Modeling Full Life-Cycle Effects of Copper on Brook Trout (Salvelinus fontinalis) Populations.

Population models are increasingly used to predict population-level effects of chemicals. For trout, most toxicity data are available on early-life stages, but this may cause population models to miss true population-level effects. We predicted population-level effects of copper (Cu) on a brook trout (Salvelinus fontinalis) population based on individual-level effects observed in either a life-cycle study or an early-life stage study. We assessed the effect of Cu on predicted trout densities (both total and different age classes) and the importance of accounting for effects on the full life cycle compared with only early-life stage effects. Additionally, uncertainty about the death mechanism and growth effects was evaluated by comparing the effect of different implementation methods: individual tolerance (IT) versus stochastic death (SD) and continuous versus temporary growth effects. For the life-cycle study, the same population-level no-observed-effect concentration (NOECpop) was predicted as the lowest reported individual-level NOEC (NOECind; 9.5 µg/L) using IT. For SD, the NOECpop was predicted to be lower than the NOECind for young-of-the-year and 1-year-old trout (3.4 µg/L), but similar for older trout (9.5 µg/L). The implementation method for growth effects did not affect the NOECpop of the life-cycle study. Simulations based solely on the early-life stage effects within the life-cycle study predicted unbounded NOECpop values (≥32.5 µg/L), that is, >3.4 times higher than the NOECpop based on all life-cycle effects. For the early-life stage study, the NOECpop for both IT and SD were predicted to be >2.6 times higher than the lowest reported NOECind. Overall, we demonstrate that effects on trout populations can be underestimated if predictions are solely based on toxicity data with early-life stages. Environ Toxicol Chem 2024;43:1662-1676. © 2024 SETAC.

Extrapolation of Metal Toxicity Data for the Rotifer Brachionus calyciflorus Using an Individual-Based Population Model.

Ecological risk assessment (ERA) of metals typically starts from standardized toxicity tests, the data from which are then extrapolated to derive safe concentrations for the envisioned protection goals. Because such extrapolation in conventional ERA lacks ecological realism, ecological modeling is considered as a promising new approach for extrapolation. Many published population models are complex, that is, they include many processes and parameters, and thus require an extensive dataset to calibrate. In the present study, we investigated how individual-based models based on a reduced version of the Dynamic Energy Budget theory (DEBkiss IBM) could be applied for metal effects on the rotifer Brachionus calyciflorus. Data on survival over time and reproduction at different temperatures and food conditions were used to calibrate and evaluate the model for copper effects. While population growth and decline were well predicted, the underprediction of population density and the mismatch in the onset of copper effects were attributed to the simplicity of the approach. The DEBkiss IBM was applied to toxicity datasets for copper, nickel, and zinc. Predicted effect concentrations for these metals based on the maximum population growth rate were between 0.7 and 3 times higher in all but one case (10 times higher) than effect concentrations based on the toxicity data. The size of the difference depended on certain characteristics of the toxicity data: both the steepness of the concentration-effect curve and the relative sensitivity of lethal and sublethal effects played a role. Overall, the present study is an example of how a population model with reduced complexity can be useful for metal ERA. Environ Toxicol Chem 2024;43:324-337. © 2023 SETAC.

Updated Chronic Copper Bioavailability Models for Invertebrates and Algae.

Chronic copper (Cu) bioavailability models have been successfully implemented in European risk assessment frameworks and compliance evaluations. However, they were developed almost two decades ago, which calls for an update. In the study, we present updated chronic Cu bioavailability models for invertebrates and algae. They consider recent ecotoxicity data sets and use the more recent speciation model Windermere Humic Aqueous Model (WHAM) VII and an optimized model structure (i.e., a generalized bioavailability model [gBAM]). Contrary to the classic biotic ligand model, a gBAM models the effect of pH on Cu2+ toxicity via a log-linear relationship parametrized through the pH slope SpH . The recalibrated SpH parameters are -0.208 for invertebrates (Daphnia magna, two clones) and -0.975 for algae (Raphidocelis subcapitata and Chlorella vulgaris). The updated models predict 80% to 100% of the observed effect levels for eight different species within a factor of 2. The only exception was one of the two data sets considering subchronic 7-day mortality to Hyalella azteca: the prediction performance of the updated invertebrate model at pH ≥ 8.3 was poor because the effect of pH on Cu2+ toxicity appeared to be dependent on the pH itself (with a steeper pH slope compared with the updated invertebrate model at pH ≥ 8.1). The prediction performance of the updated Cu bioavailability models was similar to or better than that of the models used for regulatory application in Europe until now, with one exception (i.e., H. azteca). Together with the recently published fish bioavailability model, the models developed in the present study constitute a complete, updated, and consistent bioavailability model set. Overall, the updated chronic Cu bioavailability model set is robust and can be used in regulatory applications. The updated bioavailability model set is currently used under the European Union Registration, Evaluation, Authorisation, and Restriction of Chemicals framework regulation to guide the safe use of Cu. Environ Toxicol Chem 2024;43:450-467. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Updating the Chronic Freshwater Ecotoxicity Database and Biotic Ligand Model for Nickel for Regulatory Applications in Europe.

Bioavailability has been taken into account in the regulation of nickel in freshwater ecosystems in Europe for over a decade; during that time a significant amount of new information has become available covering both the sensitivity of aquatic organisms to nickel toxicity and bioavailability normalization. The ecotoxicity database for chronic nickel toxicity to freshwater organisms has been updated and now includes 358 individual data points covering a total of 53 different species, all of which are suitable for bioavailability normalization to different water chemistry conditions. The bioavailability normalization procedure has also been updated to include updates to the bioavailability models that enable more sensitive water chemistry conditions to be covered by the model predictions. The updated database and bioavailability normalization procedure are applicable to more than 95% of regulated European surface water conditions and have been used to calculate site-specific criteria for a variety of different water chemistry scenarios, to provide an indication of how the sensitivity to nickel varies between different water types. The hazardous concentration for 5% of a species (HC5) values for this diverse selection of water types range from 1.6 to 36 µg L-1 , clearly demonstrating the importance of accounting for nickel bioavailability in freshwaters. This updated database and bioavailability normalization procedure provide a robust basis for the derivation of regulatory thresholds for chronic nickel toxicity in freshwaters such as predicted no-effect concentrations and Environmental Quality Standards and are protective of the results of several mesocosm studies. Environ Toxicol Chem 2023;42:566-580. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

European freshwater silver monitoring data do not suggest a potential European-wide risk.

European legislations frequently focus on substances that are of potential concern to human or environmental health, such as "priority substances" under the Water Framework Directive 2000/60/EC ("WFD") that are identified as substances posing a significant risk to or via the aquatic environment. The EU REACH regulation also requires the assessment of the environmental risks of chemicals put on the EU market. To properly assess the potential risk of a substance, high-quality representative monitoring data should be compared with a safe threshold concentration. The objective of this article is to evaluate different publicly available freshwater monitoring data sets for silver and investigate them for a potential European-wide risk according to the methodology used by the European Commission. Most available silver monitoring data sets contain a large proportion of undetected samples with a reported concentration below the limit of quantification (LOQ) of the analytical technique, leading to considerable uncertainty in the data set. For silver, this LOQ is often at or above the safe threshold concentration, and the method used to handle undetected samples during the data processing considerably impacts the data assessment. We demonstrate that for large data sets covering many European countries (and often a wide range of LOQs), the uncertainty in the data set does not allow us to make a general conclusion about European-wide risk. However, by examining the data sets in more detail and assessing three additional country-specific monitoring data sets, we show that silver does not pose a risk to the freshwater environment in several countries. We conclude that the available data sets need careful assessment to account for the values that are below the LOQ, and that there is currently no reliable evidence indicating a European-wide risk for silver in the aquatic environment, meaning it should not be selected as  priority substance under the WFD. Integr Environ Assess Manag 2023;19:1110-1119. © 2022 European Precious Metals Federation. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Predicting Combined Effects of Chemical Stressors: Population-Level Effects of Organic Chemical Mixtures with a Dynamic Energy Budget Individual-Based Model.

Most regulatory ecological risk-assessment frameworks largely disregard discrepancies between the laboratory, where effects of single substances are assessed on individual organisms, and the real environment, where organisms live together in populations and are often exposed to multiple simultaneously occurring substances. We assessed the capability of individual-based models (IBMs) with a foundation in the dynamic energy budget (DEB) theory to predict combined effects of chemical mixtures on populations when they are calibrated on toxicity data of single substances at the individual level only. We calibrated a DEB-IBM for Daphnia magna for four compounds (pyrene, dicofol, α-hexachlorocyclohexane, and endosulfan), covering different physiological modes of action. We then performed a 17-week population experiment with D. magna (designed using the DEB-IBM), in which we tested mixture combinations of these chemicals at relevant concentrations, in a constant exposure phase (7-week exposure and recovery), followed by a pulsed exposure phase (3-day pulse exposure and recovery). The DEB-IBM was validated by comparing blind predictions of mixture toxicity effects with the population data. The DEB-IBM accurately predicted mixture toxicity effects on population abundance in both phases when assuming independent action at the effect mechanism level. The population recovery after the constant exposure was well predicted, but recovery after the pulse was not. The latter could be related to insufficient consideration of stochasticity in experimental design, model implementation, or both. Importantly, the mechanistic DEB-IBM performed better than conventional statistical mixture assessment methods. We conclude that the DEB-IBM, calibrated using only single-substance individual-level toxicity data, produces accurate predictions of population-level mixture effects and can therefore provide meaningful contributions to ecological risk assessment of environmentally realistic mixture exposure scenarios. Environ Toxicol Chem 2022;41:2240-2258. © 2022 SETAC.

Evaluating the Theoretical Background of STOFFENMANAGER® and the Advanced REACH Tool.

STOFFENMANAGER® and the Advanced REACH Tool (ART) are recommended tools by the European Chemical Agency for regulatory chemical safety assessment. The models are widely used and accepted within the scientific community. STOFFENMANAGER® alone has more than 37 000 users globally and more than 310 000 risk assessment have been carried out by 2020. Regardless of their widespread use, this is the first study evaluating the theoretical backgrounds of each model. STOFFENMANAGER® and ART are based on a modified multiplicative model where an exposure base level (mg m-3) is replaced with a dimensionless intrinsic emission score and the exposure modifying factors are replaced with multipliers that are mainly based on subjective categories that are selected by using exposure taxonomy. The intrinsic emission is a unit of concentration to the substance emission potential that represents the concentration generated in a standardized task without local ventilation. Further information or scientific justification for this selection is not provided. The multipliers have mainly discrete values given in natural logarithm steps (…, 0.3, 1, 3, …) that are allocated by expert judgements. The multipliers scientific reasoning or link to physical quantities is not reported. The models calculate a subjective exposure score, which is then translated to an exposure level (mg m-3) by using a calibration factor. The calibration factor is assigned by comparing the measured personal exposure levels with the exposure score that is calculated for the respective exposure scenarios. A mixed effect regression model was used to calculate correlation factors for four exposure group [e.g. dusts, vapors, mists (low-volatiles), and solid object/abrasion] by using ~1000 measurements for STOFFENMANAGER® and 3000 measurements for ART. The measurement data for calibration are collected from different exposure groups. For example, for dusts the calibration data were pooled from exposure measurements sampled from pharmacies, bakeries, construction industry, and so on, which violates the empirical model basic principles. The calibration databases are not publicly available and thus their quality or subjective selections cannot be evaluated. STOFFENMANAGER® and ART can be classified as subjective categorization tools providing qualitative values as their outputs. By definition, STOFFENMANAGER® and ART cannot be classified as mechanistic models or empirical models. This modeling algorithm does not reflect the physical concept originally presented for the STOFFENMANAGER® and ART. A literature review showed that the models have been validated only at the 'operational analysis' level that describes the model usability. This review revealed that the accuracy of STOFFENMANAGER® is in the range of 100 000 and for ART 100. Calibration and validation studies have shown that typical log-transformed predicted exposure concentration and measured exposure levels often exhibit weak Pearson's correlations (r is <0.6) for both STOFFENMANAGER® and ART. Based on these limitations and performance departure from regulatory criteria for risk assessment models, it is recommended that STOFFENMANAGER® and ART regulatory acceptance for chemical safety decision making should be explicitly qualified as to their current deficiencies.

Integrating Bioavailability of Metals in Fish Population Models.

Population models are increasingly being used to extrapolate individual-level effects of chemicals, including metals, to population-level effects. For metals, it is also important to take into account their bioavailability to correctly predict metal toxicity in natural waters. However, to our knowledge, no models exist that integrate metal bioavailability into population modeling. Therefore, our main aims were to 1) incorporate the bioavailability of copper (Cu) and zinc (Zn) into an individual-based model (IBM) of rainbow trout (Oncorhynchus mykiss), and 2) predict how survival-time concentration data translate to population-level effects. For each test water, reduced versions of the general unified threshold model of survival (GUTS-RED) were calibrated using the complete survival-time concentration data. The GUTS-RED individual tolerance (IT) showed the best fit in the different test waters. Little variation between the different test waters was found for 2 GUTS-RED-IT parameters. The GUTS-RED-IT parameter "median of distribution of thresholds" (mw ) showed a strong positive relation with the Ca2+ , Mg2+ , Na+ , and H+ ion activities. Therefore, mw formed the base of the calibrated GUTS bioavailability model (GUTS-BLM), which predicted 30-d x% lethal concentration (LCx) values within a 2-fold error. The GUTS-BLM was combined with an IBM, inSTREAM-Gen, into a GUTS-BLM-IBM. Assuming that juvenile survival was the only effect of Cu and Zn exposure, population-level effect concentrations were predicted to be 1.3 to 6.2 times higher than 30-d laboratory LCx values, with the larger differences being associated with higher interindividual variation of metal sensitivity. The proposed GUTS-BLM-IBM model can provide insight into metal bioavailability and effects at the population level and could be further improved by incorporating sublethal effects of Cu and Zn. Environ Toxicol Chem 2021;40:2764-2780. © 2021 SETAC.

Setting a Protective Threshold Value for Silver Toward Freshwater Organisms.

Driven by Regulation (EC) No. 1272/2008 and the European Water Framework Directive 2000/60/EC, we have re-evaluated the available chronic freshwater ecotoxicity data for ionic silver (Ag) using strict data quality criteria. In addition, we generated new chronic ecotoxicity data for species potentially sensitive to Ag (the rotifer Brachionus calyciflorus, the cyanobacteria Anabaena flos-aquae, and the aquatic plant Lemna minor) using Ag nitrate as the test substance. The 10% effect concentrations for the most sensitive endpoint per test species were 0.31 µg dissolved Ag/L for B. calyciflorus (population size), 0.41 µg dissolved Ag/L for A. flos-aquae (growth rate), and 1.40 µg dissolved Ag/L for L. minor (root length). We included these values in the set of reliable chronic freshwater data, subsequently covering a total of 12 taxonomic groups and 15 species. Finally, we applied a species sensitivity distribution approach to the data set using various models. The best-fitting model (Rayleigh distribution) resulted in a threshold value protective for 95% of the species of 0.116 µg dissolved Ag/L. This value is considered reliable and conservative in terms of species protection and can be used as a solid basis for setting thresholds for Ag in freshwater after application of an appropriate assessment factor. Furthermore, this value represents reasonable worst-case conditions for bioavailability in European Union surface waters (low hardness and low dissolved organic carbon). Environ Toxicol Chem 2021;40:1678-1693. © 2021 European Precious Metals Federation. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Development and Validation of a Mixture Toxicity Implementation in the Dynamic Energy Budget-Individual-Based Model: Effects of Copper and Zinc on Daphnia magna Populations.

Mechanistic population models are gaining considerable interest in ecological risk assessment. The dynamic energy budget approach for toxicity (DEBtox) and the general unified threshold model for survival (GUTS) are well-established theoretical frameworks that describe sublethal and lethal effects of a chemical stressor, respectively. However, there have been limited applications of these models for mixtures of chemicals, especially to predict long-term effects on populations. We used DEBtox and GUTS in an individual-based model (IBM) framework to predict both single and combined effects of copper and zinc on Daphnia magna populations. The model was calibrated based on standard chronic toxicity test results with the single substances. A mixture toxicity implementation based on the general independent action model for mixtures was developed and validated with data from a population experiment with copper and zinc mixtures. Population-level effects of exposure to individual metals were accurately predicted by DEB-IBM. The DEB-IBM framework also allowed us to identify the potential mechanisms underlying these observations. Under independent action the DEB-IBM was able to predict the population dynamics observed in populations exposed to the single metals and their mixtures (R2 > 65% in all treatments). Our modeling shows that it is possible to extrapolate from single-substance effects at the individual level to mixture toxicity effects at the population level, without the need for mixture toxicity data at the individual level from standard mixture toxicity tests. The application of such modeling techniques can increase the ecological realism in risk assessment. Environ Toxicol Chem 2021;40:513-527. © 2020 SETAC.

A Generalized Bioavailability Model (gBAM) for Predicting Chronic Copper Toxicity to Freshwater Fish.

The generalized bioavailability model (gBAM) has been proposed as an alternative to the biotic ligand model (BLM) for modeling bioavailability and chronic toxicity of copper (Cu). The gBAM combines a log-linear effect of pH on free Cu2+ ion toxicity with BLM-type parameters for describing the protective effects of major cations (calcium [Ca]2+ , magnesium [Mg]2+ , and sodium [Na]+ ). In the present study, a Windermere Humic Aqueous Model (WHAM) VII-based gBAM for fish was parametrized based on an existing chronic (30-d) dataset of juvenile rainbow trout (Oncorhynchus mykiss). The model, with defined parameters (pH slope parameter [SpH ] = 0.4449 and biotic ligand competition constants [log KCaBL = 4.0, log KMgBL = 3.4, and log KNaBL = 3.0]), was shown to accurately predict the effects of pH, dissolved organic carbon, Ca, and Mg on chronic Cu toxicity to juvenile rainbow trout at the effect levels relevant for environmental risk assessment (i.e., median prediction error of 1.3-fold for 10 and 20% lethal concentrations). The gBAM predicted the effect of pH more accurately than a previously published Cu BLM for juvenile rainbow trout, especially at pH > 8. We also evaluated the cross-species and cross-life stage applicability of the newly developed juvenile rainbow trout gBAM using existing chronic Cu toxicity data with early life stages of fathead minnow (Pimephales promelas) and rainbow trout. We did this because using a single bioavailability model for all fish species and life stages is practical from a regulatory point of view. Although the early life stage datasets exhibit considerable uncertainties, 91% of the considered toxicity values at the effect levels most relevant in European environmental regulations (10% effect on survival or growth) were predicted within a 2-fold error. Overall, the chronic Cu gBAM we developed is a valuable alternative for the existing chronic Cu BLM for rainbow trout and performs sufficiently well to be used in risk assessment according to currently accepted standards of bioavailability model performance (from the current European regulatory point of view). However, our analysis also suggests that bioavailability relations differ between different fish life stages and between endpoints (e.g., mortality vs growth), which is currently not accounted for in environmental risk assessments. Environ Toxicol Chem 2020;39:2424-2436. © 2020 SETAC.

The Use of Mechanistic Population Models in Metal Risk Assessment: Combined Effects of Copper and Food Source on Lymnaea stagnalis Populations.

Environmental risk assessment (ERA) of chemicals aims to protect populations, communities, and ecosystems. Population models are considered more frequent in ERA because they can bridge the gap between the individual and the population level. Lymnaea stagnalis (the great pond snail) is an organism that is particularly sensitive to various metals, including copper (Cu). In addition, the sensitivity of this species to Cu differs between food sources. The first goal of the present study was to investigate whether we could explain the variability in sensitivity between food sources (lettuce and fish flakes) at the individual level with a dynamic energy budget (DEB) model. By adapting an existing DEB model and calibrating it with Cu toxicity data, thereby combining information from 3 studies and 2 endpoints (growth and reproduction), we put forward inhibition of energy assimilation as the most plausible physiological mode of action (PMoA) of Cu. Furthermore, the variation in Cu sensitivity between both food sources was considerably lower at the PMoA level than at the individual level. Higher Cu sensitivity at individual level under conditions of lower food quality or availability appears to emerge from first DEB principles when inhibition of assimilation is the PMoA. This supports the idea that DEB explained Cu sensitivity variation between food sources. Our second goal was to investigate whether this food source effect propagated to the population level. By incorporating DEB in an individual-based model (IBM), population-level effects were predicted. Based on our simulations, the food source effect was still present at the population level, albeit less prominently. Finally, we compared predicted population-level effect concentration, x% (ECx) values with individual-level ECx values for different studies. Using the DEB-IBM, the range of effect concentrations decreased significantly: at the individual level, the difference in chronic EC10 values between studies was a factor of 70 (1.13-78 µg dissolved Cu/L), whereas at the population level the difference was a factor of 15 (2.9-44.6 µg dissolved Cu/L). To improve interstudy comparability, a bioavailability correction for differences in water chemistry was performed with a biotic ligand model. This further decreased the variation, down to a factor of 7.4. Applying the population model in combination with a bioavailability correction thus significantly decreased the variability of chronic effect concentrations of Cu for L. stagnalis. Overall, the results of the present study illustrate the potential usefulness of transitioning to a more modeling-based environmental risk assessment. Environ Toxicol Chem 2019;00:1-16. © 2019 SETAC.

MeClas: An online tool for hazard identification and classification of complex inorganic metal-containing materials.

MeClas is a web-based tool to generate (eco)toxicity hazard categories and corresponding classification & labelling information of inorganic metal-containing complex materials such as ores, concentrates, intermediates or alloys for which the manual application of the GHS/CLP rules is very complex and requires a high level of consistency. The tool comprises several tiers, aimed at the progressive refinement of classification through recognition of specific mineral content, speciation/mineralogy up to bio-availability corrections. Where relevant in a regional jurisdiction (EU and US), mandatory classification references are used complementary to high quality (eco)toxicity reference values (ERV/TRV) and self-classifications. MeClas addresses the GHS human health and environmental hazard endpoints, is based on an unambiguous algorithm defined under GHS/CLP, has a well defined domain of applicability and robust predictability. MeClas allows a consistent approach across companies in line with GHS ruling (and regional implementations), considering the metal specificities and related classification GHS/CLP Guidance, and the most up to date (eco)-toxicological hazard information on self-classifications and ERV/TRV.

Updated species sensitivity distribution evaluations for acute and chronic lead toxicity to saltwater aquatic life.

The US Environmental Protection Agency's (USEPA's) ambient water quality criteria (AWQC) for lead (Pb) in salt water were developed in 1984. The acute and chronic criteria are 210 and 8.1 µg/L dissolved Pb, respectively. Because data were limited in 1984, the chronic criterion was derived using an acute-to-chronic ratio, but there are now sufficient toxicity data such that an acute-to-chronic ratio is no longer needed. Based on the data now available, the proposed updated acute and chronic salt water Pb AWQC (following USEPA methods) are 100 and 10 µg/L, respectively. In the European Union, a chronic salt water predicted no-effect concentration based on the median 5th percentile hazardous concentration (HC5-50) was developed in 2008 for the Registration, Evaluation, Authorisation, and Restriction of Chemicals program, which forms the basis for deriving chronic environmental quality standards for Pb in European marine waters. The salt water HC5-50 previously derived for Pb was 6.1 µg/L, whereas the proposed, updated chronic salt water HC5-50 derived following European Union methods is 11.0 µg/L. Thus, despite differences in derivation methodologies, the proposed AWQC and HC5-50 values are very consistent. Studies evaluating the effect of water quality factors on bioavailability and toxicity of Pb in salt water are limited; the effect of water quality on Pb toxicity in salt water should be considered in future studies. Environ Toxicol Chem 2017;36:2974-2980. © 2017 SETAC.

The derivation of effects threshold concentrations of lead for European freshwater ecosystems.

The main objective of the present study was to derive ecologically relevant effect threshold concentrations of (dissolved) Pb for selected European Union (EU) freshwater rivers, using the 2008 EU Voluntary Risk Assessment Report as a starting point and more advanced methodologies than those used in the Voluntary Risk Assessment Report. This included 1) implementing more robust quality criteria for selecting chronic toxicity data; 2) the conversion of total to dissolved Pb concentrations using a combination of an empirical equation relating inorganic Pb solubility and geochemical speciation modeling to account for effects of dissolved organic matter; 3) the use of bioavailability models for chronic toxicity for species belonging to 3 different trophic levels; and 4) the use of robust methods for large data set handling (such as species sensitivity distribution [SSD] analysis). The authors used published bioavailability models for an algal species (Pseudokirchneriella subcapitata) and a daphnid (Ceriodaphnia dubia) and developed a new model for the fathead minnow (Pimephales promelas). The research has shown that these models are also useful for, and reasonably accurate in, predicting chronic toxicity to other species, including a snail, a rotifer, midge larvae, and an aquatic plant (read-across). A comprehensive chronic toxicity data set for Pb was compiled, comprising 159 individual high-quality toxicity data for 25 different species. By applying the total dissolved conversion and the bioavailability models, normalized toxicity values were obtained, which were then entered into a SSD analysis. Based on the parametric best-fitting SSDs, the authors calculated that ecological threshold concentrations of Pb protecting 95% of freshwater species for 7 selected European freshwater scenarios were between 6.3 µg dissolved Pb/L and 31.1 µg dissolved Pb/L.

The effect of pH on chronic aquatic nickel toxicity is dependent on the pH itself: Extending the chronic nickel bioavailability models.

The environmental quality standard for Ni in the European Commission's Water Framework Directive is bioavailability based. Although some of the available chronic Ni bioavailability models are validated only for pH ≤ 8.2, a considerable fraction of European surface waters has a pH > 8.2. Therefore, the authors investigated the effect of a change in pH from 8.2 to 8.7 on chronic Ni toxicity in 3 invertebrate (Daphnia magna, Lymnaea stagnalis, and Brachionus calyciflorus) and 2 plant species (Pseudokirchneriella subcapitata and Lemna minor). Nickel toxicity was almost always significantly higher at pH 8.7 than at pH 8.2. To test whether the existing chronic Ni bioavailability models developed for pH ≤ 8.2 can be used at higher pH levels, Ni toxicity at pH 8.7 was predicted based on Ni toxicity observed at pH 8.2. This resulted in a consistent underestimation of toxicity. The results suggest that the effect of pH on Ni(2+) toxicity is dependent on the pH itself: the slope of the pH effect is steeper above than below pH 8.2 for species for which a species-specific bioavailability model exists. Therefore, the existing chronic Ni bioavailability models were modified to allow predictions of chronic Ni toxicity to invertebrates and plants in the pH range of 8.2 to 8.7 by applying a pH slope (SpH ) dependent on the pH of the target water. These modified Ni bioavailability models resulted in more accurate predictions of Ni toxicity to all 5 species (within 2-fold error), without the bias observed using the bioavailability models developed for pH ≤ 8.2. The results of the present study can decrease the uncertainty in implementing the bioavailability-based environmental quality standard under the Water Framework Directive for high-pH regions in Europe.

Assessment of human exposure to environmental sources of nickel in Europe: Inhalation exposure.

The paper describes the inhalation nickel (Ni) exposure of humans via the environment for the regional scale in the EU, together with a tiered approach for assessing additional local exposure from industrial emissions. The approach was designed, in the context of REACH, for the purpose of assessing and controlling emissions and air quality in the neighbourhood of Ni producers and downstream users. Two Derived No Effect Level (DNEL) values for chronic inhalation exposure to total Ni in PM10 (20 and 60ngNi/m(3)) were considered. The value of 20ngNi/m(3) is the current EU air quality guidance value. The value of 60ngNi/m(3) is derived here based on recently published Ni data (Oller et al., 2014). Both values are protective for respiratory toxicity and carcinogenicity but differ in the application of toxicokinetic adjustments and cancer threshold considerations. Estimates of air Ni concentrations at the European regional scale were derived from the database of the European Environment Agency. The 50th and 90th percentile regional exposures were below both DNEL values. To assess REACH compliance at the local scale, measured ambient air data are preferred but are often unavailable. A tiered approach for the use of modelled ambient air concentrations was developed, starting with the application of the default EUSES model and progressing to more sophisticated models. As an example, the tiered approach was applied to 33 EU Ni sulphate producers' and downstream users' sites. Applying the EUSES model demonstrates compliance with a DNEL of 60ngNi/m(3) for the majority of sites, while the value of the refined modelling is demonstrated when a DNEL of 20ngNi/m(3) is considered. The proposed approach, applicable to metals in general, can be used in the context of REACH, for refining the risk characterisation and guiding the selection of risk management measures.

Consideration of the bioavailability of metal/metalloid species in freshwaters: experiences regarding the implementation of biotic ligand model-based approaches in risk assessment frameworks.

After the scientific development of biotic ligand models (BLMs) in recent decades, these models are now considered suitable for implementation in regulatory risk assessment of metals in freshwater bodies. The BLM approach has been described in many peer-reviewed publications, and the original complex BLMs have been applied in prospective risk assessment reports for metals and metal compounds. BLMs are now also recommended as suitable concepts for the site-specific evaluation of monitoring data in the context of the European Water Framework Directive. However, the use is hampered by the data requirements for the original BLMs (about 10 water parameters). Recently, several user-friendly BLM-based bioavailability software tools for assessing the aquatic toxicity of relevant metals (mainly copper, nickel, and zinc) became available. These tools only need a basic set of commonly determined water parameters as input (i.e., pH, hardness, dissolved organic matter, and dissolved metal concentration). Such tools seem appropriate to foster the implementation of routine site-specific water quality assessments. This work aims to review the existing bioavailability-based regulatory approaches and the application of available BLM-based bioavailability tools for this purpose. Advantages and possible drawbacks of these tools (e.g., feasibility, boundaries of validity) are discussed, and recommendations for further implementation are given.

Water quality guidelines for chemicals: learning lessons to deliver meaningful environmental metrics.

Many jurisdictions around the globe have well-developed regulatory frameworks for the derivation and implementation of water quality guidelines (WQGs) or their equivalent (e.g. environmental quality standards, criteria, objectives or limits). However, a great many more still do not have such frameworks and are looking to introduce practical methods to manage chemical exposures in aquatic ecosystems. There is a potential opportunity for learning and sharing of data and information between experts from different jurisdictions in order to deliver efficient and effective methods to manage potential aquatic risks, including the considerable reduction in the need for aquatic toxicity testing and the rapid identification of common challenges. This paper reports the outputs of an international workshop with representatives from 14 countries held in Hong Kong in December 2011. The aim of the workshop and this paper was to identify 'good practice' in the development of WQGs to deliver to a range of environmental management goals. However, it is important to broaden this consideration to cover often overlooked facets of implementable WQGs, such as demonstrable field validation (i.e. does the WQG protect what it is supposed to?), fit for purpose of monitoring frameworks (often an on-going cost) and finally how are these monitoring data used to support management decisions in a manner that is transparent and understandable to stakeholders. It is clear that regulators and the regulated community have numerous pressures and constraints on their resources. Therefore, the final section of this paper addresses potential areas of collaboration and harmonisation. Such approaches could deliver a consistent foundation from which to assess potential chemical aquatic risks, including, for example, the adoption of bioavailability-based approaches for metals, whilst reducing administrative and technical burdens in jurisdictions.

Development and validation of a quantitative structure-activity relationship for chronic narcosis to fish.

Vertebrate testing under the European Union's regulation on Registration, Evaluation, Authorisation and Restriction of Chemical substances (REACH) is discouraged, and the use of alternative nontesting approaches such as quantitative structure-activity relationships (QSARs) is encouraged. However, robust QSARs predicting chronic ecotoxicity of organic compounds to fish are not available. The Ecological Structure Activity Relationships (ECOSAR) Class Program is a computerized predictive system that estimates the acute and chronic toxicity of organic compounds for several chemical classes based on their log octanol-water partition coefficient (K(OW)). For those chemical classes for which chronic training data sets are lacking, acute to chronic ratios are used to predict chronic toxicity to aquatic organisms. Although ECOSAR reaches a high score against the Organisation for Economic Co-operation and Development (OECD) principles for QSAR validation, the chronic QSARs in ECOSAR are not fully compliant with OECD criteria in the framework of REACH or CLP (classification, labeling, and packaging) regulation. The objective of the present study was to develop a chronic ecotoxicity QSAR for fish for compounds acting via nonpolar and polar narcosis. These QSARs were built using a database of quality screened toxicity values, considering only chronic exposure durations and relevant end points. After statistical multivariate diagnostic analysis, literature-based, mechanistically relevant descriptors were selected to develop a multivariate regression model. Finally, these QSARs were tested for their acceptance for regulatory purposes and were found to be compliant with the OECD principles for the validation of a QSAR.