Nickel partitioning in acid soils at low moisture content
Introduction
Prediction of free metal ion concentration and activity in soil solutions is a challenging problem for evaluation of metal toxicity and bioavailability in terrestrial systems (Allen, 2001). It requires computational models applicable for a wide range of soil properties. Models based on chemical processes resulting in metal retention are preferred to empirical equations because their performance is not limited by the datasets used for the development of these models.
Nickel retention in soils is usually attributed to competitive adsorption (exchange) binding, surface precipitation, and the presence of minerals containing Ni in their crystal structure. Partitioning of the metal may strongly depend on the binding mechanism. Competitive adsorption binding is non-specific and is affected by changes in ionic strength (Doner, 1978), concentration of Ca2+ (Bowman et al., 1981, Harter, 1992, Wang et al., 1997), pH (Harter, 1983, Basta and Tabatavai, 1992), and complexation reactions with inorganic (Doner, 1978) and organic (Coughlin and Stone, 1995, Poulsen and Hansen, 2000) ligands in the solution phase. Soil organic matter (SOM) content and pH are assumed to be the most significant factors affecting Ni binding (Sauvé et al., 2000). The pH influences complexation of Ni in solution, precipitation of Ni hydroxide, and protonation of soil constituents. Nickel retention in soils dramatically increased above pH 7.0 to 7.5 (Harter, 1983). However, a rapid increase in Ni sorption over a narrow pH range (adsorption edge) is commonly found to occur at pH values where the concentration of NiOH+ is negligible relative to Ni2+ (Harter, 1983, Scheidegger et al., 1996, Barrow and Whelan, 1998). This effect is attributed to the increase in the net negative surface charge of the soil, which may enhance adsorption (Barrow and Whelan, 1998). Compilation of data on metal partitioning in soils has shown that pH accounts for 58% of the variability in the logarithm of the Ni partitioning coefficient (Kd), while inclusion of both pH and log [SOM] accounted for 76% of the variability (Sauvé et al., 2000). In some soils Kd correlated not only with pH and SOM, but also with dithionite–citrate–bicarbonate extractable Fe and Mn (Anderson and Christensen, 1988).
Formation of mixed Ni–Al-hydroxide precipitates was observed in clay systems at pH > 6.25 after spiking with soluble Ni salts at levels greater than 2700 mg Ni kg− 1 (Scheidegger et al., 1996, Elzinga and Sparks, 1999, Elzinga and Sparks, 2001). Elzinga and Sparks, 1999, Elzinga and Sparks, 2001 using X-ray absorption fine structure spectroscopy (XAFS) concluded that Ni uptake in the clays (montmorillonite, pyrophyllite, and illite) at metal loading up to 3000 mg kg− 1 is related to both adsorption and surface precipitation mechanisms.
Binding of Ni by dissolved organic matter may increase total Ni concentration in soil solutions. Dunemann et al. (1991) found that a large proportion of the total Ni in soil solutions from two soils, one of which had been amended with sewage sludge, was present in large molecular size fractions. Christensen and Christensen (2000) analyzed anaerobic samples of groundwater under a landfill with dissolved organic carbon (DOC) concentration 190 mg l−1 at pH = 5.5 to 6.0 using ion-exchange resin technique and found that 50 to 75% of Ni was bound with dissolved organic matter. In lake waters with DOC concentration up to 10 mg l−1, 4 to 40% of Ni was complexed with dissolved organic matter (Guthrie et al., 2005). Diffusive gradients in thin films (DGT) method indicated that 32% of Ni available in a humic-rich stream water with pH = 7.5 containing 14.6 mg DOC l−1 was complexed by organic substances (Zhang, 2004).
Nickel retention in soils may be not completely reversible. Bowman et al. (1981) observed only slight desorption of freshly sorbed Ni by treating the samples with 0.01 M CaCl2 and concluded that there was extreme hysteresis of Ni retention. Only 70 to 80% of retained metal could be extracted with 0.01 M HCl (Harter, 1983). This hysteresis effect can preclude the prediction of metal release based on sorption isotherms.
Computational techniques used to fit chemical speciation of Ni in surface waters and soils are based on the metal distribution coefficient (Kd) (Anderson and Christensen, 1988, Sauvé et al., 2000), the Freundlich equation (Bowman et al., 1981, Zehetner and Wenzel, 2000, Buchter et al., 1989), or on chemical equilibrium models such as the Windermere Humic Aqueous Model (WHAM) (Tipping, 1998). The distribution coefficient of Ni was dependent on the pH of solution, Ni loading, and soil properties. Increase in CaCl2 concentration from 0.001 M to 0.1 M resulting in a nine-fold decrease in Kd was interpreted as being caused by the competitive adsorption between Ni and Ca and the effect of ionic strength on exchange selectivity (Bowman et al., 1981, O'Connor et al., 1983, Staunton et al., 2002, Staunton, 2004). Since adsorption isotherms of nickel were strongly nonlinear (Barrow, 1998, Zehetner and Wenzel, 2000, Bowman et al., 1981, Basta and Tabatavai, 1992, Staunton, 2004), the Kd value also decreased with increasing addition of Ni. Therefore, a constant Kd is not valid for modeling of Ni partitioning in soils. The Freundlich equation fitted measured Ni sorption isotherms in each case (Bowman et al., 1981, Buchter et al., 1989, Zehetner and Wenzel, 2000), but the relationship between the parameters of this equation and soil properties remains unclear.
A promising approach is the application of mechanistic assemblage models using a combination of sub-models for independent equilibrium interaction of the metals ions and protons with individual binding phases. The Windermere Humic Aqueous Model VI (WHAM VI) has been applied to predict metal partitioning in soil suspensions. The model described in detail by Tipping (1998) assumes fulvic and humic acids as rigid spheres of uniform size with ion-binding groups positioned on the surface. It is taken that there are only two types of binding sites (A and B), each consisting of four different types of sub-sites present in equal amount. The model also includes the electrostatic effects via a Donnan expression and the competition among protons and metal ions. The default parameters of the model have been derived by fitting using published data on metal sorption by organic matter. WHAM VI was applied to calculate Ni partitioning with aquatic suspended particulate matter (Lofts and Tipping, 1998), Ni complexation with dissolved organic matter (Christensen and Christensen, 2000), and Ni partitioning in soil solutions (Tye et al., 2004). The agreement between the measured concentration of free Ni ion and the value predicted by WHAM was within 50% for the stream water (Zhang, 2004) and within one order of magnitude for the soil leachate (Dijkstra et al., 2004). Reasonable agreement between the percentage of free Ni2+ predicted by WHAM VI based on solution composition and the measured values was reported for contaminated soil pore water (Nolan et al., in press). However, the ability of WHAM to predict free nickel ion concentration in surface waters, soil suspensions, and leachates should not be taken to imply that it is necessarily applicable to soils at low moisture content with higher concentrations of dissolved organic matter and specific properties of soil pore water (Wolt, 1994).
The objectives of this study were to determine the relationships between the amount of Ni in the soils and the concentration of Ni in soil solutions (sorption isotherms) at low moisture content for a wide range of soil properties and to evaluate the validity of various model approaches to predict Ni sorption isotherms.
Section snippets
Soil properties
This study employed 10 non-calcareous soils collected from different regions of the European Union, with pH = 3.6 to 6.7 and soil organic carbon (SOC) content 0.25 to 33.1%, that were sampled from the surface (0–20 cm) layer. Selected soil properties, determined according to standard procedures (Methods of Soil Analysis, 1996), are presented in Table 1.
Separation and analyses of soil solutions
Soil samples were spiked with NiCl2 solution to provide loading 20–4800 mg Ni per kg soil, mixed well and placed into plastic 200-mL bottles.
Effect of Ni sorption on the composition of soil solutions
The increase in the amount of added Ni resulted in the increase in Ni concentration in soil solution and in the amount of sorbed Ni (Fig. 1). The data are plotted in a log–log scale since the ranges of concentrations covered 1.5 to 3.5 orders of magnitude. The relationships between the logarithms of sorbed concentration and solution concentration were close to linear for all studied soils. The lines in the figure present a linear fit of the data. Linear log–log relationships have been
Conclusions
Nickel retention in non-calcareous soils with pH 3.6 to 6.7 results in the displacement of Ca, Mg, and Na into soil solution and decrease in soil solution pH. The total amount of cations released is from 0.36 to 1.00 of the amount of Ni sorbed (molc: molc). The main variables accounting for Ni release in soil solution are soil pH, soil organic matter content, and clay content, along with dissolved cations concentrations. In the soils with organic carbon content > 1%, Ni concentration in soil
Acknowledgments
The authors are grateful to the Nickel Producers Environmental Research Association (NiPERA) and to the Center for Study of Metals in the Environment, University of Delaware, USA for financial support of this study. Soil samples for this study and the data on soil composition were provided by courtesy of Prof. E. Smolders and Dr. K. Oorts (Katholic University Leuven, Belgium).
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