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Predicting the association of contaminants with particulate organic matter in the environment is critical in determining the fate and bioavailability of chemicals. A ubiquitous measure of contaminant association with soil and sediment particulate organic matter is the organic carbon partition coefficient K(OC) . Chemical class-specific models relating the K(OC) to the octanol-water partition coefficient K(OW) have been used to predict the partitioning to organic carbon in the water column and sediment for nonpolar hydrophobic pollutants and some polar pollutants. A single linear solvation energy relationship (LSER) is proposed as a simpler and chemically based alternative for predicting K(OC) for a more diverse set of compounds. A chemically diverse set of K(OC) data is used to obtain a more robust and more universally representative model of organic carbon partitioning than previously available LSER models. The resulting model has a root mean square error (RMSE) of prediction for log K(OC) of RMSE = 0.48 for the fitted data set and RMSE = 0.55 for an independent data set. An analysis of LSER coefficients highlights the relative importance of hydrogen bonding interactions., (Copyright © 2011 SETAC.)

Predicting the association of contaminants with both particulate and dissolved organic matter is critical in determining the fate and bioavailability of chemicals in environmental risk assessment. To date, the association of a contaminant to particulate organic matter is considered in many multimedia transport models, but the effect of dissolved organic matter is typically ignored due to a lack of either reliable models or experimental data. The partition coefficient to dissolved organic carbon (K(DOC)) may be used to estimate the fraction of a contaminant that is associated with dissolved organic matter. Models relating K(DOC) to the octanol-water partition coefficient (K(OW)) have not been successful for many types of dissolved organic carbon in the environment. Instead, linear solvation energy relationships are proposed to model the association of chemicals with dissolved organic matter. However, more chemically diverse K(DOC) data are needed to produce a more robust model. For humic acid dissolved organic carbon, the linear solvation energy relationship predicts log K(DOC) with a root mean square error of 0.43., (Copyright © 2011 SETAC.)

The tableau input coupled kinetic equilibrium transport-unit world model (TICKET-UWM) has been developed as a screening model for assessing potential environmental risks associated with the release of metals into lakes. The model is based on a fully implicit, one-step solution algorithm that allows for simultaneous consideration of dissolved and particulate phase transport; metal complexation to organic matter and inorganic ligands; precipitation of metal hydroxides, carbonates, and sulfides; competitive interactions of metals and major cations with biotic ligands; a simplified description of biogeochemical cycling of organic carbon and sulfur; and dissolution kinetics for metal powders, massives, and other solid forms. Application of TICKET-UWM to a generalized lake in the Sudbury area of the Canadian Shield is presented to demonstrate the overall cycling of metals in lakes and the nonlinear effects of chemical speciation on metal responses. In addition, the model is used to calculate critical loads for metals, with acute toxicity of Daphnia magna as the final endpoint. Model results show that the critical loads for Cu, Ni, Pb, and Zn varied from 2.5 to 39.0 g metal/m(2) -year and were found to be one or more orders of magnitude higher than comparable loads for pesticides (lindane, 4,4'-DDT) and several polyaromatic hydrocarbon (PAH) compounds. In sensitivity calculations, critical metal-loading rates were found to vary significantly as a function of the hydraulic detention time, water hardness, and metal dissolution kinetic rates., (Copyright © 2011 SETAC.)

Stability constants for metal complexation to bidentate ligands containing negatively-charged oxygen donor atoms can be estimated from the following linear free energy relationship (LFER): log K(ML) = χ(OO)(α(O) log K(HL,1) + α(O) log K(HL,2)) where K(ML) is the metal-ligand stability constant for a 1:1 complex, K(HL,1) and K(HL,2) are the proton-ligand stability constants (the ligand pK(a) values), and α(O) is the Irving-Rossotti slope. The parameter χ(OO) is metal specific and has slightly different values for 5 and 6 membered chelate rings. LFERs are presented for 21 different metal ions and are accurate to within approximately 0.30 log units in predictions of log K(ML) values. Ligands selected for use in LFER development include dicarboxylic acids, carboxyphenols, and ortho-diphenols. For ortho-hydroxybenzaldehydes, α-hydroxycarboxylic acids, and α-ketocarboxylic acids, a modification of the LFER where log K(HL,2) is set equal to zero is required. The chemical interpretation of χ(OO) is that it accounts for the extra stability afforded to metal complexes by the chelate effect. Cu-NOM binding constants calculated from the bidentate LFERs are similar in magnitude to those used in WHAM 6. This LFER can be used to make log K(ML) predictions for small organic molecules. Since natural organic matter (NOM) contains many of the same functional groups (i.e. carboxylic acids, phenols, alcohols), the LFER log K(ML) predictions shed light on the range of appropriate values for use in modeling metal partitioning in natural systems.

The soil sorption coefficient, K(OC), is an important property affecting the environmental fate of organic molecules. Difficulties associated with measuring K(OC) have led to many attempts to predict this property, but most rely on empirical descriptors for the soil phase determined from correlations with measured K(OC) data, and are thereby limited by the data quality and diversity. A new method is presented to predict K(OC) for nonionic organic compounds that requires only molecular structures. No calibration is performed. Using model humic acid (HA) and fulvic acid (FA) molecular structures from the literature, the soil organic matter is modeled as an organic solvent composed of HA or FA molecules. K(OC) is predicted as an organic solvent-water partition coefficient using the quantum mechanics-based model COSMO-SAC. The log K(OC) values for a set of 440 diverse, environmentally relevant chemicals are predicted with a root-mean-square error of 0.84-1.08, depending on which model HA or FA is used.

A method is presented for extending the target lipid model (TLM) of narcotic toxicity to polar narcotic chemicals. The proposed polyparameter TLM extends the applicability of the TLM by including polar compounds and removing explicit chemical class corrections. The validity of the model is tested using a data set of 1,687 acute toxicity tests for 42 aquatic species, including fish, amphibians, arthropods, mollusks, polychaetes, coelenterates, protozoans, and algae, and 398 chemicals. The target lipid-water partition coefficient is computed using the Abraham polyparameter model. This replaces use of the octanol-water partition coefficient so that the partitioning of polar narcotic chemicals can be described correctly. The model predicts the log median lethal concentration with a root mean square error of 0.460 for nonpolar and polar chemicals and 0.501 for only polar chemicals.

A method is presented for developing scientifically defensible, numeric guidelines for residual petroleum-related constituents, specifically monocyclic aromatic hydrocarbons (MAHs) and polycyclic aromatic hydrocarbons (PAHs), in the water column. The guidelines are equivalent to a HC5 (i.e., hazard concentration to 5% of the tested species, or the concentration that protects 95% of the tested species). The model of toxicity used in this evaluation is the target lipid model (TLM) that was developed for assessing the toxicity of type I narcotic chemicals. An acute to chronic ratio is used for chronic expression and sublethal effects. The TLM is evaluated by comparing predicted and observed toxicity of these petroleum components. The methodology is capable of predicting both the acute and chronic toxicity of MAHs and PAHs in single exposures and in mixtures. For acute exposures, the TLM was able to predict the toxicity to within a factor of three to five. The use of toxic units was an effective metric for expressing the toxicity of mixtures. Within the uncertainty bounds, the TLM correctly predicted where sublethal effects of edemas, hemorrhaging, and other abnormalities were observed to occur in early life-stage exposure to PAHs. The computed HC5s were lower than no-observed-effect concentrations based on growth, reproduction, and mortality endpoints and sublethal effects. The methodology presented can be used by the oil spill community to compare residual concentrations of PAHs against defensible, numeric guidelines to assess potential ecological impacts.

The intrinsic proton binding constants of 10 model humic acid and six model fulvic acid molecules are calculated using SPARC Performs Automated Reasoning in Chemistry (SPARC). The accuracy of the SPARC calculations is examined using estimated microscopic binding constants of various small organic acids. An equimolar mixture of the appropriate hypothetical molecules is used as a representation of soil and aqueous humic acid and fulvic acid. The probability distributions of the mixture microscopic proton binding constants and the intrinsic proton binding constants in the metal speciation models WHAM V and WHAM VI (Windermere humic aqueous models) are compared. The idea is to assess the predictive value of the molecular mixture models as representations of heterogeneous natural organic matter. For aqueous humic and fulvic acids, the results are comparable to the WHAM distribution. For soil humic acid, the WHAM probability distribution is less acidic for the carboxylic sites but similar to that of the phenolic sites. Computations made using the WHAM molecular distributions and WHAM VI are comparable to titration data for Suwannee River fulvic acid. These results suggest that mixture molecular models can be used to investigate and predict the binding of metal cations to humic and fulvic acids.

The Henry's law constants (HLCs) for all 209 polychlorinated biphenyl (PCB) congeners were predicted at 25 degrees C using the quantum mechanical (QM) continuum solvation models COSMO-SAC and SM6, and trends were examined. COSMO-SAC HLCs were also predicted for all congeners at 4, 11, 18, and 31 degrees C. The temperature dependences of the HLCs were used to calculate enthalpy of solvation (deltaHs) values. At 25 degrees C, COSMO-SAC and SM6 predicted similar values of the HLC, which are consistent with all but one of the available sets of measurements, and have smaller root-mean-square prediction errors than other models tested. This supports the validity of the QM values, and the recommendation of their use in environmental transport and fate models. Intercongener trends in the HLCs appear to be dominated by the strength of PCB-water polar interactions. The COSMO-SAC predictions between 4 and 31 degrees C indicate that the temperature dependence of the HLC is similar for all congeners. At low temperatures, the HLC predictions for several heavy congeners are substantially higher than recently reported measurements, supporting claims in the literature that these low-temperature data are inaccurate.

Statistical error distributions for enthalpies of formation as predicted by 18 different density functionals have been analyzed using a test set of 675 molecules. Systematic errors, dependent on the number of valence electrons, have been identified for some functionals. A simple empirical correction makes a significant improvement in the prediction error for these single functionals. Linear combinations of enthalpy estimates from different density functionals are identified that exploit the error correlations among the functionals and allow for further improvements in the accuracy of thermodynamic predictions. A good compromise between accuracy and computational efforts is achieved by the BLUE (best linear unbiased estimator) combination of three functionals, B3LYP, BLYP, and VSXC (polyfunctional 3 or PF3). The PF3 method has a mean absolute deviation (MAD) from experiment of 2.4 kcal/mol on the G3 set of 271 molecules. This can be compared to the MAD of 4.9 kcal/mol for B3LYP and 1.2 kcal/mol for the more costly G3 method. On the larger set of 675 molecules, the MAD for PF3 is 3.0 kcal/mol. Opportunities for further improvements in the accuracy of this method are discussed.

A novel model has been developed to describe the kinetics of Zn adsorption and desorption to soils. The model incorporates the mechanistic-based equilibrium model WHAM (Windermere humic aqueous model) to account for the chemical variation during the reaction (e.g., pH and Zn2+ concentration), the heterogeneity of binding sites of soil organic matter (SOM), and the nonlinear binding of Zn to SOM. To test the model, kinetic experiments were conducted using a stirred-flow method. Six soils, with low clay fractions and covering a wide range in SOM concentrations, and various Zn concentrations and pHs were studied. Under these experimental conditions, SOM is found to be the major adsorbent for Zn binding. The fast and slow Zn reactions with soils were associated, respectively, with the monodentate and bidentate binding sites of humic substances in WHAM. The model has only three fitting parameters, the two desorption rate coefficients for the fast (monodentate) and slow (bidentate) reaction sites which are constant and independent of soil type, and the reactive organic matter fraction of the total SOM in each soil. All other parameters are derived from WHAM. The model is able to predict Zn release from spiked soils including the effects of Ca competition.

Recent laboratory investigations into the bioaccumulation and toxicity of polycyclic aromatic hydrocarbons (PAH) have focused on low-level, time-variable exposures to early life-stage fish. Polycyclic aromatic hydrocarbon body-burden residues reported in these studies were lower than critical body-burden residues predicted by the target lipid model (TLM). To understand this discrepancy, a time-variable uptake and depuration model of PAH bioaccumulation was developed. Kinetic constants were fit using measured exposure and tissue concentrations. The resulting lipid-water partition coefficients (K(LW)) were uncorrelated with the octanol-water partition coefficient (K(OW))--a qualitatively unrealistic finding considering that numerous studies have reported a positive correlation between the two. Because PAHs are known to be metabolized, the comparison of K(LW) with K(OW) suggests that metabolism may be occurring in early life-stage fish. Therefore, the uptake and depuration model was modified to include metabolism while assuming linearity of K(LW) with K(OW). Calculated metabolism rates were positively correlated with K(OW)--a finding qualitatively similar to those of other studies. The present study provides a reasonable explanation for the discrepancy between the TLM predictions and the measured toxic effect levels. Given the time-variable exposure concentrations, the maximum measured body burdens used to relate to toxic effects may be underestimated. In addition, the maximum body burden of parent PAH plus metabolites may be a better measure in relating tissue concentrations to toxic effects. Incorporating these refinements in relating body burdens to toxic effects may result in a better comparison between TLM predictions and measured effect levels.

Cadmium (Cd) adsorption on 14 non-calcareous New Jersey soils was investigated with a batch method. Both adsorption edge and isotherm experiments were conducted covering a wide range of soil composition, e.g. soil organic carbon (SOC) concentration ranging from 0.18% to 7.15%, and varying Cd concentrations and solution pH. The SOC and solution pH were the most important parameters controlling Cd partition equilibrium between soils and solutions in our experimental conditions. The Windermere humic aqueous model (WHAM) was used to calculate Cd adsorption on soils. The effect of solution chemistry (various pH and Cd concentrations) on Cd adsorption can be well accounted for by WHAM. For different soil compositions, SOC concentration is the most important parameter for Cd binding. Only a fraction of SOC, the so-called active organic carbon (AOC), is responsible for Cd binding. We found a linear relationship between SOC and AOC based on the adsorption edge data. The linear relationship was validated by the independent data sets: adsorption isotherm data, which presumably can be used to predict Cd partition equilibrium across a wide range of soil compositions. The modeling approach presented in this study helps to quantitatively predict Cd behavior in the environment.

The toxicity of oils can be understood using the concept of toxic potential, or the toxicity of each individual component of the oil at the water solubility of that component. Using the target lipid model to describe the toxicity and the observed relationship of the solubility of oil components to log (Kow), it is demonstrated that components with lower log (Kow) have greater toxic potential than those with higher log (Kow). Weathering removes the lower-log (Kow) chemicals with greater toxic potential, leaving the higher-log (Kow) chemicals with lower toxic potential. The replacement of more toxically potent compounds with less toxically potent compounds lowers the toxicity of the aqueous phase in equilibrium with the oil. Observations confirm that weathering lowers the toxicity of oil. The idea that weathering increases toxicity is based on the erroneous use of the total petroleum hydrocarbons or the total polycyclic aromatic hydrocarbons (PAHs) concentration as if either were a single chemical that can be used to gauge the toxicity of a mixture, regardless of its makeup. The toxicity of the individual PAHs that comprise the mixture varies. Converting the concentrations to toxic units (TUs) normalizes the differences in toxicity. A concentration of one TU resulting from the PAHs in the mixture implies toxicity regardless of the specific PAHs that are present. However, it is impossible to judge whether 1 microg/L of total PAHs is toxic without knowing the PAHs in the mixture. The use of toxic potential and TUs eliminates this confusion, puts the chemicals on the same footing, and allows an intuitive understanding of the effects of weathering.

A Terrestrial Biotic Ligand Model (TBLM) was developed using noncalcareous soils from Europe based on Cu and Ni speciation and barley (Hordeum vulgare cv. Regina) root elongation bioassays. Free metal ion (M2+) activity was computed by the WHAM VI model using inputs of soil metal, soil organic matter, and alkali and alkaline earth metals concentrations, and pH in soil solution. The TBLM assumes that metal in soil and in the solution are in equilibrium. Metal ions react with the biotic ligand, the receptor site, and inhibit root elongation. Other ions, principally H+, Ca2+ and Mg2+, compete with M2+ and, therefore, affect its toxicity. Toxicity is correlated only to the fraction of the total biotic ligand sites occupied by M2+. Compared to other models using either the soil metal concentration or M2+ activity as the toxic dose, the TBLM provides a more consistent method to normalize and compare Cu and Ni toxicities to root elongation among different soils. The TBLM was able to predictthe EC50 soil Cu and Ni concentrations generally within a factor of 2 of the observed values, a level of precision similar to that for the aquatic Biotic Ligand Model, indicating its potential utility in metals risk assessment in soils.

The Terrestrial Biotic Ligand Model (TBLM) is applied to a number of noncalcareous soils of the European Union for Cu and Ni toxicities using organisms and endpoints representing three levels of terrestrial organisms: higher plants, invertebrates, and microbes. A comparison of the TBLM predictions to soil metal concentration or free metal ion activity in the soil solution shows that the TBLM is able to achieve a better normalization of the wide variation in toxicological endpoints among soils of disparate properties considered in this study. The TBLM predictions of the EC50s were generally within a factor of 2 of the observed values. To our knowledge, this is the first study that incorporates Cu and Ni toxicities to multiple endpoints associated with higher plants, invertebrates, and microbes for up to eleven noncalcareous soils of disparate properties, into a single theoretical framework. The results of this study clearly demonstrate that the TBLM can provide a general framework for modeling metals ecotoxicity in soils.

Soluble nickel compounds are carcinogenic to humans although the mechanism by which they cause cancer remains unclear. One major consequence of exposure to nickel is the stabilization of hypoxia inducible factor-1alpha (HIF-1alpha), a protein known to be overexpressed in a variety of cancers. In this study, we report a persistent stabilization of HIF-1alpha by nickel chloride up to 72 h after the removal of nickel from the culture media. In addition, we show that the HIF-prolyl hydroxylases (PHD's) are inhibited when cells are exposed to nickel and that they remain repressed for up to 72 h after nickel is removed. We then show that nickel can inhibit purified HIF-PHD's 2 in vitro, through direct interference with the enzyme. Through theoretical calculations, we also demonstrate that nickel may be able to replace the iron in the active site of this enzyme, providing a plausible mechanism for the persistent inhibition of HIF-PHD's by nickel. The data presented suggest that nickel can interfere with HIF-PHD directly and does not inhibit the enzyme by simply depleting cellular factors, such as iron or ascorbic acid. Understanding the mechanisms by which nickel can inhibit HIF-PHD's and stabilize HIF-1alpha may be important in the treatment of cancer and ischemic diseases.

Copper partitioning at moisture content of 1.2-fold the field moisture capacity (corresponding to a soil water potential of 7.84 J/kg; pF = 1.9) was studied in 11 soils with pH 3.4 to 6.8 and an organic matter content of 4.1 to 233 g C/kg. Soil solutions were separated with the centrifuge method and analyzed to determine pH, Cu2+ activity, dissolved organic carbon, and Cu, Ca, Mg, and Na concentrations. Soil organic matter content, total Cu content, and soil pH were the main variables explaining variation in Cu activity in soil solutions. Based on total Cu, soil organic matter content, and soil solution pH, the Windermere Humic Aqueous Model (WHAM) VI assemblage model provided estimates of Cu2+ activity, {Cu2}, with a root mean square error of the predicted pCu (i.e., -log{Cu2+}) of 0.77.

Arsenic contamination in aquatic systems is a worldwide concern. Understanding the redox cycling of arsenic in sediments is critical in evaluating the fate of arsenic in aquatic environments and in developing sediment quality guidelines. The direct oxidation of inorganic trivalent arsenic, As(III), by dissolved molecular oxygen has been studied and found to be quite slow. A chemical pathway for As(III) oxidation has been proposed recently in which a radical species, Fe(IV), produced during the oxidation of divalent iron, Fe(II), facilitates the oxidation of As(III). Rapid oxidation of As(III) was observed (on a time scale of hours) in batch systems at pH 7 and 7.5, but the extent of As(III) oxidation was limited. The Fe(II)-catalyzed oxidation of As(III) is examined in a sediment column using both computational and experimental studies. A reactive-transport model is constructed that incorporates the complex kinetics of radical species generation and Fe(II) and As(III) oxidation that have been developed previously. The model is applied to experimental column data. Results indicate that the proposed chemical pathway can explain As(III) oxidation in sediments and that transport in sediments plays a vital role in increasing the extent of As(III) oxidation and efficiency of the Fe(II) catalysis.

In sediments that contain iron monosulfide, cadmium, nickel, lead, zinc, and silver(I) form insoluble metal sulfides that lower the metal ion activity in the sediment-pore water system, thereby reducing toxicity. However, metal sulfides are susceptible to oxidation by molecular oxygen resulting in metal solubilization. To better understand the sources and sinks of metal sulfides in sediments, iron monsulfide-rich freshwater sediments were spiked with cadmium, nickel, lead, zinc, or silver(I) and placed into cylindrical cores with an overlying layer of oxygen-saturated water. Measurements of the dissolved metal concentration in the overlying water were made as a function of time and the vertical profiles of acid-volatile sulfide (AVS) and simultaneously extracted metal (SEM) were measured after 150 d. A one-dimensional reactive and transport model has been employed to help elucidate processes controlling the fate of metals in sediments. The model incorporates metal-sulfide formation, metal-sulfide oxidation, and metal partitioning onto sediment organic carbon and iron oxyhydroxide to simulate the vertical transport of metals throughout the sediment core.

Ionic silver is toxic to aquatic organisms at low concentrations. However, complexation to binding sites on natural organic matter has been shown to reduce silver toxicity. Research indicates that there is a need to develop reliable methods for characterizing silver binding at very low silver ion concentrations where strong binding sites have a significant influence on silver speciation. This study provides an analytical method for measuring silver binding using a solubility-enhancement procedure. Preliminary experimental results are provided that demonstrate strong silver binding in the presence of natural organic matter at very low silver ion concentrations.

An extension of the simultaneously extracted metals/acid-volatile sulfide (SEM/AVS) procedure is presented that predicts the acute and chronic sediment metals effects concentrations. A biotic ligand model (BLM) and a pore water-sediment partitioning model are used to predict the sediment concentration that is in equilibrium with the biotic ligand effects concentration. This initial application considers only partitioning to sediment particulate organic carbon. This procedure bypasses the need to compute the details of the pore-water chemistry. Remarkably, the median lethal concentration on a sediment organic carbon (OC)-normalized basis, SEM*(x,OC), is essentially unchanged over a wide range of concentrations of pore-water hardness, salinity, dissolved organic carbon, and any other complexing or competing ligands. Only the pore-water pH is important. Both acute and chronic exposures in fresh- and saltwater sediments are compared to predictions for cadmium (Cd), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) based on the Daphnia magna BLM. The SEM*(x,OC) concentrations are similar for all the metals except cadmium. For pH = 8, the approximate values (micromol/gOC) are Cd-SEM*(xOC) approximately equal to 100, Cu-SEM*(x,OC) approximately equal to 900, Ni-SEMoc approximately equal to 1,100, Zn-SEM*(x,OC) approximately equal to 1,400, and Pb-SEM*(x,OC) approximately equal to 2,700. This similarity is the explanation for an empirically observed dose-response relationship between SEM and acute and chronic effects concentrations that had been observed previously. This initial application clearly demonstrates that BLMs can be used to predict toxic sediment concentrations without modeling the pore-water chemistry.

The narcosis target lipid model (NTLM) was used to predict the toxicity of water-accommodated fractions (WAFs) of six gasoline blending streams to algae (Pseudokirchnereilla subcapitata, formerly Selenastrum capricornutum), juvenile rainbow trout (Oncorhynchus mykiss), and water flea (Daphnia magna). Gasolines are comprised of hydrocarbons that on dissolution into the aqueous phase are expected to act via narcosis. Aquatic toxicity data were obtained using a lethal-loading test in which WAFs were prepared using different gasoline loadings. The compositions of the gasolines were determined by analysis of C3 to C13 hydrocarbons grouped in classes of n-alkanes, iso-alkanes, aromatics, cyclic alkanes, and olefins. A model was developed to compute the concentrations of hydrocarbon blocks in WAFs based on gasoline composition and loading. The model accounts for the volume change of the gasoline, which varies depending on loading and volatilization loss. The predicted aqueous composition of WAFs compared favorably to measurements, and the predicted aqueous concentrations of WAFs were used in the NTLM to predict the aquatic toxicity of the gasolines. For each gasoline loading and species, total toxic units (TUs) were computed with an assumption of additivity. The acute toxicity of gasolines was predicted to within a factor of two for algae and daphnids. Predicted TUs overestimated toxicity to trout because of experimental factors that were not considered in the model. This analysis demonstrates the importance of aliphatic hydrocarbon loss to headspace during WAF preparation and the contribution of both aromatic and aliphatic hydrocarbons test to the toxicity of gasolines in closed systems and loss of aliphatics to headspace during WAF preparation. Model calculations indicate that satisfactory toxicity predictions can be achieved by describing gasoline composition using a limited number of aromatic and aliphatic hydrocarbon blocks with different octanol-water partition coefficients.

Kinetics of Cu and Zn release from soil particles was studied using two surface soils with a stirred-flow method. Different solution pH, dissolved organic matter (DOM) concentrations, and flow rates were tested in this study. A model for kinetics controlled sorption/desorption reactions between soils and solutions was globally fit to all experimental data simultaneously. Results were compared to a model that assumes local instantaneous equilibrium. We obtained one unique set of model parameters applicable to different pH, dissolved organic carbon (DOC), and flow conditions. We included DOM complexation of copper ions, which decreased their sorption. The effect of pH was included by assuming proton competition with metal ions for binding sites on soil particles. These results provide the basis for developing predictive models for metal release from soil particles to surface waters and soil solution.

The Challenger mechanism for the methylation of arsenic is a repeating sequence of a two-electron reduction of pentavalent arsenic As(V) species to trivalent arsenic As(III) species followed by a methylation-oxidation reaction forming the successive methyl As(V) species. This unusual oxidation-reduction sequence prompted an examination of the thermodynamics of these reactions. Quantum chemical methods are employed to estimate the thermodynamic parameters for the methyl arsenic species. The sequence is thermodynamically favored at neutral pH for redox potentials with pe < 0 and methyl cation activities pCH3+ < -3 to -7 depending on the precise situation analyzed. The observed distribution of methyl arsenic species in human urine, which is remarkably constant across many studied populations, can be reproduced using an equilibrium model if the formation of TMA species is prevented. The estimated thermodynamic parameters are sufficiently accurate to evaluate questions of thermodynamic plausibility but not the precise details of speciation.

The narcosis target lipid model (TLM) was developed to predict the toxicity of chemicals to aquatic organisms that act via narcosis. It is based on the hypothesis that target lipid is the site of toxic action within the organism, that octanol is the appropriate surrogate, and that target lipid has the same physical-chemical properties in all organisms. Here the TLM is extended to available freshwater green algal toxicity data to support a narcosis toxic mode-of-action (TMoA) effect assessment. For each species, significant linear relationships were observed between log(median effective concentration [EC50]) and log(Kow) of the test chemicals. The slope of the log-log relationship statistically was similar to the universal narcosis slope of -0.945 that was derived from an earlier analysis of the TLM to nonalgal species. Critical target lipid body burdens (CTLBB), C(L)* were estimated for each algal species from the intercepts of the regressions and found to be within the range (43-398 micromol/g octanol) reported previously, indicating that algae exhibit a similar sensitivity distribution relative to other aquatic species. The TLM is used to derive the predicted-no-effect concentrations (PNECs) using the hazardous concentration to 5% species (HC5) statistical extrapolation procedure. This calculation requires an analysis of the variability of the universal slope, the C(L)*, and the acute-to-chronic ratio. The PNECs derived using this procedure were consistent with chronic-no-effect concentrations reported for narcotic chemicals. This is in contrast to PNECs derived from limited chemical-specific toxicity data and default application factors. It is concluded that coupling the TLM to the HC5 extrapolation procedure allows optimal use of available toxicity data for deriving environmental quality criteria with a narcotic TMoA.

Soluble arsenic(III)-sulfide complexes (thioarsenites) play a significant role in the chemistry of arsenic in reducing, sulfidic environments at circumneutral pH. Chemical equilibrium calculations using thioarsenite thermodynamic data from the literature indicate that the formation of a dithioarsenite complex, AsS(OH)(SH)(-1), reduces the concentration of the uncomplexed inorganic As(III) species present (defined sigma H3AsO3, where sigma H3AsO3 = AsO3(-3) + HAsO3(-2) + H2AsO3(-1) + H3AsO3). With enough sulfide present, soluble As(III) is dominated by this complex. Therefore, it is of interest to examine the effect of dithioarsenite formation on As(III) toxicity. The Microtox acute toxicity test was used for this purpose. Tests performed on solutions with varying S:As ratios indicate that As(III) toxicity is a function of the uncomplexed As(III) concentration rather than the total As(III) concentration. This suggests that the dithioarsenite species is not bioavailable and that its formation reduces As(III) toxicity. Chemical equilibrium calculations and sediment pore-water field data from various sources indicate that, in many sediments, dithioarsenite formation can reduce toxicity.

Chemical speciation controls the bioavailability and toxicity of metals in aquatic systems and regulatory agencies are recognizing this as they develop updated water quality criteria (WQC) for metals. The factors that affect bioavailability may be quantitatively evaluated with the biotic ligand model (BLM). Within the context of the BLM framework, the 'biotic ligand' is the site where metal binding results in the manifestation of a toxic effect. While the BLM does account for the speciation and complexation of dissolved metal in solution, and competition among the free metal ion and other cations for binding sites at the biotic ligand, it does not explicitly consider either the physiological effects of metals on aquatic organisms, or the direct effect of water chemistry parameters such as pH, Ca(2+)and Na(+) on the physiological state of the organism. Here, a physiologically-based model of survival time is described. In addition to incorporating the effects of water chemistry on metal availability to the organism, via the BLM, it also considers the interaction of water chemistry on the physiological condition of the organism, independent of its effect on metal availability. At the same time it explicitly considers the degree of interaction of these factors with the organism and how this affects the rate at which cumulative damage occurs. An example application of the model to toxicity data for rainbow trout exposed to silver is presented to illustrate how this framework may be used to predict survival time for alternative exposure durations. The sodium balance model (SBM) that is described herein, a specific application of a more generic ion balance model (IBM) framework, adds a new physiological dimension to the previously developed BLM. As such it also necessarily adds another layer of complexity to this already useful predictive framework. While the demonstrated capability of the SBM to predict effects in relation to exposure duration is a useful feature of this mechanistically-based framework, it is envisioned that, with suitable refinements, it may also have utility in other areas of toxicological and regulatory interest. Such areas include the analysis of time variable exposure conditions, residual after-effects of exposure to metals, acclimation, chronic toxicity and species and genus sensitivity. Each of these is of potential utility to longer-term ongoing efforts to develop and refine WQC for metals.

During recent years, the biotic ligand model (BLM) has been proposed as a tool to evaluate quantitatively the manner in which water chemistry affects the speciation and biological availability of metals in aquatic systems. This is an important consideration because it is the bioavailability and bioreactivity of metals that control their potential to cause adverse effects. The BLM approach has gained widespread interest amongst the scientific, regulated and regulatory communities because of its potential for use in developing water quality criteria (WQC) and in performing aquatic risk assessments for metals. Specifically, the BLM does this in a way that considers the important influences of site-specific water quality. This journal issue includes papers that describe recent advances with regard to the development of the BLM approach. Here, the current status of the BLM development effort is described in the context of the longer-term history of advances in the understanding of metal interactions in the environment upon which the BLM is based. Early developments in the aquatic chemistry of metals, the physiology of aquatic organisms and aquatic toxicology are reviewed first, and the degree to which each of these disciplines influenced the development of water quality regulations is discussed. The early scientific advances that took place in each of these fields were not well coordinated, making it difficult for regulatory authorities to take full advantage of the potential utility of what had been learned. However, this has now changed, with the BLM serving as a useful interface amongst these scientific disciplines, and within the regulatory arena as well. The more recent events that have led to the present situation are reviewed, and consideration is given to some of the future needs and developments related to the BLM that are envisioned. The research results that are described in the papers found in this journal issue represent a distinct milestone in the ongoing evolution of the BLM approach and, more generally, of approaches to performing ecological assessments for metals in aquatic systems. These papers also establish a benchmark to which future scientific and regulatory developments can be compared. Finally, they demonstrate the importance and usefulness of the concept of bioavailability and of evaluative tools such as the BLM.

The biotic ligand model (BLM) was developed to explain and predict the effects of water chemistry on the acute toxicity of metals to aquatic organisms. The biotic ligand is defined as a specific receptor within an organism where metal complexation leads to acute toxicity. The BLM is designed to predict metal interactions at the biotic ligand within the context of aqueous metal speciation and competitive binding of protective cations such as calcium. Toxicity is defined as accumulation of metal at the biotic ligand at or above a critical threshold concentration. This modeling framework provides mechanistic explanations for the observed effects of aqueous ligands, such as natural organic matter, and water hardness on metal toxicity. In this paper, the development of a copper version of the BLM is described. The calibrated model is then used to calculate LC50 (the lethal concentration for 50% of test organisms) and is evaluated by comparison with published toxicity data sets for freshwater fish (fathead minnow, Pimephales promelas) and Daphnia.

The biotic ligand model (BLM) of acute metal toxicity to aquatic organisms is based on the idea that mortality occurs when the metal-biotic ligand complex reaches a critical concentration. For fish, the biotic ligand is either known or suspected to be the sodium or calcium channel proteins in the gill surface that regulate the ionic composition of the blood. For other organisms, it is hypothesized that a biotic ligand exists and that mortality can be modeled in a similar way. The biotic ligand interacts with the metal cations in solution. The amount of metal that binds is determined by a competition for metal ions between the biotic ligand and the other aqueous ligands, particularly dissolved organic matter (DOM), and the competition for the biotic ligand between the toxic metal ion and the other metal cations in solution, for example, calcium. The model is a generalization of the free ion activity model that relates toxicity to the concentration of the divalent metal cation. The difference is the presence of competitive binding at the biotic ligand, which models the protective effects of other metal cations, and the direct influence of pH. The model is implemented using the Windermere humic aqueous model (WHAM) model of metal-DOM complexation. It is applied to copper and silver using gill complexation constants reported by R. Playle and coworkers. Initial application is made to the fathead minnow data set reported by R. Erickson and a water effects ratio data set by J. Diamond. The use of the BLM for determining total maximum daily loadings (TMDLs) and for regional risk assessments is discussed within a probabilistic framework. At first glance, it appears that a large amount of data are required for a successful application. However, the use of lognormal probability distributions reduces the required data to a manageable amount.