Multiple linear regression models for predicting chronic aluminum toxicity to freshwater aquatic organisms and developing water quality guidelines

Prediction of freshwater ecotoxicological hazardous concentrations of major surfactants using the QSAR-ICE-SSD method

Synthetic surfactant products are continuously released into the aquatic environment in large quantities, posing a burden on ecosystems as a "pseudo-persistent" organic pollutant. Threshold derivation for protecting aquatic ecosystems is challenging due to the various homologous components of surfactants. In this study, five commercially available products were chosen as representative major types of surfactants. Corresponding quantitative structure-activity relationships (QSAR) were screened and subsequently combined with interspecific correlation estimation (ICE) to develop species sensitivity distributions (SSDs) for each component. Then, the 5th percentile hazard concentrations (HC5s) were calculated. The results indicated that the developed QSAR-ICE models demonstrated good toxicity prediction performance. The HC5 of each component showed a negatively correlation with alkyl chain length and a positive correlation with the amount of ethylene oxide. The HC5s of surfactants correlate with variations in their charged properties. Quaternary ammonium compounds (QAC) exhibited the lowest HC5s (8.5 ± 18.3 μg/L), followed by alcohol ethoxylates (AE), linear alkylbenzene sulfonates (LAS), and alcohol ethoxylated sulfates (AES); and alkyl oxide (AO) exhibited the highest HC5s (15784.2 ± 21552.6 μg/L). For cationic surfactants, the HC5s in the invertebrates were significantly lower than those in the fish; conversely, for anionic surfactants, the opposite was true, indicating a difference in the toxic mechanisms of surfactants with different charged properties across species taxa. Additionally, among invertebrates, shellfish demonstrated heightened sensitivity to surfactants, owing to their high accumulation and low metabolism of pollutants. Salmoniformes were the most sensitive among all species, indicating the necessity of prioritizing these species for aquatic ecological conservation in surfactant-contaminated waters.

Development and Validation of Multiple Linear Regression Models for Predicting Chronic Zinc Toxicity to Freshwater Microalgae

Multiple linear regression (MLR) models were developed for predicting chronic zinc toxicity to a freshwater microalga, Chlorella sp., using three toxicity-modifying factors (TMFs): pH, hardness, and dissolved organic carbon (DOC). The interactive effects between pH and hardness and between pH and DOC were also included. Models were developed at three different effect concentration (EC) levels: EC10, EC20, and EC50. Models were independently validated using six different zinc-spiked Australian natural waters with a range of water chemistries. Stepwise regression found hardness to be an influential TMF in model scenarios and was retained in all final models, while pH, DOC, and interactive terms had variable influence and were only retained in some models. Autovalidation and residual analysis of all models indicated that models generally predicted toxicity and that there was little bias based on individual TMFs. The MLR models, at all effect levels, performed poorly when predicting toxicity in the zinc-spiked natural waters during independent validation, with models consistently overpredicting toxicity. This overprediction may be from another unaccounted for TMF that may be present across all natural waters. Alternatively, this consistent overprediction questions the underlying assumption that models developed from synthetic laboratory test waters can be directly applied to natural water samples. Further research into the suitability of applying synthetic laboratory water-based models to a greater range of natural waters is needed. Environ Toxicol Chem 2023;42:2630-2641. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

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.

Water and sediment pollution of intensively used surface waters during a drought period - a case study in Central Northern Namibia

Semiarid regions are often affected by water scarcity and poor water quality. Seasonal changes in precipitation and drought events increase the pressure of use on water bodies and their pollution. In Central Northern Namibia, a high seasonal intra- and inter-annual variability of precipitation caused a 5-year lasting drought period. In the semiarid region, ephemeral channels and water pans represent the main water source, besides the institutionalized water supply. No systematic analysis of its quality has been conducted so far. The states of the surface waters at the end of the dry season in 2017 and the end of the rainy seasons in 2018 and 2019 were characterized by the analysis of physical-chemical parameters, focusing on usability. The first results show coarse contamination of the waters, which results in high turbidity values. Salt concentrations, such as Ca2+ and Na+, greatly increased due to evaporation. Al is present in high concentrations in solid and liquid phases, which indicates direct anthropogenic pollution. Spatial differences are evident in the study area and based on the precipitation gradient, land use, and population density. The waters cannot be used as drinking water without prior treatment.

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.

Outlet Liquid Material Concentration Prediction of an Evaporation Process Based on Knowledge and Data Information

The outlet liquid material concentration is a key production indicator to evaluate the evaporation quality and an important basis to adjust the evaporation operation parameters. However, the online concentration analyzer has strict installation conditions and high prices, and it is difficult to obtain the liquid material concentration in time. Usually, the field works perform imprecise operations according to the time delay information. In addition, the process data contain errors, which affects the accuracy and timeliness of process optimization and control. Therefore, a hybrid prediction model of concentration based on data reconciliation is presented in this paper. First, to obtain the high-quality process data, the data reconciliation method is applied for preprocessing. Moreover, the process mechanistic model is constructed by utilizing the process knowledge and the balance principle. Taking into account the volatility and nonlinearity characteristics, a data-driven model based on autoregressive integrated moving average integrated generalized autoregressive conditional heteroscedasticity is established, and then the support vector regression model is built for prediction residual optimization. Furthermore, the prediction results of the mechanistic model and the data-driven model are balanced comprehensively. Finally, an evaporation process is selected for simulation verification. The results demonstrate that the proposed hybrid prediction model has improved the prediction condition and performance.

General Challenges and Recommendations for the Water Quality Criteria of Endocrine Disrupting Chemicals (EDCs)

Water quality criteria (WQC) play an important role in the environmental management of pollutants in different countries or institutions. It has been found that endocrine disrupting chemicals (EDCs) can potentially alter functions of the endocrine system and consequently cause adverse effects in aquatic organisms. Therefore, the complicated modes of action and mechanisms of EDCs should be carefully considered in WQC studies. For example, the research regarding the WQC derivation of EDCs should prioritize sensitive aquatic species in consideration of the WQC derivation. Second, the chronic toxicity of EDCs should be of utmost concern. In addition, the appropriate effects and endpoints of EDCs should be carefully selected for the WQC derivation. Moreover, it was pointed out that some new methods should be taken into consideration in the WQC studies of EDCs in the near future.

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.

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.

Long-term exposure to environmentally relevant concentrations of ibuprofen and aluminum alters oxidative stress status on Danio rerio

Despite the ubiquitous presence of multiple pollutants in aqueous environments have been extensively demonstrated, the ecological impact of chemical cocktails has not been studied in depth. In recent years, environmental studies have mainly focused on the risk assessment of individual chemical substances neglecting the effects of complex mixtures even though it has been demonstrated that combined effects exerted by pollutants might represent a greater hazard to the biocenosis. The current study evaluates the effects on the oxidative stress status induced by individual forms and binary mixtures of ibuprofen (IBU) and aluminum (Al) on brain, gills, liver and gut tissues of Danio rerio after long-term exposure to environmentally relevant concentrations (0.1-11 μg L^-1 and 0.05 mg L^-1- 6 mg L^-1, respectively). Lipid peroxidation (LPO), Protein carbonyl content (PCC) and activity of Superoxide Dismutase (SOD), Catalase (CAT), and Glutathione Peroxidase (GPX) were evaluated. Moreover, concentrations of both toxicants and the metabolite 2-OH-IBU were quantified on test water and tissues. Results show that ibuprofen (IBU) and aluminum (Al) singly promote the production of radical species and alters the oxidative stress status in all evaluated tissues of zebrafish, nevertheless, higher effects were elicited by mixtures as different interactions take place.

Nickel and cadmium phytoextraction efficiencies of vetiver and lemongrass grown on Ni-Cd battery waste contaminated soil: A comparative study of linear and nonlinear models

A comparative assessment of the phytoremediation efficiency of two tolerant grass species viz. vetiver and lemongrass were performed in pots against simulated Ni-Cd battery electrolyte waste (EW) contaminated soil (EW1%, EW2% and EW4% w/w). Ni (μg g^-1) accumulation was higher in shoots (36.8) and roots (252.9) of vetiver than in lemongrass (12.5 and 79.7, respectively). While the same trend was true for Cd (μg g^-1) accumulation in vetiver and lemon grass roots (232.2 and 147.2, respectively), however, the accumulation in vetiver shoot (43.4) was less than in lemongrass (99.9). The bioaccumulation factor of metals in both grasses increased with EW contamination. Vetiver was tolerant towards EW toxicity than lemongrass, as it exhibited lesser decline in morphological parameters, lesser rise in TBARS against the doses of EW. The activities of SOD, APX, POD enzymes were higher in vetiver whereas, only GR in lemongrass. Multiple linear regression model show, pH had strong and positive influence over the Ni and Cd uptake by the plants whereas, phosphate, OM and bioavailable metals influenced negatively. The higher R² (>0.9) and Chi-square values ≤ 1 in sigmoid non-linear model demonstrates robustness of the model for predicting the Ni and Cd accumulation (M_HM) in both the grasses. Ni accumulation was higher than Cd, roots had greater accumulation of heavy metal and vetiver was a greater accumulator of Ni and Cd from EW the contaminated soil than lemongrass.

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.

Multivariate linear regression models for predicting metal content and sources in leafy vegetables and human health risk assessment in metal mining areas of Southern Jharkhand, India

The present study was intended to investigate the metal concentrations in the leafy vegetables, irrigation water, soil, and atmospheric dust deposition in the iron and copper mining areas of Southern Jharkhand, India. The study aimed to develop a multivariate linear regression (MVLR) model to predict the concentration of metals in leafy vegetables from the metals in associated environmental factors and assessment of the risk to the local population through the consumption of leafy vegetables and other allied pathways. The developed species-specific MVLR models were well fitted to predict the concentration of metals in the leafy vegetables. The coefficient of determination values (R²) was greater than 0.8 for all the species-specific models. Risk assessment was carried out considering multiple pathways of ingestion, inhalation, and dermal contact of vegetables, soil, water, and free-fall dust. Consumption of leafy vegetables was the major route of metal exposure to the local population in both the metal mining areas. The average hazard index (HI) value considering all the metals and pathways was calculated to be 5.13 and 12.1, respectively for iron and copper mining areas suggesting considerable risk to the local residents. Fe, As, and Cu were the major contributors to non-carcinogenic risk in the Iron mining areas while in the case of copper mining areas, the main contributors were Co, As, and Cu.

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.

Aluminum bioconcentration in female Nile tilapia Oreochromis niloticus (Perciformes: Cichlidae) and the effects on pituitary gonadotropins

In this study, we measured aluminum (Al) bioconcentration in the brain, ovaries, and liver of Oreochromis niloticus females, and analyzed the effects of exposure to Al and acidic pH on the gene expression of follicle-stimulating hormone (βfsh) and luteinizing hormone (βlh) in these animals. Mature females were divided into 4 groups, thus being maintained for 96 h in one of the following conditions: control at neutral pH (Ctr); Al at neutral pH (Al); acidic pH (Ac), and Al at acidic pH (Al-Ac). pH alone did not influence Al bioconcentration in the brain. The animals from the Al-Ac group bioconcentrated more Al in the ovaries than those from the Al group, while no differences were observed in the liver. Aluminum bioconcentration was higher in the brain than in the liver and ovaries in Al-exposed animals (Al and Al-Ac), and higher in the brain than in the ovaries in the Ctr and Ac groups. The liver bioconcentrates more Al than the ovaries in the females from the Ctr and Ac groups. Aluminum and/or acidic pH did not alter βfsh gene expression, while βlh gene expression decreased in females from the Al group. Aluminum acted as an endocrine disruptor, suggesting deleterious effects in reproduction that could result in ovulation failure. Aluminum can act directly and/or indirectly in the pituitary, affecting ovarian steroidogenesis and altering the reproductive endocrine axis of mature O. niloticus females in an acute period of exposure.

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.

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.

Overview of REACH: Issues Involved in the Registration of Metals

New European legislation known as REACH (Registration, Evaluation, Authorization and Restriction of Chemicals) was introduced in 2007 to increase the speed at which the health and/or environmental risks of industrial chemicals were being assessed and managed (REACH (EC) No 1907/2006). REACH consolidated earlier chemicals-control statutes and placed the burden of assessing, and identifying the means to manage risks on industry. This paper details the REACH process for controlling and managing hazardous chemicals and challenges encountered in applying the provisions of REACH and the guidance documents available from European Chemical Agency. Special attention is paid to challenges in evaluating potential health risks of metals such as aluminum and aluminum compounds. Lessons learned from over a decade of experience with REACH legislation are also noted.

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.

Development of Empirical Bioavailability Models for Metals

Recently, there has been renewed interest in the development and use of empirical models to predict metal bioavailability and derive protective values for aquatic life. However, there is considerable variability in the conceptual and statistical approaches with which these models have been developed. In the present study, we review case studies of empirical bioavailability model development, evaluating and making recommendations on key issues, including species selection, identifying toxicity-modifying factors (TMFs) and the appropriate environmental range of these factors, use of existing toxicity data sets and experimental design for developing new data sets, statistical considerations in deriving species-specific and pooled bioavailability models, and normalization of species sensitivity distributions using these models. We recommend that TMFs be identified from a combination of available chemical speciation and toxicity data and statistical evaluations of their relationships to toxicity. Experimental designs for new toxicity data must be sufficiently robust to detect nonlinear responses to TMFs and should encompass a large fraction (e.g., 90%) of the TMF range. Model development should involve a rigorous use of both visual plotting and statistical techniques to evaluate data fit. When data allow, we recommend using a simple linear model structure and developing pooled models rather than retaining multiple taxa-specific models. We conclude that empirical bioavailability models often have similar predictive capabilities compared to mechanistic models and can provide a relatively simple, transparent tool for predicting the effects of TMFs on metal bioavailability to achieve desired environmental management goals. Environ Toxicol Chem 2019;39:85-100. © 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.

Total Recoverable Aluminum: Not Totally Relevant for Water Quality Standards

A large water quality data set, representing more than 100 surface-water locations sampled from 2007 to 2017 in the Los Alamos area of New Mexico, USA's Pajarito Plateau, was assembled to evaluate Al concentrations in unfiltered and filtered samples. Aluminum concentrations often exceeded United States Environmental Protection Agency (USEPA) and New Mexico ambient water quality criteria (AWQC), regardless of filter size and sample location. However, AWQC are based on laboratory toxicity studies using soluble Al salts and do not reflect natural conditions in Pajarito Plateau surface waters. The plateau is predominately covered by glassy and recrystallized volcanic ashes (e.g., Bandelier Tuff) containing colloidal to sand-sized aluminosilicates. Samples from natural background drainages and areas downstream of developed regions exhibited similar Al concentrations, suggesting that AWQC exceedances are caused by naturally elevated Al concentrations. Solubility calculations indicated that most samples were oversaturated with respect to amorphous Al(OH)₃ (s). Therefore, AWQC exceedances are likely artifacts of the "total recoverable" sample preparation, which includes acidification and partial digestion, thereby liberating nonbioavailable Al from aluminosilicates. Accordingly, Al concentrations were strongly associated with suspended sediment concentrations (SSCs), implying that aluminosilicates in suspended sediment contributed to AWQC exceedances and Al oversaturation. Solid-phase particle characterization, using X-ray diffraction (XRD) and scanning electron microscopy with electron dispersive spectroscopy (SEM/EDS) did not identify potentially bioavailable amorphous Al(OH)₃ (s) in any sample tested. Thus, current sample collection and analysis protocols should not be used to evaluate attainment of Al AWQC on the Pajarito Plateau or locations where aluminosilicates are substantial contributors to total recoverable Al. A sample preparation method (e.g., pH 4 extraction) capable of differentiating nonbioavailable and bioavailable forms of Al is recommended. Otherwise, current New Mexico and USEPA sample preparation approaches will continue to generate artifactual AWQC exceedances in surface waters that contain aluminosilicates. Integr Environ Assess Manag 2019;00:1-14. © 2019 SETAC.

Toxicity of Aluminum to Ceriodaphnia dubia in Low-Hardness Waters as Affected by Natural Dissolved Organic Matter

We conducted a series of 7-d toxicity tests with Ceriodaphnia dubia in dilutions of low-hardness natural waters, which contained dissolved organic carbon (DOC) concentrations up to 10 mg/L. Stream waters were mixed with well water to achieve 2 target hardness levels (20 and 35 mg/L) and 4 DOC concentrations. Tests with aluminum (Al)-spiked waters were conducted in a controlled CO₂ atmosphere to maintain the pH at a range of 6.0 to 6.5. The results were used to estimate effect concentrations for survival and reproduction, expressed as total (unfiltered) Al concentrations. There were small differences in total-Al thresholds between waters with 20 and 35 mg/L hardness, but effect concentrations for C. dubia survival (median lethal concentrations) and reproduction (effect concentrations, 20%) increased log-linearly with increasing DOC concentrations in the range, 0.3 to 6 mg/L. Slopes of these regressions were similar to slopes from data used to revise the US Environmental Protection Agency water quality criterion for Al, but toxic effects in the present study occurred at total-Al concentrations 8- to 10-fold greater than toxicity values used for criteria development. This difference probably reflects the long equilibration (aging) times of Al test waters used in the present study (up to 192 h) compared with short (3-h) equilibration times in other studies used for criteria development. These results confirm the importance of DOC as a control on Al toxicity in low-hardness waters, but they also demonstrate that total-Al concentrations are not predictive of Al toxicity, except under defined water quality (pH, hardness, DOC) and exposure conditions (e.g., aging of test waters). Environ Toxicol Chem 2019;38:2121-2127. Published 2019 Wiley Periodicals, Inc. on behalf of SETAC. This article is a US government work, and as such, is in the public domain in the United States of America.

How Specific Is Site-Specific? A Review and Guidance for Selecting and Evaluating Approaches for Deriving Local Water Quality Benchmarks

Existing prescriptive guidance on the derivation of local water quality benchmarks (WQBs; e.g., guideline values, criteria, standards) for protecting aquatic ecosystems is limited to only 3 to 4 specific approaches. These approaches do not represent the full suite available for deriving local WQBs for multiple types of water quality-related issues. The general lack of guidance is inconsistent with the need for, and benefits of, local WQBs, and can constrain the appropriate selection and subsequent evaluation of derivation approaches. Consequently, the defensibility of local WQBs may not be commensurate with the nature of the issues for which they are derived. Moreover, where local WQBs are incorporated into regulatory requirements, the lack of guidance presents a potential risk to the derivation of appropriate WQBs and the achievement of desired environmental outcomes. This review addresses the deficiency in guidance by 1) defining local WQBs and outlining initial considerations for deciding if one is required; 2) summarizing the existing regulatory context; 3) summarizing existing guidance and identifying gaps; 4) describing strengths, weaknesses, and potential applications of a range of derivation approaches based on laboratory and/or field data; and 5) presenting a conceptual framework for appropriately selecting and evaluating a derivation approach to best suit the need. The guidance incorporates an existing set of guiding principles for deriving local WQBs and reinforces an existing categorization of site-adapted and site-specific WQBs. The conceptual framework recognizes the need to strike an appropriate balance between effort and ecological risk and, thus, embeds the concept of fit-for-purpose by considering both the significance of the issue being assessed and the extent to which the approach provides confidence that the ecosystem will be appropriately protected. The guidance can be used by industry, regulators, and others for both the a priori selection and the post hoc evaluation of appropriate approaches for deriving local WQBs. Integr Environ Assess Manag 2019;15:683-702. © 2019 The Authors.

Determination of Bioavailable Aluminum in Natural Waters in the Presence of Suspended Solids

Analyses of natural waters frequently show elevated levels of total aluminum (Al) attributable to acid extraction of Al from the total suspended solids (TSS) minerals. Hence, there is a need for an analytical method that measures only bioavailable Al. Natural waters high in TSS were collected to study the chronic effects of Al on Ceriodaphnia dubia. In the collected waters TSS ranged from 30 to 411 mg/L; total Al concentrations ranged from 2.0 to 44.8 mg/L. The TSS in natural waters inhibited reproduction of C. dubia up to 40% in comparison to the same filtered waters. This inhibition did not correlate with the concentration of TSS or total Al; it was attributed to nutritional deficiency and was prevented by increasing the food supply. To demonstrate that toxicity can be measured in natural waters, samples with elevated TSS were spiked with soluble Al, and survival and reproduction were measured in chronic studies performed at pH 6.3 and 8.0. To properly characterize the Al concentrations in the toxicity studies, a method was needed that could discriminate bioavailable Al from mineral forms of Al. An extraction method at pH 4 for bioavailable Al was developed and evaluated using C. dubia chronic toxicity studies in the presence of TSS. It is concluded that the proposed method is better able to discriminate chronic toxicity effects attributable to bioavailable Al from mineralized nontoxic forms of Al compared with existing methods using total or total recoverable Al (i.e., extraction at pH ≤ 1.5). We propose that this new method be used when assessing the potential for Al in natural surface waters to cause toxicity. Environ Toxicol Chem 2019;38:1668-1681. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Heavy metal uptake by water lettuce (Pistia stratiotes L.) from paper mill effluent (PME): experimental and prediction modeling studies

The present paper reports the heavy metal uptake by water lettuce (Pistia stratiotes L.) from paper mill effluent (PME) with its prediction modeling studies. Lab scale phytoremediation experiments were performed in glass aquariums to grow P. stratiotes in 0% (bore well water as a control), 25%, 50%, 75%, and 100% concentrations of PME. The influence of pH and heavy metal concentration in PME for the effective uptake and accumulation of heavy metal contents (∆Y: mg/kg) in plant tissues was modeled using two-factor multiple linear regression. The results showed that the selected input variables were supportive to develop prediction models with higher linear regression (R² > 0.72), high model efficiency (ME: 0.92-0.99), low mean average normalizing error (MANE < 0.02), and statistically significant F > Prob values. Kruskal-Wallis one-way post hoc test indicated that the contents of Cd, Cu, Fe, Pb, and Zn in the roots, leaves, and whole plant were affected by PME concentration while the contents of Mn did not. The correlation studies showed that the bioaccumulation of heavy metals was found both element and PME concentration specific. This work represents an effective method to model heavy metal uptake by P. stratiotes from PME. Furthermore, this methodology can also be adopted for predicting effective metal uptake by plant species being used for the phytoremediation of heavy metals from industrial effluents.

Determination and Prediction of Zinc Speciation in Estuaries

Lowering of the estuarine Environmental Quality Standard for zinc in the UK to 121 nM reflects rising concern regarding zinc in ecosystems and is driving the need to better understand its fate and behavior and to develop and parametrize speciation models to predict the metal species present. For the first time, an extensive data set has been gathered for the speciation of zinc within an estuarine system with supporting physicochemical characterization, in particular dissolved organic carbon. WHAM/Model VII and Visual MINTEQ speciation models were used to simulate zinc speciation, using a combination of measured complexation variables and available defaults. Data for the five estuarine transects from freshwater to seawater endmembers showed very variable patterns of zinc speciation depending on river flows, seasons, and potential variations in metal and ligand inputs from in situ and ex situ sources. There were no clear relationships between free zinc ion concentration [Zn²⁺] and measured variables such as DOC concentration, humic and biological indices. Simulations of [Zn²⁺] carried out with both models at high salinities or by inputting site specific complexation capacities were successful, but overestimated [Zn²⁺] in low salinity waters, probably owing to an underestimation of the complexation strength of the ligands present. Uncertainties in predicted [Zn²⁺] are consistently smaller than standard deviations of the measured values, suggesting that the accuracy of the measurements is more critical than model uncertainty in evaluating the predictions.

Evaluating the effects of pH, hardness, and dissolved organic carbon on the toxicity of aluminum to freshwater aquatic organisms under circumneutral conditions

Although it is well known that increasing water hardness and dissolved organic carbon (DOC) concentrations mitigate the toxicity of aluminum (Al) to freshwater organisms in acidic water (i.e., pH < 6), these effects are less well characterized in natural waters at circumneutral pHs for which most aquatic life regulatory protection criteria apply (i.e., pH 6-8). The evaluation of Al toxicity under varying pH conditions may also be confounded by the presence of Al hydroxides and freshly precipitated Al in newly prepared test solutions. Aging and filtration of test solutions were found to greatly reduce toxicity, suggesting that toxicity from transient forms of Al could be minimized and that precipitated Al hydroxides contribute significantly to Al toxicity under circumneutral conditions, rather than dissolved or monomeric forms. Increasing pH, hardness, and DOC were found to have a protective effect against Al toxicity for fish (Pimephales promelas) and invertebrates (Ceriodaphnia dubia, Daphnia magna). For algae (Pseudokirchneriella subcapitata), the protective effects of increased hardness were only apparent at pH 6, less so at pH 7, and at pH 8, increased hardness appeared to increase the sensitivity of algae to Al. The results support the need for water quality-based aquatic life protection criteria for Al, rather than fixed value criteria, as being a more accurate predictor of Al toxicity in natural waters. Environ Toxicol Chem 2018;37:49-60. © 2017 SETAC.

Chronic toxicity of aluminum, at a pH of 6, to freshwater organisms: Empirical data for the development of international regulatory standards/criteria

The chemistry, bioavailability, and toxicity of aluminum (Al) in the aquatic environment are complex and affected by a wide range of water quality characteristics (including pH, hardness, and dissolved organic carbon). Data gaps in Al ecotoxicology exist for pH ranges representative of natural surface waters (pH 6-8). To address these gaps, a series of chronic toxicity tests were performed at pH 6 with 8 freshwater species, including 2 fish (Pimephales promelas and Danio rerio), an oligochaete (Aeolosoma sp.), a rotifer (Brachionus calyciflorus), a snail (Lymnaea stagnalis), an amphipod (Hyalella azteca), a midge (Chironomus riparius), and an aquatic plant (Lemna minor). The 10% effect concentrations (EC10s) ranged from 98 μg total Al/L for D. rerio to 2175 μg total Al/L for L. minor. From these data and additional published data, species-sensitivity distributions (SSDs) were developed to derive concentrations protective of 95% of tested species (i.e., 50% lower confidence limit of a 5th percentile hazard concentration [HC5-50]). A generic HC5-50 (not adjusted for bioavailability) of 74.4 μg total Al/L was estimated using the SSD. An Al-specific biotic ligand model (BLM) was used to develop SSDs normalized for bioavailability based on site-specific water quality characteristics. Normalized HC5-50s ranged from 93.7 to 534 μg total Al/L for waters representing a range of European ecoregions, whereas a chronic HC5 calculated using US Environmental Protection Agency aquatic life criteria methods (i.e., a continuous criterion concentration [CCC]) was 125 μg total Al/L when normalized to Lake Superior water in the United States. The HC5-50 and CCC values for site-specific waters other than those in the present study can be obtained using the Al BLM. Environ Toxicol Chem 2018;37:36-48. © 2017 SETAC.

Acute and chronic toxicity of aluminum to a unionid mussel (Lampsilis siliquoidea) and an amphipod (Hyalella azteca) in water-only exposures

The US Environmental Protection Agency (USEPA) is reviewing the protectiveness of the national ambient water quality criteria (WQC) for aluminum (Al) and compiling a toxicity data set to update the WQC. Freshwater mussels are one of the most imperiled groups of animals in the world, but little is known about their sensitivity to Al. The objective of the present study was to evaluate acute 96-h and chronic 28-d toxicity of Al to a unionid mussel (Lampsilis siliquoidea) and a commonly tested amphipod (Hyalella azteca) at a pH of 6 and water hardness of 100 mg/L as CaCO₃ . The acute 50% effect concentration (EC50) for survival of both species was >6200 μg total Al/L. The EC50 was greater than all acute values in the USEPA acute Al data set for freshwater species at a pH range of 5.0 to <6.5 and hardness normalized to 100 mg/L, indicating that the mussel and amphipod were insensitive to Al in acute exposures. The chronic 20% effect concentration (EC20) based on dry weight was 163 μg total Al/L for the mussel and 409 μg total Al/L for the amphipod. Addition of the EC20s to the USEPA chronic Al data set for pH 5.0 to <6.5 would rank the mussel (L. siliquoidea) as the fourth most sensitive species and the amphipod (H. azteca) as the fifth most sensitive species, indicating the 2 species were sensitive to Al in chronic exposures. The USEPA-proposed acute and chronic WQC for Al would adequately protect the mussel and amphipod tested; however, inclusion of the chronic data from the present study and recalculation of the chronic criterion would likely lower the proposed chronic criterion. Environ Toxicol Chem 2018;37:61-69. Published 2017 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.