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Graphical presentation of the proposed multiple lines-of-evidence approach for the identification of priority substances and priority mixtures under the EU Water Framework Directive
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Current prioritisation procedures under the EU Water Framework Directive (WFD) do not account for risks from chemical mixtures. SOLUTIONS proposes a multiple-lines-of-evidence approach to tackle the problem effectively. The approach merges all available evidence from co-exposure modelling, chemical monitoring, effect-based monitoring, and ecologica...
Context in source publication
Context 1
... proposes a multiple lines-of-evidence (LOE) approach for the identification of priority mixtures presenting significant risks and drivers of mixture toxicity dominating the overall risks (Fig. 1). The suggested methodology is applicable at all scales (EU, river basin, and site-specific ...
Citations
... The organic compounds such as pharmaceuticals, personal care products, steroids, artificial sweeteners, industrial products, etc., collectively called emerging contaminants (ECs), are increasingly being reported across the globe (Ramírez-Malule et al., 2020). Many of the ECs are known or suspected to cause adverse environmental effects and are therefore required to be removed (Faust et al., 2019). Wastewater treatment plant (WWTP) effluent is one of the major contributors of ECs in the environment (Rout et al., 2021). ...
The study aims to understand the occurrence and removal of 20 emerging contaminants (ECs) in each unit process of a sequencing batch reactor-based wastewater treatment plant (WWTP) and explore the potential of biological activated carbon (BAC) for the treatment of residual ECs and organic matter in the secondary effluent. Analgesic-acetaminophen, anti-inflammatory drug-ibuprofen, and stimulant-caffeine were detected at high concentrations in the influent. Most of the removal was observed in the biological treatment stage in the SBR basins. The mass load of the ECs was 2.93 g/d in the secondary effluent and 0.4 g/d in the final sludge, while the total removal of the mass load of ECs till the secondary treatment stage was 93.22%. 12 of the 20 ECs were removed by more than 50%, while carbamazepine (negative removal), sulfamethoxazole, and trimethoprim were removed by less than 20%. As a polishing step and to remove residual ECs, two BAC units were studied for 11,000 bed volumes (324 days). Packed column studies on granular activated carbon were conducted, and GAC development to BAC was monitored. SEM and FTIR were used to confirm and characterize the BAC. The BAC appeared to be more hydrophobic than the GAC. The BAC removed 78.4% and 40% of the dissolved ECs and organic carbon at an optimum EBCT of 25 min. Carbamazepine, sulfamethoxazole, and trimethoprim were removed by 61.5, 84, and 52.2%, respectively. Parallel column tests revealed adsorption as an important mechanism for the removal of positively charged compounds. The results indicate that the BAC is an effective tertiary/polishing technique for removing organic and micropollutants in the secondary wastewater effluent.
... These anthropogenic contaminants include both legacy pollutants (compounds primarily sourced from historical industrial operations, e.g., polychlorinated biphenyls [PCBs]) and contaminants of emerging concern (CECs; nonlegacy contaminants that are often detected in aquatic systems, e.g., pharmaceuticals, current-use agrochemicals, plasticizers, flame retardants, and polycyclic aromatic hydrocarbons [PAHs]) (Baldwin et al., 2020;Bernot et al., 2016;Busch et al., 2016;Elliott et al., 2017;Focazio et al., 2008;Glassmeyer Practically, this volume of information can be challenging for risk assessors, regulators, and natural resource managers who need to allocate resources toward chemical monitoring and management. Therefore, there is often a need for a rapid, triage-like approach to identify detected chemicals of higher and lower ecotoxicological concern based on readily accessible indicators of the potential risks they may pose to aquatic organisms and the ecosystems they inhabit (Faust et al., 2019;Great Lakes Restoration Initiative, 2014. ...
... Historically, many prioritization strategies have focused on the intrinsic persistence (P), bioaccumulation (B), and toxicity (T) of organic contaminants, evaluating detected compounds based on PBT benchmarks designed to reflect risk potential (Arnot & Mackay, 2008;ECHA, 2017;Muir & Howard, 2006;United Nations Environmental Programme, 2001). However, other prioritization strategies have considered alternative benchmarks (e.g., toxicological thresholds of concern [TTC], in vitro effect thresholds, in vivo effect concentrations), chemical usage or emission, occurrence in the environment, and/or public interest to identify environmental contaminants of concern Baldwin et al., 2016;Benotti et al., 2009;Diamond et al., 2011;Faust et al., 2019;Focazio et al., 2008;Kolpin et al., 2002;Posthuma et al., 2019;Ramirez et al., 2009). Over the past decade, effects-driven analyses have been increasingly employed to assist in chemical prioritization, using either site-specific or chemical-specific biological data that feature an array of approaches and concepts sometimes termed new approach methodologies (NAMs) (e.g., quantitative structure-activity relationships [QSARs], adverse outcome pathways [AOPs], high-throughput in vitro screening, and 'omics-based measurements in organisms from the field). ...
Watersheds are subjected to diverse anthropogenic inputs, exposing aquatic biota to a wide range of chemicals. Detection of multiple, different chemicals can challenge natural resource managers who often have to determine where to allocate potentially limited resources. Here we describe a weight‐of‐evidence framework for retrospectively prioritizing aquatic contaminants. To demonstrate framework utility, we used data from 96‐h caged fish studies to prioritize chemicals detected in the Milwaukee Estuary (WI, USA; 2017 ‐ 2018). Across study years, 77/178 targeted chemicals were detected. Chemicals were assigned prioritization scores based on spatial and temporal detection frequency, environmental distribution, environmental fate, ecotoxicological potential, and effect prediction. Chemicals were sorted into priority bins based on the intersection of prioritization score and data availability. Data limited chemicals represented those that did not have sufficient data to adequately evaluate ecotoxicological potential or environmental fate. Seven compounds (fluoranthene, benzo[a]pyrene, pyrene, atrazine, metolachlor, phenanthrene, and DEET) were identified as high or medium priority and data‐sufficient and flagged as candidates for further effects‐based monitoring studies. Twenty‐one compounds were identified as high or medium priority and data‐limited and flagged as candidates for further ecotoxicological research. Fifteen chemicals were flagged as the lowest priority in the watershed. One of these chemicals (2‐methylnaphthalene) displayed no data limitations and was flagged as a definitively low priority chemical. The remaining chemicals displayed some data limitations and were considered lower priority compounds (contingent on further ecotoxicological and environmental fate assessments). The remaining 34 compounds were flagged as low or medium priority. Altogether, this prioritization provided a screening‐level (non‐definitive) assessment that could be used to focus further resource management and risk assessment activities in the Milwaukee Estuary. Furthermore, by providing detailed methodology and a practical example with real experimental data, we demonstrated that the proposed framework represents a transparent and adaptable approach for prioritizing contaminants in freshwater environments. This article is protected by copyright. All rights reserved. Integr Environ Assess Manag 2022;00:0–0.
... Predictive risk assessment methods such as those proposed by Posthuma et al. (2019b) and Van de Meent et al. (2020) have the potential to inform such prioritization efforts. Non-target screening and effect-based monitoring, remain critical tools that complement targeted chemical monitoring, and are key to improve prioritization efforts (Altenburger et al., 2015;Brack et al., 2018;Escher et al., 2018;Faust et al., 2019). ...
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. 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.
... Predictive risk assessment methods such as those proposed by Posthuma et al. (2019b) and Van de Meent et al. (2020) have the potential to inform such prioritization efforts. Non-target screening and effect-based monitoring, remain critical tools that complement targeted chemical monitoring, and are key to improve prioritization efforts (Altenburger et al., 2015;Brack et al., 2018;Escher et al., 2018;Faust et al., 2019). ...
... However, the PhACs carbamazepine, diclofenac, and amoxicillin were previously listed as Danube basin-specific pollutants, derived within the EU-project SOLUTIONS [57]. ...
The tremendous impact of natural and anthropogenic organic and inorganic substances continuously released into the environment requires a better understanding of the chemical status of aquatic ecosystems. Water contamination monitoring studies were performed for different classes of substances in different regions of the world. Reliable analytical methods and exposure assessment are the basis of a better management of water resources. Our research comprised publications from 2010 regarding the Lower Danube and North West Black Sea region, considering regulated and unregulated persistent and emerging pollutants. The frequently reported ones were: pharmaceuticals (carbamazepine, diclofenac, sulfamethoxazole, and trimethoprim), pesticides (atrazine, carbendazim, and metolachlor), endocrine disruptors—bisphenol A and estrone, polycyclic aromatic hydrocarbons, organochlorinated pesticides, and heavy metals (Cd, Zn, Pb, Hg, Cu, Cr). Seasonal variations were reported for both organic and inorganic contaminants. Microbial pollution was also a subject of the present review.
... Subsequently, these subsamples are tested by bioassays so that the chemicals of subsamples for which toxic responses are measured by the bioassays can be isolated and identified by chemical analysis (Brack et al., 2016). While there are several limitations to the EDA approach (e.g. it does not allow for quantifying mixture effects, but see Brack et al. (2016) and Hecker and Hollert (2009) for in-depth reviews), we believe that the combination of chemical monitoring, (eco)toxicological tests and EDA can aid in the understanding of effects that are driven by the interaction of different compounds Brack et al., 2019;Faust et al., 2019). ...
Monitoring of chemicals in the aquatic environment by chemical analysis alone cannot completely assess and predict the effects on aquatic species and ecosystems because of the increasing number of (unknown) chemical stressors and mixture effects in the environment. In addition, the ability of ecological indices to identify underlying stressors causing negative ecological effects is limited. Therefore, additional complementary methods are needed that can address the biological effects in a direct manner and provide a link to chemical exposure, i.e. (eco)toxicological tests. (Eco)toxicological tests are defined as test systems that expose biological components (cells, individuals, populations, communities) to (environmental mixtures of) chemicals to register biological effects. These tests measure responses at the sub-organismal (biomarkers and in vitro bioassays), whole-organismal and population/community level. We performed a literature search to obtain a state-of-art overview of ecotoxicological test available for assessing impacts of chemicals to the aquatic biota and to reveal datagaps. In total, we included 509 biomarkers, 207 in vitro bioassays, 422 tests measuring biological effects at the whole-organismal level and 78 tests at the population community-and ecosystem-level. Tests at the whole-organismal level and biomarkers were most abundant for invertebrates and fish, whilst in vitro bioassays are mostly based on mammalian cell lines. Tests are almost missing for organisms other than microorganisms and algae at the community- and ecosystem-level. In addition, we provide overview of the various extrapolation challenges faced in using data from these tests and suggest some forward looking perspectives. Although extrapolating the measured responses to relevant protection goals remains challenging, the combination of ecotoxicological experiments and models is key for a more comprehensive assessment of the effects of chemicals stressors to aquatic ecosystems.
... ECHA and the European Food Safety Authority (EFSA) (Bodar et al., 2003;ECHA 2016;EFSA 2009;EU Regulation No 528/2012); 2) targeted risk-based assessments focusing on aquatic ecotoxicity and human toxicity via the aquatic environment; 3) simplified risk-based assessments based on intrinsic hazards, widespread environmental contamination, production volumes and use patterns. The priority list of substances under the WFD focuses only on single substances (Daginnus et al., 2011;Faust et al., 2019;INERIS 2009). ...
The European Human Biomonitoring Initiative (HBM4EU¹) has established a European Union-wide human biomonitoring (HBM) programme to generate knowledge on human internal exposure to chemical pollutants and their potential health impacts in Europe, in order to support policy makers’ efforts to ensure chemical safety and improve health in Europe.
A prioritisation strategy was necessary to determine and meet the most important needs of both policy makers and risk assessors, as well as common national needs of participating countries and a broad range of stakeholders. This strategy consisted of three mains steps: 1) mapping of knowledge gaps identified by policy makers, 2) prioritisation of substances using a scoring system, and 3) generation of a list of priority substances reflective of the scoring, as well as of public policy priorities and available resources.
For the first step, relevant ministries and agencies at EU and national levels, as well as members of the Stakeholder Forum each nominated up to 5 substances/substance groups of concern for policy-makers. These nominations were collated into a preliminary list of 48 substances/substance groups, which was subsequently shortened to a list of 23 after considering the total number of nominations each substance/substance group received and the nature of the nominating entities.
For the second step, a panel of 11 experts in epidemiology, toxicology, exposure sciences, and occupational and environmental health scored each of the substances/substance groups using prioritisation criteria including hazardous properties, exposure characteristics, and societal concern. The scores were used to rank the 23 substances/substance groups. In addition, substances were categorised according to the level of current knowledge about their hazards, extent of human exposure (through the availability of HBM data), regulatory status and availability of analytical methods for biomarker measurement.
Finally, in addition to the ranking and categorisation of the substances, the resources available for the project and the alignment with the policy priorities at European level were considered to produce a final priority list of 9 substances/substance groups for research activities and surveys within the framework of the HBM4EU project.
... Further studies have provided fundamental information mostly aiming at improving the efforts of the Directive: von der Ohe et al. (2011) constructed extensive prioritization recommendations on more than 500 chemicals to improve WFD monitoring; Geissen et al. (2015) identified conceptual challenges in current monitoring protocols, especially with regards to emerging pollutants; similarly, Brack et al. (2017) extensively reviewed the current state of WFD chemical monitoring and developed solution-oriented recommendations for improvement of ecological impact assessments supporting targeted risk reduction strategies; Carvalho et al. (2019) provided a holistic analysis of novel approaches advancing current WFD monitoring in support of water management policies and highlighted a multitude of issues, organizational hindrances or lack of public stakeholder awareness. Other conceptual recommendations have also been proposed by various studies: for instance; the prioritization and assessment of chemical mixtures (Faust et al., 2019); the advancement of the linkage between analytical and ecological response interactions ; the derivation of ecological status estimates from species trait-indices in comparison to exposure measurements (von der Ohe et al., 2007); and the derivation of robust environmental quality standards from in vitro and in vivo tests for WFD water quality evaluation (Escher et al., 2018). However, to this date, no comprehensive evaluation has been conducted using the entirety of available occurrence data for organic chemicals (i.e. ...
... Also, chronic ecological risks, due to the lack of temporally more granular data, remain currently unknown but require attention in light of high detection frequencies for several chemical classes. Our analysis should therefore prime new vigor for expanding, improving, and integrating the WFD monitoring schemes, or any scheme that may follow in its footsteps, based on expansive recommendations Brack et al., 2017;Carvalho et al., 2019;Faust et al., 2019;Geissen et al., 2015), because the WFD remains one of the most ambitious environmental policies thatdespite its shortcomingscan achieve continental improvements to surface water quality. ...
Aquatic ecosystems are at risk of being impaired by various organic chemicals, however comprehensive large-scale evaluations of waterbodies’ status and trends are rare. Here, surface water monitoring data, gathered as part of the EU Water Framework Directive and comprising the occurrence of 352 organic contaminants (>8.3 mil. measurements; 2001–2015; 8213 sites) in 31 European countries, was used to evaluate past and current environmental risks for three aquatic species groups: fish, invertebrates, plants. Monitoring quality indices were defined per country and found to improve over time. Relationships became apparent between countries’ monitoring quality index and their success in detecting contaminants. Across the EU, contaminants were more frequently found in recent years. Overall, 35.7% (n = 17,484) of sites exceeded at least one acute regulatory threshold level (RTL) each year, and average risks significantly increased over time for fish (τ = 0.498, p = 0.01) and aquatic invertebrates (τ = 0.429, p = 0.03). This indicates an increased chemical pressure to Europe’s waterbodies and overall large-scale threshold exceedances. Pesticides were identified as the main risk drivers (>85% of RTL exceedances) with aquatic invertebrates being most acutely at risk in Europe. Agricultural land-use was clearly identified as the primary spatial driver of the observed aquatic risks throughout European surface waters. Issues in monitoring data heterogeneity were highlighted and also followed by subsequent improvement recommendations, strengthening future environmental quality assessments. Overall, aquatic ecosystem integrity remains acutely at risk across Europe, signaling the demand for continued improvements.
... Chemicals typically occur as mixtures in the environment and hence, organisms are exposed to a combination of these chemicals. However, prospective risk assessment is conducted for single chemicals and may not account for combined effects [1]. Since it is practically impossible to test all the possible combinations of chemical exposure, modeling of mixture toxicity allows one to at least predict an expected effect of several chemicals from their individual effects. ...
Risk assessment of chemicals is usually conducted for individual chemicals whereas mixtures of chemicals occur in the environment. Considering that neuroactive chemicals are a group of contaminants that dominate the environment, it is then imperative to understand the combined effects of mixtures. The commonly used models to predict mixture effects, namely concentration addition (CA) and independent action (IA), are thought to be suitable for mixtures of similarly or dissimilarly acting components, respectively. For mixture toxicity prediction, one important challenge is to clarify whether to group neuroactive substances based on similar mechanisms of action, e.g., same molecular target or rather similar toxicological response, e.g., hyper- or hypoactivity (effect direction). We addressed this by using the spontaneous tail coiling (STC) of zebrafish embryos, which represents the earliest observable motor activity in the developing neural network, as a model to elucidate the link between the mechanism of action and toxicological response. Our objective was to answer the following two questions: (1) Can the mixture models CA or IA be used to predict combined effects for neuroactive chemical mixtures when the components share a similar mode of action (i.e., hyper- or hypoactivity) but show different mechanism of action? (2) Will a mixture of chemicals where the components show opposing effect directions result in an antagonistic combined effect? Results indicate that mixture toxicity of chemicals such as propafenone and abamectin as well as chlorpyrifos and hexaconazole that are known to show different mechanisms of action but similar effect directions were predictable using CA and IA models. This could be interpreted with the convergence of effects on the neural level leading to either a collective activation or inhibition of synapses. We also found antagonistic effects for mixtures containing substances with opposing effect direction. Finally, we discuss how the STC may be used to amend risk assessment.
... Chemicals typically occur as mixtures in the environment and hence, organisms are exposed to a combination of these chemicals. However, prospective risk assessment is conducted for single chemicals and may not account for combined effects [1]. Since it is practically impossible to test all the possible combinations of chemical exposure, modeling of mixture toxicity allows to at least predict an expected effect of several chemicals from their individual effects. ...
Risk assessment of chemicals is usually conducted for individual chemicals whereas mixtures of chemical are occurring in the environment. Considering that neuroactive chemicals are a group of contaminants that dominate in the environment, it is then imperative to understand the combined effects from mixtures. The commonly used models to predict mixture effects, namely concentration addition (CA) and independent action (IA), are thought suitable for mixtures of similarly or dissimilarly acting components, respectively. For mixture toxicity prediction, one important challenge is to clarify whether to group neuroactive substances based on similar mechanisms of action, e.g. same molecular target or rather similar toxicological response, e.g. hyper- or hypoactivity (effect direction). We addressed this by using the spontaneous tail coiling (STC) of zebrafish embryos, which represents the earliest observable motor activity in the developing neural network, as a model to elucidate the link between mechanism of action and toxicological response. Two questions were asked: 1.) Can the mixture models CA or IA be used to predict combined effects for neuroactive chemical mixtures when the components share a similar mode of action (i.e. hyper- or hypoativity) but show different mechanism of action? 2.) Will a mixture of chemicals where the components show opposing effect directions result in an antagonistic combined effect? Results indicate that mixture toxicity of chemicals such as propafenone and abamectin as well as chlorpyrifos and hexaconazole that are known to show different mechanisms of action but similar effect directions were predictable using CA and IA models. This could be interpreted with the convergence of effects on the neural level leading to either a collective activation or inhibition of synapses. We also found antagonistic effects for mixtures containing substances with opposing effect direction. Finally, we discuss how the STC may be used to amend risk assessment.
