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

Recommended updates to the USEPA Framework for Metals Risk Assessment: Aquatic ecosystems

In 2007, the USEPA issued its "Framework for Metals Risk Assessment." The framework provides technical guidance to risk assessors and regulators when performing human health and environmental risk assessments of metals. This article focuses on advances in the science including assessing bioavailability in aquatic ecosystems, short- and long-term fate of metals in aquatic ecosystems, and advances in risk assessment of metals in sediments. Notable advances have occurred in the development of bioavailability models for assessing toxicity as a function of water chemistry in freshwater ecosystems. The biotic ligand model (BLM), the multiple linear regression model, and multimetal BLM now exist for most of the common mono- and divalent metals. Species sensitivity distributions for many metals exist, making it possible for many jurisdictions to develop or update their water quality criteria or guidelines. The understanding of the fate of metals in the environment has undergone significant scrutiny over the past 20 years. Transport and toxicity models have evolved including the Unit World Model allowing for estimation of concentrations of metals in various compartments as a function of loading and time. There has been significant focus on the transformation of metals in sediments into forms that are less bioavailable and on understanding conditions that result in resolubilization or redistribution of metals in and from sediments. Methods for spiking sediments have advanced such that the resulting chemistry in the laboratory mimics that in natural systems. Sediment bioavailability models are emerging including models that allow for prediction of toxicity in sediments for copper and nickel. Biodynamic models have been developed for several organisms and many metals. The models allow for estimates of transport of metals from sediments to organisms via their diet as well as their water exposure. All these advances expand the tool set available to risk assessors. Integr Environ Assess Manag 2024;20:924-951. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

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.

Validation of Nickel Bioavailability Models for Algae, Invertebrates, and Fish in Chinese Surface Waters

Nickel (Ni) is used primarily in the production of alloys like stainless steel and is increasingly being used in the production of batteries for the electric vehicle market. Exposure of Ni to ecosystems is of concern because Ni can be toxic to aquatic organisms. The influence of water chemistry constituents (e.g., hardness, pH, dissolved organic carbon) on the toxicity of Ni has prompted the development and use of bioavailability models, such as biotic ligand models (BLMs), which have been demonstrated to accurately predict Ni toxicity in broadly different ecosystems, including Europe, North America, and Australia. China, a leading producer of Ni, is considering bioavailability-based approaches for regulating Ni emissions. Adoption of bioavailability-based approaches in China requires information to demonstrate the validity of bioavailability models for the local water chemistry conditions. The present study investigates the toxicity of Ni to three standard test species (Daphnia magna, Pseudokirchneriella subcapitata, and Danio rerio) in field-collected natural waters that are broadly representative of the range of water chemistries and bioavailabilities encountered in Chinese lakes and rivers. All experimental data are within a factor of 3 of the BLM predicted values for all tests with all species. For D. magna, six of seven waters were predicted within a factor of 2 of the experimental result. Comparison of experimental data against BLM predictions shows that the existing Ni bioavailability models are able to explain the differences in toxicity that result from water chemistry conditions in China. Validation of bioavailability models to water chemistries and bioavailability ranges within China provides technical support for the derivation of site-specific Ni water quality criteria in China. Environ Toxicol Chem 2023;42:1257-1265. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

A modelling framework to assess multiple metals impacts on marine food webs: Relevance for assessing the ecological implications of deep-sea mining based on a systematic review

Industrial deep-sea mining will release plumes containing metals that may disperse over long distances; however, there is no general understanding of metal effects on marine ecosystems. Thus, we conducted a systematic review in search of models of metal effects on aquatic biota with the future perspective to support Environmental Risk Assessment (ERA) of deep-sea mining. According to results, the use of models to study metal effects is strongly biased towards freshwater species (83% freshwater versus 14% marine); Cu, Hg, Al, Ni, Pb, Cd and Zn are the best-studied metals, and most studies target few species rather than entire food webs. We argue that these limitations restrain ERA on marine ecosystems. To overcome this gap of knowledge, we suggest future research directions and propose a modelling framework to predict the effects of metals on marine food webs, which in our view is relevant for ERA of deep-sea mining.

Use of non-linear multiple regression models for setting water quality criteria for copper: Consider the effects of salinity and dissolved organic carbon

Cu pollution is a global concern because of its high toxicity and persistence. Few investigations have been conducted on the effects of salinity and dissolved organic carbon (DOC) on Cu toxicity and water quality criteria (WQC). To analyze their impact on the WQC of Cu, non-linear multiple regression (NLMR) models based on salinity and DOC were constructed. The NLMR models demonstrated that when salinity increased, the toxicity values for Cu on fish, mollusca, rotifer, and echinodermata first increased and then declined, whereas those for arthropoda and algae increased. These findings demonstrate that salinity has a substantial impact on Cu toxicity, primarily owing to changes in physiological activity. The original and corrected WQC values in the upper, middle, and outer regions of the Yangtze Estuary were derived based on the species sensitivity distribution method. These values were 1.49, 3.49, 8.86, and 0.87 μg·L^-1. An important finding was that lower Cu concentrations in the outer areas posed the highest ecological risk owing to the effects of salinity and DOC. NLMR models are applicable to other coastal areas worldwide. This provides valuable information for the establishment of an accurate and protective estuary for Cu-related WQC.

Comparison of the Estimation Methods from Acute to Chronic Biotic Ligand Model-Based Predicted No-Effect Concentrations for Nickel in Freshwater Species

Biotic ligand models (BLMs) and the sensitivities of indigenous species are used to assess the environmental risk considering the bioavailability of metals, such as nickel. However, the BLM-based acute-to-chronic ratio (ACR) is required if the predicted no-effect concentration (PNEC) cannot be derived from the chronic species sensitivity distribution (SSD). The applicability of the ACR approach for estimating BLM-based PNEC for nickel from acute toxicity data was evaluated in the present study. The BLM-based acute SSD for nickel was built using the sensitivities of 21 indigenous species and different taxon-specific BLMs for each taxonomic group. To predict the acute sensitivity of invertebrates, the chronic crustacean nickel BLM with pH effect term, which can account for nickel toxicity at high pH levels, was used. This was used instead of the existing acute BLM for crustacean, which has too narrow a pH range to cover the pH dependency of toxicity. The final BLM-based ACR of nickel, determined within a factor of 1.53 from the species-specific acute and chronic sensitivities of the six species, was more reliable than the typical ACR estimated within a factor of 1.84. A linear relationship (r²  = 0.95) was observed between the PNECs using BLM-based ACR and the PNECs derived from the BLM-based chronic SSD of the European Union Risk Assessment Reports. In conclusion, the BLM-based PNEC for nickel could be derived using the ACR approach, unlike when copper BLM was applied. The BLM-based ACR for nickel is the first result calculated by directly comparing acute and chronic species sensitivities, and will contribute to the application of BLM-based risk assessment in broader ecoregions. Environ Toxicol Chem 2023;42:914-927. © 2023 SETAC.

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.

Chemodynamic features of nickel(II) and its complexes: Implications for bioavailability in freshwaters

A robust description of the bioavailability of Ni(II) in freshwaters is fundamental for the setting of environmental quality standards. Current approaches assume that bioavailability is governed by the equilibrium concentration of the free metal ion in the bulk aqueous medium. Such strategies generally have limited predictive value: a suite of empirical fitting parameters is required to deal with variations in water chemistry. Herein we compile data on Ni(II) speciation under typical freshwater conditions and compute the lability of Ni(II) complexes with typical molecular and nanoparticulate components of dissolved organic carbon. In combination with an analysis of the kinetic setting of Ni(II) biouptake by freshwater organisms, we assess the potential contribution from dissociation of Ni(II) complexes to the diffusive supply flux of free Ni²⁺. The strategy takes into account the absolute and relative magnitudes of the Michaelis-Menten bioaffinity and bioconversion parameters for a range of freshwater organisms, together with dynamic chemical speciation descriptors under environmentally relevant conditions. The results show that the dissociation kinetics of Ni(II) complexes play a crucial role in buffering the free metal ion concentration at the biointerface. Our results highlight the need to couple the timescales of chemical reactivity with those of biouptake to properly identify the bioavailable fraction of Ni(II) in freshwaters.