Using advanced surface complexation models for modelling soil chemistry under forests: Solling forest, Germany

A multi-surface model to predict Cd phytoavailability to wheat (Triticum aestivum L.)

The prediction of metal bioavailability in soils is critical to metal risk assessments and the amount of dissolved metal in soils is a key factor determining bioavailability. Because the recently developed geochemical multi-surface models (MSMs) offer a promising tool for the determination of metal partitioning in soils, in this study, a MSM based on generic parameters was used to assess the bioavailability of Cd in wheat (Triticum aestivum L.) growing in 12 soils with a wide range of properties. The amount of MSM-calculated dissolved Cd correlated strongly with the amount of Cd uptake by wheat (R²=0.873 for roots and R²=0.837 for shoots), and the model's performance was better than that of chemical extraction methods (0.01M CaCl₂, 0.43M HNO₃ and soil total Cd). The reactive fraction of soil organic matter, the soil/solution ratio, and the inclusion/exclusion of background cations influenced the calculation results. The best calculation condition was optimized. The application of the MSM was also examined in 84 wheat-soil samples from the field. The amount of Cd in wheat seeds had a stronger correlation with the amount of MSM-predicted Cd than with the amount of Cd obtained using chemical extraction methods. Our results suggested that MSM-calculated Cd is an effective indicator of the bioavailability of Cd in soils and demonstrated the utility of the method as a tool to assess the risk of Cd contamination in soils.

Modelling the potential mobility of Cd, Cu, Ni, Pb and Zn in Mollic Fluvisols

European floodplain soils are frequently contaminated with potentially toxic inorganic substances. We used a multi-surface model to estimate the aqueous concentrations of Cd, Cu, Ni, Pb and Zn in three Mollic Fluvisols from the Central Elbe River (Germany). The model considered complexation in solution and interactions with soil organic matter (SOM), a clay mineral and hydrous Al, Fe and Mn oxides. The amounts of reactive metals were derived from extraction with 0.43 M HNO₃. Modelling was carried out as a function of pH (soil pH ± 1.4) because it varies in floodplain soils owing to redox processes that consume or release protons. The fraction of reactive metals, which were dissolved according to the modelling, was predominantly <1%. Depending on soil properties, especially pH and contents of SOM and minerals of the clay fraction, the modelled concentrations partially exceeded the trigger values for the soil-groundwater pathway of the German soil legislation. This differentiation by soil properties was given for Ni, Pb and Zn. On the other hand, Cd was more mobile, i.e., the trigger values were mostly exceeded. Copper represented the opposite, as the modelling did not predict exceeding the trigger values in any horizon. Except for Pb and partially Zn (where oxides were more important), SOM was the most important adsorbent for metals. However, given the special composition and dynamics of SOM in mollic horizons, we suggest further quantitative and qualitative investigations on SOM and on its interaction with metals to improve the prediction of contaminant dynamics.

Modelling the concentrations of dissolved contaminants (Cd, Cu, Ni, Pb, Zn) in floodplain soils

Central European floodplain soils are often contaminated with potentially toxic metals. The prediction of their aqueous concentrations is a prerequisite for an assessment of environmental concerns. We tested the aqueous concentrations of cadmium (Cd), copper (Cu), nickel (Ni), lead (Pb) and zinc (Zn) derived from multi-surface adsorption modelling (on hydrous iron, aluminum and manganese oxides, clay and soil organic matter) against those analyzed in situ in the soil solution of four horizons of floodplain soils at the Elbe River, Germany. The input data for the reactive metals were derived from a seven-step sequential extraction scheme or from extraction with 0.43 M nitric acid (HNO₃) and evaluated in four modelling scenarios. In all scenarios, measured and modelled concentrations were positively related, except partially for Pb. Close reproduction of the measured data was obtained using measured data of accompanying cations and anions together with amounts of reactive metals from both the sequential extraction or from 0.43 M HNO₃ extraction, except for Cu, which was often strongly overestimated, and partially Cd. We recommend extraction with 0.43 M HNO₃ to quantify reactive metals in soil because the modelling results were metal-specific with better or equal results using the single extractant, the application of which is also less laborious. Approximations of ion concentrations and water contents yielded similar results. Modelled solid-phase speciation of metals varied with pH and differed from that from sequential extraction. Multi-surface modelling may be an effective tool to predict both aqueous concentrations and solid-phase speciation of metals in soil.

The use of assemblage models to describe trace element partitioning, speciation, and fate: a review

The fate of trace elements in soils, sediments, and surface waters is largely determined by their binding to reactive components, of which organic matter, metal oxides, and clays are considered most important. Assemblage models, combining separate mechanistic complexation models for each of the reactive components, can be used to predict the solid-solution partitioning and speciation of trace elements in natural environments. In the present review, the authors provide a short overview of advanced ion-binding models for organic matter and oxides and of their application to artificial and natural assemblages. Modeling of artificial assemblages of mineral components and organic matter indicates that the interactions between organic and mineral components are important for trace element binding, particularly for oxyanions. The modeling of solid-solution partitioning in natural systems is generally adequate for metal cations but less so for oxyanions, probably because of the neglect of organic matter-oxide interactions in most assemblage models. The characterization of natural assemblages in terms of their components (active organic matter, reactive oxide surface) is key to successful model applications. Improved methods for characterization of reactive components in situ will enhance the applicability of assemblage models. Collection of compositional data for soil and water archetypes, or the development of relationships to estimate compositions from geospatially available data, will further facilitate assemblage model use for predictive purposes.

Impact of root-induced mobilization of zinc on stable Zn isotope variation in the soil-plant system

Stable Zn isotopes are increasingly used to trace the source of metal pollution in the environment and to gain a better understanding of the biogeochemical cycle of Zn. In this work, we investigated the effect of plants on Zn isotope fractionation in the soil-plant system of the surface horizon of two Zn-rich Technosols (pH 6.73-7.51, total Zn concentration = 9470-56600 mg kg(-1)). In a column experiment, the presence of Agrostis capillaris L. significantly increased the mobilization of Zn from soil to leachate, predominantly as a result of root-induced soil acidification. The zinc isotope compositions of plants and leachates indicated that the Zn uptake by A. capillaris did not fractionate Zn isotopes as compared to the leachates. Within the plant, heavier Zn isotopes were preferentially retained in roots (Δ66Znroot - shoot=+0.24 to +0.40 ‰). More importantly, the Zn released in leachates due to root-induced mobilization was isotopically heavier than the Zn released in the absence of plants (Δ66Zn=+0.16 to +0.18 ‰). This indicates that the rhizosphere activity of A. capillaris mobilized Zn from another pool than the one that spontaneously releases Zn upon contact with the percolating solution. Mobilization of Zn by the roots might thus exert a stronger influence on the Zn isotope composition in the soil solution than the Zn uptake by the plant. This study highlights the key role of the rhizosphere activity in Zn release in soil and demonstrates that stable Zn isotopes provide a useful proxy for the detection of Zn mobilization in soil-plant systems.

An intermediate complexity dynamic model for predicting accumulation of atmospherically-deposited metals (Ni, Cu, Zn, Cd, Pb) in catchment soils: 1400 to present

The Intermediate Dynamic Model for Metals (IDMM) is a model for prediction of the pools of metals (Ni, Cu, Zn, Cd, Pb) in topsoils of catchments resulting from deposition of metals from the atmosphere. We used the model to simulate soil metal pools from 1400 onwards in ten UK catchments comprising semi-natural habitats, and compared the results with present day observations of soil metal pools. Generally the model performed well in simulating present day pools, and further improvements were made to simulations of Ni, Cu, Zn and Cd by adjusting the strength of metal adsorption to the soils. Some discrepancies between observation and prediction for Pb appeared to be due either to underestimation of cumulative deposition, or to overestimation of the metal pool under 'pristine', pre-industrial conditions. The IDMM provides a potential basis for large scale assessment of metal dynamics in topsoils.

Evaluation of the performance and limitations of empirical partition-relations and process based multisurface models to predict trace element solubility in soils

Here we evaluate the performance and limitations of two frequently used model-types to predict trace element solubility in soils: regression based "partition-relations" and thermodynamically based "multisurface models", for a large set of elements. For this purpose partition-relations were derived for As, Ba, Cd, Co, Cr, Cu, Mo, Ni, Pb, Sb, Se, V, Zn. The multi-surface model included aqueous speciation, mineral equilibria, sorption to organic matter, Fe/Al-(hydr)oxides and clay. Both approaches were evaluated by their application to independent data for a wide variety of conditions. We conclude that Freundlich-based partition-relations are robust predictors for most cations and can be used for independent soils, but within the environmental conditions of the data used for their derivation. The multisurface model is shown to be able to successfully predict solution concentrations over a wide range of conditions. Predicted trends for oxy-anions agree well for both approaches but with larger (random) deviations than for cations.