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Soil Science Society of America Journal 66:1182-1189 (2002)
© 2002 Soil Science Society of America

DIVISION S-2—SOIL CHEMISTRY

Soil Chemical Properties Controlling Zinc2+ Activity in 18 Colorado Soils

Kathryn M. Catlett*,a, Dean M. Heilb, Willard L. Lindsayc and Michael H. Ebingerd

a Neptune and Company, 1505B 15th Street, Los Alamos, NM 87544
b Dep. of Soil & Crop Sciences, Colorado State Univ., Fort Collins, CO 80523
c 205 Woodside Drive, Provo, UT 89604
d MS J495, Los Alamos National Lab., Los Alamos, NM 87545

* Corresponding author (kcatlett{at}neptuneandco.com)


   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
Zinc is a heavy metal of much interest since it is a plant micronutrient as well as a potential contaminant in soils. In soil solution, the speciation of Zn, and thus the free Zn activity, determines the plant availability of Zn as a micronutrient and its characteristics as a heavy metal contaminant. A better understanding of the mechanisms that control free Zn activity could improve soil treatments of Zn deficiency or toxicity. Possible controlling mechanisms for Zn activity include adsorption or precipitation. In our study, Zn2+ activity was measured by chelation and was related to soil properties for 18 alkaline soils from three farms in eastern Colorado. Soil organic C (OC) and pH were statistically significant parameters in a multiple regression with log Zn2+ activity. The significance of OC may suggest that adsorption onto organic matter controls Zn solubility in some of our soils. Log Zn2+ activities plotted with pH fell near the soil-Zn solubility line. However, the slope of the regression line was -1 rather than an expected -2, which indicates that another mechanism besides precipitation and dissolution of soil Zn may occur. Another possibility is that there are two different regions of solubility, one below pH 8.4 and one above pH 8.4. It is suggested that free Zn ions may adsorb on organic matter in a region of low pH and may precipitate as franklinite or other minerals, such as a Zn-containing kerolite, at high pH.

Abbreviations: CEC, cation-exchange capacity • EC, electrical conductivity • EDTA, ethylenediaminetetraacetic acid • IC, inorganic C • ICP-AES, inductively-coupled plasma-atomic emission spectroscopy • IS, ionic strength • ISE, ion-selective electrode • MF, mole fraction • OC, organic C • XAFS, X-ray absorption fine structure spectroscopy • XRD, X-ray diffraction


   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
ZINC has been the subject of much research in agriculture because it is an essential micronutrient for plants (e.g., Sadiq, 1991; Tiller et al., 1972). Zinc deficiencies commonly occur in Colorado and other Western states because of high soil pH. In contrast, Zn in high concentrations can be toxic to plants and animals, a subject of current environmental research (e.g., Barbarick et al., 1997; Lerch et al., 1990).

The solubility of Zn in soil solution must be quantified to evaluate bioavailability and transport of Zn in soils. Zinc solubility can be represented by the total concentration of Zn in solution or by Zn2+ activity. The activity of Zn2+ represents Zn availability to plants and can be used to predict possible solid phases that control Zn solubility in the soil (e.g., Lindsay 1979). Depending on the soil and soil properties, different Zn precipitates may form in soils and control Zn solubility at different levels. Lindsay (1979) explores the solubility of various Zn minerals that may be present in soils. A mineral without specific chemical properties, called "soil Zn," was used to indicate a lower Zn solubility than expected for many well-characterized Zn minerals.

Current studies have used spectroscopic techniques such as x-ray absorption fine structure spectroscopy (XAFS) and X-ray diffraction (XRD) to identify Zn minerals present in soils. Ford and Sparks (2000) used XAFS to suggest the formation of a Zn-Al layered double hydroxide in a pyrophyllite system. Manceau et al. (2000) identified franklinite (ZnFe2O4), willemite (Zn2SiO4), hemimorphite (Zn4Si2O7[OH]2 H2O), and Zn-containing magnetite ([Fe,Zn]Fe2O4) in smelter-contaminated soils using XRD and powder-extended XAFS.

It appears that Zn availability in some alkaline soils may be controlled by franklinite. Ma and Lindsay (1990)(1993) estimated free Zn activity by chelation in Colorado soils. They found that Zn2+ activities for uncontaminated soils were near the soil-Zn line (Lindsay, 1979) and that the solid phase that controls Zn availability could be franklinite in alkaline soils. However, the presence of franklinite in these soils was not confirmed by spectroscopic analysis. The solubility of franklinite varies according to Fe activity, which is a function of Fe mineral solubility (Lindsay, 1979). Iron minerals with greater solubility will depress franklinite solubility. Thus Zn solubility, as controlled by franklinite, is indirectly controlled by the dissolution or precipitation of Fe minerals in the soil.

The solubility of Zn and the mechanisms that control Zn solubility may vary with soil properties, such as pH, organic matter content, and clay content. Some studies have shown changes in Zn solubility with pH where adsorption appears to control Zn solubility at low pH while precipitation controls at high pH. Gupta et al. (1987) suggest that at high pH, precipitation reactions control Zn solubility, whereas at neutral to acidic pH, specifically adsorbed Zn may control Zn solubility. McBride and Blasiak (1979) state that different adsorption mechanisms are likely to control Zn solubility at different pH values. Singh and Abrol (1985) found that precipitation of willemite (Zn2SiO4) was likely at pH >7.9 in the sodic soils they studied. They also found that precipitation or adsorption may occur between pH 6 and 7.9 and that adsorption may occur below pH 6. Jeffrey and Uren (1983) conclude that at neutral to alkaline pH, specific adsorption of a hydrolyzed form of Zn (e.g., Zn[OH]+) may account for low soluble Zn concentrations.

Various studies have shown that there may be changes in Zn solubility with other soil properties. Zinc may bind to Fe, Mn, and Al oxides; clays; or organic matter in soils. Iron, Mn, and Al oxides contain surface-hydroxyl functional groups that may strongly bind metals, with increased adsorption at high pH (Sposito, 1984). Adsorption of Zn by these oxides has been suggested by several studies (Dang et al., 1996; Loganathan et al., 1977; McBride and Blasiak, 1979). McBride and Blasiak (1979) suggest that adsorption to oxide surfaces, which have a high affinity for Zn, may be important in controlling Zn solubility. Other studies have explored the adsorption of Zn onto clays (e.g., Bar-Tal et al., 1988; Elrashidi and O'Connor, 1982). Zinc adsorption by clays has been shown to be pH dependent (Baeyens and Bradbury, 1997; Cavallaro and McBride, 1984; Kurdi and Doner, 1983). The soil cation-exchange capacity (CEC) may also be related to Zn solubility (Brigatti et al., 1996; Choudhari, 1984; Maguire et al., 1981).

The effects of organic matter on Zn2+ activity are not clear. As discussed by McBride et al. (1997), it is difficult to distinguish the effects of organic matter since this property is often related to pH and since organic matter composition tends to vary across soils. In addition, it is difficult to design a study in which organic matter has a wide concentration range but other soil properties do not. Some studies indicate that total soluble Zn is not affected by organic matter (e.g., McBride et al., 1997). However, organic matter in soils may vary in concentration and in the types of functional groups. Such heterogeneity may bias a study by producing different metal solubilities in soils with similar OC concentrations.

The current study explores the effects of OC, pH, and other soil properties on Zn2+ activity in neutral to alkaline soils. The objectives of this experiment are to: (i) estimate the Zn2+ activity in neutral and alkaline soils with similar organic matter composition; (ii) investigate the relationships between the Zn2+ activity and the chemical properties of these soils; and (iii) relate the estimated Zn2+ activity to potential solid phases in the soils.


   MATERIALS AND METHODS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 REFERENCES
 
Soils
Soil samples were collected from a subset of farms used in a study by Iversen et al. (1998). The purpose of that study was to explore the variation in crop quality across farms in a relatively small area. Three farms (CF, LP, and Weld) were chosen for our study based on their range of organic matter contents and similarities in soil chemical properties. The goal in selecting three of the 18 farms was to choose soils of neutral to alkaline pH that had a relatively wide range of OC concentrations but similar expected organic matter composition, so that the OC concentrations varied while the types of organic functional groups did not. Each farm was divided into three parts and sampled at two depths (surface, 0–5 cm, and subsurface, 5–15 cm) for a total of 18 sampling locations. Two of the farms, CF and LP, were sampled along a toposequence from hilltop, to sideslope and footslope, whereas the Weld farm was relatively flat. For these two farms, the hilltop corresponded to the poorest quality crop, the sideslope to intermediate crop quality, and the footslope to the highest crop quality. Samples for the Weld farm were taken along the length of the field, assuming that organic matter varied across the field. The field was cleared of crop and residue at the time of sampling, and the crop quality could not be assigned to a soil unambiguously. The soils were air-dried, ground lightly with a mortar and pestle, and manually shaken through a 2-mm sieve.

Chemical Analysis
Several soil properties were measured for each sample. Total soil Zn was measured from a HNO3–HClO4 digest, and the solution was analyzed by inductively coupled plasma-atomic emission spectroscopy (ICP-AES) (Hossner, 1996). We determined the percentage of inorganic C (IC) by a modified volumetric method (Sherrod et al., 2002; Wagner et al., 1998). We measured total C by a Dorhmann DC-190 High-Temperature Total Carbon Analyzer. Organic C was estimated by the difference in total C and IC. We determined CEC by a method for soils with carbonates (Sumner and Miller, 1996). Percentage of clay was measured by the hydrometer method (Gee and Bauder, 1986).

The pH of the soil samples was measured in a 1:2 ratio of soil/solution after equilibration for 24 h and as part of the chelation method at 5 d. The 5-d pH average was used for all data and statistical analyses since it corresponds to the Zn2+ activity measurement. Soil chemical properties for the 18 soil samples are listed in Table 1 along with the farm, crop quality, and depth for each sample.


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  		Table 1. Soil properties for the 18 soils of this study, including inorganic C (IC), organic C (OC), and cation-exchange capacity (CEC). A represents good crop quality. B represents intermediate crop quality. C represents poor crop quality.

 
Chelation Method
The free Zn activity was measured by a modified chelation method (Ma and Lindsay, 1990; Norvell and Lindsay, 1969). We prepared soil suspensions with 10 g of soil and a final solution volume of 20 mL. Initially, the soil was added to a 125-mL Erlenmeyer flask along with 12 mL of deionized water. The samples were covered with parafilm slightly folded back at the top and equilibrated with the atmosphere on an oscillating shaker for 24 h at about 150 rpm. Subsequently, 8 mL of chelate solution (described below) were added to each of the samples, and the samples were shaken for four more days. A blank treatment for each soil was prepared by adding 8 mL of deionized water to the flask instead of a chelate solution. Samples were weighed daily and adjusted for evaporation loss. Duplicates and in some cases triplicates of each soil were used.

In this study, we chose ethylenediaminetetraacetic acid (EDTA) as the chelating agent because of the strong binding of Zn with EDTA at neutral pH. Calcium was chosen as the competing ion because in soils of neutral to alkaline pH, Ca competes well with Zn for EDTA. We prepared chelate solutions of different mole fractions (MFs) of Zn- and Ca-EDTA so that the total concentration of EDTA was 100 µM in the soil solution. Zinc chloride and CaCl2 standards were added to flasks containing the EDTA stock solution for a range of initial MFs of Zn- and Ca-EDTA from ~0 to 1. Zinc-EDTA MFs from 0.0001 to 0.2 and 0.005 to 0.9 (for more acidic soils) were used. We adjusted the pH of these solutions to ~7 with NaOH to reduce dissolution of the soil because of acidity. The solutions were then allowed to shake overnight and the pH was again adjusted to 7.0.

At the end of the 5-d shaking period, we measured the pH of each suspension with a combination pH electrode. The suspensions were then centrifuged at 39000 x g (18000 rpm) for 10 min using a Sorvall RC-5B refrigerated superspeed centrifuge (DuPont Instruments, Newtown, CT). We filtered the supernatant solutions through a 0.45-µm nylon syringe filter. The electrical conductivity (EC) of the filtrates was measured using a conductivity meter and the Ca2+ ion concentration was measured with an Orion Ca ion-selective electrode (ISE). We determined concentrations of Fe, Zn, Mn, and Cu in the extract by ICP-AES, since Fe, Mn, and Cu are the metals most likely to compete with Zn and Ca for EDTA in these soils. One hundred percent recovery of EDTA from solution is not expected and thus total EDTA concentration must be estimated. We found the concentration of total EDTA in the extract by adding excess ZnCl2 to the solution and measuring ZnEDTA2- by ion chromatography (Catlett, 2000). Excess Zn displaces other metals attached to EDTA so that the ZnEDTA2- peak is distinct in the spectra.

Theory and Calculations: Chelation
To calculate the Zn2+ activity, we combined equilibrium dissociation equations for CaEDTA and ZnEDTA to form an equation for Zn activity (L = EDTA):

where log Km0.01 is the mixed equilibrium constant for the given reaction at an ionic strength (IS) of 0.01 (Lindsay 1979). Mixed indicates that H ion is expressed in activity and all other quantities are in concentrations.

Rearranging Eq. [1] and recognizing that activity coefficients of Ca and Zn are equal yields:

[2]
where {theta} = [ZnL2-]/([ZnL2-] + [CaL2-]), the equilibrium MF of ZnEDTA2- with respect to ZnEDTA2- and CaEDTA2-.

The Ca2+ activity in solution and the equilibrium MF of ZnEDTA2- are needed to calculate Zn2+ activity. The Ca2+ activity is calculated by multiplying the Ca2+ concentration (measured by ISE) by the activity coefficient. The activity coefficient was estimated by the Davies equation that uses the ionic strength (IS) of the solution (Davies, 1962; Lindsay, 1979). The IS, in mol L-1, was estimated by the equation:

[3]
where EC is the electrical conductivity in dS m-1 (Griffin and Jurinak, 1973; Lindsay, 1979).

To calculate the equilibrium MF (MFeq) of ZnEDTA2-, a graph is made of the final MF (MFf) of ZnEDTA2- versus the initial MF of ZnEDTA2-. The MFf is calculated by:

[4]

The total Ca concentration in solution cannot be considered as CaEDTA2- because there is likely a significant amount of free Ca ion and inorganic Ca complexes in solution. Thus total EDTA concentration is measured and then CaEDTA2- is calculated by taking the total EDTA concentration and subtracting the sum of the metal-EDTA concentrations:

[5]

The total metal concentration, measured by ICP-AES, is assumed to be metal-EDTA, adjusted for the blank, since free metal concentrations are low in calcareous soils and form inorganic complexes of <1% of the concentration of EDTA. Near pH 8 total inorganic Zn, Fe, and Cu solubilities are expected to be ~10-10 M (Lindsay, 1979) and total Mn solubility is expected to be ~10-8 M (Lindsay, 1979), which are <1% the 10-4 M total EDTA concentration. Adjustments are made for the blank because sometimes metals can form measurable colloid complexes in the soil extract. Maximum Fe, Mn, and Cu solution concentrations were 22, 0.5, and 3.4 µM, respectively, with typical concentrations lower than these values for most soils.

The equilibrium ZnEDTA MF is the point of intersection of the final ZnEDTA MF versus initial ZnEDTA MF, with the line defined by: initial ZnEDTA MF = final ZnEDTA MF (i.e., the line y = x). An illustration of this calculation is shown in Fig. 1 for Soil 1.



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  		Fig. 1. For Soil 1, the final mole fractions (MFf) of ZnEDTA2- are plotted with the initial MFs of ZnEDTA2-. The equilibrium MF (MFeq) is found at the intersection of the data with the identity line (y = x).

 
Statistical Analyses
We performed statistical analyses using the statistical analysis package SAS (SAS Institute, 1988). The PROC REG command was used for regressions. Model selection was performed by stepwise selection with a significance level of 0.15 for variables to remain in the model.


   RESULTS AND DISCUSSION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
REFERENCES
 
The results from the chelation method are summarized in Table 2. The MFeq, log (Zn2+) and log (Ca2+) are averages of two or three replications. Standard deviations of Zn2+ activity were small, with the largest standard deviation being 0.30 log units. Soil 9 was the only soil without a replication, and thus has no standard deviation.


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  		Table 2. Equilibrium mole fractions of ZnEDTA2-, ZN2+, and Ca2+ activities for 18 Colorado soils.

 
A plot of the average log Zn2+ activity versus pH is given in Fig. 2 , with error bars of one standard deviation for log Zn2+ activity. The plot appears somewhat linear, with an R2 of 0.66 and regression line given by:

[6]



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  		Fig. 2. Log of Zn2+ activities plotted with pH for the 18 Colorado soils. Error bars are based on one standard deviation.

 
Log Zn2+ activity is also nearly linear with percentage of OC content, so that log Zn2+ activity increases with OC (Fig. 3) . The regression equation, without Soil 12, has an R2 of 0.61 and regression line given by:

[7]



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  		Fig. 3. Log Zn2+ activity versus percentage of soil organic C. Soil 12, the outlier, is labeled. Error bars are based on one standard deviation.

 
Soil 12 lies outside the linear trend of the data, and further regression analysis showed that soil 12 is an outlier according to Cook's distance (Neter et al., 1990). Cook's distance is a measure of the influence of a single point in the estimation of parameter coefficients in a regression model. Because of the large carbonate concentrations in Soil 12, there could have been an error in the total C or IC measurements.

There was not a significant relationship between clay content, total soil Zn, IC, or CEC and log (Zn2+). For these analyses, the logarithm was taken of the percentage of IC because of the large spread of the IC data. A value of 1 was added because some of the soils contained no measurable IC, and the log of zero is undefined.

Stepwise Regression Results
A multiple regression line was fit to the data to predict log (Zn2+) using a stepwise selection of the following parameters: pH, % OC, % clay, log (% IC + 1), and total soil Zn (ZnT). The stepwise selection procedure was used to identify the parameters that best predict log (Zn2+) for these data. Thus, a better empirical understanding of the soil chemical factors that influence log (Zn2+) can be developed. The outlier, Soil 12, was removed from the data set for this regression analyses. The resulting model is:

[8]
which has an R2 value of 0.81 and a p-value of <0.01.

A three-dimensional mesh plot of the data is depicted in Fig. 4 . In this figure, the largest Zn2+ activities are shown at low pH and high organic matter. One can see that Zn2+ activity decreases as pH increases and as organic matter decreases. There is a slight bulge in the graph at high pH and low organic matter. This bulge could indicate an interaction between pH and organic matter or simply variability in the data.



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  		Fig. 4. Three-Dimensional plot of log (Zn2+) versus pH and percentage of organic matter (OM) for the 18 Colorado soils.

 
The model of Eq. [8] differs from some previous studies (Anderson and Christensen, 1988; McBride et al., 1997) in that it shows that OC is important in predicting Zn solubility in soils. Anderson and Christensen (1988) reported that pH is more important than any other single property in predicting Zn mobility and that organic matter did not have much effect. McBride et al. (1997), using data from Gerritse and van Driel (1984), concluded that pH and total soil Zn were significant predictors of total Zn in solution, while organic matter was not. Those soils had a pH range of 4.3 to 7.9, a total soil Zn range from 9 to 2400 mg kg-1, an organic matter range of 1 to 34%, and a total soluble Zn concentration range of 0.8 to 2200 µg L-1. Some of the differences in results may be explained because those soils used total soluble Zn whereas in our study free Zn activity was used.

Thermodynamic Relationships
We plotted data from our research along with results from previous studies versus the solubility relationships for soil Zn and franklinite, where Fe was controlled by soil Fe or maghemite (Fig. 5) . These minerals were minerals with the closest Zn2+ activity values to the data. Some Zn minerals, such as Zn-Al layered double hydroxides (Zn2Al[OH]6Cl) (Ford and Sparks, 2000), had much lower Zn2+ activities than the data, while other Zn minerals, such as smithsonite (ZnCO3) and willemite-amorphous quartz (Lindsay, 1979), had much higher Zn2+ activities than the data. Zinc-containing kerolite (Si4Zn3O10[OH]2) (Manceau et al., 2000) in equilibrium with amorphous Si2O4 had a Zn2+ activity about two orders of magnitude below the franklinite-soil Fe solubility line. Manceau et al. (2000) gives the logarithm of the solubility constant for Zn-containing kerolite as 8 ± 6 and we used 8 for our calculations. This mineral or another Zn phyllosilicate may control Zn solubility, if the solubility were specified more closely. Additional research is needed to determine solubility constants of such Zn phyllosilicates with greater confidence. The chelation method was used to estimate Zn2+ activity in all of the studies represented in Fig. 5, except Sanders (1983), who used a resin method to distinguish Zn2+ from total soluble Zn.



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  		Fig. 5. Log Zn2+ activity versus pH including data from this study and other studies from the literature. The solid lines correspond to the franklinite-soil Fe, soil-Zn, and franklinite-maghemite lines of Lindsay (1979). Only the data for the uncontaminated soils from Ma and Lindsay (1993) were used.

 
All the data appear to be within 1.2 log units of the soil Zn line, which is between the franklinite-soil Fe and franklinite-maghemite lines. It is possible that franklinite controls the free Zn activity for these soils, since the franklinite lines could shift up or down depending upon which Fe mineral controls Fe solubility. For example, if a more amorphous maghemite (i.e., more soluble) controlled Fe solubility, the franklinite-maghemite line would shift down, since increased Fe solubility would decrease Zn solubility. The work of Brennan and Lindsay (1998) suggests that amorphous ferric hydroxide and amorphous magnetite could possibly control Fe solubility at a higher activity than maghemite, especially in microsites of lower redox potential. The Zn solubility could then be very close to the soil Zn line. The Zn solubility could also change if other cations substitute for Fe or Zn in franklinite. Ma (1991) showed that franklinite could vary somewhat in composition, depending on conditions of its synthesis, although franklinite is not known to form under ambient soil conditions. Franklinite has only been synthesized under elevated temperatures or pressures.

The present study reconfirms that franklinite or another Zn mineral could explain the solubility of Zn found in some alkaline soils. However, more research is needed to clarify the role of such a mineral in Zn solubility. Further research could confirm the presence of franklinite or a Zn-containing kerolite in noncontaminanted soils.

Interpretation of Slope
For many Zn minerals, two moles of H+ ions are consumed for every mole of Zn2+ released by dissolution when factors other than pH and Zn2+ activity are held constant. So the slope of the log (Zn2+) versus pH data is expected to be -2. Since for our study the slope is closer to -1 than to -2, there may be mechanisms at work besides precipitation and dissolution. One possibility is that OC may play a role in the control of free Zn solubility as indicated by the regression equation (Eq. [7]). In neutral to alkaline soils, Zn(OH)+ is a dominant solution species of Zn that may adsorb to soil and replace one H+:

[9]
where L is an organic ligand in the soil capable of complexing Zn. The resulting slope of log (Zn2+) versus pH would be -1. Jeffrey and Uren (1983) concluded that at neutral to alkaline pH, specific adsorption of a hydrolyzed form of Zn (e.g., Zn(OH)+) may control Zn solubility. The results of this study support a similar conclusion.

On the other hand, Zn2+ adsorption to organic matter could occur by two other mechanisms. Zinc may adsorb to organic matter and replace only one proton by adsorption to a carboxyl group, resulting in a slope of -1 for log (Zn2+) versus pH:


Another possibility is that an ion-exchange reaction occurs with a zero slope for log (Zn2+) versus pH. For example,

[11]

Different reactions may occur in soils, depending upon pH, solution composition, organic matter content, CEC, or other soil properties.

Previous studies of metals in soils have indicated the possibility of different regions of solubility depending on pH (e.g., Ma and Lindsay, 1995; Sauve et al., 1998). Some studies have noted that precipitation at high pH and adsorption at low pH may occur with Zn in soils (e.g., Gupta et al., 1987; Singh and Abrol, 1985). Brennan and Lindsay (1996) and Lindsay and Catlett (1998) illustrate that the slope may level off at low pH for all metals, including Zn. The data from our study may also be represented by two regions of different slopes for the log (Zn2+) versus pH graph (Fig. 6) . In Region 1, at pH <8.4, the plot of log (Zn2+) versus pH has a slope of ~-1; in Region 2, at pH >8.4, the slope is near -2. At high pH these soils may be controlled by a precipitation reaction involving franklinite or another zinc mineral, whereas at neutral pH an adsorption reaction, possibly to organic matter, may control Zn solubility. At low pH, adsorption reactions can hold Zn2+ activity at lower levels than solubility reactions would, allowing Zn solubility to be controlled by adsorption at low pH. Similarly, at high pH, precipitation reactions can hold Zn2+ activity at lower levels than adsorption reactions, thus allowing Zn solubility to be controlled by precipitation-dissolution at high pH. The pH value at which the change in the mechanism that controls solubility occurs will depend on the soil properties. Models of Zn adsorption to organic matter and Zn precipitation reactions could be used in future research to explore the possibility of two different solubility regions for the data.



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  		Fig. 6. Log of Zn2+ activities are plotted with pH. Two possible trend lines are drawn. Region 1 represents adsorption of Zn to organic matter or other surface. Region 2 represents precipitation of a Zn mineral, such as franklinite.

 
Caution should be used when comparing experimental results from different studies. Many different methods are used in discussions of Zn solubility. For example, some researchers use total soluble Zn concentrations for Zn solubility, whereas others use free Zn ion activities or labile Zn concentrations. In acidic soils these values may be similar, but in neutral to alkaline soils they can be different. At low pH the total soluble Zn and free Zn activity are nearly the same, but at high pH they are not the same because of hydrolysis species, organic Zn species, etc. Zinc solubility could also be controlled by other reactions in the soils of this study. Those reactions include other mineral precipitation reactions, such as the precipitation of a Ca-ZnCO3, or other adsorption reactions, such as adsorption onto Fe or Mn oxides or clay.

Future research on Zn adsorption in soils should include organic matter, as well as clay and oxides. Spectroscopic verification of mineral phases in soils should help justify proposed solubility controls, such as franklinite or a Zn phyllosilicate. Further investigation into the mechanism of Zn adsorption to organic matter and the characterization of important functional groups for Zn adsorption would prove to be interesting and worthwhile research. If functional groups could be distinguished and soil organic matter easily characterized, this possible mechanism for controlling Zn solubility could be given proper consideration in soil management decisions.


   NOTES
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 NOTES
ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 REFERENCES
 
Sponsoring organizations: National Science Foundation, Colorado State University, Los Alamos National Laboratory. From a thesis submitted to the Academic Faculty of Colorado State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy.

Received for publication March 5, 2001.


   REFERENCES
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 ABSTRACT
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