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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.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Freshwater ecosystems provide major benefits to human wellbeing-so-called ecosystem services (ES)-but are currently threatened among others by ecotoxicological pressure from chemicals reaching the environment. There is an increased motivation to incorporate ES in quantification tools that support decision-making, such as life cycle assessment (LCA). However, mechanistic models and frameworks that can systematically translate ecotoxicity effect data from chemical tests into eventual damage on species diversity, functional diversity, and ES in the field are still missing. While current approaches focus on translating predicted ecotoxicity impacts to damage in terms of species loss, no approaches are available in LCA and other comparative assessment frameworks for linking ecotoxicity to damage on ecosystem functioning or ES. To overcome this challenge, we propose a way forward based on evaluating available approaches to characterize damage of chemical pollution on freshwater ES. We first outline an overall framework for linking freshwater ecotoxicity effects to damage on related ES in compliance with the boundary conditions of quantitative, comparative assessments. Second, within the proposed framework, we present possible approaches for stepwise linking ecotoxicity effects to species loss, functional diversity loss, and damage on ES. Finally, we discuss strengths, limitations, and data availability of possible approaches for each step. Although most approaches for directly deriving damage on ES from either species loss or damage to functional diversity have not been operationalized, there are some promising ways forward. The Threshold Indicator Taxa ANalysis (TITAN) seems suitable to translate predicted ecotoxicity effects to a metric of quantitative damage on species diversity. A Trait Probability Density Framework (TPD) approach that incorporates various functional diversity components and functional groups could be adapted to link species loss to functional diversity loss. An Ecological Production Function (EPF) approach seems most promising for further linking functional diversity loss to damage on ES flows for human wellbeing. However, in order to integrate the entire pathway from predicted freshwater ecotoxicity to damage on ES into LCA and other comparative frameworks, the approaches adopted for each step need to be harmonized in terms of assumptions, boundary conditions and consistent interfaces with each other., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Current regulatory chemical safety assessments do not acknowledge that ambient exposures are to multiple chemicals at the same time. As a result, potentially harmful exposures to unintentional mixtures may occur, leading to potential insufficient protection of the environment. The present study describes cumulative environmental risk assessment results for European fresh water ecosystems, based on the NORMAN chemical surface water monitoring database (1998-2016). It aims to characterize the magnitude of the mixture problem and the relative contribution of chemicals to the mixture risk, and evaluates how cumulative risks reduce when the acceptable risk per single chemical is fractionally lowered. Available monitoring data were curated and aggregated to 26,631 place-time combinations with at least two chemicals, of which 376 place-time combinations had at least 25 chemicals identified above the Limit of Detection. Various risk metrics were based on measured environmental concentrations (MECs). Mixture risk characterization ratio's (ΣRCRs) ≥ 1 were found for 39% of the place-time combinations, with few chemicals dominating the ΣRCR. Analyses of mixture toxic pressures, expressed as multi-substance Potentially Affected Fractions of species based on No Observed Effect Concentrations (msPAF NOEC ), showed similar outcomes. Small fractional reductions of the ambient chemical concentrations give a steep increase of the percentage of sufficiently protected water bodies (i.e. ΣRCR < 1 and msPAF NOEC < 5%). Scientific and regulatory aspects of these results are discussed, especially with reference to the representativeness of the monitoring data for characterizing ambient mixtures, the robustness of the findings, and the possible regulatory implementation of the concept of a Mixture Allocation Factor (MAF) for prospective chemicals risk management. Although the monitoring data do not represent the full spectrum of ambient mixture exposures in Europe, results show the need for adapting policies to reach European Union goals for a toxic-free environment and underpin the utility and possible magnitude of a MAF., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Chemical pollution impinges on the quality of water systems and the ecosystem services (ESs) they provide. Expression of ESs in monetary units has become an essential tool for sustainable ecosystem management. However, the impact of chemical pollution on ESs is rarely quantified, and ES valuation often focuses on individual services without considering the total services provided by the ecosystem. The purpose of the study was to develop a stepwise approach to quantify the impact of sediment pollution on the total ES value provided by water systems. Thereby, we calculated the total ES value loss as a function of the multi-substance potentially affected fraction of species at the HC50 level (msPAF(HC50)). The function is a combination of relationships between, subsequently: the msPAF(HC50), diversity, productivity and total ES value. Regardless of the inherent differences between terrestrial and aquatic ecosystems, an increase of diversity generally corresponded to an increase in productivity with curvilinear or linear effects. A positive correlation between productivity and total values of ESs of biomes was observed. The combined relationships showed that 1% msPAF(HC50) corresponded to on average 0.5% (0.05-1.40%) of total ES value loss. The ES loss due to polluted sediments in the Waal-Meuse river estuary (the Netherlands) and Flemish waterways (Belgium) was estimated to be 0.3-5 and 0.6-10 thousand 2007$/ha/yr, respectively. Our study presents a novel methodology to assess the impact of chemical exposure on diversity, productivity, and total value that ecosystems provide. With sufficient monitoring data, our generic methodology can be applied for any chemical and region of interest and help water managers make informed decisions on cost-effective measures to remedy pollution. Acknowledging that the ES loss estimates as a function of PAF(HC50) are crude, we explicitly discuss the uncertainties in each step for further development and application of the methodology., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Climate and land-use change drive a suite of stressors that shape ecosystems and interact to yield complex ecological responses (that is, additive, antagonistic and synergistic effects). We know little about the spatial scales relevant for the outcomes of such interactions and little about effect sizes. These knowledge gaps need to be filled to underpin future land management decisions or climate mitigation interventions for protecting and restoring freshwater ecosystems. This study combines data across scales from 33 mesocosm experiments with those from 14 river basins and 22 cross-basin studies in Europe, producing 174 combinations of paired-stressor effects on a biological response variable. Generalized linear models showed that only one of the two stressors had a significant effect in 39% of the analysed cases, 28% of the paired-stressor combinations resulted in additive effects and 33% resulted in interactive (antagonistic, synergistic, opposing or reversal) effects. For lakes, the frequencies of additive and interactive effects were similar for all spatial scales addressed, while for rivers these frequencies increased with scale. Nutrient enrichment was the overriding stressor for lakes, with effects generally exceeding those of secondary stressors. For rivers, the effects of nutrient enrichment were dependent on the specific stressor combination and biological response variable. These results vindicate the traditional focus of lake restoration and management on nutrient stress, while highlighting that river management requires more bespoke management solutions.

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.)

Because of the great variety in behavior and modes of action of chemicals, impact assessment of multiple substances is complex, as is the communication of its results. Given calls for cumulative impact assessments, we developed a methodology that is aimed at expressing the expected cumulative impacts of mixtures of chemicals on aquatic ecosystems for a region and subsequently allows to present these results as a chemical pollution footprint, in short: a chemical footprint. Setting and using a boundary for chemical pollution is part of the methodology. Two case studies were executed to test and illustrate the methodology. The first case illustrates that the production and use of organic substances in Europe, judged with the European water volume, stays within the currently set policy boundaries for chemical pollution. The second case shows that the use of pesticides in Northwestern Europe, judged with the regional water volume, has exceeded the set boundaries, while showing a declining trend over time. The impact of mixtures of substances in the environment could be expressed as a chemical footprint, and the relative contribution of substances to that footprint could be evaluated. These features are a novel type of information to support risk management, by helping prioritization of management among chemicals and environmental compartments.

The Water Framework Directive (WFD) of the European Union requires member states to attain a good ecological status for all water bodies by the year 2015. This implies that the bioecological protection endpoint itself is upfront, next to abiotic chemical quality standards, as tools to protect those endpoints. Within the requirements of the Directive, ecological status and abiotic conditions will be monitored extensively. Based on the analysis of the monitoring data, authorities are required to derive Programs of Measures (PoMs) for impacted sites. Optimization of these programs requires diagnosis, to provide site-specific or catchment-specific information on the causes of observed deviations from a good ecological status. This article shows one pilot analysis of monitoring data (Scheldt River, Belgium) compiled in the scope of the EU MODELKEY project. Ecological, ecotoxicological, and statistical models are combined to quantify local ecological impact magnitudes and to identify site-specific factors that are associated with those impacts. Results show significant ecological effects in terms of taxa loss at study sites, which are highly variable among sites, with variable combinations of environmental factors associated with those effects. The results of the diagnostic approach are discussed, which appear to be complementary to the assessment of chemical status required by the Directive. Both types of assessment are useful to assist in the derivation of optimized PoMs. In addition, it could be concluded that the acute toxic pressure parameter relates to reduced taxon abundance for more than half of the studied taxa and that this parameter relates to the fraction of taxa lost under field conditions. Finally, various lessons for the execution of monitoring programs are derived because the Scheldt (bio)monitoring data set has its weaknesses, although it can be seen as typical for current monitoring programs.

Determination of local ecological impacts and stressor identification in aquatic ecosystems is increasingly needed and required for designing effective watershed management plans in various jurisdictions. Spatial database evaluation methods applied to available environmental data resources can provide screening-level, geographically based stressor identification hypotheses. Cross-comparison of the output of independent methods is a critical step to address common concerns with the interpretation of output, identify strengths and weaknesses, and reduce uncertainty. Two current approaches were compared in this study: (1) the "Effect and Probable Cause" (EPC) method and (2) a GIS "Weights-of-Evidence/Weighted Logistic Regression" (WOE/WLR) method. The methods were applied to the same Ohio (U.S.) spatial data resources to link impacts on local fish assemblages with various natural and anthropogenic stressors. The methods generally yielded significantly similar results in the identification of stressors and their relative influence. However, key differences were also observed between the methods which reflected the distinctive objectives and sensitivities of each. The findings show that scientific interpretation of analysis output requires an understanding of method characteristics, and suggests the potential value of utilizing multiple methods as quantitative lines of evidence in screening-level regional diagnostic assessment.

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.

Ecotoxicological effect factors are part of the analysis of relative impacts by chemical contaminants on ecosystems. Uncertainty distributions, represented by the 90% confidence interval, belonging to ecotoxicological effect factors for freshwater ecosystems were determined. This study includes 869 high production volume chemicals, related to 7 nonspecific toxic modes of action (TMoAs). The ecotoxicological effect factors are divided into a TMoA-specific part and a chemical-specific part. The 90% confidence interval of the TMoA-specific part of the effect factor ranges from 23 orders of magnitude for acrylate toxicity to 2 orders of magnitude for nonpolar narcosis. The range in the TMoA-specific part of the effect factor is mainly caused by uncertainty in the spread in toxic sensitivity between species (sigma(j)). Average uncertainty in the chemical-specific part of the effect factors depends on the number of species tested and ranges on average from a factor of 5 for more than 3 species tested to a factor of about 1,000 for 2 species tested. Average uncertainty in the ecotoxicological effect factors ranges from a factor of 100 for more than 3 species tested to a factor of nearly 10,000 for 2 species tested. It is recommended that the ecotoxicological effect factor of a chemical is based on toxicity data of at least 4 species.

Biological assessments should both estimate the condition of a biological resource (magnitude of alteration) and provide environmental managers with a diagnosis of the potential causes of impairment. Although methods of quantifying condition are well developed, identifying and proportionately attributing impairment to probable causes remain problematic. Furthermore, analyses of both condition and cause have often been difficult to communicate. We developed an approach that (1) links fish, habitat, and chemistry data collected from hundreds of sites in Ohio (USA) streams, (2) assesses the biological condition at each site, (3) attributes impairment to multiple probable causes, and (4) provides the results of the analyses in simple-to-interpret pie charts. The data set was managed using a geographic information system. Biological condition was assessed using a RIVPACS (river invertebrate prediction and classification system)-like predictive model. The model provided probabilities of capture for 117 fish species based on the geographic location of sites and local habitat descriptors. Impaired biological condition was defined as the proportion of those native species predicted to occur at a site that were observed. The potential toxic effects of exposure to mixtures of contaminants were estimated using species sensitivity distributions and mixture toxicity principles. Generalized linear regression models described species abundance as a function of habitat characteristics. Statistically linking biological condition, habitat characteristics including mixture risks, and species abundance allowed us to evaluate the losses of species with environmental conditions. Results were mapped as simple effect and probable-cause pie charts (EPC pie diagrams), with pie sizes corresponding to magnitude of local impairment, and slice sizes to the relative probable contributions of different stressors. The types of models we used have been successfully applied in ecology and ecotoxicology, but they have not previously been used in concert to quantify impairment and its likely causes. Although data limitations constrained our ability to examine complex interactions between stressors and species, the direct relationships we detected likely represent conservative estimates of stressor contributions to local impairment. Future refinements of the general approach and specific methods described here should yield even more promising results.

Although many chemicals are in use, the environmental impacts of only a few have been established, usually on per-chemical basis. Uncertainty remains about the overall impact of chemicals. This paper estimates combined toxic pressure on coastal North Sea ecosystems from 343 high-production-volume chemicals used within the catchment of rivers Rhine, Meuse, and Scheldt. Multimedia fate modeling and species sensitivity distribution-based effects estimation are applied. Calculations start from production volumes and emission rates and use physicochemical substance properties and aquatic ecotoxicity data. Parameter uncertainty is addressed by Monte Carlo simulations. Results suggest that the procedure is technically feasible. Combined toxic pressure of all 343 chemicals in coastal North Seawater is 0.025 (2.5% of the species are exposed to concentration levels above EC50 values), with a wide confidence interval of nearly 0-1. This uncertainty appears to be largely due to uncertainties in interspecies variances of aquatic toxicities and, to a lesser extent, to uncertainties in emissions and degradation rates. Due to these uncertainties, the results support gross ranking of chemicals in categories: negligible and possibly relevant contributions only. With 95% confidence, 283 of the 343 chemicals (83%) contribute negligibly (less than 0.1%) to overall toxic pressure, and only 60 (17%) need further consideration.