Development of Empirical Bioavailability Models for Metals

Applicability of Chronic Multiple Linear Regression Models for Predicting Zinc Toxicity in Australian and New Zealand Freshwaters

Bioavailability models, for example, multiple linear regressions (MLRs) of water quality parameters, are increasingly being used to develop bioavailability-based water quality criteria for metals. However, models developed for the Northern Hemisphere cannot be adopted for Australia and New Zealand without first validating them against local species and local water chemistry characteristics. We investigated the applicability of zinc chronic bioavailability models to predict toxicity in a range of uncontaminated natural waters in Australia and New Zealand. Water chemistry data were compiled to guide a selection of waters with different zinc toxicity-modifying factors. Predicted toxicities using several bioavailability models were compared with observed chronic toxicities for the green alga Raphidocelis subcapitata and the native cladocerans Ceriodaphnia cf. dubia and Daphnia thomsoni. The most sensitive species to zinc in five New Zealand freshwaters was R. subcapitata (72-h growth rate), with toxicity ameliorated by high dissolved organic carbon (DOC) or low pH, and hardness having a minimal influence. Zinc toxicity to D. thomsoni (reproduction) was ameliorated by both high DOC and hardness in these same waters. No single trophic level-specific effect concentration, 10% (EC10) MLR was the best predictor of chronic toxicity to the cladocerans, and MLRs based on EC10 values both over- and under-predicted zinc toxicity. The EC50 MLRs better predicted toxicities to both the Australian and New Zealand cladocerans to within a factor of 2 of the observed toxicities in most waters. These findings suggest that existing MLRs may be useful for normalizing local ecotoxicity data to derive water quality criteria for Australia and New Zealand. The final choice of models will depend on their predictive ability, level of protection, and ease of use. Environ Toxicol Chem 2023;42:2614-2629. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Bioavailability and Toxicity Models of Copper to Freshwater Life: The State of Regulatory Science

Efforts to incorporate bioavailability adjustments into regulatory water quality criteria in the United States have included four major procedures: hardness-based single-linear regression equations, water-effect ratios (WERs), biotic ligand models (BLMs), and multiple-linear regression models (MLRs) that use dissolved organic carbon, hardness, and pH. The performance of each with copper (Cu) is evaluated, emphasizing the relative performance of hardness-based versus MLR-based criteria equations. The WER approach was shown to be inherently highly biased. The hardness-based model is in widest use, and the MLR approach is the US Environmental Protection Agency's (USEPA's) present recommended approach for developing aquatic life criteria for metals. The performance of criteria versions was evaluated with numerous toxicity datasets that were independent of those used to develop the MLR models, including olfactory and behavioral toxicity, and field and ecosystem studies. Within the range of water conditions used to develop the Cu MLR criteria equations, the MLR performed well in terms of predicting toxicity and protecting sensitive species and ecosystems. In soft waters, the MLR outperformed both the BLM and hardness models. In atypical waters with pH <5.5 or >9, neither the MLR nor BLM predictions were reliable, suggesting that site-specific testing would be needed to determine reliable Cu criteria for such settings. The hardness-based criteria performed poorly with all toxicity datasets, showing no or weak ability to predict observed toxicity. In natural waters, MLR and BLM criteria versions were strongly correlated. In contrast, the hardness-criteria version was often out of phase with the MLR and, depending on waterbody and season, could be either strongly overprotective or underprotective. The MLR-based USEPA-style chronic criterion appears to be more generally protective of ecosystems than other models. Environ Toxicol Chem 2023;42:2529-2563. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

A Review of Mechanistic Models for Predicting Adverse Effects in Sediment Toxicity Testing

Since recognizing the importance of bioavailability for understanding the toxicity of chemicals in sediments, mechanistic modeling has advanced over the last 40 years by building better tools for estimating exposure and making predictions of probable adverse effects. Our review provides an up-to-date survey of the status of mechanistic modeling in contaminated sediment toxicity assessments. Relative to exposure, advances have been most substantial for non-ionic organic contaminants (NOCs) and divalent cationic metals, with several equilibrium partitioning-based (Eq-P) models having been developed. This has included the use of Abraham equations to estimate partition coefficients for environmental media. As a result of the complexity of their partitioning behavior, progress has been less substantial for ionic/polar organic contaminants. When the EqP-based estimates of exposure and bioavailability are combined with water-only effects measurements, predictions of sediment toxicity can be successfully made for NOCs and selected metals. Both species sensitivity distributions and toxicokinetic and toxicodynamic models are increasingly being applied to better predict contaminated sediment toxicity. Furthermore, for some classes of contaminants, such as polycyclic aromatic hydrocarbons, adverse effects can be modeled as mixtures, making the models useful in real-world applications, where contaminants seldomly occur individually. Despite the impressive advances in the development and application of mechanistic models to predict sediment toxicity, several critical research needs remain to be addressed. These needs and others represent the next frontier in the continuing development and application of mechanistic models for informing environmental scientists, managers, and decisions makers of the risks associated with contaminated sediments. Environ Toxicol Chem 2023;00:1-17. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Acute Toxicity of Copper to Three Species of Pacific Salmon Fry in Water with Low Hardness and Low Dissolved Organic Carbon

Proposed development of a mine within Alaska's Bristol Bay watershed (USA) has raised concerns about the potential impact of copper (Cu) on Pacific salmon (Oncorhynchus spp.). We conducted 96-h flow-through bioassays using low-hardness and low dissolved organic carbon water to determine the acute lethal toxicity of Cu to sockeye (Oncorhynchus nerka), Chinook (Oncorhynchus tshawytscha), and coho salmon (Oncorhynchus kisutch) fry. We aimed to determine Cu toxicity under field-relevant water quality conditions and to assess three methods of calculating ambient Cu criteria: the biotic ligand model (BLM), a multiple linear regression model endorsed by the US Environmental Protection Agency, and the hardness-based model currently used by the State of Alaska. The criteria generated by all models were below 20% lethal Cu concentrations by factors ranging from 2.2 to 54.3, indicating that all criteria would be protective against mortality. The multiple linear regression-based criteria were the most conservative and were comparable to BLM-based criteria. The median lethal concentrations (LC50s) for sockeye, Chinook, and coho were 35.2, 23.9, and 6.3 µg Cu/L, respectively. We also used the BLM to predict LC50s for each species. Model predictions differed from empirical LC50s by factors of 0.7 for sockeye and Chinook salmon, and 1.1 for coho salmon. These differences fell within the acceptable range of ±2, indicating the model's accuracy. We calculated critical lethal Cu accumulation values for each species to account for differing water chemistry in each bioassay; the present study revealed that coho salmon were most sensitive to Cu, followed by sockeye and Chinook salmon. Our findings underscore the importance of considering site- and species-specific factors when modeling Cu toxicity. The empirical data we present may enhance Cu risk assessments for Pacific salmon. Environ Toxicol Chem 2023;42:2440-2452. © 2023 SETAC.

Prediction models and major controlling factors of antibiotics bioavailability in hyporheic zone

Recently, antibiotics have been frequently detected in the hyporheic zone (HZ) as a novel contaminant. Bioavailability assessment has gradually attracted more attention in order to provide a more realistic assessment of human health risks. In this study, two typical antibiotics, oxytetracycline (OTC) and sulfamethoxazole (SMZ), were used as target pollutants in the HZ of the Zaohe-Weihe River, and the polar organics integrated sampler was used to analyze the variation of antibiotics bioavailability. According to the characteristics of the HZ, the total concentration of pollutants, pH, and dissolved oxygen (DO) were selected as major predictive factors to analyze their correlation with the antibiotics bioavailability. Then the predictive antibiotic bioavailability models were constructed by stepwise multiple linear regression method. The results showed that there was a highly significant negative correlation between OTC bioavailability and DO (P < 0.001), while SMZ bioavailability showed a highly significant negative correlation with total concentration of pollutants (P < 0.001) and a significant negative correlation with DO (P < 0.01). The results of correlation analysis were further verified by Principal Component Analysis. Based on the experimental data, we constructed eight prediction models for the bioavailability of two antibiotics and verified them. The data points of the six prediction models were distributed in the 95% prediction band, indicating that the models were more reliable and accurate. The prediction models in this study provide reference for the accurate ecological risk assessment of the bioavailability of pollutants in the HZ, and also provide a new idea for predicting the bioavailability of pollutants in practical applications.

Assessment of heavy metal pollution in Nigerian surface freshwaters and sediment: A meta-analysis using ecological and human health risk indices

Heavy metal pollution in surface freshwaters is prevalent globally and is an environmental issue of concern. Many studies have described sources, concentrations in selected waterbodies and toxic effects in biological systems. The purpose of the present study was to assess the status of heavy metal pollution in Nigerian surface freshwaters as well as the ecological and public health risks associated with current levels of pollution. A literature review of studies which assessed concentrations of heavy metals in named freshwater bodies around the country was done to gather relevant data. These waterbodies included rivers, lagoons, and creeks. The data gathered was subjected to a meta-analysis using referenced heavy metal pollution indices, sediment quality guidelines, ecological risk indices and non-carcinogenic and carcinogenic human health risk indices. The result obtained showed that concentrations of Cd, Cr, Mn, Ni and Pb in Nigerian surface freshwaters are higher than the maximum recommended levels in drinking water. The heavy metal pollution indices calculated using drinking water quality criteria by the World Health Organization and the US Environmental Protection Agency, were also significantly higher than the threshold value of 100 (13,672.74 and 1890.65 respectively). These results indicate that the surface waters are unsafe for drinking purposes. The enrichment factor, contamination factor and ecological risk factor indices for cadmium (684.62, 41.73 and 1251.90 respectively) were all higher than the maximum threshold for each index (40, 6, 320 respectively). These results indicate that cadmium contributes significantly to the ecological risk associated with pollution in Nigerian surface waters. In terms of public health risk, the current levels of heavy metal pollution in Nigerian surface waters pose both non-carcinogenic and carcinogenic risks to children and adults who are exposed through ingestion and dermal routes as shown by results from the present study. Nigeria is blessed with abundant surface freshwater resources and many coastal indigenous populations use the water resources for drinking and domestic purposes. Many of them are also commercial fish farmers earning their daily living from fisheries resources. Heavy metal pollution must be regulated to levels below which end users and aquatic life are protected from adverse impacts of pollution.

Development of Multiple Linear Regression Models for Predicting Chronic Iron Toxicity to Aquatic Organisms

We developed multiple linear regression (MLR) models for predicting iron (Fe) toxicity to aquatic organisms for use in deriving site-specific water quality guidelines (WQGs). The effects of dissolved organic carbon (DOC), hardness, and pH on Fe toxicity to three representative taxa (Ceriodaphnia dubia, Pimephales promelas, and Raphidocelis subcapitata) were evaluated. Both DOC and pH were identified as toxicity-modifying factors (TMFs) for P. promelas and R. subcapitata, whereas only DOC was a TMF for C. dubia. The MLR models based on effective concentration 10% and 20% values were developed and performed reasonably well, with adjusted R² of 0.68-0.89 across all species and statistical endpoints. Differences among species in the MLR models precluded development of a pooled model. Instead, the species-specific models were assumed to be representative of invertebrates, fish, and algae and were applied accordingly to normalize toxicity data. The species sensitivity distribution (SSD) included standard laboratory toxicity data and effects data from mesocosm experiments on aquatic insects, with aquatic insects being the predominant taxa in the lowest quartile of the SSD. Using the European Union approach for deriving WQGs, application of MLR models to this SSD resulted in WQGs ranging from 114 to 765 μg l^-1 Fe across the TMF conditions evaluated (DOC: 0.5-10 mg l^-1 ; pH: 6.0-8.4), with slightly higher WQGs (199-910 μg l^-1 ) derived using the US Environmental Protection Agency (USEPA) methodology. An important uncertainty in these derivations is the applicability of the C. dubia MLR model (no pH parameter) to aquatic insects, and understanding the pH sensitivity of aquatic insects to Fe toxicity is a research priority. An Excel-based tool for calculating Fe WQGs using both European Union and USEPA approaches across a range of TMF conditions is provided. Environ Toxicol Chem 2023;00:1-15. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Comparison of Multiple Linear Regression and Biotic Ligand Models for Predicting Acute and Chronic Zinc Toxicity to Freshwater Organisms

Multiple linear regression (MLR) models for predicting zinc (Zn) toxicity to freshwater organisms were developed based on three toxicity-modifying factors: dissolved organic carbon (DOC), hardness, and pH. Species-specific, stepwise MLR models were developed to predict acute Zn toxicity to four invertebrates and two fish, and chronic toxicity to three invertebrates, a fish, and a green alga. Stepwise regression analyses found that hardness had the most consistent influence on Zn toxicity among species, whereas DOC and pH had a variable influence. Pooled acute and chronic MLR models were also developed, and a k-fold cross-validation was used to evaluate the fit and predictive ability of the pooled MLR models. The pooled MLR models and an updated Zn biotic ligand model (BLM) performed similarly based on (1) R² , (2) the percentage of effect concentration (ECx) predictions within a factor of 2.0 of observed ECx, and (3) residuals of observed/predicted ECx versus observed ECx, DOC, hardness, and pH. Although fit of the pooled models to species-specific toxicity data differed among species, species-specific differences were consistent between the BLM and MLR models. Consistency in the performance of the two models across species indicates that additional terms, beyond DOC, hardness, and pH, included in the BLM do not help explain the differences among species. The pooled acute and chronic MLR models and BLM both performed better than the US Environmental Protection Agency's existing hardness-based model. We therefore conclude that both MLR models and the BLM provide an improvement over the existing hardness-only models and that either could be used for deriving ambient water quality criteria. Environ Toxicol Chem 2023;42:393-413. © 2022 SETAC.

A review of regulatory modeling frameworks supporting numeric water quality criteria development in the United States

The US Environmental Protection Agency (USEPA) has a long history of leveraging environmental models and integrated modeling frameworks to support the regulatory development of numeric ambient water quality criteria for the protection of aquatic life and human health. Primary modeling types include conceptual, mechanistic, and data-driven empirical models; Bayesian and probabilistic models; and risk-based modeling frameworks. These models and modeling frameworks differ in their applicability to and suitability for various water quality criteria objectives. They require varying knowledge of system processes and stressor-response relationships, data availability, and expertise of stakeholders. In addition, models can be distinguished by their ability to characterize variability and uncertainty. In this work, we review USEPA recommendations for model use in existing regulatory frameworks, technical support documents, and peer-reviewed literature. We characterize key attributes, identify knowledge gaps and opportunities for future research, and highlight where renewed USEPA guidance is needed to promote the development and use of models in numeric criteria derivation. These outcomes then inform a decision-based framework for determining model suitability under particular scenarios of available knowledge, data, and access to technical resources. Integr Environ Assess Manag 2023;19:191-201. © 2022 SETAC.

Predicting Metal Bioavailability and Risk of Toxicity in Nigerian Surface Waters: Are the Existing User-Friendly Bioavailability Tools Applicable?

In the present study, we assessed the use of existing user-friendly bioavailability tools to predict metal bioavailability and the risk of toxicity in a typical Nigerian surface water. The effect of prevailing water chemistry on toxicity of metals was also assessed in laboratory studies. Surface water samples were collected at four locations downstream in the Ogun River in Lagos State, and water chemistry analysis was carried out using standard methods. Relevant parameters were inputted into the Bio-Met software and Metal Bioavailability Assessment Tool (M-Bat), which are run on a Microsoft Excel spreadsheet, to obtain the site-specific hazardous concentrations affecting 5% of the population (HC5)/predicted-no-effect concentrations (PNECs) for selected metals and risk characterization ratios (RCRs) at locations downstream in the river. Assessments using the bioavailability tools showed that two locations, Owode-Onirin and Kara, were more sensitive to Zn and Pb inputs compared to the other locations. The RCRs for Cu, Zn, and Pb, respectively, were >1 at all locations, indicating a potential risk of toxicity to aquatic life. Results from laboratory studies conformed with predictions from the bioavailability tools because Zn and Pb were more toxic to aquatic organisms in surface water collected from Owode-Onirin and Kara locations, respectively, compared to toxicity in surface water from other locations. The issue of bioavailability in metal pollution control is widely accepted and has been incorporated into water quality guidelines (WQGs) in the United States, the United Kingdom, and Europe. In the absence of regulations incorporating bioavailability in developing countries including Nigeria, it is essential to assess the applicability of existing methods incorporating bioavailability to surface waters in this region. Findings from such studies will facilitate the development of region-specific WQGs for metals which will be protective of locally relevant aquatic life. Environ Toxicol Chem 2022;41:2537-2547. © 2022 SETAC.

The influence of hardness at varying pH on zinc toxicity and lability to a freshwater microalga, Chlorella sp

Zinc is an essential element for aquatic organisms, however, activities such as mining and refining, as well as zinc's ubiquitous role in modern society can contribute to elevated environmental concentrations of zinc. Water hardness is widely accepted as an important toxicity modifying factor for metals in aquatic systems, though other factors such as pH are also important. This study investigated the influence of increasing water hardness, at three different pH values (6.7, 7.6 and 8.3), on the chronic toxicity of zinc to the growth rate of a microalgae, Chlorella sp. Zinc toxicity decreased with increasing hardness from 5 to 93 mg CaCO₃ L^-1 at all three pH values tested. The 72 h growth rate inhibition EC50 values ranged from 6.2 μg Zn L^-1 (at 5 mg CaCO₃ L^-1, pH 8.3) to 184 μg Zn L^-1 (at 92 mg CaCO₃ L^-1, pH 6.7). Increases in hardness from 93 to 402 mg CaCO₃ L^-1 generally resulted in no significant (p > 0.05) reduction in zinc toxicity. DGT-labile zinc measurements did not correspond with the observed changes in zinc toxicity as hardness was varied within a pH treatment. This suggests that cationic competition from increased hardness is decreasing zinc toxicity, rather than changes in metal lability. This study highlighted that current hardness algorithms used in water quality guidelines may not be sufficiently protective of sensitive species, such as Chlorella sp., in high hardness waters.

Stream Mesocosm Experiments Show no Protective Effects of Calcium on Copper Toxicity to Macroinvertebrates

Although the concept and modeling of metal bioavailability and toxicity have been well developed based largely on laboratory experiments with standard test species, additional evidence is required to demonstrate their applicability for macroinvertebrates typically found in natural lotic ecosystems. We conducted 10-day stream mesocosm experiments to test the hypothesis that increased water hardness (in the present study, the calcium [Ca] concentration was increased by adding CaCl₂ ) would mitigate the effects of copper (Cu) on natural benthic macroinvertebrate communities. Exposure of macroinvertebrate communities to 25 μg/L Cu for 10 days in stream mesocosm experiments resulted in significant decreases in total abundance, in number of taxa, and in abundance of many macroinvertebrate taxa. However, the addition of Ca to stream mesocosms and the associated increase in water hardness up to 250 mg/L CaCO₃ did not mitigate these effects of Cu on macroinvertebrate communities. The results showed that the hardness-based water quality criteria for Cu of the US Environmental Protection Agency were not protective under the conditions of relatively high hardness, low alkalinity, and circumneutral pH. In contrast, the water quality criteria based on the biotic ligand model predicted little protective effects of Ca on Cu toxicity, which is consistent with our results. Additional experiments are required to understand the influence of modifying factors on the toxicity of metals to macroinvertebrate communities. Environ Toxicol Chem 2022;41:1304-1310. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Development of Fluoride Protective Values for Aquatic Life Using Empirical Bioavailability Models

The derivation of protective values for aquatic life can be enhanced by the development and use of bioavailability models. Recent advances to metals bioavailability modeling are applicable to other analyte groups and should be widely considered. We conducted a meta-analysis of the available aquatic toxicity literature for fluoride to evaluate the utility of hardness, alkalinity, and chloride as toxicity-modifying factors (TMFs) in empirical bioavailability models of freshwater taxa. The resulting optimal multiple linear regression model predicting acute fluoride toxicity to the invertebrate Hyalella azteca included all three TMFs (observed vs. predicted 50% lethal concentrations, R²  = 0.88) and the optimal model predicting toxicity to the fish Oncorhynchus mykiss included alkalinity and hardness (R²  = 0.37). At >20 mg/L chloride, the preliminary final acute values for fluoride were within 1 order of magnitude and ranged from approximately 18.1 to 56.3 mg/L, depending on water chemistry. Sensitivity of H. azteca to low-chloride conditions increased model uncertainty when chloride was <20 mg/L. Because of limited toxicity data, chronic bioavailability models were not developed, and final chronic values were derived using an acute-to-chronic ratio (ACR) approach. Accounting for TMFs, the geometric mean ACR was 5.4 for fish and invertebrate taxa (n = 6). The present assessment highlights the need to expand bioavailability modeling to include inorganic anions, particularly fluoride, and demonstrates that existing promulgated protective values for fluoride are likely overly conservative. More toxicological studies are recommended to further refine multivariate empirical bioavailability models for inorganic anions. Environ Toxicol Chem 2022;41:396-409. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Modeling the Bioavailability of Nickel and Zinc to Ceriodaphnia dubia and Neocloeon triangulifer in Toxicity Tests with Natural Waters

We studied biotic ligand model (BLM) predictions of the toxicity of nickel (Ni) and zinc (Zn) in natural waters from Illinois and Minnesota, USA, which had combinations of pH, hardness, and dissolved organic carbon (DOC) more extreme than 99.7% of waters in a nationwide database. We conducted 7-day chronic tests with Ceriodaphnia dubia and 96-hour acute and 14-day chronic tests with Neocloeon triangulifer and estimated median lethal concentrations and 20% effect concentrations for both species. Toxicity of Ni and Zn to both species differed among test waters by factors from 8 (Zn tests with C. dubia) to 35 (Zn tests with N. triangulifer). For both species and metals, tests with Minnesota waters (low pH and hardness, high DOC) showed lower toxicity than Illinois waters (high pH and high hardness, low DOC). Recalibration of the Ni BLM to be more responsive to pH-related changes improved predictions of Ni toxicity, especially for C. dubia. For the Zn BLM, we compared several input data scenarios, which generally had minor effects on model performance scores (MPS). A scenario that included inputs of modeled dissolved inorganic carbon and measured Al and Fe(III) produced the highest MPS values for tests with both C. dubia and N. triangulifer. Overall, the BLM framework successfully modeled variation in toxicity for both Zn and Ni across wide ranges of water chemistry in tests with both standard and novel test organisms. Environ Toxicol Chem 2021;40:3049-3062. © 2021 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

The Influence of pH on Zinc Lability and Toxicity to a Tropical Freshwater Microalga

Increased focus on the development and application of bioavailability-based metal water quality guideline values requires increased understanding of the influence of water chemistry on metal bioavailability and toxicity. Development of empirical models, such as multiple linear regression models, requires the assessment of the influence of individual water quality parameters as toxicity-modifying factors. The present study investigated the effect of pH on the lability and toxicity of zinc (Zn) to a tropical green microalga (Chlorella sp.). Zinc speciation and lability were explored using the Windermere Humic Aqueous Model (WHAM7), ultrafiltration, and diffusive gradients in thin films (DGT). Zinc toxicity increased significantly with increasing pH from 6.7 to 8.3, with 50% growth inhibition effect concentrations decreasing from 185 to 53 µg l^-1 across the pH range. Linear relationships between DGT-labile Zn and dissolved Zn did not vary across the tested pH range, nor did the linear relationship between dissolved (<0.45 µm) and ultrafiltered (<3 kDa) Zn. Our findings show that Zn toxicity to this freshwater alga is altered as a function of pH across environmentally realistic pH ranges and that these toxicity changes could not be explained by Zn speciation and lability as measured by DGT and WHAM7. Environ Toxicol Chem 2021;40:2836-2845. © 2021 SETAC.

Deriving Human Health and Aquatic Life Water Quality Criteria in the United States for Bioaccumulative Substances: A Historical Review and Future Perspective

Methods used to derive water quality regulations for persistent, bioaccumulative, and toxic substances (PBTs) in the United States have evolved substantially over the past 50 yr, leveraging current understandings and assumptions about the nature and magnitude of partitioning and accumulation of substances in water, sediments, and organisms. In the United States and across the world, environmental regulations continue to evolve into more refined water quality criteria protective of aquatic life and human health. The present review provides historical context on the establishment of aquatic life and human health water quality criteria in the United States by compiling information from regulatory agencies and peer-reviewed literature on methods used to characterize and quantify bioaccumulation of substances in aquatic organisms and humans. Primary data needs and assumptions for various methods, as well as their application in setting criteria by the US Environmental Protection Agency over the past half century, are highlighted. Our review offers an important retrospective on the data and methods used to derive water quality criteria for PBTs and provides commentary on the future of US criteria development. Environ Toxicol Chem 2021;40:2394-2405. © 2021 SETAC.

Comparison of Multiple Linear Regression and Biotic Ligand Models to Predict the Toxicity of Nickel to Aquatic Freshwater Organisms

Toxicity-modifying factors can be modeled either empirically with linear regression models or mechanistically, such as with the biotic ligand model (BLM). The primary factors affecting the toxicity of nickel to aquatic organisms are hardness, dissolved organic carbon (DOC), and pH. Interactions between these terms were also considered. The present study develops multiple linear regressions (MLRs) with stepwise regression for 5 organisms in acute exposures, 4 organisms in chronic exposures, and pooled models for acute, chronic, and all data and compares the performance of the Pooled All MLR model to the performance of the BLM. Independent validation data were used for evaluating model performance, which for pooled models included data for organisms and endpoints not present in the calibration data set. Hardness and DOC were most often selected as the explanatory variables in the MLR models. An attempt was also made at evaluating the uncertainty of the predictions for each model; predictions that showed the most error tended to show the highest levels of uncertainty as well. The performances of the 2 models were largely equal, with differences becoming more apparent when looking at the performance within subsets of the data. Environ Toxicol Chem 2021;40:2189-2205. © 2021 SETAC.

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.

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.

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.

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.

Updated Multiple Linear Regression Models for Predicting Chronic Aluminum Toxicity to Freshwater Aquatic Organisms and Developing Water Quality Guidelines

Multiple linear regression (MLR) models for predicting chronic aluminum toxicity to a cladoceran (Ceriodaphnia dubia) and a fish (Pimephales promelas) as a function of 3 toxicity-modifying factors (TMFs)-dissolved organic carbon (DOC), pH, and hardness-have been published previously. However, the range over which data for these TMFs were available was somewhat limited. To address this limitation, additional chronic toxicity tests with these species were subsequently conducted to expand the DOC range up to 12 mg/L, the pH range up to 8.7, and the hardness range up to 428 mg/L. The additional toxicity data were used to update the chronic MLR models. The adjusted R² for the C. dubia 20% effect concentration (EC20) model increased from 0.71 to 0.92 with the additional toxicity data, and the predicted R² increased from 0.57 to 0.89. For P. promelas, the adjusted R² increased from 0.87 to 0.92 and the predicted R² increased from 0.72 to 0.87. The high predicted R² relative to the adjusted R² indicates that the models for both species are not overly parameterized. When data for C. dubia and P. promelas were pooled, the adjusted R² values were comparable to the species-specific models (0.90 and 0.88 for C. dubia and P. promelas, respectively). This indicates that chronic aluminum EC20s for C. dubia and P. promelas respond similarly to variation in DOC, pH, and hardness. Overall, the pooled model predicted EC20s that were within a factor of 2 of observed in 100% of the C. dubia tests and 94% of the P. promelas tests. Environ Toxicol Chem 2020;39:1724-1736. © 2020 SETAC.

Multiple Linear Regression Modeling Predicts the Effects of Surface Water Chemistry on Acute Vanadium Toxicity to Model Freshwater Organisms

Multiple linear regression (MLR) modeling has been successfully used to predict how water chemistry variables influence the toxicity of cationic metals to aquatic organisms, but no MLR model exists for vanadium (V). Recent research has indicated that an increase in pH (from 6 to 9), or high concentrations of sodium (473 mg Na⁺ /L), increase V toxicity to Daphnia pulex. In contrast, increases in alkalinity (>100 mg as CaCO₃ ) and sulfate (>100 mg SO₄^2- /L) reduce V toxicity. How these variables influence V toxicity to Oncorhynchus mykiss (rainbow trout) was still unknown. Our results show that increasing pH from 6.2 to 8.9 tended to decrease the 96-h median lethal concentration (LC50) for V toxicity to O. mykiss by 9.6 mg V/L. An alkalinity increase from 71 to 330 mg/L as CaCO₃ tended to increase the 96-h LC50 by 3.3 mg V/L, whereas when SO₄^2- rose from 150 to 250 mg/L, the LC50 significantly increased by 0.3 mg V/L followed by a significant decrease of 1 mg V/L when SO₄^2- was >250 mg/L. Sodium (between 100 and 336 mg/L) showed no effect on V toxicity to O. mykiss. The toxicity patterns for O. mykiss were similar to those observed for D. pulex, except for that of SO₄^2- , potentially indicating different mechanisms of V uptake or regulation in the 2 species. The LC50s and associated water chemistry were combined to develop an MLR model for O. mykiss and D. pulex. Alkalinity and pH modified V toxicity to both species, whereas SO₄^2- influenced V toxicity to D. pulex. Overall, MLR models should be considered for creating new local benchmarks or water quality guidelines for V. Environ Toxicol Chem 2020;39:1737-1745. © 2020 SETAC.

Bioavailability Assessment of Metals in Freshwater Environments: A Historical Review

Many metals (aluminum, cadmium, cobalt, copper, nickel, lead, zinc) are widely studied environmental contaminants because of their ubiquity, potential toxicity to aquatic life, and tendency for toxicity to vary widely as a function of water chemistry. The interactions between metal and water chemistry influence metal "bioavailability," an index of the rate and extent to which the metal reaches the site of toxic action. The implications of metal bioavailability for ecological risk assessment are large, with as much as a 100-fold variability across a range of water chemistries in surface waters. Beginning as early as the 1930s, considerable research effort was expended toward documenting and understanding metal bioavailability as a function of total and dissolved metal, water hardness, natural organic matter, pH, and other water characteristics. The understanding of these factors and improvements in both analytical and computational chemistry led to the development of modeling approaches intended to describe and predict the relationship between water chemistry and metal toxicity, including the free ion activity model, the gill surface interaction model, the biotic ligand model, and additional derivatives and regression models that arose from similar knowledge. The arc of these scientific advances can also be traced through the evolution of the US Environmental Protection Agency's ambient water quality criteria over the last 50 yr, from guidance in the "Green Book" (1968) to metal-specific criteria produced in the last decade. Through time, water quality criteria in many jurisdictions have incorporated increasingly sophisticated means of addressing metal bioavailability. The present review discusses the history of scientific understanding of metal bioavailability and the development and application of models to incorporate this knowledge into regulatory practice. Environ Toxicol Chem 2019;39:48-59. © 2019 SETAC.

Metal Bioavailability Models: Current Status, Lessons Learned, Considerations for Regulatory Use, and the Path Forward

Since the early 2000s, biotic ligand models and related constructs have been a dominant paradigm for risk assessment of aqueous metals in the environment. We critically review 1) the evidence for the mechanistic approach underlying metal bioavailability models; 2) considerations for the use and refinement of bioavailability-based toxicity models; 3) considerations for the incorporation of metal bioavailability models into environmental quality standards; and 4) some consensus recommendations for developing or applying metal bioavailability models. We note that models developed to date have been particularly challenged to accurately incorporate pH effects because they are unique with multiple possible mechanisms. As such, we doubt it is ever appropriate to lump algae/plant and animal bioavailability models; however, it is often reasonable to lump bioavailability models for animals, although aquatic insects may be an exception. Other recommendations include that data generated for model development should consider equilibrium conditions in exposure designs, including food items in combined waterborne-dietary matched chronic exposures. Some potentially important toxicity-modifying factors are currently not represented in bioavailability models and have received insufficient attention in toxicity testing. Temperature is probably of foremost importance; phosphate is likely important in plant and algae models. Acclimation may result in predictions that err on the side of protection. Striking a balance between comprehensive, mechanistically sound models and simplified approaches is a challenge. If empirical bioavailability tools such as multiple-linear regression models and look-up tables are employed in criteria, they should always be informed qualitatively and quantitatively by mechanistic models. If bioavailability models are to be used in environmental regulation, ongoing support and availability for use of the models in the public domain are essential. Environ Toxicol Chem 2019;39:60-84. © 2019 SETAC.

State of the Science on Metal Bioavailability Modeling: Introduction to the Outcome of a Society of Environmental Toxicology and Chemistry Technical Workshop

A Society of Environmental Toxicology and Chemistry technical workshop was held in December 2017 to critically evaluate the current state of the science of metal bioavailability modeling. The availability of mechanistic models such as the biotic ligand model and the rapid development of empirical models such as multiple linear regressions means that choices are available in terms of bioavailability normalization approaches that can be used in metal risk assessments and the development of risk-based protective values for aquatic life. A key goal of the workshop was to provide potential users of metal bioavailability models with the information required to make appropriate decisions when choosing among mechanistic and empirical models. Workshop participants focused on the state of the science of metal bioavailability modeling, mechanistic and empirical model frameworks, validation of bioavailability models, and application of bioavailability models in risk-based decision-making approaches. The output of this workshop provides the necessary scientific information to incorporate bioavailability normalization in regulations pertaining to metals in freshwater systems. Environ Toxicol Chem 2019;39:42-47. © 2019 SETAC.

Validation of Bioavailability-Based Toxicity Models for Metals

Regulatory jurisdictions worldwide are increasingly incorporating bioavailability-based toxicity models into development of protective values (PVALs) for freshwater and saltwater aquatic life (e.g., water quality criteria, standards, and/or guidelines) for metals. Use of such models for regulatory purposes should be contingent on their ability to meet performance criteria as specified through a model-validation process. Model validation generally involves an assessment of a model's appropriateness, relevance, and accuracy. We review existing guidance for validation of bioavailability-based toxicity models, recommend questions that should be addressed in model-validation studies, discuss model study type and design considerations, present several new ways to evaluate model performance in validation studies, and suggest a framework for use of model validation in PVAL development. We conclude that model validation should be rigorous but flexible enough to fit the user's purpose. Although a model can never be fully validated to a level of zero uncertainty, it can be sufficiently validated to fit a specific purpose. Therefore, support (or lack of support) for a model should be presented in such a way that users can choose their own level of acceptability. We recommend that models be validated using experimental designs and endpoints consistent with the data sets that were used to parameterize and calibrate the model and validated across a broad range of geographically and ecologically relevant water types. Environ Toxicol Chem 2019;39:101-117. © 2019 SETAC.

Best Practices for Derivation and Application of Thresholds for Metals Using Bioavailability-Based Approaches

The primary goal of the present study is to provide a broad view of best practices for evaluating bioavailability models for metals for use in the protection of aquatic life. We describe the state of the science regarding 1) the evaluation and selection of ecotoxicity data, 2) the selection of bioavailability models for use in normalization, and 3) subsequent application of bioavailability models. Although many examples of normalization steps exist worldwide, a scheme is proposed to evaluate and select a model that takes account of its representativeness (water chemistry and taxonomic coverage of the ecotoxicity data set) and validation performance. Important considerations for a suitable model are the quantity of inputs needed, accuracy, and ease of use, all of which are needed to set protective values for aquatic life and to use these values to evaluate potential risks to organisms in receiving waters. Although the end results of different model application approaches may be broadly similar, the differences in these application frameworks ultimately come down to a series of trade-offs between who needs to collect the data and use the bioavailability model, the different requirements of spatial scales involved (e.g., regional vs site-specific values), and model predictiveness and protectiveness. Ultimately, understanding the limits and consequences of these trade-offs allows for selection of the most appropriate model and application framework to best provide the intended levels of aquatic life protection. Environ Toxicol Chem 2019;39:118-130. © 2019 SETAC.