Updated Chronic Copper Bioavailability Models for Invertebrates and Algae.

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

Assessing the relevance of environmental exposure data sets.

Environmental exposure data are used by decision-makers to assess environmental risks and implement actions to mitigate risks from contaminants. The first article in this series summarized the available evaluation schemes for environmental exposure data, of which there are few compared to those available for environmental hazard data. The second article covered the assessment of the reliability of environmental exposure data sets under the Criteria for the Reporting and Evaluation of Exposure Data (CREED). The aim of this article is to provide an overview and practical guidance on the relevance assessment in the context of the CREED approach for evaluating exposure monitoring data sets. Systematically considering relevance is critical for both evaluating existing data sets and for optimizing the design of new monitoring studies. Relevance is defined here as the degree of suitability or appropriateness of a data set to address a specific purpose or to answer the questions that have been defined by the assessor or for those generating exposure data. The purpose definition will be the foundation for the relevance assessment, to clarify how the assessor should rate the assessment criteria (fully met, partly met, not met/inappropriate, not reported, not applicable). This will provide transparency for anyone reviewing the outcomes. An explicit gap analysis (i.e., an articulation of the data set limitations for the stated purpose) is an important outcome of the relevance assessment. The relevance evaluation approach is demonstrated with three case studies, all relating to the freshwater aquatic environment, where the data sets are scored as relevant with or without restrictions, not relevant, or not assignable. The case studies represent both organic and inorganic constituents, and have different data characteristics (e.g., percentage of censored data, sampling frequencies, relation to supporting parameters). Integr Environ Assess Manag 2024;00:1-15. © 2023 SETAC.

Land degradation neutrality: Testing the indicator in a temperate agricultural landscape.

Land degradation directly affects around 25% of land globally, undermining progress on most of the UN Sustainable Development Goals (SDG), particularly target 15.3. To assess land degradation, SDG indicator 15.3.1 combines sub-indicators of productivity, soil carbon and land cover. Over 100 countries have set Land Degradation Neutrality (LDN) targets. Here, we demonstrate application of the indicator for a well-established agricultural landscape using the case study of Great Britain. We explore detection of degradation in such landscapes by: 1) transparently evaluating land cover transitions; 2) comparing assessments using global and national data; 3) identifying misleading trends; and 4) including extra sub-indicators for additional forms of degradation. Our results demonstrate significant impacts on the indicator both from the land cover transition evaluation and choice or availability of data. Critically, we identify a misleading improvement trend due to a trade-off between improvement detected by the productivity sub-indicator, and 30-year soil carbon loss trends in croplands (11% from 1978 to 2007). This carbon loss trend would not be identified without additional data from Countryside Survey (CS). Thus, without incorporating field survey data we risk overlooking the degradation of regulating and supporting ecosystem services (linked to soil carbon), in favour of signals from improving provisioning services (productivity sub-indicator). Relative importance of these services will vary between socioeconomic contexts. Including extra sub-indicators for erosion or critical load exceedance, as additional forms of degradation, produced a switch from net area improving (9%) to net area degraded (58%). CS data also identified additional degradation for soil health, including 44% arable soils exceeding bulk density thresholds and 35% of CS squares exceeding contamination thresholds for metals.

Predicting accidental release of engineered nanomaterials to the environment.

Challenges in distinguishing between natural and engineered nanomaterials (ENMs) and the lack of historical records on ENM accidents have hampered attempts to estimate the accidental release and associated environmental impacts of ENMs. Building on knowledge from the nuclear power industry, we provide an assessment of the likelihood of accidental release rates of ENMs within the next 10 and 30 years. We evaluate risk predictive methodology and compare the results with empirical evidence, which enables us to propose modelling approaches to estimate accidental release risk probabilities. Results from two independent modelling approaches based on either assigning 0.5% of reported accidents to ENM-releasing accidents (M1) or based on an evaluation of expert opinions (M2) correlate well and predict severe accidental release of 7% (M1) in the next 10 years and of 10% and 20% for M2 and M1, respectively, in the next 30 years. We discuss the relevance of these results in a regulatory context.

UV-Vis Spectroscopic Characterization of Nanomaterials in Aqueous Media.

The physicochemical characterization of nanomaterials (NMs) is often an analytical challenge, due to their small size (at least one dimension in the nanoscale, i.e. 1-100 nm), dynamic nature, and diverse properties. At the same time, reliable and repeatable characterization is paramount to ensure safety and quality in the manufacturing of NM-bearing products. There are several methods available to monitor and achieve reliable measurement of nanoscale-related properties, one example of which is Ultraviolet-Visible Spectroscopy (UV-Vis). This is a well-established, simple, and inexpensive technique that provides non-invasive and fast real-time screening evaluation of NM size, concentration, and aggregation state. Such features make UV-Vis an ideal methodology to assess the proficiency testing schemes (PTS) of a validated standard operating procedure (SOP) intended to evaluate the performance and reproducibility of a characterization method. In this paper, the PTS of six partner laboratories from the H2020 project ACEnano were assessed through an interlaboratory comparison (ILC). Standard gold (Au) colloid suspensions of different sizes (ranging 5-100 nm) were characterized by UV-Vis at the different institutions to develop an implementable and robust protocol for NM size characterization.

Measuring ZnO nanoparticles available concentrations in contaminated soils using the diffusive gradient in thin-films (DGT) technique.

A major gap in understanding nanomaterials behaviour in the environment is a lack of reliable tools to measure their available concentrations. In this research we use diffusive gradients in thin films (DGT) for measuring concentrations of zinc oxide nanoparticles (ZNO NPs) in soils. Available nanoparticle concentrations were assessed by difference, using paired DGT devices with and without 1000 MWCO dialysis membranes to exclude NPs. We used ZnO because its toxic effects are accelerated through dissolution to Zn2+. Our test soils had different pH and organic matter (OM) contents, which both affect the dissolution rate of ZnO NPs. Woburn (pH ≈ 6.9, OM ≈ 1.8%) and Lufa (pH ≈ 5.9, OM ≈ 4.2%) soils were spiked to a single concentration of 500 mg of ZnO NPs per 1 kg of soil and the available concentrations of ZnO NPs and dissolved zinc were evaluated in 3, 7, 14, 21, 28, 60, 90, 120, 150 and 180 day intervals using DGT. The results showed that the dissolution of ZnO NPs, as well as the available concentrations of both dissolved and nanoparticulate Zn, was much higher in Lufa soil than in Woburn. This work demonstrates that DGT can be used as a simple yet reliable technique for determining concentrations of ZnO NPs in soils and probing its dissolution kinetics.

Enriching the Shared Socioeconomic Pathways to co-create consistent multi-sector scenarios for the UK.

As the pressure to take action against global warming is growing in urgency, scenarios that incorporate multiple social, economic and environmental drivers become increasingly critical to support governments and other stakeholders in planning climate change mitigation or adaptation actions. This has led to the recent explosion of future scenario analyses at multiple scales, further accelerated since the development of the Intergovernmental Panel on Climate Change (IPCC) research community Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). While RCPs have been widely applied to climate models to produce climate scenarios at multiple scales for investigating climate change impacts, adaptation and vulnerabilities (CCIAV), SSPs are only recently being scaled for different geographical and sectoral applications. This is seen in the UK where significant investment has produced the RCP-based UK Climate Projections (UKCP18), but no equivalent UK version of the SSPs exists. We address this need by developing a set of multi-driver qualitative and quantitative UK-SSPs, following a state-of-the-art scenario methodology that integrates national stakeholder knowledge on locally-relevant drivers and indicators with higher level information from European and global SSPs. This was achieved through an intensive participatory process that facilitated the combination of bottom-up and top-down approaches to develop a set of UK-specific SSPs that are locally comprehensive, yet consistent with the global and European SSPs. The resulting scenarios balance the importance of consistency and legitimacy, demonstrating that divergence is not necessarily the result of inconsistency, nor comes as a choice to contextualise narratives at the appropriate scale.

Nanoparticle Tracking Analysis of Gold Nanoparticles in Aqueous Media through an Inter-Laboratory Comparison.

In the field of nanotechnology, analytical characterization plays a vital role in understanding the behavior and toxicity of nanomaterials (NMs). Characterization needs to be thorough and the technique chosen should be well-suited to the property to be determined, the material being analyzed and the medium in which it is present. Furthermore, the instrument operation and methodology need to be well-developed and clearly understood by the user to avoid data collection errors. Any discrepancies in the applied method or procedure can lead to differences and poor reproducibility of obtained data. This paper aims to clarify the method to measure the hydrodynamic diameter of gold nanoparticles by means of Nanoparticle Tracking Analysis (NTA). This study was carried out as an inter-laboratory comparison (ILC) amongst seven different laboratories to validate the standard operating procedure's performance and reproducibility. The results obtained from this ILC study reveal the importance and benefits of detailed standard operating procedures (SOPs), best practice updates, user knowledge, and measurement automation.

Key principles and operational practices for improved nanotechnology environmental exposure assessment.

Nanotechnology is identified as a key enabling technology due to its potential to contribute to economic growth and societal well-being across industrial sectors. Sustainable nanotechnology requires a scientifically based and proportionate risk governance structure to support innovation, including a robust framework for environmental risk assessment (ERA) that ideally builds on methods established for conventional chemicals to ensure alignment and avoid duplication. Exposure assessment developed as a tiered approach is equally beneficial to nano-specific ERA as for other classes of chemicals. Here we present the developing knowledge, practical considerations and key principles need to support exposure assessment for engineered nanomaterials for regulatory and research applications.

NanoSolveIT Project: Driving nanoinformatics research to develop innovative and integrated tools for in silico nanosafety assessment.

Nanotechnology has enabled the discovery of a multitude of novel materials exhibiting unique physicochemical (PChem) properties compared to their bulk analogues. These properties have led to a rapidly increasing range of commercial applications; this, however, may come at a cost, if an association to long-term health and environmental risks is discovered or even just perceived. Many nanomaterials (NMs) have not yet had their potential adverse biological effects fully assessed, due to costs and time constraints associated with the experimental assessment, frequently involving animals. Here, the available NM libraries are analyzed for their suitability for integration with novel nanoinformatics approaches and for the development of NM specific Integrated Approaches to Testing and Assessment (IATA) for human and environmental risk assessment, all within the NanoSolveIT cloud-platform. These established and well-characterized NM libraries (e.g. NanoMILE, NanoSolutions, NANoREG, NanoFASE, caLIBRAte, NanoTEST and the Nanomaterial Registry (>2000 NMs)) contain physicochemical characterization data as well as data for several relevant biological endpoints, assessed in part using harmonized Organisation for Economic Co-operation and Development (OECD) methods and test guidelines. Integration of such extensive NM information sources with the latest nanoinformatics methods will allow NanoSolveIT to model the relationships between NM structure (morphology), properties and their adverse effects and to predict the effects of other NMs for which less data is available. The project specifically addresses the needs of regulatory agencies and industry to effectively and rapidly evaluate the exposure, NM hazard and risk from nanomaterials and nano-enabled products, enabling implementation of computational 'safe-by-design' approaches to facilitate NM commercialization.

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.

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.

Predicting the bioavailability of sediment-bound uranium to the freshwater midge (Chironomus dilutus) using physicochemical properties.

Assessment of uranium (U)-contaminated sediment is often hindered by the inability to accurately account for the physicochemical properties of sediment that modify U bioavailability. The present goal was to determine whether sediment-associated U bioavailability could be predicted over a wide range of conditions and sediment properties using simple regressions and a geochemical speciation model, the Windermere Humic Aqueous Model (WHAM7). Data from a U-contaminated field sediment bioaccumulation test, along with previously published bioaccumulation studies with U-spiked field and formulated sediments, were used to examine the models. Observed U concentrations in Chironomus dilutus larvae exposed to U-spiked and U-contaminated sediments correlated well (r2 > 0.74, p < 0.001) with the WHAM-calculated concentration of U bound to humic acid, indicating that humic acid may be a suitable surrogate for U binding sites (biotic ligands) in C. dilutus larvae. Subsequently, the concentration of U in C. dilutus was predicted with WHAM7 by numerically optimizing the equivalent mass of humic acid per gram of organism. The predicted concentrations of U in C. dilutus larvae exposed to U-spiked and U-contaminated field sediment compared well with the observed values, where one of the regression models provided a slightly better fit (mean absolute error = 18.1 mg U/kg dry wt) than WHAM7 (mean absolute error = 34.2 mg U/kg dry wt). The regression model provides a predictive capacity with a minimal number of variables, whereas WHAM7 provides additional complementary insight into the chemical variables influencing the speciation, sorption, and bioavailability of U in sediment. The present results indicate that physicochemical properties of sediment can be used to account for variability in U bioavailability as measured through bioaccumulation in chironomids exposed to U-contaminated sediments. Environ Toxicol Chem 2018;37:1146-1157. © 2017 SETAC.

Comparison of four methods for bioavailability-based risk assessment of mixtures of Cu, Zn, and Ni in freshwater.

Although chemical risk assessment is still mainly conducted on a substance-by-substance basis, organisms in the environment are typically exposed to mixtures of substances. Risk assessment procedures should therefore be adapted to fit these situations. Four mixture risk assessment methodologies were compared for risk estimations of mixtures of copper (Cu), zinc (Zn), and nickel (Ni). The results showed that use of the log-normal species sensitivity distribution (SSD) instead of the best-fit distribution and sampling species sensitivities independently for each metal instead of using interspecies correlations in metal sensitivity had little impact on risk estimates. Across 4 different monitoring datasets, between 0% and 52% of the target water samples were estimated to be at risk, but only between 0% and 15% of the target water samples were at risk because of the mixture of metals and not any single metal individually. When a natural baseline database was examined, it was estimated that 10% of the target water samples were at risk because of single metals or their mixtures; when the most conservative method was used (concentration addition [CA] applied directly to the SSD, i.e., CASSD ). However, the issue of metal mixture risk at geochemical baseline concentrations became relatively small (2% of target water samples) when a theoretically more correct method was used (CA applied to individual dose response curves, i.e., CADRC ). Finally, across the 4 monitoring datasets, the following order of conservatism for the 4 methods was shown (from most to least conservative, with ranges of median margin of safety [MoS] relative to CASSD ): CASSD > CADRC (MoS = 1.17-1.25) > IADRC (independent action (IA) applied to individual dose-response curves; MoS = 1.38-1.60) > IASSD (MoS = 1.48-1.72). Therefore, it is suggested that these 4 methods can be used in a general tiered scheme for the risk assessment of metal mixtures in a regulatory context. In this scheme, the CASSD method could serve as a first (conservative) tier to identify situations with likely no potential risk at all, regardless of the method used (the sum toxic unit expressed relative to the 5% hazardous concentration [SumTUHC5 ] < 1) and the IASSD method to identify situations of potential risk, also regardless of the method used (the multisubstance potentially affected fraction of species using the IASSD method [msPAFIA,SSD ] > 0.05). The CADRC and IADRC methods could be used for site-specific assessment for situations that fall in between (SumTUHC5 > 1 and msPAFIA,SSD < 0.05). Environ Toxicol Chem 2017;36:2123-2138. © 2017 SETAC.

Effects of aging and soil properties on zinc oxide nanoparticle availability and its ecotoxicological effects to the earthworm Eisenia andrei.

To assess the influence of soil properties and aging on the availability and toxicity of zinc (Zn) applied as nanoparticles (Zn oxide [ZnO]-NPs) or as Zn2+ ions (Zn chloride [ZnCl2 ]), 3 natural soils were individually spiked with either ZnO-NPs or ZnCl2 and incubated for up to 6 mo. Available Zn concentrations in soil were measured by porewater extraction (ZnPW), whereas earthworms (Eisenia andrei) were exposed to study Zn bioavailability. Porewater extraction concentrations were lower when Zn was applied as NPs compared to the ionic form and decreased with increasing soil pH. For both Zn forms and Zn-PW values were affected by aging, but they varied among the tested soils, highlighting the influence of soil properties. Internal Zn concentration in the earthworms (ZnE) was highest for the soil with high organic carbon content (5.4%) and basic pH (7.6) spiked with Zn-NPs, but the same soil spiked with ZnCl2 showed the lowest increase in ZnE compared to the control. Survival, weight change, and reproduction of the earthworms were affected by both Zn forms; but differences in toxicity could not be explained by soil properties or aging. This shows that ZnO-NPs and ZnCl2 behave differently in soils depending on soil properties and aging processes, but differences in earthworm toxicity remain unexplained. Environ Toxicol Chem 2017;36:137-146. © 2016 SETAC.

The role of sediment properties and solution pH in the adsorption of uranium(VI) to freshwater sediments.

Uranium (U) can enter aquatic environments from natural and anthropogenic processes, accumulating in sediments to concentrations that could, if bioavailable, adversely affect benthic organisms. To better predict the sorption and mobility of U in aquatic ecosystems, we investigated the sediment-solution partition coefficients (Kd) of U for nine uncontaminated freshwater sediments with a wide range of physicochemical characteristics over an environmentally relevant pH range. Test solutions were reconstituted to mimic water quality conditions and U(VI) concentrations (0.023-2.3 mg U/L) found downstream of Canadian U mines. Adsorption of U(VI) to each sediment was greatest at pH 6 and 7, and significantly reduced at pH 8. There were significant differences in pH-dependent sorption among sediments with different physicochemical properties, with sorption increasing up until thresholds of 12% total organic carbon, 37% fine fraction (≤50 µm), and 29 g/kg of iron content. The Kd values for U(VI) were predicted using the Windermere Humic Aqueous Model (WHAM) using total U(VI) concentrations, and water and sediment physicochemical parameters. Predicted Kd-U values were generally within a factor of three of the observed values. These results improve the understanding and assessment of U sorption to field sediment, and quantify the relationship with sediment properties that may influence the bioavailability and ecological risk of U-contaminated sediments.

Effect of Ocean Acidification on Organic and Inorganic Speciation of Trace Metals.

Rising concentrations of atmospheric carbon dioxide are causing acidification of the oceans. This results in changes to the concentrations of key chemical species such as hydroxide, carbonate and bicarbonate ions. These changes will affect the distribution of different forms of trace metals. Using IPCC data for pCO2 and pH under four future emissions scenarios (to the year 2100) we use a chemical speciation model to predict changes in the distribution of organic and inorganic forms of trace metals. Under a scenario where emissions peak after the year 2100, predicted free ion Al, Fe, Cu, and Pb concentrations increase by factors of up to approximately 21, 2.4, 1.5, and 2.0 respectively. Concentrations of organically complexed metal typically have a lower sensitivity to ocean acidification induced changes. Concentrations of organically complexed Mn, Cu, Zn, and Cd fall by up to 10%, while those of organically complexed Fe, Co, and Ni rise by up to 14%. Although modest, these changes may have significance for the biological availability of metals given the close adaptation of marine microorganisms to their environment.

Assessment of co-contaminant effects on uranium and thorium speciation in freshwater using geochemical modelling.

Speciation modelling of uranium (as uranyl) and thorium, in four freshwaters impacted by mining activities, was used to evaluate (i) the influence of the co-contaminants present on the predicted speciation, and (ii) the influence of using nine different model/database combinations on the predictions. Generally, co-contaminants were found to have no significant effects on speciation, with the exception of Fe(III) in one system, where formation of hydrous ferric oxide and adsorption of uranyl to its surface impacted the predicted speciation. Model and database choice on the other hand clearly influenced speciation prediction. Complexes with dissolved organic matter, which could be simulated by three of the nine model/database combinations, were predicted to be important in a slightly acidic, soft water. Model prediction of uranyl and thorium speciation needs to take account of database comprehensiveness and cohesiveness, including the capability of the model and database to simulate interactions with dissolved organic matter. Measurement of speciation in natural waters is needed to provide data that may be used to assess and improve model capabilities and to better constrain the type of predictive modelling work presented here.

Metal mixture modeling evaluation project: 2. Comparison of four modeling approaches.

As part of the Metal Mixture Modeling Evaluation (MMME) project, models were developed by the National Institute of Advanced Industrial Science and Technology (Japan), the US Geological Survey (USA), HDR|HydroQual (USA), and the Centre for Ecology and Hydrology (United Kingdom) to address the effects of metal mixtures on biological responses of aquatic organisms. A comparison of the 4 models, as they were presented at the MMME workshop in Brussels, Belgium (May 2012), is provided in the present study. Overall, the models were found to be similar in structure (free ion activities computed by the Windermere humic aqueous model [WHAM]; specific or nonspecific binding of metals/cations in or on the organism; specification of metal potency factors or toxicity response functions to relate metal accumulation to biological response). Major differences in modeling approaches are attributed to various modeling assumptions (e.g., single vs multiple types of binding sites on the organism) and specific calibration strategies that affected the selection of model parameters. The models provided a reasonable description of additive (or nearly additive) toxicity for a number of individual toxicity test results. Less-than-additive toxicity was more difficult to describe with the available models. Because of limitations in the available datasets and the strong interrelationships among the model parameters (binding constants, potency factors, toxicity response parameters), further evaluation of specific model assumptions and calibration strategies is needed.