Linear Free Energy Relationships for Metal-Ligand Complexation: Bidentate Binding to Negatively-Charged Oxygen Donor Atoms

Unravelling the impacts of soluble Mn(III)-NOM on arsenic immobilization by ferrihydrite or goethite under aquifer conditions

The environmental fate of arsenic (As) relies substantially on its speciation, which occurs frequently coupled to the redox transformation of manganese. While trivalent manganese (Mn(III)), which is known for its high reactivity, is believed to play a role in As mobilization by iron (oxyhydr)oxides in dynamic aquifers, the exact roles and underlying mechanisms are still poorly understood. Using increasingly complex batch experiments that mimick As-affected aquifer conditions in combination with time-resolved characterization, we demonstrate that Mn(III)-NOM complexes play a crucial role in the manganese-mediated immobilization of As(III) by ferrihydrite and goethite. Under anaerobic condition, Mn(III)-fulvic acid (FA) rapidly oxidized 31.8% of aqueous As(III) and bound both As(III) and As(V). Furthermore, Mn(III)-FA exerted significantly different effects on the adsorption of As by ferrihydrite and goethite. Mn(III)-FA increased the adsorption of As by 6-16% due to the higher affinity of oxidation-produced As(V) for ferrihydrite under circumneutral conditions. In contrast, As adsorption by crystalline goethite was eventually inhibited due to the competitive effect of Mn(III)-FA. To summarize, our results reveal that Mn(III)-NOM complexes play dual roles in As retention by iron oxides, depending on the their crystallization. This highlights the importance of Mn(III) for the fate of As particularly in redox fluctuating groundwater environments.

Prediction of stability constants of metal-ligand complexes by machine learning for the design of ligands with optimal metal ion selectivity

The new LOGKPREDICT program integrates HostDesigner molecular design software with the machine learning (ML) program Chemprop. By supplying HostDesigner with predicted log K values, LOGKPREDICT enhances the computer-aided molecular design process by ranking ligands directly by metal-ligand binding strength. Harnessing reliable experimental data from a historic National Institute of Standards and Technology (NIST) database and data from the International Union of Pure and Applied Chemistry (IUPAC), we train message passing neural net algorithms. The multi-metal NIST-based ML model has a root mean square error (RMSE) of 0.629 ± 0.044 (R2 of 0.960 ± 0.006), while two versions of lanthanide-only IUPAC-based ML models have, respectively, RMSE of 0.764 ± 0.073 (R2 of 0.976 ± 0.005) and 0.757 ± 0.071 (R2 of 0.959 ± 0.007). For relative log K predictions on an out-of-sample set of six ligands, demonstrating metal ion selectivity, the RMSE value reaches a commendably low 0.25. We showcase the use of LOGKPREDICT in identifying ligands with high selectivity for lanthanides in aqueous solutions, a finding supported by recent experimental evidence. We also predict new ligands yet to be verified experimentally. Therefore, our ML models implemented through LOGKPREDICT and interfaced with the ligand design software HostDesigner pave the way for designing new ligands with predetermined selectivity for competing metal ions in an aqueous solution.

Unified Modeling Approach for Quantifying the Proton and Metal Binding Ability of Soil Dissolved Organic Matter

Soil dissolved organic matter (DOM) is composed of a mass of complex organic compounds in soil solutions and significantly affects a range of (bio)geochemical processes in soil environment. However, how the chemical complexity (i.e., heterogeneity and chemodiversity) of soil DOM molecules affects their proton and metal binding ability remains unclear, which limits our ability for predicting the environmental behavior of DOM and metals. In this study, we developed a unified modeling approach for quantifying the proton and metal binding ability of soil DOM based on Cu titration experiments, Fourier transform ion cyclotron resonance mass spectrometry data, and molecular modeling method. Although soil DOM samples from different regions have enormously heterogeneous and diverse properties, we found that the molecules of soil DOM can be divided into three representative groups according to their Cu binding capacity. Based on the molecular models for individual molecular groups and the relative contributions of each group in each soil DOM, we were able to further develop molecular models for all soil DOM to predict their molecular properties and proton and metal binding ability. Our results will help to develop mechanistic models for predicting the reactivity of soil DOM from various sources.

Dissolved organic matter (DOM) was detected in MSWI plant: An investigation of DOM and potential toxic elements variation in the bottom ash and fly ash

The content of dissolved organic matter (DOM) and potentially toxic elements (PTEs) were investigated in the bottom ash (BA) and fly ash (FA) of different sections of the municipal solid waste incineration (MSWI) plant. BA and FA were collected from the dry (BA1-BA2), burn (BA3-BA4), and burn-out (BA5) sections of the grate incinerator; FA was collected after denitration (DNFA), and from the deacidification tower (FA1) and bag-type dust remover (FA2), respectively. The DOM concentration in BA was higher than that in FA, the highest concentration was in BA3 (556.18 mg/kg), while the lowest concentration was in DNFA (17.53 mg/kg). DOM in BA was mainly composed of protein-like, fulvic-like, tryptophan-like, and humic-like substances, of which humic-like substances accounted for more than 40%. DOM in FA consisted of tryptophan-like and humic-like substances, of which humic-like substances accounted for more than 80%. DOM still existed in BA which may be related to the incomplete combustion, and the influence of microbes, while DOM was increased in FA1, which might be due to the addition of lime slurry. PTEs were analyzed by the Tessier extraction method, Fe-Mn hydroxide-bound fraction of PTEs increased in FA1 in which DOM concentration (137.22 mg/kg) was 7.83 times that in DNFA. The increase of DOM may lead to a higher risk of PTEs in FA. FTIR results indicated that DOM can bond to PTEs in BA and FA. The contents of humus-like substances in DOM were positively correlated with the effective fraction of As, Cu, Pb, Cr, and Cd. This paper investigated the risk of DOM existing in BA and FA in MSWI plant, which can provide a new perspective on how to deal with BA and FA, and reduce their environmental risks.

Structure-Activity Relationships of 8-Hydroxyquinoline-Derived Mannich Bases with Tertiary Amines Targeting Multidrug-Resistant Cancer

A recently proposed strategy to overcome multidrug resistance (MDR) in cancer is to target the collateral sensitivity of otherwise resistant cells. We designed a library of 120 compounds to explore the chemical space around previously identified 8-hydroxyquinoline-derived Mannich bases with robust MDR-selective toxicity. We included compounds to study the effect of halogen and alkoxymethyl substitutions in R5 in combination with different Mannich bases in R7, a shift of the Mannich base from R7 to R5, as well as the introduction of an aromatic moiety. Cytotoxicity tests performed on a panel of parental and MDR cells highlight a strong influence of experimentally determined pK_a values of the donor atom moieties, indicating that protonation and metal chelation are important factors modulating the MDR-selective anticancer activity of the studied compounds. Our results identify structural requirements increasing MDR-selective anticancer activity, providing guidelines for the development of more effective anticancer chelators targeting MDR cancer.

Time-dependent accumulation of Cd, Co, Cu, Ni, and Zn in natural communities of mayfly and caddisfly larvae: Metal sensitivity, uptake pathways, and mixture toxicity

Conceptual and quantitative models were developed to assess time-dependent processes in four sequential experimental stream studies that determined abundances of natural communities of mayfly and caddisfly larvae dosed with single metals (Cd, Co, Cu, Ni, Zn) or multiple metals (Cd + Zn, Co + Cu, Cu + Ni, Cu + Zn, Ni + Zn, Cd + Cu + Zn, Co + Cu + Ni, Cu + Ni + Zn). Metal mixtures contained environmentally relevant metal ratios found in mine drainage. Free metal ion concentrations, accumulation of metals by periphyton, and metal uptake by four families of aquatic insect larvae were either measured (Brachycentridae) or predicted (Ephemerellidae, Heptageniidae, Hydropsychidae) using equilibrium and biodynamic models. Toxicity functions, which included metal accumulations by larvae and metal potencies, were linked to abundances of the insect families. Model results indicated that mayflies accumulated more metal than caddisflies and the relative importance of metal uptake by larvae via dissolved or dietary pathways highly depended on metal uptake rate constants for each insect family and concentrations of metals in food and water. For solution compositions in the experimental streams, accumulations of Cd, Cu, and Zn in larvae occurred primarily through dietary uptake, whereas uptake of dissolved metal was more important for Co and Ni accumulations. Cd, Cu, and Ni were major contributors to toxicity in metal mixtures and for metal ratios examined. Our conceptual approach and quantitative results should aid in designing laboratory experiments and field studies that evaluate metal uptake pathways and metal mixture toxicity to aquatic biota.

A Soluble Humic Substance for the Simultaneous Removal of Cadmium and Arsenic from Contaminated Soils

With abundant oxygen-containing functional groups, a humic substance (HS) has a high potential to remediate soils contaminated by heavy metals. Here, HS was first extracted from a leonardite and analyzed for its chemical compositions and spectroscopic characteristics. Then it was assessed for its ability as a washing agent to remove Cd and As from three types of soils (red soil, black soil, and fluvo-aquic soil) that were spiked with those contaminants (Cd: 40.5–49.1 mg/kg; As: 451–584 mg/kg). The operational washing conditions, including the pH and concentration of the HS, washing time and cycles, and liquid–soil ratio, were assessed for Cd and As removal efficiency. At pH 7, with an HS concentration (3672 mg C/L) higher than its critical micelle concentration and a liquid–soil ratio of 30, a single washing for 6–12 h removed 41.9 mg Cd/kg and 199.3 mg As/kg from red soil, 33.5 mg Cd/kg and 291.5 mg As/kg from black soil, and 30.4 mg Cd/kg and 325.5 mg As/kg from fluvo-aquic soil. The removal of Cd and As from the contaminated soils involved the complexation of Cd and As with the carboxyl and phenolic groups of HS. Outcomes from this research could be used to develop a tailor-made HS washing agent for the remediation of Cd- and As-contaminated soils with different properties.

Rigorous Physicochemical Framework for Metal Ion Binding by Aqueous Nanoparticulate Humic Substances: Implications for Speciation Modeling by the NICA-Donnan and WHAM Codes

Latest knowledge on the reactivity of charged nanoparticulate complexants toward aqueous metal ions is discussed in mechanistic detail. We present a rigorous generic description of electrostatic and chemical contributions to metal ion binding by nanoparticulate complexants, and their dependence on particle size, particle type (i.e., reactive sites distributed within the particle body or confined to the surface), ionic strength of the aqueous medium, and the nature of the metal ion. For the example case of soft environmental particles such as fulvic and humic acids, practical strategies are delineated for determining intraparticulate metal ion speciation, and for evaluating intrinsic chemical binding affinities and heterogeneity. The results are compared with those obtained by popular codes for equilibrium speciation modeling (namely NICA-Donnan and WHAM). Physicochemical analysis of the discrepancies generated by these codes reveals the a priori hypotheses adopted therein and the inappropriateness of some of their key parameters. The significance of the characteristic time scales governing the formation and dissociation rates of metal-nanoparticle complexes in defining the relaxation properties and the complete equilibration of the metal-nanoparticulate complex dispersion is described. The dynamic features of nanoparticulate complexes are also discussed in the context of predictions of the labilities and bioavailabilities of the metal species.

Interaction of Arsenic Species with Organic Ligands: Competitive Removal from Water by Coagulation-Flocculation-Sedimentation (C/F/S)

The co-occurrence of arsenic (As) and organic ligands in water bodies has raised environmental concerns due to their toxicity and adverse effects on human health. The present study aims to elucidate the influences of hydrophobic/hydrophilic organic ligands, such as humic acid (HA) and salicylic acid (SA), on the interactive behavior of As species in water. Moreover, the competitive removal behaviors of As(III, V) species and total organic carbon (TOC) were systematically investigated by coagulation-flocculation-sedimentation (C/F/S) under various aqueous matrices. The results showed the stronger binding affinity of As(V) than As(III) species, with a higher complexation ability of hydrophobic ligands than hydrophilic. The media containing hydrophilic ligands require smaller ferric chloride (FC) doses to achieve the higher As(III, V) removal, while the optimum FC dose required for As(III) removal was found to be higher than that for As(V). Moreover, hydrophobic ligands showed higher TOC removal than hydrophilic ligands. The pronounced adverse effect of a higher concentration of hydrophobic ligands on the removal efficiencies of As(V) and TOC was observed. The adsorption of As(V) on Fe precipitates was better fitted with the Langmuir model but the Freundlich isotherm was more suitable for As(III) in the presence of hydrophilic SA. Moreover, TOC removal was substantially decreased in the As(V) system as compared to the As(III) system due to the dissolution of Fe precipitates at higher As(V) concentrations. The results of FC composite flocs demonstrated that the combined effect of oxidation, charge neutralization and adsorption played an important role in the removal of both toxicants during the C/F/S process. In summary, the findings of the present study provide insights into the fate, mobility and competitive removal behavior of As(III, V) species and organic ligands in the water treatment process.

Complexation of Antimony with Natural Organic Matter: Performance Evaluation during Coagulation-Flocculation Process

The presence of natural organic matter (NOM) in drinking water sources can stabilize toxic antimony (Sb) species, thus enhancing their mobility and causing adverse effects on human health. Therefore, the present study aims to quantitatively explore the complexation of hydrophobic/hydrophilic NOM, i.e., humic acid (HA), salicylic acid (SA), and L-cysteine (L-cys), with Sb in water. In addition, the removal of Sb(III, V) species and total organic carbon (TOC) was evaluated with ferric chloride (FC) as a coagulant. The results showed a stronger binding affinity of hydrophobic HA as compared to hydrophilic NOM. The optimum FC dose required for Sb(V) removal was found to be higher than that for Sb(III), due to the higher complexation ability of hydrophobic NOM with antimonate than antimonite. TOC removal was found to be higher in hydrophobic ligands than hydrophilic ligands. The high concentration of hydrophobic molecules significantly suppresses the Sb adsorption onto Fe precipitates. An isotherm study suggested a stronger adsorption capacity for the hydrophobic ligand than the hydrophilic ligand. The binding of Sb to NOM in the presence of active Fe sites was significantly reduced, likely due to the adsorption of contaminants onto precipitated Fe. The results of flocs characteristics revealed that mechanisms such as oxidation, complexation, charge neutralization, and adsorption may be involved in the removal of Sb species from water. This study may provide new insights into the complexation behavior of Sb in NOM-laden water as well as the optimization of the coagulant dose during the water treatment process.

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 pK_a values of every binding sites of individual molecules of the SOM model. Based on the pK_a 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.

Potential Toxicity of Dissolved Metal Mixtures (Cd, Cu, Pb, Zn) to Early Life Stage White Sturgeon ( Acipenser transmontanus) in the Upper Columbia River, Washington, United States

The Upper Columbia River (UCR) received historical releases of smelter waste resulting in elevated metal concentrations in downstream sediments. Newly hatched white sturgeon hide within the rocky substrate at the sediment-water interface in the UCR for a few weeks before swim-up. Hiding behavior could expose them to metal contaminants, and metal toxicity could contribute to population declines in white sturgeon over the past 50 years. This study evaluates whether there is a link between the toxicity of dissolved metals across the sediment-water interface in the UCR and the survival of early life stage (ELS) white sturgeon. Toxicity of dissolved metal mixtures is evaluated using a combination of previously collected laboratory and field data and recently developed metal mixture toxicity models. The laboratory data consist of individual metal (Cd, Cu, Pb, and Zn) toxicity studies with ELS white sturgeon. The field data include the chemical composition of surface and pore water samples that were collected across the sediment-water interface in the UCR. These data are used in three metal accumulation and two response models. All models predict low toxicity in surface water, whereas effects concentrations greater than 20% are predicted for 60-72% of shallow pore water samples. The flux of dissolved metals, particularly Cu, from shallow pore water to surface water likely exposes prime ELS sturgeon habitat to toxic conditions.

Larval aquatic insect responses to cadmium and zinc in experimental streams

To evaluate the risks of metal mixture effects to natural stream communities under ecologically relevant conditions, the authors conducted 30-d tests with benthic macroinvertebrates exposed to cadmium (Cd) and zinc (Zn) in experimental streams. The simultaneous exposures were with Cd and Zn singly and with Cd+Zn mixtures at environmentally relevant ratios. The tests produced concentration-response patterns that for individual taxa were interpreted in the same manner as classic single-species toxicity tests and for community metrics such as taxa richness and mayfly (Ephemeroptera) abundance were interpreted in the same manner as with stream survey data. Effect concentrations from the experimental stream exposures were usually 2 to 3 orders of magnitude lower than those from classic single-species tests. Relative to a response addition model, which assumes that the joint toxicity of the mixtures can be predicted from the product of their responses to individual toxicants, the Cd+Zn mixtures generally showed slightly less than additive toxicity. The authors applied a modeling approach called Tox to explore the mixture toxicity results and to relate the experimental stream results to field data. The approach predicts the accumulation of toxicants (hydrogen, Cd, and Zn) on organisms using a 2-pK_a bidentate model that defines interactions between dissolved cations and biological receptors (biotic ligands) and relates that accumulation through a logistic equation to biological response. The Tox modeling was able to predict Cd+Zn mixture responses from the single-metal exposures as well as responses from field data. The similarity of response patterns between the 30-d experimental stream tests and field data supports the environmental relevance of testing aquatic insects in experimental streams. Environ Toxicol Chem 2017;36:749-762. Published 2016 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

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.

Metal mixture modeling evaluation project: 3. Lessons learned and steps forward

A comparison of 4 metal mixture toxicity models (that were based on the biotic ligand model [BLM] and the Windermere humic aqueous model using the toxicity function [WHAM-FTOX ]) was presented in a previous paper. In the present study, a streamlined version of the 4 models was developed and applied to multiple data sets and test conditions to examine key assumptions and calibration strategies that are crucial in modeling metal mixture toxicity. Results show that 1) a single binding site on or in the organism was a useful and oftentimes sufficient framework for predicting metal toxicity; 2) a linear free energy relationship (LFER) for bidentate binding of metals and cations to the biotic ligand provided a good first estimate of binding coefficients; 3) although adjustments in metal binding coefficients or adjustments in chemical potency factors can both be used in model calibration for single-metal exposures, changing metal binding coefficients or chemical potency factors had different effects on model predictions for metal mixtures; and 4) selection of a mixture toxicity model (based on concentration addition or independent action) was important in predicting metal mixture toxicity. Moving forward, efforts should focus on reducing uncertainties in model calibration, including development of better methods to characterize metal binding to toxicologically active binding sites, conducting targeted exposure studies to advance the understanding of metal mixture toxicity, and further developing LFERs and other tools to help constrain the model calibration.

Expanding metal mixture toxicity models to natural stream and lake invertebrate communities

A modeling approach that was used to predict the toxicity of dissolved single and multiple metals to trout is extended to stream benthic macroinvertebrates, freshwater zooplankton, and Daphnia magna. The approach predicts the accumulation of toxicants (H, Al, Cd, Cu, Ni, Pb, and Zn) in organisms using 3 equilibrium accumulation models that define interactions between dissolved cations and biological receptors (biotic ligands). These models differ in the structure of the receptors and include a 2-site biotic ligand model, a bidentate biotic ligand or 2-pKa model, and a humic acid model. The predicted accumulation of toxicants is weighted using toxicant-specific coefficients and incorporated into a toxicity function called Tox, which is then related to observed mortality or invertebrate community richness using a logistic equation. All accumulation models provide reasonable fits to metal concentrations in tissue samples of stream invertebrates. Despite the good fits, distinct differences in the magnitude of toxicant accumulation and biotic ligand speciation exist among the models for a given solution composition. However, predicted biological responses are similar among the models because there are interdependencies among model parameters in the accumulation-Tox models. To illustrate potential applications of the approaches, the 3 accumulation-Tox models for natural stream invertebrates are used in Monte Carlo simulations to predict the probability of adverse impacts in catchments of differing geology in central Colorado (USA); to link geology, water chemistry, and biological response; and to demonstrate how this approach can be used to screen for potential risks associated with resource development.

Experimental determination and modeling of arsenic complexation with humic and fulvic acids

The complexation of humic acid (HA) and fulvic acid (FA) with arsenic (As) in water was studied. Experimental results indicate that arsenic may form complexes with HA and FA with a higher affinity for arsenate than for arsenite. With the presence of iron oxide based adsorbents, binding of arsenic to HA/FA in water was significantly suppressed, probably due to adsorption of As and HA/FA. A two-site ligand binding model, considering only strong and weak site types of binding affinity, was successfully developed to describe the complexation of arsenic on the two natural organic fractions. The model showed that the numbers of weak sites were more than 10 times those of strong sites on both HA and FA for both arsenic species studied. The numbers of both types of binding sites were found to be proportional to the HA concentrations, while the apparent stability constants, defined for describing binding affinity between arsenic and the sites, are independent of the HA concentrations. To the best of our knowledge, this is the first study to characterize the impact of HA concentrations on the applicability of the ligand binding model, and to extrapolate the model to FA. The obtained results may give insights on the complexation of arsenic in HA/FA laden groundwater and on the selection of more effective adsorption-based treatment methods for natural waters.

Evaluating the ameliorative effect of natural dissolved organic matter (DOM) quality on copper toxicity to Daphnia magna: improving the BLM

Various quality predictors of seven different natural dissolved organic matter (DOM) and humic substances were evaluated for their influence on protection of Daphnia magna neonates against copper (Cu) toxicity. Protection was examined at 3 and 6 mg l(-1) of dissolved organic carbon (DOC) of each DOM isolate added to moderately hard, dechlorinated water. Other water chemistry parameters (pH, concentrations of DOC, calcium, magnesium and sodium) were kept relatively constant. Predictors included absorbance ratios Abs(254/365) (index of molecular weight) and Abs-octanol(254)/Abs-water(254) (index of lipophilicity), specific absorption coefficient (SAC(340); index of aromaticity), and fluorescence index (FI; index of source). In addition, the fluorescent components (humic-like, fulvic-like, tryptophan-like, and tyrosine-like) of the isolates were quantified by parallel factor analysis (PARAFAC). Up to 4-fold source-dependent differences in protection were observed amongst the different DOMs. Significant correlations in toxicity amelioration were found with Abs(254/365), Abs-octanol(254)/Abs-water(254), SAC(340), and with the humic-like fluorescent component. The relationships with FI were not significant and there were no relationships with the tryptophan-like or tyrosine-like fluorescent components at 3 mg C l(-1), whereas a negative correlation was seen with the fulvic-like component. In general, the results indicate that larger, optically dark, more lipophilic, more aromatic DOMs of terrigenous origin, with higher humic-like content, are more protective against Cu toxicity. A method for incorporating SAC(340) as a DOM quality indicator into the Biotic Ligand Model is presented; this may increase the accuracy for predicting Cu toxicity in natural waters.

Density functional theory studies on the structures and water-exchange reactions of aqueous Al(III)-oxalate complexes

The structures and water-exchange reactions of aqueous aluminum-oxalate complexes are investigated using density functional theory. The present work includes (1) The structures of Al(C(2)O(4))(H(2)O)(4)(+) and Al(C(2)O(4))(2)(H(2)O)(2)(-) were optimized at the level of B3LYP/6-311+G(d,p). The geometries obtained suggest that the Al-OH(2) bond lengths trans to C(2)O(4)(2-) ligand in Al(C(2)O(4))(H(2)O)(4)(+) are much longer than the Al-OH(2) bond lengths cis to C(2)O(4)(2-). For Al(C(2)O(4))(2)(H(2)O)(2)(-), the close energies between cis and trans isomers imply the coexistence in aqueous solution. The (27)Al NMR and (13)C NMR chemical shifts computed with the consideration of sufficient solvent effect using HF GIAO method and 6-311+G(d,p) basis set are in agreement with the experimental values available, indicating the appropriateness of the applied models; (2) The water-exchange reactions of Al(III)-oxalate complexes were simulated at the same computational level. The results show that water exchange proceeds via dissociative pathway and the activation energy barriers are sensitive to the solvent effect. The energy barriers obtained indicate that the coordinated H(2)O cis to C(2)O(4)(2-) in Al(C(2)O(4))(H(2)O)(4)(+) is more labile than trans H(2)O. The water-exchange rate constants (k(ex)) of trans- and cis-Al(C(2)O(4))(2)(H(2)O)(2)(-) were estimated by four methods and their respective characteristics were explored; (3) The significance of the study on the aqueous aluminum-oxalate complexes to environmental chemistry is discussed. The influences of ubiquitous organic ligands in environment on aluminum chemistry behavior can be elucidated by extending this study to a series of Al(III)-organic system.

Linear Free Energy Relationships for Metal-Ligand Complexation: Bidentate Binding to Negatively-Charged Oxygen Donor Atoms

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.