Windermere Humic Aqueous Model Research Articles

Comparison of mercury (Hg) bioaccumulation with mono- and mixed Lemna minor and Spirodela polyrhiza cultures.

Mercury (Hg) is a prevalent and harmful contaminant that persists in the environment. For phytoremediation, it is important to discover which plants can bioaccumulate meaningful amounts of Hg while also tolerating its toxicity. Additionally, increasing biodiversity could create a more resilient and self-sustaining system for remediation. This study explores whether mixed populations of Lemna minor and Spirodela polyrhiza can better bioaccumulate and tolerate Hg than monocultures. Mono- and mixed cultures of L. minor and S. polyrhiza were grown in mesocosms of 0.5µg/L or 100µg/L Hg (HgCl2) spiked water for 96h. Change in weight of duckweed was used to assess Hg tolerance. Diffusive gradients in thin-films (DGTs) were used as surrogate monitoring devices for bioavailable levels of Hg. For biomass growth, the mixed culture of the L. minor was greater than the monoculture at the high dose. The L. minor accumulated more Hg in the mixed culture at the low dose while the S. polyrhiza was higher in the mixed at the high dose. Hg speciation in water was modeled using Windermere Humic Aqueous Model 7 (WHAM7) to compare the bioavailable species indicated by the DGTs. Potentially due to the controlled conditions, the WHAM7 output of bioavailable Hg was almost 1:1 to that estimated by the DGTs, indicating good predictive capability of geochemical modeling and passive sampler DGT on metal bioavailability. Overall, the mixed cultures statistically performed as well as or better than the monocultures when tolerating and bioaccumulating Hg. However, there needs to be further work to see if the significant differences translate into practical differences worth the extra resources to maintain multiple species.

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.

Linking molecular composition to proton and copper binding ability of fulvic acid: A theoretical modeling approach based on FT-ICR-MS analysis

Dissolved organic matter (DOM) is one of the most important ligands governing the geochemical cycling of metals in the environment, but recent studies with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) have shown enormous complexity and diversity of DOM composition. How the diverse molecular composition of DOM affects the reactivity of DOM with metals is still largely unknown, which precludes us from developing accurate geochemical models for the fate of metals in the environment. In this study, we combined FT-ICR-MS analysis and theoretical modeling approaches and specifically elucidated the link between molecular composition and the proton and Cu binding ability of DOM, using the Suwannee River fulvic acid (FA) as a model humic substance. Batch adsorption experiments were conducted to generate different extents of molecular fractionation of FA samples by ferrihydrite. FT-ICR-MS analyses were employed to investigate the changes of molecular composition while Cu titration and the Windermere Humic Aqueous Model (WHAM) were used to quantify the variations on the Cu binding capacities of FA samples. We developed a general theoretical modeling approach, which integrated a suite of theoretical modeling methods, including the Vienna Soil-Organic-Matter-Modeler (VSOMM), SPARC Performs Automated Reasoning in Chemistry (SPARC), and the linear free energy relationships (LFER), for molecular modeling based on FT-ICR-MS data. Based on the FT-ICR-MS results, we found that, despite of the complex molecular composition of FA, FA molecules can be divided into three representative groups and each group of molecules had distinct chemical properties. Interestingly, molecules within the same group had similar distributions of molecular properties. Based on the chemical properties of the three groups of FA molecules, we successfully constructed three molecular models of FA using VSOMM, and quantified the distributions of proton and Cu binding constants with SPARC and LFER. Those independently determined binding constants were comparable to the WHAM default proton and Cu binding constants, supporting the validity of our modeling approach. Our modeling results suggested that the molecular complexity of DOM may be simplified with representative groups of molecules based on their binding ability with metals in theoretical modeling. Our modeling approach based on FT-ICR-MS data shed light on developing mechanistical models for metal reactions with DOM based on the molecular data, which is helpful for predicting the geochemical cycling of carbon and metals in the environment.

The effect of soil properties on zinc lability and solubility in soils of Ethiopia – an isotopic dilution study

Abstract. Zinc (Zn) deficiency is a widespread nutritional problem in human populations, especially in sub-Saharan Africa (SSA). The Zn concentration of crops consumed depends in part on the Zn status of the soil. Improved understanding of factors controlling the phyto-availability of Zn in soils can contribute to potential agronomic interventions to tackle Zn deficiency, but many soil types in SSA are poorly studied. Soil samples (n=475) were collected from a large part of the Amhara Region of Ethiopia, where there is widespread Zn deficiency. Zinc status was quantified by measuring several fractions, including the pseudo-total (aqua regia digestion; ZnTot), available (DTPA (diethylenetriamine pentaacetate) extractable; ZnDTPA), soluble (dissolved in 0.01 M Ca(NO3); ZnSoln) and isotopically exchangeable Zn, using the enriched stable Zn isotope 70Zn (ZnE). Soil geochemical properties were assessed for their influence on Zn lability and solubility. A parameterized geochemical assemblage model (Windermere Humic Aqueous Model – WHAM) was also employed to predict the solid phase fractionation of Zn in tropical soils rather than using sequential chemical extractions. ZnTot ranged from 14.1 to 291 mg kg−1 (median = 100 mg kg−1), whereas ZnDTPA in the majority of soil samples was less than 0.5 mg kg−1, indicating widespread phyto-available Zn deficiency in these soils. The labile fraction of Zn in soil (ZnE as % ZnTot) was low, with median and mean values of 4.7 % and 8.0 %, respectively. Labile Zn partitioning between the solid and the solution phases of soil was highly pH dependent, where 94 % of the variation in the partitioning coefficient of 70Zn was explained by soil pH. Similarly, 86 % of the variation in ZnSoln was explained by soil pH. Zinc distribution between adsorbed ZnE and ZnSoln was controlled by pH. Notably, Zn isotopic exchangeability increased with soil pH. This contrasts with literature on contaminated and urban soils and may arise from covarying factors, such as contrasting soil clay mineralogy across the pH range of the soils used in the current study. These results could be used to improve agronomic interventions to tackle Zn deficiency in SSA.

Effect of Dissolved Organic Matter Concentration and Source on the Chronic Toxicity of Copper and Nickel Mixtures to Chlorella sp.

There have been limited studies on the effects of toxicity-modifying factors, such as dissolved organic matter (DOM), on the toxicity of metal mixtures to aquatic biota. The present study investigated the effects of DOM concentration (low, 2.8 ± 0.1 mg C/L; high, 11 ± 1.0 mg C/L) and DOM source (predominantly terrestrial or microbial) on the chronic toxicity of copper (Cu) and nickel (Ni) binary mixtures to the green freshwater microalga Chlorella sp. This was assessed by using a full factorial design of 72-h growth inhibition bioassays. Measured algal growth rate was compared with growth predicted by the concentration addition and independent action reference models. Model predictions were based on concentrations of dissolved metals, labile metals (measured by diffusive gradients in thin films [DGT]), and calculated free metal ions (determined by the Windermere Humic Aqueous Model). Copper/Ni mixture toxicity was synergistic to Chlorella sp. in the absence of added DOM, with evidence of metal concentration-dependent toxicity at low effect concentrations. As DOM concentration increased, the mixture interaction changed from synergism to noninteraction or antagonism depending on the metal speciation method used. The DOM source had no significant effect on mixture interaction when based on dissolved and free metal ion concentrations but was significantly different when based on DGT-labile metal concentrations. Ratio-dependent mixture interaction was observed in all treatments, with increased deviation from the reference model predictions as the mixture changed from Ni- to Cu-dominated. The present study demonstrated that both DOM concentration and source can significantly change metal mixture toxicity interactions and that these interactions can be interpreted differently depending on the metal speciation method used. Environ Toxicol Chem 2021;40:1908-1918. © 2021 SETAC.

Developing understanding of the fate and behaviour of silver in fresh waters and waste waters

The Windermere Humic Aqueous Model (WHAM) is often used for risk assessment of metals; WHAM can be used to estimate the potential bioavailability of dissolved metals, where metals complexed to dissolved organic matter (DOM) are expected to be less toxic than ionic forms. Silver is a potential metal of concern but WHAM has not been rigorously tested against experimental measurements. This study compares WHAM predictions to measured ionic silver during fixed pH (4, 8 or 10) argentometric titrations of DOM from diverse origins. There were almost two orders of magnitude variation in free silver between sources but, within model uncertainty, WHAM captured this variability. This agreement, between measurements and models, suggests that WHAM is an appropriate tool for silver risk assessment in surface receiving waters when DOM is predominantly in the form of humic/fulvic acids. In sewage samples WHAM dramatically underestimated silver binding by approximately 3 orders of magnitude. Simulations with additional specific strong silver binding sulphide-like binding sites could explain Ag binding at low loadings, but not at higher loadings. This suggests the presence of additional intermediate strength binding sites. These additional ligands would represent components of the raw sewage largely absent in natural waters unimpacted by sewage effluents. A revised empirical model was proposed to account for these sewage-specific binding sites. Further, it is suspected that as sewage organic matter is degraded, either by natural attenuation or by engineered treatment, that sewage organic matter will degrade to a form more readily modelled by WHAM; i.e., humic-like substances. These ageing experiments were performed starting from raw sewage, and the material did in fact become more humic-like, but even after 30 days of aerobic incubation still showed greater Ag+ binding than WHAM predictions. In these incubation experiments it was found that silver (up to 1000 μg/L) had minimal impact on ammonia oxidation kinetics.

A Generalized Bioavailability Model (gBAM) for Predicting Chronic Copper Toxicity to Freshwater Fish

The generalized bioavailability model (gBAM) has been proposed as an alternative to the biotic ligand model (BLM) for modeling bioavailability and chronic toxicity of copper (Cu). The gBAM combines a log-linear effect of pH on free Cu2+ ion toxicity with BLM-type parameters for describing the protective effects of major cations (calcium [Ca]2+ , magnesium [Mg]2+ , and sodium [Na]+ ). In the present study, a Windermere Humic Aqueous Model (WHAM) VII-based gBAM for fish was parametrized based on an existing chronic (30-d) dataset of juvenile rainbow trout (Oncorhynchus mykiss). The model, with defined parameters (pH slope parameter [SpH ] = 0.4449 and biotic ligand competition constants [log KCaBL = 4.0, log KMgBL = 3.4, and log KNaBL = 3.0]), was shown to accurately predict the effects of pH, dissolved organic carbon, Ca, and Mg on chronic Cu toxicity to juvenile rainbow trout at the effect levels relevant for environmental risk assessment (i.e., median prediction error of 1.3-fold for 10 and 20% lethal concentrations). The gBAM predicted the effect of pH more accurately than a previously published Cu BLM for juvenile rainbow trout, especially at pH > 8. We also evaluated the cross-species and cross-life stage applicability of the newly developed juvenile rainbow trout gBAM using existing chronic Cu toxicity data with early life stages of fathead minnow (Pimephales promelas) and rainbow trout. We did this because using a single bioavailability model for all fish species and life stages is practical from a regulatory point of view. Although the early life stage datasets exhibit considerable uncertainties, 91% of the considered toxicity values at the effect levels most relevant in European environmental regulations (10% effect on survival or growth) were predicted within a 2-fold error. Overall, the chronic Cu gBAM we developed is a valuable alternative for the existing chronic Cu BLM for rainbow trout and performs sufficiently well to be used in risk assessment according to currently accepted standards of bioavailability model performance (from the current European regulatory point of view). However, our analysis also suggests that bioavailability relations differ between different fish life stages and between endpoints (e.g., mortality vs growth), which is currently not accounted for in environmental risk assessments. Environ Toxicol Chem 2020;39:2424-2436. © 2020 SETAC.

Amelioration of copper toxicity to a tropical freshwater microalga: Effect of natural DOM source and season

Australian tropical freshwaters can experience extreme seasonal variability in rainfall and run off, particularly due to pulse events such as storms and cyclones. This study investigated how seasonal variability in dissolved organic matter (DOM) quality impacted the chronic toxicity of copper to a tropical green alga (Chlorella sp.) in the presence of two concentrations of DOM (low: ∼2 mg C/L; high: ∼10 mg C/L) collected from three tropical waters. Copper speciation and lability were explored using diffusive gradients in thin-films (DGT) and modelled maximum dynamic concentrations (cdynmax) using data derived from the Windermere Humic Aqueous Model (WHAM VII). Relationships between copper lability and copper toxicity were assessed as potential tools for predicting toxicity. Copper toxicity varied significantly with DOM concentration, source and season. Copper toxicity decreased with increasing concentrations of DOM, with 50% growth inhibition effect concentrations (EC50) increasing from 1.9 μg Cu/L in synthetic test waters with no added DOM (0.34 mg C/L) up to 63 μg Cu/L at DOM concentrations of 9.9 mg C/L. Copper toxicity varied by up to 2-fold between the three DOM sources and EC50 values were generally lower in the presence of wet season DOM compared to dry season DOM. Linear relationships between DGT-labile copper and dissolved copper were significantly different between DOM source, but not concentration or season. Modelled cdynmax consistently under-predicted labile copper in high DOM treatments compared to DGT measurements but performed better in low DOM treatments, indicating that this method is DOM-concentration dependent. Neither speciation method was a good surrogate for copper toxicity in the presence of different sources of natural DOM. Our findings show that DOM source and season, not just DOM concentration, affect copper toxicity to freshwater biota. Therefore, DOM quality should be considered as a toxicity-modifying factor for future derivation of bioavailability-based site-specific water quality guideline values.

Estimation of WHAM7 constants for GaIII, InIII, SbIII and BiIII from linear free energy relationships, and speciation calculations for natural waters

Environmental contextNatural organic matter exerts a powerful control on chemical conditions in waters and soils, affecting pH and influencing the biological availability, transport and retention of metals. Modelling can help to predict these effects, but for many metals, model parameters are missing. We report parameters for four technology-critical elements in a chemical speciation model, and consider the chemistries of the elements in natural waters. AbstractWe compiled the equilibrium constants for the interactions of the technology-critical elements (TCEs) GaIII, InIII, SbIII and BiIII with ammonia, fluoride, hydroxyl and ligands with oxygen atoms. We then combined them with predictive equations to estimate parameters for Humic Ion-Binding Model VII, which permits the calculation of metal binding by natural organic matter (fulvic acid, FA, and humic acid, HA). Derived values of the Model VII parameter quantifying the interaction of metal ions with carboxyl-type groups (log KMA) were among the highest estimated so far, as were the values for the parameter (ΔLK2) that quantifies the tendency of the metal ion to interact with softer ligand atoms (N and S). The Windermere Humic Aqueous Model, version 7 (WHAM7), which incorporates Model VII, was then used to estimate the chemical speciation of each TCE element.

Increased soil pH and dissolved organic matter after a decade of organic fertilizer application mitigates copper and zinc availability despite contamination

Long-term organic fertilizer (OF) application on agricultural soils is known to induce soil Cu and Zn contamination, along with pH and organic matter changes, which in turn alter the soil Cu and Zn availability. Our study was aimed at assessing Cu and Zn availability in long-term OF-amended soils by distinguishing the importance of increased contamination levels versus pH and organic matter changes in soil. Seventy-four soil samples were collected over time from fields corresponding to three soil types upon which no, mineral, or organic fertilization had been applied over a decade, and thus exhibited a gradient of Cu and Zn contamination, pH, and organic matter concentration. Soil Cu and Zn contamination (i.e. total and DTPA-extractable Cu and Zn concentration), soil solution chemistry (i.e. pH and dissolved organic matter concentration and aromaticity) and Cu and Zn availability (i.e. total concentration and free ionic activity in solution and DGT-available concentration in soil) levels were measured. The Windermere humic aqueous model (WHAM) was used to estimate Zn2+ activity and dissolved organic matter (DOM) binding properties in soil solution. Regardless of the soil type, organic fertilization increased Cu and Zn contamination in soil, in addition to the pH and the DOM concentration, aromaticity and binding properties in soil solution. The pH increase prompted a decrease in the total Zn concentration and Zn2+ activity in soil solution. The concomitant pH increase and DOM concentration, aromaticity and binding properties boosted the total Cu concentration but decreased the Cu2+ activity in soil solution. DGT-available Cu and Zn varied very little between the three fertilization modalities. Our results suggest that pH and DOM changes were able to regulate Cu and Zn availability in long-term OF amended soils by exerting a protective effect that offset the concomitant increase in soil Cu and Zn contamination.

Review: mine tailings in an African tropical environment-mechanisms for the bioavailability of heavy metals in soils.

Heavy metals are of environmental significance due to their effect on human health and the ecosystem. One of the major exposure pathways of Heavy metals for humans is through food crops. It is postulated in the literature that when crops are grown in soils which have excessive concentrations of heavy metals, they may absorb elevated levels of these elements thereby endangering consumers. However, due to land scarcity, especially in urban areas of Africa, potentially contaminated land around industrial dumps such as tailings is cultivated with food crops. The lack of regulation for land-usage on or near to mine tailings has not helped this situation. Moreover, most countries in tropical Africa have not defined guideline values for heavy metals in soils for various land uses, and even where such limits exist, they are based on total soil concentrations. However, the risk of uptake of heavy metals by crops or any soil organisms is determined by the bioavailable portion and not the total soil concentration. Therefore, defining bioavailable levels of heavy metals becomes very important in HM risk assessment, but methods used must be specific for particular soil types depending on the dominant sorption phases. Geochemical speciation modelling has proved to be a valuable tool in risk assessment of heavy metal-contaminated soils. Among the notable ones is WHAM (Windermere Humic Aqueous Model). But just like most other geochemical models, it was developed and adapted on temperate soils, and because major controlling variables in soils such as SOM, temperature, redox potential and mineralogy differ between temperate and tropical soils, its predictions on tropical soils may be poor. Validation and adaptation of such models for tropical soils are thus imperative before such they can be used. The latest versions (VI and VII) of WHAM are among the few that consider binding to all major binding phases. WHAM VI and VII are assemblages of three sub-models which describe binding to organic matter, (hydr)oxides of Fe, Al and Mn and clays. They predict free ion concentration, total dissolved ion concentration and organic and inorganic metal ion complexes, in soils, which are all important components for bioavailability and leaching to groundwater ways. Both WHAM VI and VII have been applied in a good number of soils studies with reported promising results. However, all these studies have been on temperate soils and have not been tried on any typical tropical soils. Nonetheless, since WHAM VII considers binding to all major binding phases, including those which are dominant in tropical soils, it would be a valuable tool in risk assessment of heavy metals in tropical soils. A discussion of the contamination of soils with heavy metals, their subsequent bioavailability to crops that are grown in these soils and the methods used to determine various bioavailable phases of heavy metals are presented in this review, with an emphasis on prospective modelling techniques for tropical soils.

Modeling kinetics of Ni dissociation from humic substances based on WHAM 7

Understanding the kinetics of Ni dissociation from dissolved organic matter (DOM) helps to better predict the fate and bioavailability of Ni ions in the environment. However, there is still a lack of predictive models for the kinetics of Ni dissociation from DOM under different reaction conditions. In this study, kinetics of Ni dissociation from humic acids (HA) and fulvic acids (FA), two most important components in DOM for Ni binding, was studied with a competing ligand exchange method at varying Ni concentrations, reaction pH, and ionic strength. The kinetic data were analyzed using a mechanistic kinetics model developed based on the Windermere Humic Aqueous Model (WHAM). Experimental results showed that Ni dissociation rates were affected by both Ni concentrations and pH, and Ni dissociation from FA had faster rates than that from HA. The kinetics model can reproduce the experimental data well, with only two model fitting parameters for different reaction conditions. The modeling results showed that various HA and FA binding sites played different roles in controlling Ni dissociation rates, with bidentate binding sites and the weak tridentate sites being the most significant. At high pH values the Ni re-association reactions were significant for controlling the overall rates of Ni dissociation but had minimal impact at lower pH values. Our model provided a modeling framework based on WHAM 7 for predicting Ni dissociation rates when humic substances were the dominant binding ligands.

Molecular characteristics, proton dissociation properties, and metal binding properties of soil organic matter: A theoretical study

Soil organic matter (SOM) is a key soil sorbent with a large number of reactive binding sites that may complex with metals, controlling their fate, transport, and bioavailability in soil. However, due to the complex and heterogeneous nature of SOM, it is not easy to probe its physical and chemical properties at the molecular level. In this study, an a priori method was developed to predict the molecular properties of SOM, which incorporated computational molecular modeling, SPARC Performs Automated Reasoning in Chemistry's (SPARC's) chemical reactivity models, and linear free energy relationships (LFERs). Specifically, the method uses SOM models simulated by molecular dynamics modeling based on the experimental elemental composition and functional group information of SOM. For the molecular characteristics, the molecular H/C and O/C ratios, molecular weight, aromatic index, and double bond equivalence of the SOM molecules were calculated. For the proton binding constants, the SPARC was used to calculate the microscopic pKa values of every binding sites of individual molecules of the SOM model. Based on the pKa values, the metal binding constants for individual monodentate binding sites were calculated using the Irving-Rossotti LFERs for different heavy metals. The results agreed reasonably with the default values used in the Windermere Humic Aqueous Model (WHAM) (VI) for the investigated metals. The theoretical SOM models, to some extent, represented the average properties of the investigated SOM. Overall, this study gives new quantitative and molecular insight into the structure and chemical properties of SOM. Detailed deprotonation and metal-SOM complexation information was gained for individual SOM binding sites. Such feasible and straightforward predictive scheme is useful to assess the risk of heavy metals in various aquatic and terrestrial environment involving heterogeneous natural organic matter.

Predicting Heavy Metal Partition Equilibrium in Soils: Roles of Soil Components and Binding Sites

Core Ideas WHAM 7 successfully predicted heavy metal partition in various soils. Major soil and solution parameters influenced the accuracy of model predictions. Soil organic matter dominated metal binding at most acidic to neutral pH in soils. WHAM 7 predicted bidentate binding as the dominant form of metal complexes. The reactivity and bioavailability of heavy metals in soils are controlled by their binding to reactive soil components, including soil organic matter (SOM), metal (hydr)oxides, and clay minerals. In this study, we specifically investigated how soil components and SOM binding sites controlled metal partition at various chemistry conditions. We used the Windermere Humic Aqueous Model (WHAM 7) to predict the solid‐solution partition and speciation of Cd, Cu, Ni, Pb, and Zn based on compiled literature data including 98 soil samples from five continents. Based on the root‐mean‐square‐error (RMSE) values of logarithm of dissolved metal concentrations between model predictions and experimental results, WHAM 7 reasonably predicted metal partition equilibrium over a wide range of reaction conditions, with RMSE less than 0.5 for Cd and Zn, and less than 1.0 for the other three metals. Soil organic matter dominated metal binding at most acidic to neutral pH, clay minerals were significant at low pH, and iron (hydr)oxides might effectively compete with SOM for metal binding when pH was high. For all five heavy metals, WHAM 7 predicted the bidentate bindings were the dominant form of metal complexes, in which both complexes formed by two carboxylic sites and that by one carboxylic and another phenolic sites were major complexes. The formation of monodentate complexes and electrostatic outer‐sphere complexes was significant at low pH, while tridentate complexes were only significant at high pH values. The modeling results help to accurately predict the environmental behavior of heavy metals in pH 3 to 7 soil environments.

Metal (Pb, Cd, and Zn) Binding to Diverse Organic Matter Samples and Implications for Speciation Modeling.

This study evaluated the influence of dissolved organic matter (DOM) properties on the speciation of Pb, Zn, and Cd. A total of six DOM samples were categorized into autochthonous and allochthonous sources based on their absorbance and fluorescence properties. The concentration of free metal ions ( CM2+) measured by titration using the absence of gradients and Nernstian equilibrium stripping (AGNES) method was compared with that predicted by the Windermere humic aqueous model (WHAM). At the same binding condition (pH, dissolved organic carbon, ionic strength, and total metal concentration) the allochthonous DOM showed a higher level of Pb binding than the autochthonous DOM (84- to 504-fold CPb2+ variation). This dependency, however, was less pronounced for Zn (12- to 74-fold CZn2+ variation) and least for Cd (2- to 14-fold CCd2+ variation). The WHAM performance was affected by source variation through the active DOM fraction ( F). The commonly used F = 1.3 provided reliable CPb2+ for allochthonous DOMs and acceptable CCd2+ for all DOM, but it significantly under-predicted CPb2+ and CZn2+ for autochthonous DOM. Adjusting F improved CM2+ predictions, but the optimum F values were metal-specific (e.g., 0.03-1.9 for Pb), as shown by linear correlations with specific optical indexes. The results indicate a potential to improve WHAM by incorporating rapid measurement of DOM optical properties for site-specific F.

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.

Trace metal speciation in a wastewater wetland and its bioaccumulation in tilapia Oreochromis niloticus

Trace metal species in the water column of a canal system forming a wetland filled with wastewater were analyzed to determine their correlation with metal accumulation in the gills of locally fished Oreochromis niloticus. The metal concentrations in the suspended particles and water dissolved were analyzed. The metal species were calculated using Windermere Humic Aqueous Model version VII showing that the high organic matter and major cation contents were important parameters. Also, the free ion metal concentration was expected to correlate with the organic matter aromaticity; however, organic compounds other than humic susbtances seem to be complexing the metals in the system. Additionally, no clear correlation could be found between metal accumulation in gills and any of the dissolved metal species. Nonetheless, certain trends could be seen between the calculated metal species and metal accumulation in the tilapia from the suspended particles.

Modelling toxicity of metal mixtures: A generalisation of new advanced methods, considering potential application to terrestrial ecosystems

ABSTRACTNo chemical properties have been found to be a reliable predictor of metal toxicity, attributed to the influence of various specific processes on metal toxicokinetics and toxicodynamics.Metal toxicity is affected by interactions between metal ions and of metals with organisms. The present review aims to provide an outlook on recent progress in estimating toxicity of metal mixtures. Three methods applied recently have the potential of accounting for the interactions between metals as well as the interactions of metals with organisms. The methods are based on the Biotic Ligand Model (BLM), electrostatic interactions, and Windermere Humic Aqueous Model (WHAM). These methods can be generalised to a common principle that affinity of metals for binding sites on sorption surfaces (i.e., biotic ligands on organisms, plasma membrane surface, and humic acid-surrogated biological surface) is a unifying factor for the biological response. The scientific basis for these approaches was reviewed in the present study, accompanied by a preliminary assessment on the toxicity of Cu2+, Ag+, Zn2+, and their binary mixtures to lettuce, Lactuca sativa, using previously published data. The difference in the predictive performance of the modelling approaches reflects the difference in the simulation of metal-ligand binding and is related to the specific exposure conditions considered.

Including the spatial variability of metal speciation in the effect factor in life cycle impact assessment: Limits of the equilibrium partitioning method.

In life cycle assessment (LCA), the potential terrestrial ecotoxicity effect of metals, calculated as the effect factor (EF), is usually extrapolated from aquatic ecotoxicological data using the equilibrium partitioning method (EqP) as it is more readily available than terrestrial data. However, when following the AMI recommendations (i.e. with at least enough species that represents three different phyla), there are not enough terrestrial data for which soil properties or metal speciation during ecotoxicological testing are specified to account for the influence of soil property variations on metal speciation when using this approach. Alternatively, the TBLM (Terrestrial Biotic Ligand Model) has been used to determine an EF that accounts for speciation, but is not available for metals; hence it cannot be consistently applied to metals in an LCA context. This paper proposes an approach to include metal speciation by regionalizing the EqP method for Cu, Ni and Zn with a geochemical speciation model (the Windermere Humic Aqueous Model 7.0), for 5213 soils selected from the Harmonized World Soil Database. Results obtained by this approach (EFEqPregionalized) are compared to the EFs calculated with the conventional EqP method, to the EFs based on available terrestrial data and to the EFs calculated with the TBLM (EFTBLMregionalized) when available. The spatial variability contribution of the EF to the overall spatial variability of the characterization factor (CF) has been analyzed. It was found that the EFsEqPregionalized show a significant spatial variability. The EFs calculated with the two non-regionalized methods (EqP and terrestrial data) fall within the range of the EFsEqPregionalized. The EFsTBLMregionalized cover a larger range of values than the EFsEqPregionalized but the two methods are not correlated. This paper highlights the importance of including speciation into the terrestrial EF and shows that using the regionalized EqP approach is not an acceptable proxy for terrestrial ecotoxicological data even if it can be applied to all metals.

Parameterizing the binding properties of dissolved organic matter with default values skews the prediction of copper solution speciation and ecotoxicity in soil.

Parameterizing speciation models by setting the percentage of dissolved organic matter (DOM) that is reactive (% r-DOM) toward metal cations at a single 65% default value is very common in predictive ecotoxicology. The authors tested this practice by comparing the free copper activity (pCu2+ = -log10 [Cu2+ ]) measured in 55 soil sample solutions with pCu2+ predicted with the Windermere humic aqueous model (WHAM) parameterized by default. Predictions of Cu toxicity to soil organisms based on measured or predicted pCu2+ were also compared. Default WHAM parameterization substantially skewed the prediction of measured pCu2+ by up to 2.7 pCu2+ units (root mean square residual = 0.75-1.3) and subsequently the prediction of Cu toxicity for microbial functions, invertebrates, and plants by up to 36%, 45%, and 59% (root mean square residuals ≤9 %, 11%, and 17%), respectively. Reparametrizing WHAM by optimizing the 2 DOM binding properties (i.e., % r-DOM and the Cu complexation constant) within a physically realistic value range much improved the prediction of measured pCu2+ (root mean square residual = 0.14-0.25). Accordingly, this WHAM parameterization successfully predicted Cu toxicity for microbial functions, invertebrates, and plants (root mean square residual ≤3.4%, 4.4%, and 5.8%, respectively). Thus, it is essential to account for the real heterogeneity in DOM binding properties for relatively accurate prediction of Cu speciation in soil solution and Cu toxic effects on soil organisms. Environ Toxicol Chem 2017;36:898-905. © 2016 SETAC.