Stable isotopic signature of cadmium in tracing the source, fate, and translocation of cadmium in soil: A review.

Cadmium (Cd), one of the most severe environmental pollutants in soil, poses a great threat to food safety and human health. Understanding the potential sources, fate, and translocation of Cd in soil-plant systems can provide valuable information on Cd contamination and its environmental impacts. Stable Cd isotopic ratios (δ114/110Cd) can provide "fingerprint" information on the sources and fate of Cd in the soil environment. Here, we review the application of Cd isotopes in soil, including (i) the Cd isotopic signature of soil and anthropogenic sources, (ii) the interactions of Cd with soil constituents and associated Cd isotopic fractionation, and (iii) the translocation of Cd at soil-plant interfaces and inside plant bodies, which aims to provide an in-depth understanding of Cd transport and migration in soil and soil-plant systems. This review would help to improve the understanding and application of Cd isotopic techniques for tracing the potential sources and (bio-)geochemical cycling of Cd in soil environment.

Mechanistic and data-driven perspectives on plant uptake of organic pollutants.

Establishing reliable predictive models for plant uptake of organic pollutants is crucial for environmental risk assessment and guiding phytoremediation efforts. This study compiled an expanded dataset of plant cuticle-water partition coefficients (Kcw), a useful indicator for plant uptake, for 371 data points of 148 unique compounds and various plant species. Quantum/computational chemistry software and tools were utilized to compute various molecular descriptors, aiming to comprehensively characterize the properties and structures of each compound. Three types of models were developed to predict Kcw: a mechanism-driven pp-LFER model, a data-driven machine learning model, and an integrated mechanism-data-driven model. The mechanism-data-driven GBRT-ppLFER model exhibited superior performance, achieving RMSEtrain = 0.133 and RMSEtest = 0.301 while maintaining interpretability. The Shapley Additive Explanation analysis indicated that pp-LFER parameters, ESPI, FwRadicalmax, ExtFP607, and RDF70s are the key factors influencing plant uptake in the GBRT-ppLFER model. Overall, pp-LFER parameter, ESPI, and ExtFP607 show positive effects, while the remaining factors exhibit negative effects. Partial dependency analysis further indicated that plant uptake is not solely determined by individual factors but rather by the combined interactions of multiple factors. Specifically, compounds with ppLFER parameter >4, ESPI > -25.5, 0.098 < FwRadicalmax <0.132, and 2 < RFD70s < 3, are generally more readily taken up by plants. Besides, the predicted Kcw values from the GBRT-ppLFER model were effectively employed to estimate the plant-water partition coefficients and bioconcentration factors across different plant species and growth media (water, sand, and soil), achieving an outstanding performance with an RMSE of 0.497. This study provides effective tools for assessing plant uptake of organic pollutants and deepens our understanding of plant-environment-compound interactions.

Improving predictions and understanding of primary and ultimate biodegradation rates with machine learning models.

This study aimed to develop machine learning based quantitative structure biodegradability relationship (QSBR) models for predicting primary and ultimate biodegradation rates of organic chemicals, which are essential parameters for environmental risk assessment. For this purpose, experimental primary and ultimate biodegradation rates of high consistency were compiled for 173 organic compounds. A significant number of descriptors were calculated with a collection of quantum/computational chemistry software and tools to achieve comprehensive representation and interpretability. Following a pre-screening process, multiple QSBR models were developed for both primary and ultimate endpoints using three algorithms: extreme gradient boosting (XGBoost), support vector machine (SVM), and multiple linear regression (MLR). Furthermore, a unified QSBR model was constructed using the knowledge transfer technique and XGBoost. Results demonstrated that all QSBR models developed in this study had good performance. Particularly, SVM models exhibited high level of goodness of fit (coefficient of determination on the training set of 0.973 for primary and 0.980 for ultimate), robustness (leave-one-out cross-validated coefficient of 0.953 for primary and 0.967 for ultimate), and external predictive ability (external explained variance of 0.947 for primary and 0.958 for ultimate). The knowledge transfer technique enhanced model performance by learning from properties of two biodegradation endpoints. Williams plots were used to visualize the application domains of the models. Through SHapley Additive exPlanations (SHAP) analysis, this study identified key features affecting biodegradation rates. Notably, MDEO-12, APC2D1_C_O, and other features contributed to primary biodegradation, while AATS0v, AATS2v, and others inhibited it. For ultimate biodegradation, features like No. of Rotatable Bonds, APC2D1_C_O, and minHBa were contributors, while C1SP3, Halogen Ratio, GGI4, and others hindered the process. Also, the study quantified the contributions of each feature in predictions for individual chemicals. This research provides valuable tools for predicting both primary and ultimate biodegradation rates while offering insights into the mechanisms.

Theoretical modeling of molecular fractionation of dissolved organic matter on ferrihydrite and its impact on proton and metal binding properties.

Molecular fractionation of dissolved organic matter (DOM) at the mineral-liquid interfaces in soil changes its molecular composition, thus altering its reactivity, such as proton and metal binding properties. Therefore, a quantitative understanding of compositional change of DOM molecules after adsorptive fractionation by minerals is of great environmental significance for predicting the cycling of organic carbon (C) and metals in the ecosystem. In this study, we conducted adsorption experiments to investigate the adsorption behaviors of DOM molecules on ferrihydrite. The molecular compositions of the original and fractionated DOM samples were analyzed with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). For all DOM molecules, three molecular groups with significantly different chemical properties were identified through Spearman correlation analysis between the relative intensities of DOM molecules and organic C concentrations in solutions after adsorptive fractionation. Three corresponding molecular models for the three molecular groups were constructed based on Vienna Soil-Organic-Matter Modeler and FT-ICR-MS results, which were used as base units to construct molecular models for the original or fractionated DOM samples (model(DOM)). The models well described the chemical properties of the original or fractionated DOM as compared with the experimental data. Furthermore, based on model(DOM), the proton and metal binding constants of DOM molecules were quantified by SPARC chemical reactivity calculations and linear free energy relationships. We found the density of binding sites of the fractionated DOM samples was negatively correlated with the adsorption percentage. Our modeling results suggested that adsorption of DOM on ferrihydrite gradually removed acidic functional groups from the solution, dominated by the adsorption of both carboxyl and phenol groups. This study proposed a new modeling approach to quantify the molecular fractionation processes of DOM on Fe oxides and their impact on proton and metal binding properties, which is expected to be applicable to DOM from different environments.

Photoinduced transformation of ferrihydrite in the presence of aqueous sulfite and its influence on the repartitioning of Cd.

The photoinduced transformation of ferrihydrite is an important process that can predict the geochemical cycle of Fe in anoxic environments as well as the fate of trace elements bonded to Fe minerals. We report that the photooxidation of sulfite by UV irradiation produces hydrated electrons (super-reductants), which significantly promote ferrihydrite reduction to Fe(II), and SO3•- (a moderate oxidant), enabling its further oxidation to more crystalline Fe(III) products. The experimental results show that the concentration of sulfite was key in influencing the rate and extent of surface-bound Fe(II) formation, which ultimately determined the distribution of individual products. For example, fitting of the Mössbauer spectroscopy data revealed that the relative abundances of mineral species after 8 h of treatment in the UV/sulfite systems were 41.9% lepidocrocite and 58.1% ferrihydrite at 2 mM SO32-; 41.8% goethite, 28.2% lepidocrocite, and 29.1% ferrihydrite at 5 mM SO32-; and 100% goethite at 10 mM SO32-. The combined results of the chemical speciation analysis and the Cd K-edge EXAFS characterization provided compelling evidence that Cd was firmly incorporated into the structure of newly formed minerals, particularly at high sulfite concentrations. These findings provide an understanding of the role of UV/sulfite in facilitating ferrihydrite transformation and promoting Cd stabilization in oxygen-deficit soils and aquatic environments.

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.

Kinetics of cadmium (Cd), nickel (Ni), and lead (Pb) release from fulvic acid: Role of re-association reactions and quantitative models.

Dissolved organic matter (DOM), a ubiquitous ligand for heavy metals, plays a crucial role in regulating the bioavailability and fate of heavy metals in the environment. However, owing to complex structure and heterogeneity of DOM, it is still challenging to develop kinetics models to predict the rates of heavy metal reactions with DOM. In this study, we investigated the kinetics of Cd, Ni, and Pb release from a typical fulvic acid (FA) under a wide range of experimental conditions using a competing ligand exchange (CLE) method. Among three metals, Cd showed the fastest release from FA while Ni and Pb had slower release rates. Reaction pH also had different impact on the release rates of the three metals, presumably attributed to different proton/metal exchange ratios for the metal ion complexation with FA. We formulated a kinetics model for Cd, Ni, and Pb release from FA by considering metal ions dissociation from FA, re-association of metal ions with FA, and metal ion uptake by the resin in the CLE experiments. The chemical speciation model WHAM 7 was used to predict the local equilibrium status that the kinetic reactions were away from, which help to derive the kinetic parameters based on the equilibrium parameters. For both Cd and Pb, model calculations were sensitive to the re-association rates, especially at high pH, while for Ni, the impact of the re-association rates was less significant. Based on the model parameters obtained in this study, our model simulations have also demonstrated that metal-FA complexes may undergo different rates of dissociation in the environment, affecting the dynamic speciation and transfer of metals to other biological processes. This work has provided a quantitative tool for predicting metal release from DOM, which would be useful for predicting the bioavailability and fate of heavy metals in the environment.

Kinetic modeling of As release from contaminated soils: Consideration of particle size and co-contamination of Cu.

Prediction on the release kinetics of metalloids from soils is challenging due to the physio-chemical heterogeneity of soil and the varying binding abilities of metalloid contaminants on soil. In this study, the kinetics of As(V), together with Cu(II), release from two typical field contaminated soils were investigated by the stirred-flow experiments. We formulated the quantitative models to describe the release kinetics of As(V) from the contaminated soils with consideration of varying soil particle size and presence of Cu(II). The results showed that the release kinetics of As(V) and Cu(II) from different particle size fractions and at different reaction pH was well described by the model. The models also indicated that the bidentate binding sites on goethite were the major contributor for As(V) release, while soil organic matter (SOM) mainly controlled the Cu(II) release. Finer particle size fractions had more significant contributions to As(V) and Cu(II) release due to higher concentrations of reactive metal(loid)s and more reactive adsorbents. Moreover, the models also showed applicability for predicting metal(loid) release from the bulk soils by considering the contribution of each soil particle size fraction, and the kinetic behaviors of two individual contaminants, As(V) and Cu(II), can be modeled independently. Our results provided a modeling framework to predict the release kinetics of metal(loid)s from soils co-contaminated with different cation and anion pollutants with consideration on the effects of physical and chemical heterogeneity of soils.

Coupled Sorption and Oxidation of Soil Dissolved Organic Matter on Manganese Oxides: Nano/Sub-nanoscale Distribution and Molecular Transformation.

In soil environments, the sequestration and transformation of organic carbon are closely associated with soil minerals. Birnessite (MnO2) is known to strongly interact with soil dissolved organic matter (DOM), but the microscopic distribution and molecular transformation of soil DOM on birnessite are still poorly understood. In this study, the coupled sorption and oxidation of soil DOM on birnessite were investigated at both the microscopic scale and the molecular level. Spherical aberration corrected scanning transmission electron microscopy (Cs-STEM) results revealed, at the nano- to sub-nanoscale, that DOM was located both on the surfaces and within the interflakes or pore spaces of birnessite, and DOM within the interflakes displayed a higher oxidation state than that on the surfaces. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) results suggested that a portion of phenolic compounds were preferentially sorbed and oxidized, resulting in the formation of compounds with higher oxygen contents and polymeric products. Our Cs-STEM and FT-ICR-MS results highlighted the significance of organo-mineral associations in the microscopic mineral structure for the reactivity of organic carbon and provided the molecular evidence for the transformation of soil DOM by birnessite, which contributed to the understanding of the dynamics of soil dissolved organic carbon.

Fulvic Acid-Mediated Interfacial Reactions on Exposed Hematite Facets during Dissimilatory Iron Reduction.

Although the dual role of natural organic matter (NOM) as an electron shuttle and an electron donor for dissimilatory iron (Fe) reduction has been extensively investigated, the underlying interfacial interactions between various exposed facets and NOM are poorly understood. In this study, fulvic acid (FA), as typical NOM, was used and its effect on the dissimilatory reduction of hematite {001} and {100} by Shewanella putrefaciens CN-32 was investigated. FA accelerates the bioreduction rates of hematite {001} and {100}, where the rate of hematite {100} is lower than that of hematite {001}. Secondary Fe minerals were not observed, but the HR-TEM images reveal significant defects. The ATR-FTIR results demonstrate that facet-dependent binding mainly occurs via surface complexation between the surface iron atoms and carboxyl groups of NOM. The spectroscopic and mass spectrometry analyses suggest that organic compounds with large molecular weight, highly aromatic and unsaturated structures, and lower H/C ratios are easily adsorbed on Fe oxides or decomposed by bacteria in FA-hematite {001} treatment after iron reduction. Due to the metabolic processes of cells, a significant number of compounds with higher H/C and medium O/C ratios appear. The Tafel curves show that hematite {100} possessed higher resistance (4.1-2.6 Ω) than hematite {001} (3.5-2.2 Ω) at FA concentrations ranging from 0 to 500 mg L-1, indicating that hematite {100} is less conductive during the electron transfer from reduced FA or cells to Fe oxides than hematite {001}. Overall, the discrepancy in the iron bioreduction of two exposed facets is attributed to both the different electrochemical activities of the Fe oxides and the different impacts on the properties and composition of OM. Our findings shed light on the molecular mechanisms of mutual interactions between FA and Fe oxides with various facets.

Reductive release of Fe mineral-associated organic matter accelerated by oxalic acid.

The properties and composition of soil dissolved organic matter (DOM) are highly affected by the adsorption and desorption of organic matter (OM) on soil minerals and heterotrophic microbial respiration. Organic acids (e.g., oxalic acid), components of root exudates, have been revealed to liberate organic matter (OM) by the dissolution of protective mineral phases and stimulate microbial degradation of OM. However, the effects of organic acids on the properties and composition of soil DOM molecules and the related mechanisms are still poorly understood. In this study, we conducted microcosm incubation experiments with and without oxalic acid addition, and aimed to elucidate the variations of DOM properties and composition, employing a combination of Fourier transform ion cyclotron resonance mass spectrometry, optical spectroscopy, and bacterial community composition analysis. Our results indicated that the released OM from the direct dissolution of protective mineral phases by oxalic acid further stimulated the microbial reductive release of Fe mineral-associated OM under anoxic conditions. Furthermore, the addition of oxalic acid enhanced the degradation of aliphatic compounds and lignins with low O/C ratios, and increased the accumulation of lignins with high O/C ratios, tannins, and condensed aromatics. Linking the bacterial community composition to DOM molecular properties and composition further suggested that the enhanced reductive release of Fe mineral-associated OM was highly related to the increased abundances of Proteobacteria and Actinobacteria. Overall, oxalic acid induced long-lasting impacts on soil DOM properties and composition under anoxic soil conditions in our study. We expect that our results will contribute to understanding the dynamics of soil DOM molecules in the environment.

Quinone-mediated dissimilatory iron reduction of hematite: Interfacial reactions on exposed {001} and {100} facets.

Although quinone-mediated bioreduction of iron oxides has been investigated extensively, little is known about the interfacial interactions between quinone and various exposed facets. In this study, the reduction of hematite {001} and {100} by Shewanella putrefaciens CN-32 with anthraquinone-2,6-disulfonate (AQDS) was investigated. The added AQDS can enhance the bioreduction of both hematite {001} and {100}, with hematite {001} showing a higher reduction degree than hematite {100}. No significant secondary iron oxides were found, but defects were observed in HR-TEM images. AQDS sorption was higher on hematite {001} (0.13 µM m-2) than hematite {100} (0.1 µM m-2). Electron transfer rate between hematite {001} and AQDS (19.6 s-1) was higher than hematite {100} (18.2 s-1). Tafel curves revealed that hematite {001} possesses lower resistance (3.5-2.4 Ω) than hematite {100} (4.1-2.9 Ω) with AQDS from 0 to 400 µM, indicating that hematite {001} is more favorable for electron transfer from cells or anthrahydroquinone-2,6,-disulfonate (AH2QDS) to Fe oxide. In addition to the well-known electron shuttling role of AQDS, the higher adsorption sites and electrochemical activity of hematite {001} over {100} jointly contributed to the enhanced iron bioreduction. The findings provide a mechanistic understanding of the interactions between quinone and various facets of iron oxides.

Different Pathways for Cr(III) Oxidation: Implications for Cr(VI) Reoccurrence in Reduced Chromite Ore Processing Residue.

Hexavalent chromium contamination is a global environmental issue and usually reoccurs in alkaline reduced chromite ore processing residues (rCOPR). The oxidation of Cr(III) solids in rCOPR is one possible cause but as yet little studied. Herein, we investigated the oxidation of Cr(OH)3, a typical species of Cr(III) in rCOPR, at alkaline pH (9-11) with δ-MnO2 under oxic/anoxic conditions. Results revealed three pathways for Cr(III) oxidation under oxic conditions: (1) oxidation by oxygen, (2) oxidation by δ-MnO2, and (3) catalytic oxidation by Mn(II). Oxidations in the latter two were efficient, and oxidation via Pathway 3 was continuous and increased dramatically with increasing pH. XANES data indicated feitknechtite (ß-MnOOH) and hausmannite (Mn3O4) were the reduction products and catalytic substances. Additionally, a kinetic model was established to describe the relative contributions of each pathway at a specific time. The simulation outcomes showed that Cr(VI) was mainly formed via Pathway 2 (>51%) over a short time frame (10 days), whereas in a longer-term (365 days), Pathway 3 predominated the oxidation (>78%) with an increasing proportion over time. These results suggest Cr(III) solids can be oxidized under alkaline oxic conditions even with a small amount of manganese oxides, providing new perspectives on Cr(VI) reoccurrence in rCOPR and emphasizing the environmental risks of Cr(III) solids in alkaline environments.

Quantifying Microbially Mediated Kinetics of Ferrihydrite Transformation and Arsenic Reduction: Role of the Arsenate-Reducing Gene Expression Pattern.

The behavior of arsenic (As) is usually coupled with iron (Fe) oxide transformation and mediated by both abiotic reactions and microbial processes in the environment. However, quantitative models for the coupled kinetic processes, which specifically consider the arsenate-reducing gene expression correspondent to different reaction conditions, are lacking. In this study, based on the pure cultured Shewanella putrefaciens incubation experiments, extended X-ray absorption fine structure spectroscopy, high resolution transmission electron microscopy, and a suite of microbial analyses, we developed a coupled kinetics model for microbially mediated As reduction and Fe oxide transformation and specifically quantified the As(V) reduction rate coefficients based on the expression patterns of arrA genes. The model reasonably described the temporal changes of As speciation and distribution. The microbial reduction rates of As(V) varied dramatically during the reactions, which were well represented by the varying transcript abundances of arrA genes at different As concentrations. The contributions of biotic and abiotic reactions to the overall reaction rates were assessed. The results improved our quantitative understanding on the key role of As(V)-reducing genes in regulating the speciation and distribution of As. The kinetic modeling approaches based on microbial gene expression patterns are promising for developing comprehensive biogeochemical models of As involving multiple coupled reactions.

Chemodiversity of Soil Dissolved Organic Matter.

Dissolved organic matter (DOM) plays a key role in many biogeochemical processes, but the drivers controlling the diversity of chemical composition and properties of DOM molecules (chemodiversity) in soils are poorly understood. It has also been debated whether environmental conditions or intrinsic molecular properties control the accumulation and persistence of DOM due to the complexity of both molecular composition of DOM and interactions between DOM and surrounding environments. In this study, soil DOM samples were extracted from 33 soils collected from different regions of China, and we investigated the effects of climate and soil properties on the chemodiversity of DOM across different regions of China, employing a combination of Fourier transform ion cyclotron resonance mass spectrometry, optical spectroscopy, and statistical analyses. Our results indicated that, despite the heterogeneity of soil samples and complex influencing factors, aridity and clay can account for the majority of the variations of DOM chemical composition. The finding implied that DOM chemodiversity is an ecosystem property closely related to the environment, and can be used in developing large-scale soil biogeochemistry models for predicting C cycling in soils.

Modeling coupled kinetics of arsenic adsorption/desorption and oxidation in ferrihydrite-Mn(II)/manganese (oxyhydr)oxides systems.

The speciation and mobility of As are controlled by both Fe and Mn (oxyhydr)oxides through a series of surface complexation and redox reactions occurring in the environment, which is also complicated by the solution chemistry conditions. However, there is still a lack of quantitative tools for predicting the coupled kinetic processes of As reactions with Fe and Mn (oxyhydr)oxides. In this study, we developed a quantitative model for the coupled kinetics of As adsorption/desorption and oxidation in ferrihydrite-Mn (oxyhydr)oxides and ferrihydrite-Mn(II)-O2 systems. This model also accounted for the variations in solution chemistry conditions and binding site heterogeneity. Our model suggested that Mn (oxyhydr)oxide and ferrihydrite mainly served as an oxidant and an adsorbent, respectively, when they coexisted. Among the three types of binding sites of ferrihydrite, the adsorbed As(V) was mainly distributed on the nonprotonated bidentate sites. Our model quantitatively showed that the oxidation rates of different reaction systems varied significantly. The rates of As(III) oxidation were enhanced with higher pH values and higher molar ratios of Mn(II)/As(III) in the ferrihydrite-Mn(II)-O2 system. This study provides a modeling framework for predicting the kinetic behavior of As when multiple adsorption/desorption and oxidation reactions are coupled in the environment.

Predicting Cr(vi) adsorption on soils: the role of the competition of soil organic matter.

Cr(vi) has posed a serious risk for the environment and human beings because of its pollution and toxicity. It is essential to understand the equilibrium behavior of Cr(vi) in soils. In this study, the adsorption of Cr(vi) on fourteen soils was studied with batch experiments and quantitative modeling. The batch experiments included the adsorption edge and adsorption isotherm experiments, investigating the adsorption of Cr(vi) with varying soil properties, solution pH, and initial Cr(vi) concentrations. The experimental data were then modeled using the surface complexation models in Visual MINTEQ of CD-MUSIC by considering the adsorption of Cr(vi) and ions onto Fe (hydr)oxides and Al (hydr)oxides, and the Stockholm Humic Model and the fixed charge site model by accounting for the adsorption of the cations to soil organic matter and clay, respectively. Particularly, the modeling method of this study introduced an important parameter RO- to account for the amount of soil organic matter irreversibly adsorbed on soil minerals. Overall, the model predicted reasonably well for the equilibrium partition of Cr(vi) under various conditions with a root-mean-square-error of 0.35 for the adsorption edge data and 0.19 for the adsorption isotherm data. According to the model calculations, ferrihydrite dominated the binding of Cr(vi) at pH of 3.0-7.0. The content of ferrihydrite and reactive soil organic matter was found to be the main factor influencing RO-. The modeling results help to understand and predict Cr(vi) adsorption on different soils and are beneficial to environmental risk assessment and pollution remediation.

Quantifying the Coupled Kinetic Reactions of Metals/Metalloids on Iron and Manganese Oxides.

Quantifying the coupled kinetic reactions of metals/metalloids on iron and manganese oxides is essential for predicting the fate of contaminants in the environment. In this perspective, a few key issues related to developing the quantitative models for the coupled kinetic reactions of metal and metalloids are discussed, including adsorption/desorption processes, redox reactions, and mineral dissolution/transformation. Future research areas are also briefly discussed.

Antimony oxidation and sorption behavior on birnessites with different properties (δ-MnO2 and triclinic birnessite).

Birnessites are abundant naturally occurring minerals with high sorption and oxidation capacity that could therefore play an important role in antimony (Sb) migration and transformation. There are various types of birnessites in the environment. However, little is known about the similarities and differences in Sb oxidation and sorption on birnessites with different properties. In this study, the behavior of Sb oxidation and sorption on two contrasting birnessites (δ-MnO2 and triclinic birnessite (TrBir)) were investigated via batch and kinetic experiments and various spectroscopic techniques. Our results showed that the reaction mechanisms between Sb and the two birnessites were similar. The edge sites of birnessites were responsible for Sb(III) oxidation. Mn(IV) was reduced to Mn(III) and Mn(II), bound with birnessites and released to the solution, respectively. Because of the rapid rate of electron transfer of adsorbed Sb(III) to birnessites, the only Sb species on δ-MnO2 after the oxidation reaction was Sb(V). Sb(V) was adsorbed at the edge sites of birnessites by replacing the OH group of birnessites, forming corner-sharing complexes with birnessites. However, the Sb sorption and oxidation capacities of the two birnessites were significantly different. Poorly-crystallized δ-MnO2 exhibited a much higher oxidation and sorption capacity than well-crystallized TrBir because the former had many more edge sites than the latter. This study reveals the general mechanism of the reaction between Sb and birnessite and indicates that birnessite with a high number of edge sites would exhibit a huge capacity in Sb oxidation and sorption.

Coupled Kinetics Model for Microbially Mediated Arsenic Reduction and Adsorption/Desorption on Iron Oxides: Role of Arsenic Desorption Induced by Microbes.

The dynamic behavior of arsenic (As) species is closely associated with iron mineral dissolution/transformation in the environment. Bacterially induced As(V) desorption from iron oxides may be another important process that facilitates As(V) release from iron oxides without significant reductive dissolution of iron oxides. Under the impact of bacterially induced desorption, As kinetic behavior is controlled by both the microbial reduction of As(V) and the As(III)&As(V) reactions on iron oxide surfaces. However, there is still a lack of quantitative understanding on the coupled kinetics of these processes in complex systems. We developed a quantitative model that integrated the time-dependent microbial reduction of As(V) with nonlinear As(III)&As(V) adsorption/desorption kinetics on iron oxides under the impact of bacterially induced As(V) desorption. We collected and modeled literature data from 11 representative studies, in which microbial reduction reactions occurred with minimal iron oxide dissolution/transformation. Our model highlighted the significance of microbially induced As(V) desorption and time-dependent changes of microbial reduction rates. The model can quantitatively assess the roles and the coupling of individual reactions in controlling the overall reaction rates. It provided a basis for developing comprehensive models for As cycling in the environment by coupling with other chemical, physical, and microbial processes.