on 0.02 to 7.07% of the total days modeled, depending on the scenario, the taxa, and whether considering acute or chronic risk. Taxa at risk were influenced by receiving water body characteristics along with chemical use profiles and associated properties. The present study demonstrates that a scenario-based approach can be used to determine whether mixtures of chemicals pose risks over and above any identified using existing approaches for single chemicals, how often and to what magnitude, and ultimately which mixtures (and dominant chemicals) cause greatest concern. Environ Toxicol Chem 2018;37:674-689. © 2017 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC., (© 2017 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.)

Eco-epidemiological studies utilizing existing monitoring program data provide a cost-effective means to bridge the gap between the ecological status and chemical status of watersheds and to develop hypotheses of stressor attribution that can influence the design of higher-tier assessments and subsequent management. The present study describes the process of combining existing data and models to develop a robust starting point for eco-epidemiological analyses of watersheds over large geographic scales. Data resources from multiple federal and local agencies representing a range of biological, chemical, physical, toxicological, and other landscape factors across the state of Ohio, USA (2000-2007), were integrated with the National Hydrography Dataset Plus hydrologic model (US Environmental Protection Agency and US Geological Survey). A variety of variable reduction, selection, and optimization strategies were applied to develop eco-epidemiological data sets for fish and macroinvertebrate communities. The relative importance of landscape variables was compared across spatial scales (local catchment, watershed, near-stream) using conditional inference forests to determine the scales most relevant to variation in biological community condition. Conditional inference forest analysis applied to a holistic set of environmental variables yielded stressor-response hypotheses at the statewide and eco-regional levels. The analysis confirmed the dominant influence of state-level stressors such as physical habitat condition, while highlighting differences in predictive strength of other stressors based on ecoregional and land-use characteristics. This exercise lays the groundwork for subsequent work designed to move closer to causal inference., (© 2014 SETAC.)

Species sensitivity distributions (SSDs) quantify fractions of species potentially affected in contaminated environmental compartments using test species sensitivity data. The present study quantitatively describes associations between predicted and observed ecological impacts of contaminant mixtures, based on monitoring data of benthic macroinvertebrates. Local mixture toxic pressures (multisubstance potentially affected fraction of species [msPAF]) were quantified based on measured concentrations of 45 compounds (eight metals, 16 chlorinated organics, mineral oil, 16 polycyclic aromatic hydrocarbons, four polychlorinated biphenyls), using acute as well as chronic 50%-effective concentration-based SSD-modeling combined with bioavailability and mixture modeling. Acute and chronic toxic pressures were closely related. Generalized linear models (GLMs) were derived to describe taxon abundances as functions of environmental variables (including acute toxic pressure). Acute toxic pressure ranged from 0 to 42% and was related to abundance for 74% of the taxa. Habitat-abundance curves were generated using the GLMs and Monte Carlo simulation. Predicted abundances for the taxa were associated with acute mixture toxic pressure in various ways: negative, positive, and optimum abundance changes occurred. Acute toxic pressure (msPAF) was associated almost 1:1 with the observed fraction of taxa exhibiting an abundance reduction of 50% or more. The findings imply that an increase of mixture toxic pressure associates to increased ecological impacts in the field. This finding is important, given the societal relevance of SSD model outputs in environmental policies., (Copyright © 2012 SETAC.)

Although risk assessments on a per-chemical basis are required during the registration procedure of pesticides, cumulative risks from the use of all pesticides on the variety of crops in a catchment area of a river are not assessed. The present study aimed to rank pesticides used in outdoor agricultural practice within the catchment of the rivers Rhine, Meuse, and Scheldt according to their potential toxic impact on the North Sea coastal ecosystem. Toxic pressure calculations (based on steady-state concentrations calculated with a multimedia fate model) and species-sensitivity distribution-based risk estimations were performed for pesticide emissions in the years 1998 (189 pesticides) and 2004 (133 pesticides). A ranking was established according to the relative contribution of single pesticides and crop types to the overall toxic pressure. Calculations were performed probabilistically to deal with parameter uncertainties. Only a few pesticides and crop types dominate overall toxic pressure because of emissions in both years, and the uncertainty appears to be caused largely by uncertainties in interspecies variances of aquatic toxicities. For 1998, these pesticides were fentin-acetate, with a median relative contribution (RCx) to the toxic pressure of multiple chemicals on an ecosystem of 0.43. For 2004, the pesticides that contributed most were pencycuron and paraquat-dichloride, with a median RCx, of 4.4 x 10(-2) and 3.9 x 10(-2), respectively. Pesticides applied to potato cropland and fruit trees contributed most to the overall toxic pressure.

The purposes of this study were to investigate whether exposure to toxicant mixtures is associated with fish assemblage characteristics in the field and to describe the relationships between predicted chronic and acute mixture risks and observed impacts. Fish abundance and abiotic monitoring data from Ohio, USA, surface waters were compiled and analyzed. Variability of biotic and abiotic parameters was large. Exposure assessment, risk assessment with species-sensitivity distributions, and mixture toxicity rules were used to calculate a relative risk predictor: The multisubstance potentially affected fraction of species (msPAF). Predicted acute and chronic risks ranged from low values to more than 10 and 50% of species potentially affected, respectively. Pearson correlations between predicted risk and observed assemblage characteristics were nonsignificant for total abundance, number of species, Shannon-Weaver index, and evenness. Moderately significant correlations were found between predicted risk and abundance for 23% of individual species. Both abundance increases and decreases were observed. Generalized linear model (GLM) regressions revealed significant nonlinear associations between predicted risk and the abundance for 50% (metals and ammonia) and 55% (household product ingredients) of the species. Local ecological impact was expressed as the fraction of species expected but not observed, both with and without attribution of impact to mixture exposure. The association between predicted impacted fraction and the fraction of species expected but not observed was not significant. Predicted acute and chronic impacted fractions were associated significantly with the observed fraction of species likely lost by the action of toxicant mixtures under field conditions, with wide confidence bounds. These findings confirm the view that higher mixture impacts are expected in the field at higher msPAF.

Methods for the assessment of ecological risks associated with exposure to defined mixtures of toxicants are reviewed and formalized for single-species toxicity. Depending on the modes of action of toxicants in a mixture, these methods apply either the model for concentration additivity (CA) or the model for response additivity (RA). For complex mixtures, the present paper advocates the use of a new, two-step, mixed-model approach as a logical extension of model selection: Mixture toxicity for individual modes of action is evaluated with the CA model, and the toxicities of different modes of action are combined using the RA model. Using comparable mixture toxicity strategies in combination with the concept of species-sensitivity distributions, we develop a method to address and predict the risk for direct effects on the composition of species assemblages and biodiversity. The data needed for modeling can be obtained from existing databases, and lack of data can, in part, be addressed by the use of toxicity patterns in those databases. Both single- and multiple-species methods of mixture risk prediction are useful for risk management, because they allow ranking of polluted sites and affected species as well as identification of the most hazardous contaminants, at least in a comparative way. Validation of the proposed methods is feasible but currently limited because of a lack of appropriate data.

When chemical analysis indicates metal pollution, a second-tier method is needed to evaluate whether toxic effects occur at the polluted sites. A method based on pollution-induced community tolerance (PICT) was developed using samples taken from locations polluted with sewage more than 20 years ago. Microorganisms extracted from soil samples were exposed to a concentration range of zinc, nickel, copper, chromium (III), or chromium (VI) salts in a buffer suspension. The remaining activity of the intoxicated microorganisms was determined by color formation with 31 different organic substrates in microtiter plates. Microorganisms from moderately Zn-polluted sites (>45 mg/kg) showed an increased tolerance for zinc. Nickel tolerance was observed at 51 mg Ni/kg soil, chromium (VI) tolerance at 923 mg Cr/kg. In most cases, tolerance also was observed at higher concentrations. High concentrations of 1,494 mg Cu/kg or 3,935 mg Cr/kg did not show PICT, indicating a limited bioavailability of Cu and Cr at these sites. The benefits of our method are its greater sensitivity compared to other tests used at these sites, and its specificity for those metals that exceed allowable levels.

Soil-dwelling organisms are exposed to metals in different ways. Evidence exists for predominant pore water uptake of metals by soft-bodied oligochaete species. In the present research, uptake kinetics of metals and the metalloid As by the semi-soft-bodied springtail Folsomia candida were studied, for which uptake via the pore water is less obvious. Springtails were exposed in 16 field soils and in metal-spiked artificial Organization for Economic Cooperation and Development (Paris, France) soil (OECD soil). Subsequently, accumulation parameters were statistically related to soil metal pools and soil properties. In Cd-spiked OECD soil, internal Cd levels were linearly related to external Cd concentrations, whereas the springtails maintained fixed internal levels of Cu and Zn regardless of spiked concentrations. In the field soils, all body concentrations of the elements As, Cr, and Ni were below detection limit. The essential metals Cu and Zn were presumably regulated, and no influence of soil characteristics could be demonstrated. For Cd and Pb, accumulation patterns were correlated mainly to solid-phase soil characteristics. The presence of these explanatory variables in the multiple correlations suggests that an uptake mechanism that is solely determined by pore water concentrations should not be taken as a universally applicable principle in risk assessments of metals for soil invertebrates. Cadmium in OECD soils was more available for uptake than in the field soils. The difference remained when extractability was taken into account. The results suggest that experiments in OECD soil cannot be used directly in risk assessment for nonessential metals (at least for F. candida), although a reduction of uncertainties in metal risk assessment can be reached by consistent use of body residues rather than external concentrations.