A Unified Surface Complexation Modeling Approach for Chromate Adsorption on Iron Oxides

Complexation mechanism of Pb2+ on Al-substituted hematite: A modeling study and theoretical calculation

Hematite nanoparticles commonly undergoes isomorphic substitution of Al3+ in nature, while how the Al-substitution-induced morphological change, defective structure and newly generated Al-OH sites affect the adsorption behavior of hematite for contaminants remains poorly understood. Herein, the interfacial reactions between Al-substituted hematite and Pb2+ was investigated via CD-MUSIC modeling and DFT calculations. As the Al content increased from 0% to 9.4%, Al-substitution promoted the proportion of (001) facets and caused Fe vacancies on hematite, which increased the total active site density of hematite from 5.60 to 17.60 sites/nm2. The surface positive charge of hematite significantly increased from 0.096 to 0.418 C/m2 at pH 5.0 due to the increases in site density and proton affinity (logKH) of hematite under Al-substitution. The adsorption amount of hematite for Pb2+ increased from 3.92 to 9.74 mmol/kg at pH 5.0 and 20 μmol/L initial Pb2+ concentration with increasing Al content. More Fe vacancies may lead to a weaker adsorption energy (Ead) of hematite for Pb2+, while the Ead was enhanced at higher Al content. The adsorption affinity (logKPb) of bidentate Pb complexes slightly increased while that of tridentate Pb complexes decreased with increasing Al content due to the presence of ≡ AlOH-0.5 and ≡ Fe2AlO-0.5 sites. Tridentate Pb complexes were dominant species on the surface of pure hematite, while bidentate ones became more dominant with increasing Al content. The obtained model parameters and molecular scale information are of great importance for better describing and predicting the environmental fate of toxic heavy metals in terrestrial and aquatic environments.

Bridging molecular-scale interfacial science with continuum-scale models

Solid-water interfaces are crucial for clean water, conventional and renewable energy, and effective nuclear waste management. However, reflecting the complexity of reactive interfaces in continuum-scale models is a challenge, leading to oversimplified representations that often fail to predict real-world behavior. This is because these models use fixed parameters derived by averaging across a wide physicochemical range observed at the molecular scale. Recent studies have revealed the stochastic nature of molecular-level surface sites that define a variety of reaction mechanisms, rates, and products even across a single surface. To bridge the molecular knowledge and predictive continuum-scale models, we propose to represent surface properties with probability distributions rather than with discrete constant values derived by averaging across a heterogeneous surface. This conceptual shift in continuum-scale modeling requires exponentially rising computational power. By incorporating our molecular-scale understanding of solid-water interfaces into continuum-scale models we can pave the way for next generation critical technologies and novel environmental solutions.

Prediction of Cr(VI) and As(V) adsorption on goethite using hybrid surface complexation-machine learning model

This study aimed to develop surface complexation modeling-machine learning (SCM-ML) hybrid model for chromate and arsenate adsorption on goethite. The feasibility of two SCM-ML hybrid modeling approaches was investigated. Firstly, we attempted to utilize ML algorithms and establish the parameter model, to link factors influencing the adsorption amount of oxyanions with optimized surface complexation constants. However, the results revealed the optimized chromate or arsenate surface complexation constants might fall into local extrema, making it unable to establish a reasonable mapping relationship between adsorption conditions and surface complexation constants by ML algorithms. In contrast, species-informed models were successfully obtained, by incorporating the surface species information calculated from the unoptimized SCM with the adsorption condition as input features. Compared with the optimized SCM, the species-informed model could make more accurate predictions on pH edges, isotherms, and kinetic data for various input conditions (for chromate: root mean square error (RMSE) on test set = 5.90 %; for arsenate: RMSE on test set = 4.84 %). Furthermore, the utilization of the interpretable formula based on Local Interpretable Model-Agnostic Explanations (LIME) enabled the species-informed model to provide surface species information like SCM. The species-informed SCM-ML hybrid modeling method proposed in this study has great practicality and application potential, and is expected to become a new paradigm in surface adsorption model.

Quantifying the mitigating effect of organic matter on heavy metal availability in soils with different manure applications: A geochemical modelling study

Manure is one of the main sources of heavy metal (HM) pollution on farmlands. It has become the focus of global ecological research because of its potential threat to human health and the sustainability of food systems. Soil pH and organic matter are improved by manure and play pivotal roles in determining soil HM behavior. Geochemical modeling has been widely used to assess and predict the behavior of soil HMs; however, there remains a research gap in manure applications. In this study, a geochemical model (LeachXS) coupled with a pH-dependent leaching test with continuously simulations over a broad pH range was used to determine the effects and pollution risks of pig or cattle manure separate application on soil HMs distribution. Both pig and cattle manure applications led to soil pH reduction in alkaline soils and increased organic matter content. Pig manure application resulted in a potential 90.5-156.0 % increase in soil HM content. Cattle manure did not cause significant HM contamination. The leaching trend of soil HMs across treatments exhibited a V-shaped change, with the lowest concentration at pH = 7, gradually increasing toward strong acids and bases. The dissolved organic matter-bound HM content directly increased the HM availability, especially for Cu (up to 8.4 %) after pig manure application. However, more HMs (Cr, Cu, Zn, Ni) were in the particulate organic matter-bound state than in other solid phases (e.g., Fe-Al(hydr) oxides, clay minerals), which inhibited the HMs leaching by more than 19.3 % after cattle manure application. Despite these variations, high HM concentrations introduced by pig manure raised the soil contamination risk, potentially exceeding 40 times at pH ±1. When manure is returned to the field, reducing its HM content and mitigating possible pollution is necessary to realize the healthy and sustainable development of circular agriculture.

Using machine learning to explore oxyanion adsorption ability of goethite with different specific surface area

In this study, we developed prediction models for the adsorption of divalent and trivalent oxyanions on goethite based on machine learning algorithms. After verifying the reliability of the models, the importance of goethite specific surface area (SSA) and the average oxyanion adsorption capacities of goethite with different SSAs were calculated by shapley additive explanations (SHAP) importance analysis and partial dependence (PD) analysis. Despite there were differences in the feature importance of divalent and trivalent oxyanions, the contribution of goethite's SSA to the adsorption amount ranked the fourth based on SHAP importance, indicating SSA played the important role in oxyanion adsorption. Meanwhile, the PD values of SSA and the optimized complexation constants from surface complexation modeling (SCM) both indicated a non-monotonic relationship between the goethite with different SSA and its oxyanions binding capacity. When the total site concentration and crystal face composition were used as the machine learning model input features, the SHAP importance values of crystal faces and the PD decomposition results indicated that the (001) face showed the crucial influence on oxyanions adsorption amount. These findings demonstrated the important role of crystal face composition in goethite's adsorption ability, and provided a theoretical explanation for the variations of oxyanions adsorption amount on different SSA goethite.

Emerging iron-based mesoporous materials for adsorptive removal of pollutants: Mechanism, optimization, challenges, and future perspective

Iron-based materials (IBMs) have shown promise as adsorbents due to their unique physicochemical properties. This review provides an overview of the different types of IBMs, their synthesis methods, and their properties. Results found in the adsorption of emerging contaminants to a wide range of IBMs are discussed. The IBMs used were evaluated in terms of their maximum uptake capacity, with special consideration given to environmental conditions such as contact time, solution pH, initial pollutant concentration, etc. The adsorption mechanisms of pollutants are discussed taking into account the results of kinetic, isotherm, thermodynamic studies, surface complexation modelling (SCM), and available spectroscopic data. A current overview of molecular modeling and simulation studies related to density functional theory (DFT), surface response methodology (RSM), and artificial neural network (ANN) is presented. In addition, the reusability and suitability of IBMs in real wastewater treatment is shown. The review concludes with the strengths and weaknesses of current research and suggests ideas for future research that will improve our ability to remove contaminants from real wastewater streams.

Nanoconfinement boosts affinity of hydrated zirconium oxides to arsenate: Surface complexation modeling study

Nanoscale hydrated zirconium oxide (HZO) holds great potential in groundwater purification due to its ability to form inner-sphere coordination with arsenate. Despite being frequently used, especially as encapsulations in host materials for practical application in water treatment, the adsorption mechanisms of solutes on HZO are not appropriately explored, in particular for arsenate adsorption. In this study, we investigated the Zr-As coordination configuration and identified the most credible Zr-As configuration using surface complexation modeling (SCM), XPS and FT-IR analysis. The corresponding intrinsic coordination constants (Kintr) values was calculated by SCM, and the nanoconfinement effects were distinguished by comparing bare HZO with the HZO nanoparticles (NPs) encapsulated inside the strongly basic anion exchanger D201. Potentiometric titration suggests that the surface Zirconium hydroxyl groups (≡ZrOH) mainly exist in protonated form (≡ZrOH2+). Batch adsorption experiments demonstrate that the D201 hosts could adsorb As(V) through ion exchange by the quaternary ammonium groups under the low ionic strength (≤0.01 M NaNO3) and at pH > 6. The nanocomposite (HZO@D201) exhibits a higher adsorption capacity in a wide range of pH (3-10) and ionic strength (0.001-0.1 M NaNO3) than bare HZO. SCM simulations reveal that the coordination configuration of diprotonated monodentate mononuclear (MM-H2) dominates at pH 3-6, while deprotonated bidentate binuclear (BB-H0) dominates at pH > 7. For each configuration, the intrinsic coordination constants (Kintr) of HZO@D201 (10-0.66 and 10-16.10, respectively) are significantly higher than those of bare HZO (10-12.24 and 10-44.42, respectively), indicating a superior chemical bonding affinity caused by nanoconfinement. The obtained Kintr values are used to predict arsenate adsorption isotherms in pH 3 and 9, and the results align with the SCM simulation outcomes. This study may offer a feasible method for investigating the nanoconfinement effect of emerging nanocomposite adsorbents from a thermodynamic perspective, and provide reference coordination equilibrium constants of HZO for research and practical application.

Eu(III) and Am(III) adsorption on aluminum (hydr)oxide minerals: surface complexation modeling

Americium is a highly radioactive actinide element found in used nuclear fuel. Its adsorption on aluminum (hydr)oxide minerals is important to study for at least two reasons: (i) aluminum (hydr)oxide minerals are ubiquitous in the subsurface environment and (ii) bentonite clays, which are proposed engineered barriers for the geologic disposal of used nuclear fuel, have the same ≡AlOH sites as aluminum (hydr)oxide minerals. Surface complexation modeling is widely used to interpret the adsorption behavior of heavy metals on mineral surfaces. While americium sorption is understudied, multiple adsorption studies for europium, a chemical analog, are available. In this study we compiled data describing Eu(III) adsorption on three aluminum (hydr)oxide minerals-corundum (α-Al₂O₃), γ-alumina (γ-Al₂O₃) and gibbsite (γ-Al(OH)₃)-and developed surface complexation models for Eu(III) adsorption on these minerals by employing diffuse double layer (DDL) and charge distribution multisite complexation (CD-MUSIC) electrostatic frameworks. We also developed surface complexation models for Am(III) adsorption on corundum (α-Al₂O₃) and γ-alumina (γ-Al₂O₃) by employing a limited number of Am(III) adsorption data sourced from literature. For corundum and γ-alumina, two different adsorbed Eu(III) species, one each for strong and weak sites, were found to be important regardless of which electrostatic framework was used. The formation constant of the weak site species was almost 10,000 times weaker than the formation constant for the corresponding strong site species. For gibbsite, two different adsorbed Eu(III) species formed on the single available site type and were important for the DDL model, whereas the best-fit CD-MUSIC model for Eu(III)-gibbsite system required only one Eu(III) surface species. The Am(III)-corundum model based on the CD-MUSIC framework had the same set of surface species as the Eu(III)-corundum model. However, the log K values of the surface reactions were different. The best-fit Am(III)-corundum model based on the DDL framework had only one site type. Both the CD-MUSIC and the DDL model developed for Am(III)-γ-alumina system only comprised of one site type and the formation constant of the corresponding surface species was ~ 500 times stronger and ~ 700 times weaker than the corresponding Eu(III) species on the weak and the strong sites, respectively. The CD-MUSIC model for corundum and both the DDL and the CD-MUSIC models for γ-alumina predicted the Am(III) adsorption data very well, whereas the DDL model for corundum overpredicted the Am(III) adsorption data. The root mean square of errors of the DDL and CD-MUSIC models developed in this study were smaller than those of two previously-published models describing Am(III)-γ-alumina system, indicating the better predictive capacity of our models. Overall, our results suggest that using Eu(III) as an analog for Am(III) is practical approach for predicting Am(III) adsorption onto well-characterized minerals.

Oxide- and Silicate-Water Interfaces and Their Roles in Technology and the Environment

Interfacial reactions drive all elemental cycling on Earth and play pivotal roles in human activities such as agriculture, water purification, energy production and storage, environmental contaminant remediation, and nuclear waste repository management. The onset of the 21st century marked the beginning of a more detailed understanding of mineral aqueous interfaces enabled by advances in techniques that use tunable high-flux focused ultrafast laser and X-ray sources to provide near-atomic measurement resolution, as well as by nanofabrication approaches that enable transmission electron microscopy in a liquid cell. This leap into atomic- and nanometer-scale measurements has uncovered scale-dependent phenomena whose reaction thermodynamics, kinetics, and pathways deviate from previous observations made on larger systems. A second key advance is new experimental evidence for what scientists hypothesized but could not test previously, namely, interfacial chemical reactions are frequently driven by "anomalies" or "non-idealities" such as defects, nanoconfinement, and other nontypical chemical structures. Third, progress in computational chemistry has yielded new insights that allow a move beyond simple schematics, leading to a molecular model of these complex interfaces. In combination with surface-sensitive measurements, we have gained knowledge of the interfacial structure and dynamics, including the underlying solid surface and the immediately adjacent water and aqueous ions, enabling a better definition of what constitutes the oxide- and silicate-water interfaces. This critical review discusses how science progresses from understanding ideal solid-water interfaces to more realistic systems, focusing on accomplishments in the last 20 years and identifying challenges and future opportunities for the community to address. We anticipate that the next 20 years will focus on understanding and predicting dynamic transient and reactive structures over greater spatial and temporal ranges as well as systems of greater structural and chemical complexity. Closer collaborations of theoretical and experimental experts across disciplines will continue to be critical to achieving this great aspiration.

Generic CD-MUSIC-eSGC model parameters to predict the surface reactivity of iron (hydr)oxides

The surface reactivity of iron (hydr)oxides plays a crucial role in controlling their interfacial reactions, for which various surface complexation models have been developed. The diversity of mineralogical properties of iron (hydr)oxides has resulted in a redundancy of model parameters, which hampers the modeling of iron (hydr)oxides in soils and sediments, where goethite, hematite and ferrihydrite dominate the iron (hydr)oxide mass fraction. To capture their combined surface reactivity, optimized generic protonation parameters of the Charge Distribution-Multisite Complexation (CD-MUSIC) extended-Stern-Gouy-Chapman (eSGC) model were derived by reanalyzing literature datasets and tested with some newly synthesized iron (hydr)oxides. It was observed that the proton and monovalent ion affinity constants of the different iron (hydr)oxides were located in a narrow range. For the singly- and triply-coordinated hydroxyl sites the obtained generic log(affinity constants) were 8.3 and 11.7 for the protonation reaction and -0.5 for the reaction with the monovalent background ions. Their combination with fixed site densities of singly-/triply-coordinated hydroxyl sites of 3.45/2.70, 5.00/2.50, and 5.80/1.40 sites/nm² for goethite, hematite, and ferrihydrite, respectively, provided good results. The Stern layer capacitances of the inner and outer Stern layers were set equal and could be acquired by an empirical correlation with the sample specific surface area (SSA). The CD-MUSIC-eSGC model with the generic model parameters enables good quality predictions of the proton reactivity of iron (hydr)oxides in 1:1 electrolyte solutions regardless of the sample heterogeneity. The advantages of the generic CD-MUSIC-eSGC model are twofold: (1) protonation of iron (hydr)oxides can be described without making use of spectroscopic measurements and proton titrations, and (2) the model calculations are greatly simplified.

Structural-controlled formation of nano-particle hematite and their removal performance for heavy metal ions: A review

Hematite is ubiquitous in nature and holds great promise for a wide variety of applications in many frontiers of environmental issues such as heavy metal remediation in environment. Over the past decades, numerous efforts have been made to control and tailor the crystal structures of hematite to improve its adsorption performance for heavy metal ions (HMIs). It is now well established that the adsorption behavior of hematite nanocrystals is strongly affected by their particle sizes, crystal facet contributions, and defective structures. This review examined the size- and facet-dependent hematite, as well as the defective hematite according to their fabrication methods and growth mechanisms. Furthermore, the adsorption performance of various hematite particles for HMIs were introduced and compared to clarify the structure-active relationships of hematite. We also overviewed the advances in charge distribution (CD)-multisite complexation (MUSIC) modeling studies about the HMIs adsorption at the hematite-water interface and the binding parameters. The Present review systematically describes how the formation conditions impact the structural and surface properties of hematite particles, thereby providing new strategies for enhancing the performance of hematite for environmental remediation.

Complexation mechanism of Pb2+ at the ferrihydrite-water interface: The role of Al-substitution

Ferrihydrite is a poorly crystalline iron (hydr)oxide and highly efficient adsorbent for heavy metals. Al-substitution in ferrihydrite is ubiquitous in nature. However, the effect of Al-substitution on the surface reactivity of ferrihydrite remains unclear due to its low crystallinity. The present study aims to clarify the microstructure and interfacial reaction of Al-substituted ferrihydrite. Al-substitution had little effect on the morphology and surface site density of ferrihydrite, while the presence of ≡AlOH^-0.5 sites resulted in higher proton affinity and surface positive charge of ferrihydrite. Besides, the affinity constant of Pb²⁺ adsorption on the surface of ferrihydrite decreased at higher Al content, which further decreased the adsorption performance of ferrihydrite for Pb²⁺. The modeling results revealed that bidentate complex was the dominant Pb complexation species on the surface of ferrihydrite, which was less affected by Al-substitution. The present study provides important insights into the effect of Al-substitution on the interfacial reaction at the ferrihydrite-water interface. The obtained parameters may facilitate the future advance of surface complexation model.

Thermal Transformation of Natural Schwertmannite in the Presence of Chromium

Schwertmannite is a metastable mineral playing a crucial role in the immobilization of metal(oid)s in acid mine drainage (AMD) systems. High temperatures associated with wildfires could lead to a sudden schwertmannite transformation, changing the mobility of metal(oid)s. The objective of the present study was to examine the thermal transformation from schwertmannite to hematite, and the subsequent effect on the chromium partitioning. The immobilization of arsenate after thermal transformation and its implications on chromium mobility was also evaluated. Natural schwertmannite, with increasing contents of chromium, was thermally treated between 200 to 800 °C. Transformation products were characterized by solid-phase techniques and selective chemical extractions. Results indicated a transformation to hematite at temperatures above 400 °C. The presence of chromium barely affected the temperature at which the transformation occurred, although partitioning of chromium in the mineral changed with temperature. As the temperature increased from 25 °C to 400 °C, chromium was less mobile and less outcompeted by arsenic adsorption, suggesting a larger contribution of inner-sphere complexes with increasing temperature. At temperatures above 600 °C, non-mobile forms strongly associated with neo-formed hematite were found. Finally, neo-formation of hematite led to a decrease in arsenic adsorption, implying a potentially enhanced arsenic mobility in AMD systems upon wildfires.

Outstanding performance of sulfurated titanomaghemite (Fe2TiO5) for hexavalent chromium removal: Sulfuration promotion mechanism and its application in chromium resource recovery

A lot of magnetic sorbents have been developed to meet the current demand for removing Cr (VI) from wastewater. However, the application of magnetic sorbents remains restricted by the unsatisfactory Cr (VI) removal efficiency, sorbent regeneration, and safe disposition of adsorbed Cr species. In this study, magnetic titanomaghemite (Fe₂TiO₅) was sulfurated with gaseous H₂S to improve its Cr (VI) removal efficiency. Sulfuration significantly improved the Cr (VI) removal efficiency of Fe₂TiO₅ from 3%-14% to 27%-82% at pH 4-10 due to drastically increased the electrostatic adsorption of Cr (VI) and heterogeneous reduction of adsorbed Cr (VI) to Cr (III). Furthermore, the sulfurated Fe₂TiO₅ recovered using magnetic separation can be regenerated by re-sulfuration without degrading the Cr (VI) removal efficiency, therefore, sulfurated Fe₂TiO₅ can be recycled for Cr (VI) removal after the regeneration. Moreover, Cr (VI) in aqueous solution can be enriched on sulfurated Fe₂TiO₅ after multiple adsorptions in the form of Cr₂O₃ in a content of more than 30% what can be considered as a source of chrome ore. Therefore, sulfurated Fe₂TiO₅ may be a promising, low-cost, and environment-friendly sorbent for Cr recovery as a co-benefit of Cr (VI) removal from wastewater.

Microstructure of Al-substituted goethite and its adsorption performance for Pb(II) and As(V)

Naturally occurring goethite commonly undergoes Al-substitution, while how changes in microstructure induced by Al-substitution affect the interactive reaction of Pb(II) or As(V) at the goethite-water interface remains poorly understood. This study reveals the structural properties of Al-substituted goethite and its adsorption behavior for Pb(II) and As(V) by multiple characterization techniques and Charge Distribution-Multisite Surface Complexation (CD-MUSIC) modeling. Al-substitution caused an obvious decrease in the length-to-width ratio in goethite particles and a slight decrease in the proportion of (110) facets. The presence of Al-O sites and higher surface roughness induced by Al-substitution contributed to a higher inner Stern layer capacitance (C₁) and surface charge density of goethite. CD-MUSIC modeling results further revealed that the affinity constant of Pb(II) complex (log K_Pb) at the goethite-water interface and the adsorption capacity of goethite for Pb(II) decreased with increasing amount of Al-substitution, while an opposite tendency was observed for As(V) adsorption. The dominant species of both Pb(II) and As(V) on goethite were bidentate complexes, and Al-substitution had a minor impact on the abundance of Pb(II) and As(V) complexes on the surface of goethite. Overall, these experimental and modeling results provide new and important insights into the interfacial reactivity of Al-substituted goethite and facilitate the prediction of the environmental fate of heavy metals.

Intercomparison and Refinement of Surface Complexation Models for U(VI) Adsorption onto Goethite Based on a Metadata Analysis

Adsorption of uranium onto goethite is an important partitioning process that controls uranium mobility in subsurface environments, for which many different surface complexation models (SCMs) have been developed. While individual models can fit the data for which they are parameterized, many perform poorly when compared with experimental data covering a broader range of conditions. There is an imperative need to quantitatively evaluate the variations in the models and to develop a more robust model that can be used with more confidence across the wide range of conditions. We conducted an intercomparison and refinement of the SCMs based on a metadata analysis. By seeking the globally best fit to a composite dataset with wide ranges of pH, solid/sorbate ratios, and carbonate concentrations, we developed a series of models with different levels of complexity following a systematic roadmap. The goethite-uranyl-carbonate ternary surface complexes were required in every model. For the spectroscopically informed models, a triple-plane model was found to provide the best fit, but the performance of the double-layer model with bidentate goethite-uranyl and goethite-uranyl-carbonate complexes was also comparable. Nevertheless, the models that ignore the bidentate feature of uranyl surface complexation consistently performed poorly. The goodness of fitting for the models that ignore adsorption of carbonate and the charge distributions was not significantly compromised compared with that of their counterparts that considered those. This approach of model development for a large and varied dataset improved our understanding of U(VI)-goethite surface reactions and can lead to a path for generating a single set of reactions and equilibrium constants for including U(VI) adsorption onto goethite in reactive transport models.

Application of surface complexation modeling on adsorption of uranium at water-solid interface: A review

Precise prediction of uranium adsorption at water-mineral interface is of great significance for the safe disposal of radionuclides in geologic environments. Surface complexation modeling (SCM) as a very useful tool has been extensively investigated for simulating adsorption behavior of metals/metalloids at water-mineral interface. Numerous studies concerning the fitting of uranium adsorption on various adsorbents using SCM are well documented, but the systematic and comprehensive review of uranium adsorption using various SCM is not available. In this review, we briefly summarized the rationale of SCM, including constant-capacitance-model (CCM), diffuse-layer-model (DLM), triple-layer-model (TLM); The recent progress in the application of SCM on the fitting of uranium adsorption towards metal (hydr)oxides, clay minerals and soil/sediments was reviewed in details. This review hopefully provides the beneficial guidelines for predicting the transport and fate of uranium in geologic environments beyond laboratory timescales.

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.