Biotic Ligand Model Research Articles

Gypsum soil amendment in metal-polluted soils—an added environmental hazard

Scientists around the world have long been searching for effective strategies to reduce the bioavailability of metals in contaminated soils. In case of metal-spiked soils, some studies have proposed gypsum as a soil amendment to alleviate metal phytotoxicity. However, for real field-collected soils, evidence on the efficacy of gypsum as a metal phytotoxicity amendment is limited. Therefore, the present study was designed to examine the effect of gypsum on plant growth in soils polluted by a copper smelter. We grew perennial ryegrass on untreated and gypsum-treated soils (at a dose of 3% by weight) under laboratory conditions. We found that gypsum had no effect on alleviating metal phytotoxicity in our soils. We also demonstrated – for the first time – that gypsum increased the concentrations of soluble metals in the soil, enhancing metal uptake by plants. The calcium ions from gypsum displace metals in the soil exchangeable complex; however, the metals do not get immobilized in soils because gypsum is a neutral salt. While our results contrast with the Terrestrial Biotic Ligand Model, that Model has never been tested on real industrially polluted soils but only on metal-spiked soils. Our main conclusion is that gypsum is ineffective in alleviating metal phytotoxicity in real industrially polluted soils and, moreover, its use is inappropriate as a soil remediation method, because it increases the environmental hazard rather than reducing it. Our study is the very first attempt to recognize that gypsum is a hazardous material when used to ameliorate soils polluted by metals.

Comparative Performance of Multiple Linear Regression and Biotic Ligand Models for Estimating the Bioavailability of Copper in Freshwater.

An increasing number of metal bioavailability models are available for use in setting regulations and conducting risk assessments in aquatic systems. Selection of the most appropriate model is dependent on the user's needs but will always benefit from an objective, comparative assessment of the performance of available models. In 2017, an expert workshop developed procedures for assessing metal bioavailability models. The present study applies these procedures to evaluate the performance of biotic ligand models (BLMs) and multiple linear regression (MLR) models for copper. We find that the procedures recommended by the expert workshop generally provide a robust series of metrics for evaluating model performance. However, we recommend some modifications to the analysis of model residuals because the current method is insensitive to relatively large differences in residual patterns when comparing models. We also provide clarification on details of the evaluation procedure which, if not applied correctly, could mischaracterize model performance. We found that acute Cu MLR and BLM performances are quite comparable, though there are differences in performance on a species‐specific basis and in the resulting water quality criteria as a function of water chemistry. In contrast, the chronic Cu MLR performed distinctly better than the BLM. Observed differences in performance are due to the smaller effects of hardness and pH on chronic Cu toxicity compared to acute Cu toxicity. These differences are captured in the chronic MLR model but not the chronic BLM, which only adjusts for differences in organism sensitivity. In general, we continue to recommend concurrent development of both modeling approaches because they provide useful comparative insights into the strengths, limitations, and predictive capabilities of each model. Environ Toxicol Chem 2021;40:1649–1661. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Complexation reduces nickel toxicity to purple sea urchin embryos (Strongylocentrotus purpuratus), a test of biotic ligand principles in seawater

The potential for Ni toxicity in seawater is of concern because of mining and processing activities in coastal regions. Determining Ni speciation is vital to understanding and predicting Ni toxicity and for bioavailability-based nickel risk assessment. The goal of this study was to characterize the complexation of Ni in relation to toxicity using embryological development of purple sea urchin (S. purpuratus). It was predicted that free ion [Ni2+] would be a better predictor of toxicity than total dissolved Ni concentrations (NiD). Synthetic ligands with known logKf values (Ethylenediaminetetraacetic acid (EDTA), Nitrilotriacetic acid (NTA), tryptophan (TRP), glutamic acid (GA), histidine (HD), and citric acid (CA)) were used to test the assumptions of the biotic ligand model (BLM) for Ni in seawater. [NiD] was measured by graphite furnace atomic absorption spectroscopy (GFAAS) and Ni2+ was first quantified using the ion-exchange technique (IET) and then concentrations were measured by GFAAS; [Ni2+] was also estimated using aquatic geochemistry modelling software (Visual Minteq). The mean EC50 values for [NiD] in unmodified artificial seawater control was 3.6 µM (95% CI 3.0–4.5) [211 µg/L 95% CI 176–264] and the addition of ligands provided protection, up to 6.5-fold higher [NiD] EC50 for EDTA. Compared to the control, measured EC50 values based on total dissolved nickel were higher in the presence of ligands. As predicted by BLM theory, [Ni2+] was a better predictor of Ni toxicity with 17% variability in EDTA and CA media while there was 72% variability in the prediction of Ni toxicity with total dissolved Ni. The results of this research provide support for the application of BLM- based prediction models for estimating Ni impacts in seawater.

Derivation of acute copper biotic ligand model-based predicted no-effect concentrations and acute-chronic ratio.

The copper biotic ligand model (BLM) can quantitatively describe the bioavailability depending on various environmental factors and has been used to derive the predicted no-effect concentrations (PNECs). The commonly employed acute BLM tool, HydroQual, which applies the biotic ligand constants of fathead minnow in the same model structure for all taxonomic groups, estimates lower acute copper toxicity values compared to the chronic copper PNECs of the European Union Risk Assessment Reports (EU-RAR), which are based on taxon-specific model structures and biotic ligand constants for vertebrates, invertebrates, and algae. In this study, the full-BLM approach was applied using an appropriate acute BLM for each taxonomic group to derive acute HC5s (fifth percentile value in the species sensitivity distribution [SSD]) and an acute-chronic ratio for copper. Two acute BLMs for vertebrates and invertebrates were used and validated against site waters using the new method to estimate the intrinsic sensitivity for each species across different environmental conditions. To derive acute copper full BLM-based HC5s in Korean freshwater, acute toxicity tests were performed with 10 indigenous species, which were used to build the acute BLM-based SSD at each site. The final estimated acute full-BLM HC5s were higher than the EU-RAR chronic PNECs within the BLM calibration range. Furthermore, a linear relationship was observed between the acute full-BLM HC5s and the EU-RAR chronic PNECs. This linear regression function was suggested as an acute to chronic transformation function that can be applied to calculate chronic PNEC values. In conclusion, if the chronic ecotoxicity database of indigenous aquatic organisms for copper is lacking, it may be more efficient to derive chronic PNECs using an acute-chronic ratio after deriving BLM-based acute copper SSDs for indigenous species within representative taxonomic groups. This study provides a scientific foundation for the derivation of water quality criteria for copper in freshwater.

Evaluation of measured dissolved and bio-met predicted bioavailable Cu, Ni and Zn concentrations in runoff from three urban catchments

Urban runoff is a diffuse source of pollution contributing to the poor ecological and chemical status of surface waters. Whilst the EU Priority Hazardous Substances Directive now identifies environmental quality standards for selected metals in relation to the bioavailable metal fraction the relationship between analytically determined metal size fractions transported by urban runoff and the often variably defined concept of bioavailability has not been thoroughly evaluated. This paper provides a review of the terminology used within urban runoff studies to characterise metal fractions and behaviour. Measured dissolved and truly dissolved (determined by ultrafiltration; <3000 molecular weight cutoff) Cu, Ni, and Zn concentrations are also compared to the bioavailable metal fraction (as predicted using Bio-met, a simplified biotic ligand model) in snowmelt and rainfall derived runoff samples from three urban catchments. The study shows that predicted bioavailable concentrations were significantly lower than truly dissolved concentrations for all metals and discusses current bioavailability modelling parameters in relation to rainfall and snowmelt runoff data sets. Statistical analysis of relationships between field and predicted bioavailable data sets indicate that the bioavailable fractions originate from both colloidal and truly dissolved fractions.

Proton Competition and Free Ion Activities Drive Cadmium, Copper, and Nickel Accumulation in River Biofilms in a Nordic Ecosystem

Biofilms can be used as a biomonitoring tool to determine metal bioavailability in streams affected by mining and other anthropogenic activities. Surface water and biofilm were sampled over two years from rivers located in the vicinity of a mine located in a Nordic ecosystem (Nunavik, Quebec). Biofilm metal content (Cd, Cu, and Ni) as well as a variety of physicochemical properties were determined to examine relationships between metal accumulation and water quality. Among the three metals of interest, copper and nickel had the highest levels of accumulation and cadmium had the lowest. When considering the exposure levels, nickel was the most abundant metal in our sampling sites. Both exposure and accumulation levels were consistent over time. Biofilm metal content was highly correlated to the ambient free metal ion concentration for sites of circumneutral pHs for all three metals. When the surface water pH was below 6, biofilm metal content was much lower than at other sites with similar aqueous metal concentrations of exposure. This apparent protective effect of decreasing pH can be explained by proton competition with dissolved metals for uptake binding sites at the surface of the organisms within the biofilm as described by the Biotic Ligand Model principles. The relationships obtained for Cd and Cu were overlapping those observed in previous publications, indicating strong similarities in metal accumulation processes in biofilms over very large geographical areas. Although more data are needed for Ni, our results show that biofilms represent a promising metal biomonitoring tool.

Competition Among Trivalent Elements (Al, Eu, Fe, Gd, Nd, Tm, and Y) for Uptake in Algae and Applicability of the Biotic Ligand Model.

Rare earth elements (REE) are essential in many new technologies. While anthropogenic dispersion of REE into the environment are expected in the future, their biogeochemical fate and interactions at biological interfaces are still largely unexplored. Due to their chemical nature (generally trivalent and hard metals), REE can potentially compete among themselves or with other ubiquitous trivalent metals for uptake sites at the surface of aquatic organisms. In the current study, the bioavailability and uptake of gadolinium (Gd) was assessed in the green alga, Chlamydomonas reinhardtii, while in the presence of various trivalent elements (Al, Eu, Fe, Nd, Tm, and Y). In the absence of competitors, Gd uptake was well described by a Michaelis-Menten equation with an affinity constant (KGd) of 107.1 and a maximum internalization flux (Jmax) of 1.95 ± 0.09 × 10-2amolµm-2min-1. Neither Al(III) nor Fe(III) had notable effects on Gd uptake in the conditions tested; however, Gd uptake was reduced with increasing concentrations of other REE. These had binding constants with uptake sites very similar to that of Gd (KNd, Y, Tm, Eu = 107.0). Our results suggest that the different REE likely share common transport sites and that the biotic ligand model (BLM) can be used to predict their uptake.

Empirical Bioavailability Corrections for Nickel in Freshwaters for Australia and New Zealand Water Quality Guideline Development.

Bioavailability-based approaches have been developed for the regulation of metals in freshwaters in several countries. Empirical multiple linear regression (MLR) models have been developed for nickel that can be applied to aquatic organisms. The MLR models have been compared against the use of previously developed biotic ligand models (BLMs) for the normalization of an ecotoxicity dataset compiled for the derivation of a water quality guideline value that could be applied in Australia and New Zealand. The MLR models were developed from data for a number of specific species and were validated independently to confirm their reliability. An MLR modeling approach using different models for algae, plants, invertebrates, and vertebrates performed better than either a pooled MLR model for all taxa or the BLMs, in terms of its ability to correctly predict the results of the tests in the ecotoxicity database based on their water chemistry and a fitted species-specific sensitivity parameter. The present study demonstrates that MLR approaches can be developed and validated to predict chronic nickel toxicity to freshwater ecosystems from existing datasets. The MLR approaches provide a viable alternative to the use of BLMs for taking account of nickel bioavailability in freshwaters for regulatory purposes. Environ Toxicol Chem 2021;40:113-126. © 2020 SETAC.

Application of Bioavailability Models to Derive Chronic Guideline Values for Nickel in Freshwaters of Australia and New Zealand.

There has been an increased emphasis on incorporating bioavailability‐based approaches into freshwater guideline value derivations for metals in the Australian and New Zealand water quality guidelines. Four bioavailability models were compared: the existing European biotic ligand model (European Union BLM) and a softwater BLM, together with 2 newly developed multiple linear regressions (MLRs)—a trophic level‐specific MLR and a pooled MLR. Each of the 4 models was used to normalize a nickel ecotoxicity dataset (combined tropical and temperate data) to an index condition of pH 7.5, 6 mg Ca/L, 4 mg Mg/L, (i.e., approximately 30 mg CaCO3/L hardness), and 0.5 mg DOC/L. The trophic level‐specific MLR outperformed the other 3 models, with 79% of the predicted 10% effect concentration (EC10) values within a factor of 2 of the observed EC10 values. All 4 models gave similar normalized species sensitivity distributions and similar estimates of protective concentrations (PCs). Based on the index condition water chemistry proposed as the basis of the national guideline value, a protective concentration for 95% of species (PC95) of 3 µg Ni/L was derived. This guideline value can be adjusted up and down to account for site‐specific water chemistries. Predictions of PC95 values for 20 different typical water chemistries for Australia and New Zealand varied by >40‐fold, which confirmed that correction for nickel bioavailability is critical for the derivation of site‐specific guideline values. Environ Toxicol Chem 2021;40:100–112. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Demonstrating the Reliability of bio-met for Determining Compliance with Environmental Quality Standards for Metals in Europe.

The importance of considering the bioavailability of metals in understanding and assessing their toxicity in freshwaters has been recognized for many years. Currently, biotic ligand models (BLMs) are being applied for the derivation and implementation of environmental quality standards (EQS) for metals under the Water Framework Directive in Europe. bio-met is a simplified tool that was developed for implementing bioavailability-based EQS for metals in European freshwaters. We demonstrate the reliability of the relationship between the full BLM predictions and the thresholds (hazardous concentration affecting 5% of species [HC5] values) predicted by bio-met in 3 stages, for the metals copper, nickel, and zinc. First, ecotoxicity data for specific species from laboratory tests in natural waters are compared with predictions by the individual species BLMs included in the full BLMs. Second, the site-specific HC5 values predicted by bio-met for the natural waters used for ecotoxicity testing are compared with those provided by the full BLMs. The reliability of both relationships is demonstrated for all 3 metals, with more than 80% of individual species BLM predictions being within a factor of 3 of the experimental results, and 99% of bio-met local HC5 predictions being within a factor of 2 of the full BLM result. Third, using a larger set of European natural waters in addition demonstrates the reliability of bio-met over a broad range of water chemistry conditions. bio-met is therefore an appropriate tool for performing compliance assessments against EQS values in Europe, due to the demonstrated consistency with the toxicity test data. Environ Toxicol Chem 2020;39:2361-2377. © 2020 SETAC.

Modeling of selenite toxicity to wheat root elongation using biotic ligand model: Considering the effects of pH and phosphate anion.

It has not been well understood that the binding affinity and potential toxicity of different chemical forms of selenite (Se(IV)), which are predominant forms of selenium with plant availability. The influences of pH and major anions on Se(IV) toxicity to wheat root elongation were determined in solutions and modeled based on the biotic ligand model (BLM) and free ion activity model (FIAM) concepts. Results showed that EC50[Se(IV)]T values increased from 164 to 273μM as the pH raised from 4.5 to 8.0, indicating the increase of pH induced weakened Se(IV) toxicity. The EC50{SeO32-} values increased from 0.019 to 71.3μM while the EC50{H2SeO3} values sharply decreased from 2.08μM to 0.760nM with the pH increasing from 4.5 to 8.0. The effect of pH on Se(IV) toxicity could be explained by the changes of Se(IV) species in different pH solutions as H2SeO3, HSeO3- and SeO32- were differently toxic to wheat root elongation. The toxicity of Se(IV) decreased with increasing H2PO4- activity but not for SO42-, NO3- and Cl- activities, indicating that only H2PO4- had a competitive effect with Se(IV) on the binding sites. A site-specific BLM was developed to count in effects of pH and H2PO4-, and stability constants of H2SeO3, HSeO3-, SeO32- and H2PO4- to the binding sites were obtained: log [Formula: see text] =4.96, log [Formula: see text] =3.47, log [Formula: see text] =2.56 and log [Formula: see text] =2.00. Results implied that BLM performed much better than FIAM in the wheat root elongation prediction when coupling toxic species H2SeO3, HSeO3-, SeO32-, and the competitions of H2PO4- for the binding sites while developing the Se(IV)-BLM.

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.

Making the Biotic Ligand Model kinetic, easier to develop, and more flexible for deriving water quality criteria

In aquatic environments, the ecological risks posed by metals are greatly affected by water chemistry, thereby creating challenges for water quality management. Biotic ligand models (BLMs) have become the most widely used tools to interpret and predict water chemistry effects. Traditional BLM development methods require a large number of toxicity tests and organisms, and model predictions are limited to certain toxicity statistics (e.g., 48-h median effective concentration, 48-h EC50), to which the models were calibrated. To address these limitations, we propose a new method to develop BLMs by integrating them into the toxicokinetic-toxicodynamic (TK-TD) framework. Metal bioaccumulation was predicted from metal exposure and water chemistry using the BLM-type toxicokinetics, whilst metal toxicity was predicted from metal bioaccumulation using the toxicodynamics. Using the new method, we developed a kinetic BLM of cadmium for Daphnia magna with only six toxicity tests and 1540 daphnids; this represents a 60−80% reduction compared to the traditional methods. The model was validated in the presence of commercial dissolved organic matter (DOM) and in natural waters sampled from 12 lakes. The kinetic BLM was able to accurately simulate the protective effects of the commercial DOM by employing the Stockholm humic model, whilst the complexation capabilities of some natural DOM were overestimated. We further used the model to predict Cd EC50 and no-effect concentrations for different waters, generating predictions close to the effect concentrations reported in the literature. Overall, our method requires fewer resources and presents an easier approach to develop BLMs; the kinetic BLM is more flexible and can serve as a useful tool for developing water quality criteria.

Predicting Risks of Cadmium Toxicity in Salinity-Fluctuating Estuarine Waters Using the Toxicokinetic–Toxicodynamic Model

In estuaries, salinity fluctuates rapidly and continuously, greatly affecting the bioavailability and thus toxicity of contaminants, especially metals, causing difficulties in deriving site-specific water quality criteria. We developed a method for predicting the toxicity of the metal cadmium (Cd) in estuarine waters of any salinity fluctuation scenario. Cd bioaccumulation and toxicity were measured in an estuarine clam Potamocorbula laevis under stable salinities (salinity = 5, 15, 25) and fluctuating salinities (5-25), using the toxicokinetic-toxicodynamic (TK-TD) framework. Cd bioaccumulation decreases with increasing salinity; whereas intrinsic Cd sensitivity of organisms reaches the minimum at an intermediate salinity around 20. At each specific Cd level, interpolating TK-TD parameters measured at the stable salinities well predicts the Cd bioaccumulation and toxicity under fluctuating salinities. To extend the model for various Cd levels, the biotic ligand model (BLM) was integrated into the TK-TD framework. The BLM-based TK-TD model was successfully applied to scenarios of simulated and monitored salinity fluctuations in estuarine waters, for which the median lethal concentrations and no-effect concentrations (2.0-3.1 μg L-1) of Cd were derived. Overall, we integrated the BLM and TK-TD models and provided a useful tool for predicting metal risks and deriving criteria values for salinity-fluctuating estuarine waters.

Extension of a biotic ligand model for predicting the toxicity of metalloid selenate to wheat: The effects of pH, phosphate and sulphate

It has not been well understood that the influences of pH and accompanying anions on the toxicity of selenate (Se(VI)). The influences of pH and major anions on Se(VI) toxicity to wheat root elongation were determined and modeled based on the biotic ligand model (BLM) and free ion activity model (FIAM) concepts. Results showed that EC50[Se(VI)]T values increased from 162 to 251 μM as the pH values increased from 4.5 to 8.0, indicating that the pH increases alleviated the Se(VI) toxicity. The EC50{SeO42−} values increased from 133 to 203 μM while the EC50{HSeO4−} values sharply decreased from 210 to 0.102 nM with the pH increasing from 4.5 to 8.0. The effect of pH on Se(VI) toxicity could be explained by the changes of Se(VI) species in different pH solutions as SeO42− and HSeO4−were differently toxic to wheat root elongation. The toxicity of Se(VI) decreased with the increasing activities of H2PO4− and SO42− but not for NO3− and Cl− activities, indicating that only H2PO4− and SO42− had competitive effects with Se(VI) on the binding sites. An extended BLM was developed to consider effects of pH, phosphate and sulphate, and stability constants of SeO42−, HSeO4−, H2PO4− and SO42− to the binding sites were obtained: logKSeO4BL = 3.45, logKHSeO4BL = 5.98, logKH2PO4BL = 2.05, logKSO4BL = 1.85. Results implied that BLM performed much better than FIAM in the wheat root elongation prediction when coupling with toxic species SeO42− and HSeO4−, and the competitions of H2PO4− and SO42− for the binding sites while developing the Se(VI)-BLM.

Bioavailability and phytotoxicity of rare earth metals to Triticum aestivum under various exposure scenarios

It is a daunting challenge to predict toxicity and accumulation of rare earth metals (REMs) in different exposure scenarios (e.g., varying water chemistry and metal combinations). Herein, we investigated the toxicity and uptake of La and Ce in the presence of various levels of Ca, Mg, Na, K, and at different pH values, as well as the combined effects of La and Ce in wheat Triticum aestivum. Major cations (Ca2+ and Mg2+) significantly mitigated the toxicity and accumulation of La3+/Ce3+. Toxicity and uptake of La, Ce, and La–Ce mixtures could be well quantified by the multi-metal biotic ligand model (BLM) and by the Langmuir-type uptake model with the consideration of the competitive effects of Ca2+ and Mg2+, with more than 85.1% of variations explained. The derived binding constants of Ca, Mg, La, and Ce to wheat root were respectively 3.87, 3.59, 6.97, and 6.48 on the basis of toxicity data, and 3.23, 2.84, 6.07, and 5.27 on the basis of uptake data. The use of the alternative WHAM-Ftox approach, requiring fewer model parameters than the BLM but with similar Akaike information criterion (AIC) values, successfully predicted the toxicity and accumulation of La/Ce as well as toxicity of La–Ce mixtures, with at least 76.4% of variations explained. However, caution should be taken when using this approach to explain the uptake of La–Ce mixtures. Our results provided promising tools for delineating REMs toxicity/uptake in the presence of other toxicity-modifying factors or in mixture scenarios.

Predicting the combined toxicity of binary metal mixtures (Cu–Ni and Zn–Ni) to wheat

In order to investigate and model toxicity and interactions between metals in mixtures, inhibition of wheat root elongation in response to additions of single-metals of copper (Cu), zinc (Zn), and nickel (Ni) and of binary mixed-metal combinations of Cu–Ni and Zn–Ni was tested, using water culture experiments under different Mg concentrations and pH values. A biotic ligand model (BLM) of single-metal Cu, Zn, and Ni was established. The results showed that the toxicity of Cu, Zn or Ni in isolation decreased with increasing Mg concentration whereas the effects of pH on Cu, Zn, or Ni toxicity were related not only to free Cu2+, Zn2+, and Ni2+ concentrations, but also to inorganic metal complexes. In binary mixtures, the two metals in the Cu–Ni mixture showed a weakly antagonistic effect, whereas the two metals in the Zn–Ni mixture showed greater antagonism. Using data from single-metal Cu, Zn, and Ni BLMs, combined with the toxicity index and the overall amounts of metal ions bound to the biotic ligands, one simple model was developed. This model consisted of the toxic unit (TUM, no competition included) and two extended BLMs, BLM-TUf (f as a function of TU, including competition between Mg2+ and metal ions) and BLM-fmix (including the competition between Mg2+ and metal ions, as well as between free metal ions). They were then used to predict the joint toxicity of Cu–Ni and Zn–Ni binary mixtures to wheat. Both of the extended BLMs could provide more accurate predictions of toxic effects of Cu–Ni and Zn–Ni than TUM. BLM-fmix performed best for the Zn–Ni binary mixture (r2 = 0.93; root-mean-square error, RMSE = 9.87). On the other hand, for the Cu–Ni mixture, the predictive effect based on BLM-TUf (r2 = 0.93; RMSE = 9.60) was similar to that of BLM-fmix (r2 = 0.93; RMSE = 9.56). The results provide a theoretical basis for the evaluation and remediation of soils contaminated with mixtures of heavy metals.

Deriving a bioavailability-based zinc environmental quality standard for France.

National Environmental Quality Standards (EQS) for zinc used for the assessment of ecological status in freshwaters have been shown to vary by over two orders of magnitude across 25 European countries. Such variability is unlikely to reflect consistent ecological protection or environmental relevance. Recent European technical guidance on EQS derivation gives an opportunity to derive protective metrics for zinc that are relevant to national water chemistry conditions. To derive a zinc EQS relevant to national water chemistry conditions and account for bioavailability, the new technical guidance requires high-quality spatial and temporal monitoring data. These data must be of water samples with concurrent measures of pH, dissolved organic carbon (DOC) and calcium, the parameters that most influence zinc bioavailability in freshwaters. A national bioavailability-based zinc EQS for France has been derived from Biotic Ligand Model calculations undertaken for freshwaters samples from 4645 sites (22,000 samples with concurrent measures of pH, DOC, calcium) in 96 regions. An EQS of 11.3 μg Zn L-1 was derived based on sensitive waters from the Bretagne region typically of circumneutral pH and relatively low DOC and low dissolved calcium. The least sensitive waters to zinc exposures in France are found in the Hauts-De-France, higher pH values than those in Bretagne, similar dissolved organic carbon and higher dissolved calcium. An indicative assessment of compliance showed that across France, 2% of the sites would exceed this bioavailability-based EQS.

Predicting copper toxicity in zebrafish larvae under complex water chemistry conditions by using a toxicokinetic–toxicodynamic model

Multiple water chemistry parameters influence metal toxicity in natural waters and accurate quantification of those influences may accelerate the development of site-specific water quality criteria (WQC) and further execute metal risk assessment for better protection of aquatic biota. Here, we investigated the effects of water chemistry parameters on copper (Cu) toxicity of larval zebrafish (Danio rerio) and then incorporated the effects of key parameters in a Toxicokinetic and Toxicodynamic (TK-TD) model. Further, the proposed TK-TD model was used to predict Cu toxicity in laboratory artificial waters as well as natural water samples. The predictive performance of the TK-TD model was evaluated in comparison to the biotic ligand model (BLM). The results showed that increasing Ca, Mg, pH, and fulvic acid (FA) levels significantly mitigated Cu toxicity in larvae, while K and Na levels had no significant effect on Cu toxicity. A predictive TK-TD model based on these data described 91 % of Cu accumulation and 87 % of survival of larvae exposed to Cu under 0, 2.5, 5, 10 mg/L FA. Compared with BLM, TK-TD model predicted better Cu accumulation and toxicity for an independent dataset in low DOC concentration (<10.95 mg L−1) of 9 sites in Haihe river (Tianjin, China) media during 96 h exposure. The BLM under-predicted the acute Cu toxicity to larvae when compared with observed values. In high DOC concentration (13.12–17.78 mg L−1) among three field sites, BLM and TK-TD model both under-predicted the acute Cu toxicity to larvae when compared with observed values. Our research provides a TK-TD approach for predicting Cu toxicity under complex water chemistry conditions and deriving Cu-WQC in different scenarios where there exist limits for using the BLM.

Lanthanum and Cerium Toxicity to the Freshwater Green Alga Chlorella fusca: Applicability of the Biotic Ligand Model.

The environmental risk assessment of rare earth elements (REEs) requires data on their potential toxicity. In the present study, the toxicity of lanthanum (La) and cerium (Ce) was studied in relation to metal speciation in solution. For both La and Ce, the use of organic ligands demonstrated that the calculated free ion concentration was a good indicator of toxicity. Whether in the absence or presence of organic ligands, when based on free ion concentrations, the obtained half-maximal effective concentrations were similar. When all generated data were pooled, Ce and La showed identical toxicity thresholds after 120 h of exposure with free ion concentration-based median effective concentration values (95% confidence intervals) of 0.48 (0.38-0.60) µM and 0.47 (0.36-0.61) µM for La3+ and Ce3+ , respectively. The inhibition of algal growth was also correlated with the intracellular lanthanide concentrations, regardless of the ligand used. Finally, increasing the ambient calcium concentration protected the test algae by reducing the amount of lanthanide internalized into the cells. These results suggest that, at constant pH (5.5), REE accumulation and toxicity are linked to the free ion concentration and ambient calcium concentration, as predicted by the biotic ligand model. Environ Toxicol Chem 2020;39:996-1005. © 2020 SETAC.