author's personal copy · author's personal copy a surface complexation and ion exchange...

This article appeared in a journal published by Elsevier. The attachedcopy is furnished to the author for internal non-commercial researchand education use, including for instruction at the authors institution

and sharing with colleagues.

Other uses, including reproduction and distribution, or selling orlicensing copies, or posting to personal, institutional or third party

websites are prohibited.

In most cases authors are permitted to post their version of thearticle (e.g. in Word or Tex form) to their personal website orinstitutional repository. Authors requiring further information

regarding Elsevier’s archiving and manuscript policies areencouraged to visit:

http://www.elsevier.com/copyright

http://www.elsevier.com/copyright

Author's personal copy

A surface complexation and ion exchange model of Pband Cd competitive sorption on natural soils

Susana Serrano a,b,*, Peggy A. O’Day b, Dimitri Vlassopoulos c,Maria Teresa Garcıa-Gonzalez a, Fernando Garrido a

a Centro de Ciencias Medioambientales, Consejo Superior de Investigaciones Cientıficas., Serrano 115 dup., 28006 Madrid, Spainb School of Natural Sciences, University of California, Merced, CA 95344, USA

c S.S. Papadopulos & Associates Inc., Portland, OR 97204, USA

Received 5 May 2008; accepted in revised form 3 November 2008; available online 3 December 2008

Abstract

The bioavailability and fate of heavy metals in the environment are often controlled by sorption reactions on the reactivesurfaces of soil minerals. We have developed a non-electrostatic equilibrium model (NEM) with both surface complexationand ion exchange reactions to describe the sorption of Pb and Cd in single- and binary-metal systems over a range of pH andmetal concentration. Mineralogical and exchange properties of three different acidic soils were used to constrain surface reac-tions in the model and to estimate surface densities for sorption sites, rather than treating them as adjustable parameters. Soilheterogeneity was modeled with >FeOH and >SOH functional groups, representing Fe- and Al-oxyhydroxide minerals andphyllosilicate clay mineral edge sites, and two ion exchange sites (X� and Y�), representing clay mineral exchange. An opti-mization process was carried out using the entire experimental sorption data set to determine the binding constants for Pb andCd surface complexation and ion exchange reactions.

Modeling results showed that the adsorption of Pb and Cd was distributed between ion exchange sites at low pH valuesand specific adsorption sites at higher pH values, mainly associated with >FeOH sites. Modeling results confirmed the greatertendency of Cd to be retained on exchange sites compared to Pb, which had a higher affinity than Cd for specific adsorptionon >FeOH sites. Lead retention on >FeOH occurred at lower pH than for Cd, suggesting that Pb sorbs to surface hydroxylgroups at pH values at which Cd interacts only with exchange sites. The results from the binary system (both Pb and Cd pres-ent) showed that Cd retained in >FeOH sites decreased significantly in the presence of Pb, while the occupancy of Pb in thesesites did not change in the presence of Cd. As a consequence of this competition, Cd was shifted to ion exchange sites, where itcompetes with Pb and possibly Ca (from the background electrolyte). Sorption on >SOH functional groups increased withincreasing pH but was small compared to >FeOH sites, with little difference between single- and binary-metal systems. Modelreactions and conditional sorption constants for Pb and Cd sorption were tested on a fourth soil that was not used for modeloptimization. The same reactions and constants were used successfully without adjustment by estimating surface site concen-trations from soil mineralogy. The model formulation developed in this study is applicable to acidic mineral soils with loworganic matter content. Extension of the model to soils of different composition may require selection of surface reactionsthat account for differences in clay and oxide mineral composition and organic matter content.Published by Elsevier Ltd.

1. INTRODUCTION

In the last decades, changes in the global budget of hea-vy metals at the earth’s surface have led to either accumu-lations in excess of the natural background, or leachingthat potentially pollutes water bodies, or both. Their

0016-7037/$ - see front matter Published by Elsevier Ltd.

doi:10.1016/j.gca.2008.11.018

* Corresponding author. Address: Centro de Ciencias Medioam-bientales, Consejo Superior de Investigaciones Cientıficas., Serrano115 dup., 28006 Madrid, Spain.

E-mail address: [email protected] (S. Serrano).

www.elsevier.com/locate/gca

Available online at www.sciencedirect.com

Geochimica et Cosmochimica Acta 73 (2009) 543–558


ultimate fate in the environment is often controlled by sorp-tion reactions onto the mineral surfaces of soil particles,such as exchange and surface complexation reactions(Sposito, 1984). Surface complexation models (SCM) havebeen used widely as an equilibrium-based approach to de-scribe and predict metal cation and anion sorption reac-tions on surfaces of reactive phases in soils such as oxideand clay minerals (Hayes and Leckie, 1987; Schindleret al., 1987; Davis and Kent, 1990; Gunneriusson et al.,1994; Lackovic et al., 2004a; Hizal and Apak, 2006; Pont-hieu et al., 2006). Most of these studies have consisted ofcontrolled laboratory investigations of metal sorption fromsingle-ion solutions on pure mineral surfaces, in the pres-ence or absence of organic compounds. However, theoreti-cal applications of SCM based on simple systems have thusfar been unable to generally supply quantitative predictionsof multiple metal ion uptake in natural soil mixtures. Thecomplexity of soil materials and their surface site heteroge-neity hinder the direct identification of the most activemineralogical and organic components. Thus, the determi-nation of ‘‘intrinsic” stability constants for molecular-scalemetal sorption reactions and estimation of surface site den-sities for sorption sites is problematic (Lee et al., 1996;Wang et al., 1997; Davis et al., 1998; Wen et al., 1998;Christl and Kretzschmar, 1999; Calvet et al., 2007).

Since the early work of Stumm et al. (1970), numerousvariations of SCM have been developed to describe metaluptake onto soil components (Davis and Leckie, 1979; vanRiemsdijk et al., 1986; Westall, 1986; Dzombak and Morel,1990). These models can be characterised by differentschemes of the interfacial structure in terms of supposedreactions and description of the electric double-layer (Wes-tall and Hohl, 1980). More recently, SCM approaches havebeen used to model adsorption of cations and anions in nat-ural soils. For instance, Weng et al. (2001) applied a multi-surface model to predict heavy metal activity in sandy soilsamples using the Charge Distribution Multi-Site Complex-ation (CD-MUSIC) model (Hiemstra and van Riemsdijk,1996; Hiemstra and van Riemsdijk, 1999). This model wasused by Weerasooriya et al. (2007) to describe the interac-tions of Hg(II) with gibbsite-rich soils. CD-MUSIC andother electrostatic double-layer models treat sorption pro-cesses as intrinsic and electrostatic interactions between theion and the surface. In this approach, surface complexesare considered as having a spatial distribution of charge thatcan be attributed to different electrostatic planes. In con-trast, the non-electrostatic surface complexation model(NEM) excludes explicit electrostatic terms from the masslaw equations for surface equilibria, such that all chemicaland electrostatic interactions are implicitly included in theequilibrium constant for the reaction (i.e, the free energyof sorption). This approach treats surface functional groupsin the same manner as dissolved ligands or complexing metalions (Davis and Kent, 1990), but without a separate activitycoefficient correction for the surface complex. The applica-tion of NEM to describe heavy metal sorption in soils andsediments is not common in the literature. Some exceptionsare the study of Voegelin et al. (2001), who used a combinedcation exchange and specific sorption model to describe thecompetitive sorption of Cd, Zn and Ni in an acidic soil, and

the study of Van Benschoten et al. (1998), who applied aNEM to Pb sorption on soils and mineral phases.

Multiple metal species are often simultaneously presentin a natural soil solution. While single-ion sorption studiesmay adequately predict the retention of strongly bondedions, sorption of less strongly bonded ions is more likelyto be affected by the presence of competing species in sys-tems with multiple metal ions (Harter, 1992). Assessmentsof potential bioavailability and toxicity of metals in con-taminated soils may depend on whether experiments areperformed using single- or multi-metal solutions. Althoughthe significance of competitive sorption on individual metalsorption behavior has long been addressed (Benjamin andLeckie, 1981a; Christl and Kretzschmar, 1999; Bradburyand Baeyens, 2005; Serrano et al., 2005; Tsang and Lo,2006), the development of consistent and predictive SCMthat can be applied to describe multiple metal-soil systemsare still lacking. Only a few studies have modeled competi-tive sorption of metals in soils and sediments. For example,Voegelin et al. (2001) described competitive sorption andtransport of Cd, Zn and Ni in an acidic soil. Voegelinand Kretzschmar (2003) developed an empirical model forCd–Ca and Zn–Ca exchange that described coupled effluentpatterns arising from sorption competition between cation,and Kretzschmar and Voegelin (2001) modeled competitivesorption and release of heavy metals in soils.

Spectroscopic studies of metal ions such as Pb and Cd canbe used to place constraints on the stoichiometry of sorbedcomplexes considered in SCM formulations. Using X-rayabsorption spectroscopy (XAS), Pb has been shown to be ad-sorbed mainly as a mononuclear bidentate complex to edgesof FeO6 octahedra on both goethite and hematite (Bargaret al., 1997; Trivedi et al., 2003), and as both bidentateedge-sharing and monodentate corner-sharing complexeson ferrihydrite (Dyer et al., 2003; Trivedi et al., 2003). Resultsfrom XAS also indicated the formation of inner-sphere com-plexes for Pb sorption on the edges of phyllosilicate mineralphases (Strawn and Sparks, 1999). For Cd, Spadini et al.(1994) used XAS to show the formation of inner-sphere com-plexes on high affinity sites on ferrihydrite. Randall et al.(1999) corroborated this study by showing the adsorptionof Cd on goethite as bidentate surface complexes. Prior stud-ies (Schindler et al., 1987; Lackovic et al., 2004b; Bhattachar-yya and Gupta, 2007; Gu and Evans, 2007) suggested specificCd retention on clay mineral hydroxyl sites, although nospectroscopic studies have been published to date to ourknowledge for Cd sorption on clay minerals.

In addition to specific metal sorption, previous studiesindicate that retention of Pb and Cd on permanent chargesites of the siloxane surfaces of phyllosilicate minerals alsooccurs through ion exchange reactions in which the sorbedion is assumed to retain its inner hydration sphere (Dzom-bak and Morel, 1990; Lackovic et al., 2004b). Electrostati-cally bound Pb and Cd can be displaced by other cationspresent in solution through exchange reactions that are as-sumed to be reversible (Ziper et al., 1988; Kraepiel et al.,1999; Bradbury and Baeyens, 2005; Srivastava et al.,2005; Gu and Evans, 2007).

In this study, we developed a non-electrostatic surfacecomplexation and ion exchange model for the sorption of

544 S. Serrano et al. / Geochimica et Cosmochimica Acta 73 (2009) 543–558


Pd and Cd on three soils from Central Spain. We modeledthe sorption behavior of these two toxic and ubiquitousheavy metals in single (Pb or Cd) or binary (Pb and Cd)solutions as a function of pH and initial metal concentra-tion. The model employs both surface complexation and ex-change reactions for which surface site densities wereestimated from mineralogical fractions in the soil (ratherthan treated as an adjustable model parameter). Optimiza-tion of equilibrium constants for surface reactions was donewith an iterative global minimization using the entire set ofexperimental data to identify a minimum set of surfacereactions and equilibrium constants. Model results of Pband Cd sorption behavior in single and binary systemsprovide insight into competitive sorption processes in thesoils. Lastly, we examined the general applicability of theapproach by modeling competitive sorption of Pb and Cdon a fourth soil not used in the model calibration byestimating surface site densities from mineralogical charac-teristics, but with no adjustment of previously optimizedsurface equilibrium constants.

2. MATERIALS AND METHODS

2.1. Soil characteristics

The surface horizons (0–15 cm) of three acid soils wereobtained from two different locations in Central Spain.Two soils (1 and 2) were developed from Pliocene-Quater-nary-aged formations in Caceres and were classified as Plin-thic Palexerult and Arenic Pachic Palexerult, respectively.The third soil (3) was developed on a hillslope in Madridand was classified as a Vertic Haploxerert. A fourth soil(soil T), not used in parameter optimization, was classifiedas Ultic Palexeralf (Soil Survey Staff, 1999) and was alsodeveloped from Pliocene-Quaternary-aged formations inCaceres. All samples were air-dried, crushed and sievedthrough a 2 mm mesh prior to characterization and sorp-tion studies. Physical, chemical, and mineralogical proper-ties were determined in a previous study (Serrano et al.,2005) and are summarized in Table 1. Soil pH was mea-sured in deionized water (pHw) and in 74.54 g/L KCl(pHK) (in a 1:2.5 suspension). The exchangeable bases wereextracted with 1 M ammonium acetate (NH4OAc), pH 7(Thomas, 1982) and the exchangeable aluminium (AlK)was extracted with 1 M KCl (Barnhisel and Bertsch,1982). The effective cation exchange capacity (ECEC) wascalculated as the sum of AlK and the amounts of Ca, Mg,Na and K extracted by 1 M NH4OAc at pH 7 (Shuman,1990). Soil organic carbon (OC) content was determinedby wet digestion (Walkley and Black, 1934). Total Al andFe concentration in the poorly crystalline and amorphousfraction of the soils was measured by chemical extractionwith 0.2 M ammonium oxalate + 0.2 M oxalic acid solutionat pH 3 (McKeague and Day, 1966). The mineralogicalcompositions of the clay (62 lm) fractions were identifiedby X-ray powder diffraction on a Philips X’Pert diffractom-eter with graphite-monochromated CuKa radiation. TheXRD patterns were obtained from random powder mountsand various oriented aggregates of the Mg- and K-clay (air-dried, ethylene glycol-solvated, heated at 300 �C for 3 h and

heated at 500 �C for 3 h). Semi-quantitative estimates ofmineral fractions for quartz, feldspar, goethite, hematiteand total phyllosilicates were obtained from random pow-der patterns, integrating the area of the diffraction maximaat 0.426, 0.325, 0.416, 0.269 and 0.444 nm, respectively, andusing the mineral intensity factors reported by Schultz(1964). Approximate abundances of kaolinite, illite, andsmectite were obtained in a similar way, using the orientedaggregate patterns (peak areas at 0.72 nm for kaolinite,1.00 nm for illite, and 1.69 nm for smectite in ethylene gly-col-solvated aggregate).

2.2. Metal sorption experiments

Lead and/or Cd uptake by soils was examined amongthree soils, six pH values between 2 and 6, and five initial

Table 1Physical and chemical properties of the experimental soils.

Soilsa 1 2 3 T

pHwb 5.2 (0.02) 5.0 (0.02) 5.8 (0.03) 6.1 (0.02)

pHkc 4.2 (0.03) 3.8 (0.01) 4.3 (0.02) 4.5 (0.02)

ECEC (cmolc kg�1)d 1.79 (0.11) 1.09 (0.05) 20.5(1.25)

3.01(0.11)

Ca (g kg�1) 0.06 (0.02) 0.01(0.00) 2.82(0.58)

0.32(0.04)

Mg (g kg�1) 0.009(0.00)

0.02 (0.02) 0.62(0.50)

0.05(0.01)

Na (g kg�1) 0.009(0.00)

0.004(0.00)

0.04(0.03)

0.02(0.12)

K (g kg�1) 0.03 (0.00) 0.04 (0.01) 0.15(0.02)

0.26(0.12)

Al (g kg�1) 0.11 (0.08) 0.06 (0.03) 0.05(0.05)

0.02(0.01)

Organic Carbon (gkg�1)

17 (1.0) 3 (0.1) 61 (6.5) 12 (1.0)

Clay (g kg�1)e 75 (5) 45 (6) 230 (19) 156 (5)Feext (g kg�1)f 3.11 2.35 1.65 3.83Alext (g kg�1)f 10.64 5.86 4.30 4.88

Fraction 6 2 lmg

Kaolinite (%) 57 26 12 32Illite (%) 11 52 36 22Smectite (%) nd nd 48 14Vermiculite (%) 8 nd nd ndGoethite (%) 6 nd nd 7Hematite (%) 6 nd nd 3Feldspar (%) nd 9 nd ndQuartz (%) 12 13 4 22

a Mean values and standard deviation between parenthesis(n = 3); nd = not detected.

b pHw = pH measured in deionized water.c pHk = pH measured in 1 M KCl.d ECEC = Effective cation exchange capacity (centimoles charge

per kg) as the sum of Ca, Mg, Na, K and Al (Shuman, 1990).e62 lm fraction.

f Total Al and Fe contents in the poorly crystalline andamorphous fraction of the soils measured by extraction (McKea-gue and Day, 1966).

g Semi-quantitative mineralogical composition (relative%) of thesoils. Maximum errors are 15% for major constituents and 25% forminerals whose concentrations are less than 20%.

A surface complexation and ion exchange model of Pb and Cd competitive sorption on soils 545


metal concentrations in a full factorial scheme, with tworepetitions for two metals both in single- (Pb or Cd) andbinary-metal (Pb + Cd) systems. All sorption experimentswere performed by adding 15 ml of single- (Pb or Cd) orbinary-metal (Pb + Cd) solutions to 2 g soil samples inpolypropylene centrifuge tubes. Metal solutions were pre-pared from the chloride salt of each metal using 1 mMCaCl2 as a background electrolyte. The initial concentra-tions of Pb and Cd in the single-metal solutions were 0.5,1, 2, 4, and 6 mM. In the binary-metal systems, the Pband Cd initial concentrations were adjusted to 0.23, 1,1.7, 2.3, and 3.75 mM for Pb and 0.18, 0.8, 1.5, 2.00, and3.0 mM for Cd. The solutions used in each single-metalexperiment had a similar ionic strength (1 mMCaCl2 ± 0.02 mM) as that used in the corresponding binaryexperiment. Suspensions were shaken for 24 h at25 �C ± 2 �C and the pH was maintained at 2, 3, 4, 4.5, 5and 6 by the addition of 0.1 M HNO3 or 1 M NaOH as nec-essary. The pH was measured before, during, and after 24 hequilibration and adjusted as needed (typically one to twoadjustments during equilibration were done, with changesin pH of 0.1–0.6). The isotherm equilibrium experimentswith soil T were carried out at the natural pH of the soiland the same metal concentrations as above (Serranoet al., 2005). The suspensions were then centrifuged at6640g and supernatant solutions removed, filtered (What-man No. 42, pore size 2.5 lm) and acidified prior to thedetermination of metal concentration using ICP-AES.The precision of the measurement for Cd and Pb was1.56 and 1.63% RSD, respectively. Limits of detection werecalculated as three standard deviations of the instrument re-sponse from 10 repeated analyses of sample matrix-matched blank solutions. The detection limits showed thatconcentrations as low as 6.3 and 20.4 lg l�1 for Cd and Pb,respectively, could be analysed.

2.3. Model simulations and parameter optimization

Model simulations were carried out using the computercode PHREEQC v.2 (Parkhurst and Appelo, 1999) in com-bination with the parameter optimization program PEST(Doherty, 2002). A non-electrostatic equilibrium model(NEM) was developed in PHREEQC (using wateq4f.dat

thermodynamic database file for aqueous species) to de-scribe Pb and Cd sorption in single and binary systems(see below). Model simulations were generated for a totalof 393 batch experiments of Pb and Cd sorption on all threesoils, where 333 points correspond to the sorption pHexperiments carried out in this study and the other 60points were taken from equilibrium adsorption experimentsof a previous study (Serrano et al., 2005). Surface site con-centrations were estimated (see below) and held fixed dur-ing model optimization. Surface site deprotonationconstants were fixed on values taken from the literature.Conditional equilibrium constants for metal ion sorptionon hydroxyl surface sites and ion exchange sites were ad-justed during the optimization process. The program PESTwas used to solve the non-linear regression problem byminimizing a weighted least-squares objective function withrespect to the adjusted parameter values using the Gauss–

Marquardt–Levenberg algorithm. The model was itera-tively optimized to all of the experimental data simulta-neously in order to capture the maximum experimentalvariability. Sorption reactions whose adjusted parametersdid not statistically contribute to the overall variance reduc-tion of the optimization process were progressively elimi-nated from the final model.

Saturation indices for possible Pb or Cd phases werealso calculated and used to identify experiments in whichprecipitation might have occurred based on the metal con-centrations of the initial solutions. Experiments in whichsaturation of any solid phase was theoretically exceededwere excluded from the model data set. In addition, disso-lution of solid phases was not included in the model,although some dissolution of poorly crystalline materialin low pH experiments may have occurred.

3. RESULTS AND DISCUSSION

3.1. Soil properties

The four soils examined in this study differed in theirpH, organic carbon, clay content, and mineralogical com-position of the clay fraction (Table 1). The measuredECEC was much higher in soil 3 than in soil 1 or 2(Table 1). The clay fraction (62 lm) of soil 1 was domi-nated by kaolinite and to a lesser extent by illite, andcontained a small proportion of well-crystallized goethiteand hematite. The clay fraction of soil 2 consisted pre-dominantly of illite with less kaolinite than soil 1. Soil2 had the lowest clay content (45 g kg�1) and the smallestproportion of phyllosilicates in the clay fraction. The clayfraction of soil 3 was dominated by well-crystallizedsmectite and illite. Soil 3 exhibited both the largest claycontent (230 g kg�1) and highest proportion of phyllosili-cates in the 62-lm soil fraction, which accounts for thehigh permanent surface charge (as measured by theECEC). The presence of smectite as the dominant clayprovides a high capacity for metal sorption (Gomeset al., 2001; Appel and Ma, 2002; Veeresh et al., 2003)through both ion exchange on interlayer sites and adsorp-tion on hydroxyl edge sites (Sposito, 1984). The lowercontent of illite and smectite in soil T compared to soil3 accounts for its lower ECEC.

Chemical extraction results showed that the highest Feconcentrations were present in soil T and soil 1, followedby soil 2 and soil 3 (Table 1). The highest extractable Alconcentrations were found in soil 1, followed by soil 2, soil3 and soil T. On the other hand, organic carbon contentwas low in all of the soils studied, varying from 3 to61 g kg�1 (Table 1). The lowest value corresponded to soil2 and the highest one to soil 3 which, along with its largeclay content, explains the high ion exchange capacity of thissoil.

3.2. Model formulation

3.2.1. Choice of surface sites and reactions

Soil materials have been defined as assemblages of phyl-losilicate minerals and iron and aluminium oxides based on



the mineralogical and chemical characterizations above.The model considers two different hydroxyl functionalgroups: >FeOH, associated with Fe-oxyhydroxide mineralphases (indicated by the fraction of extractable Fe), and>SOH, which represents both clay mineral edges andAl-oxyhydroxide (indicated by the fraction of extractableAl) functional groups (see below). Consequently, no dis-tinction was made between aluminol and silanol clay edgesurface groups, and all >SOH groups involved in adsorp-tion were assumed to be aluminol (Schindler et al., 1987).The model also includes ion exchange sites associated withthe siloxane surface of layered silicates (Sposito, 1984). Twodifferent exchange sites, represented by X� and Y�, wereincluded in the model to account for the ion exchangecapacity measured in the soils attributed to the phyllosili-cate minerals, smectite, weathered illite, and kaolinite,and organic matter. Because of the low total organic carboncontent of the soils, ion exchange associated with organiccarbon was not considered as a distinct site, although itmay be important in soil 3.

The stoichiometry of surface complexation reactions forPb and Cd on mineral surface sites was constrained by spec-troscopic evidence from previous sorption studies on puremineral phases discussed above. Surface complexes formonodentate (>FeOPb+) and bidentate (>(FeOH)2P-bOH+) Pb, and for monodentate (>FeOCd+) and bidentate(>(FeOH)2CdOH+) Cd were included in the initial set ofreactions to describe metal retention on Fe oxide mineralphases. A similar coordination was considered for Pb andCd complexes on the hydroxyl sites on phyllosilicates,and both (>SOPb+) and (>(SOH)2PbOH+) and (>SOCd+)and (>(SOH)2CdOH+) surface complexes were initially

included in the model. However, as discussed below, theoptimization process indicated that not all of the reactionsinitially considered in the model were necessary for describ-ing the experimental Pb and Cd sorption data and thuswere eliminated from the final set of model sorptionreactions.

The final set of surface complexation and cation ex-change reactions shown in Table 2 were used in a NEMto describe the sorption of Pb and Cd. The selection of thismodel, and thus the exclusion of the electrostatic term fromthe mass law equation, are justified by the observation that,for moderately and strongly adsorbing ions, the chemicalcontribution to the free energy of adsorption dominatesover the electrostatic contribution (Davis and Kent,1990). In addition, given the complexity of natural soilmaterials with respect to the number, type, and abundanceof surface sites, a surface complexation model with a mini-mum number of adjustable parameters that can account forthe sorption variability of soils is desirable for modelingpurposes. In view of the difficulties involved in the determi-nation of double-layer model parameters for natural soilparticles, the NEM provides a simpler alternative. Despitethese advantages, few examples applying this approach tonatural system are found in the literature (Van Benschotenet al., 1998; Voegelin et al., 2001; Pagnanelli et al., 2006).However, we recognize that this model formulation com-bines sites with similar sorption affinity that may be associ-ated with different solid phases (see below).

3.2.2. Site concentration estimation

Concentrations for specific types of surface sites wereestimated from the mineral and chemical composition of

Table 2Surface complexation reactions and conditional equilibrium constants for sorption of Pb and Cd.

Mineralogical fraction Site type Surface reactions Log Kcond (final)a SDb

Hydroxyl

Fe >FeOH >FeOH + H+ = >FeOHþ2 4.70c

oxyhydroxide >FeOH = >FeO� + H+ �10.30c

>2(FeOH) + Pb2+ + H2O = >(FeOH)2PbOH+ + H+ 1.33 (±0.30) 0.13

>2(FeOH) + Cd2+ = >(FeO)2Cd� + 2H+ �6.26 (±0.32) 0.21Phyllosilicate >SOH >SOH + H+ = >SOHþ2 3.50d

>SOH = >SO� + H+ �7.20d

>2(SOH) + Pb2+ + H2O = >(SOH)2PbOH+ + H+ �2.21 (±0.83) 0.73>2(SOH) + Cd2+ = >(SO)2Cd� + 2 H+ �9.71 (±2.02) 0.50

Exchange site

X� Pb2+ + 2XH = PbX2 + 2H+ 0.48 (±0.12) 0.24Cd2+ + 2XH = CdX2 + 2H+ 0.23 (±0.09) 0.26Ca2+ + 2XH = CaX2 + 2H+ �0.005 (±0.06) 0.28

Y� Pb2+ + 2YH = PbY2 + 2H+ �0.97 (±0.23) 0.12Cd2+ + 2YH = CdY2 + 2H+ �0.89 (±0.24) 0.12Ca2+ + 2YH = CaY2 + 2H+ �1.32 (±0.31) 0.15

a Conditional Log K after model optimization. Number in parentheses is the 95% confidence interval. Constants for surface protonationfixed on values from the literature.

b Standard deviation (SD) determined from global fit to all experimental data points.c Cowen et al. (1991).d Schroth and Sposito (1998).



the soils and the conditions of the sorption experimentsusing the equation:

N t ¼ SAN sCs1018=N a ð1Þ

where Nt is the surface site concentration (mol g�1 soil), SA

is the specific surface area (m2 g�1), Ns is the surface sitedensity (sites nm�2), Cs is the concentration of mineral frac-tion associated with Nt (g g�1 soil), and Na is Avogadro’snumber (Davis and Kent, 1990) (Table 3). For Al and Feoxides, the concentration of Al and Fe determined throughchemical extraction (McKeague and Day, 1966) in the soils(g g�1 soil) was used for Cs. Consequently, 1 mol of ex-tracted Fe or Al was assumed to correspond to 1 mol ofFe(OH)3 or Al(OH)3 oxide phases, respectively. The surfacesite density values (Ns) and the specific surface areas (SA)for Al and Fe oxide phases were taken from the literature,assuming aluminium oxide and hydrous ferric oxide(HFO), respectively (Table 3). This approach assumes thatextractable Fe and Al provide a reasonable estimate of the

amount of high surface area Fe- and Al-oxides that partic-ipate in metal sorption in the soil.

The functional group represented by >SOH in the modelis the sum of >SOH sites on clay mineral edges and >AlOHsites on Al-oxides estimated above from chemical extrac-tion (see Section 3.2.3 below). Mineral phases (Cs) that cor-respond to >SOH sites were estimated from the total claycontent and the proportion of different clays determinedby X-ray diffraction and mineral intensity factors. The per-cent of each different type of clay in the fraction 6 2 lm ofthe soils was normalized and multiplied by the total clayfraction in each soil. The surface site density for >SOH sitesand specific surface area for phyllosilicates were taken fromthe literature (Table 3).

The surface site concentrations for X� and Y� weredetermined using the measured ECEC and the proportionof each clay mineral determined by X-ray diffraction. Sim-ilar to the estimate for >SOH sites, X� and Y� site concen-trations were calculated by multiplying the percent of each

Table 3Total site concentrations estimated for the experimental soils.

Soil Surface sitea Csb (g g�1 soil)

(10�3)SA

c (m2

g�1)NS

d (sitesnm�2)

Nte (mol g�1)

(10�6)Surface site used inmodelf

Nt model (mol g�1 soil)(10�6)

1 >FeOH 3.11 600 10 31.0 >FeOH 31.0>AlOH 10.64 100 10 17.7>SOHkaolinite 45 4.76 12.2 4.3 >SOH 26.6>SOHillite 30 66.8 1.37 4.6X� 17.9 X� 17.9

2 >FeOH 2.35 600 10 23.4 23.4>AlOH 5.86 100 10 9.7>SOHkaolinite 13 4.76 12.2 1.3 >SOH 15.8>SOHillite 31 66.8 1.37 4.8X� 10.9 X� 10.9

3 >FeOH 1.65 600 10 16.4 >FeOH 16.4>AlOH 4.30 100 10 7.1>SOHkaolinite 69 4.76 12.2 6.6 >SOH 18.5>SOHillite 69 66.8 1.37 1.0>SOHsmectite 92 762.69 0.03 3.6X� 34.8 X� 34.8Y� 170.0 Y� 170.0

T >FeOH 3.83 600 10 38.2 >FeOH 38.2>AlOH 4.88 100 10 6.7>SOHkaolinite 31 4.76 12.2 3.0 >SOH 19.9>SOHillite 47 66.8 1.37 7.1>SOHsmectite 77 762.69 0.03 3.0X� 8.9 X� 8.9Y� 21.2 Y� 21.2

a X� and Y� ion exchange site concentration determined from measured ion exchange capacity; proportion of each site determined by X-raydiffraction. Kaolinite and illite fractions were combined into single exchange site (X�); smectite fraction represented by Y� site. >AlOH and>FeOH estimated from extractable total Al and Fe; >SOH proportions estimated from total clay content and X-ray diffraction (from Table1).

b Concentration of mineral fraction associated with surface site.c Specific surface area taken from the literature: >FeOH: Davis and Leckie (1979) assumes hydrous ferric oxide (HFO); >AlOH: Nowack

et al. (1996) assumes aluminium oxide (Al2O3); >SOHkaolinite: Heidmann et al. (2005); >SOHillite: Gu and Evans (2007); >SOHsmectite: Choi(2006).

d Surface site density taken from the literature: >FeOH and >AlOH: Hayes et al. (1990); >SOHkaolinite: Heidmann et al. (2005); >SOHillite:Gu and Evans (2007); >SOHsmectite: Choi (2006), surface sites restricted to clay edge aluminol sites only.

e Total site concentration using: Nt = SA NS CS 1018/Na where Na is Avogadro’s number.f >SOH = >AlOH + >SOHkaolinite + >SOHillite + >SOHsmectite.



clay by the total ECEC. Because total measured organiccarbon content was generally low and variable, it was notconsidered in the apportionment of X� and Y� site concen-tration, although organic matter contributes to measuredECEC and thus is included implicitly in the site concentra-tion estimate. Since illite behaves more like kaolinite thanmontmorillonite with regard to its capacity to adsorb waterand its smaller cation exchange capacity (Gu and Evans,2007), weathered kaolinite and illite fractions were com-bined into a single exchange site (X�) and the smectite frac-tion was represented by Y� (Table 3). Ion exchange inkaolinite is attributed to the small permanent negativecharge arising from the low isomorphic substitution(Sposito, 1984; Coles and Yong, 2002). In illite, K+ in theinterlayer exhibits exchangeable behavior with increasedmineral weathering (Gu and Evans, 2007). Therefore, insoil 1 and soil 2, where kaolinite and illite are the main clayminerals present in the soil, X� site concentration was set tothe ECEC value determined for these soils. In contrast, insoil 3, where kaolinite, illite and smectite are present inthe clay fraction, the concentration of X� and Y� siteswas calculated by partitioning the ECEC value betweenX� (kaolinite + illite) and Y� (smectite) using fractionsestimated from XRD.

It should be kept in mind that estimation of site concen-tration for different surface functional groups was carriedout based on characteristics of soil mineralogy, with associ-ated errors and assumptions. It is well known that selectiveextraction treatments are not completely selective (Gruebelet al., 1988). Weaknesses of sequential chemical extractionsinclude their operationally defined nature, the potential for

alteration of the sediment during extraction, and the lack ofwell-tested extractions for specific elements (Keon et al.,2001). Quantification of the minerals in the clay fractionusing mineral intensity factors depends on the phase chem-istry, degree of structural disorder, and interstratificationsof the soil clay mineral (Kahle et al., 2002). Estimation ofsurface site concentrations also assumes that all sites of aparticular type have the same reaction affinity towards thebonding of a surface complex, which is probably not strictlytrue for the same site type present in different minerals. Be-cause of these uncertainties, the sensitivity of the model tothe estimated surface site concentrations was tested. Valueswere increased and decreased by half an order of magnitudefrom the original estimate. Model results showed no signif-icant differences (within the 95% confidence interval) for thedescription of Pb and Cd uptake using the entire set ofsorption data.

3.2.3. Model optimization

Fig. 1 shows the complete set of metal sorption data thatwas used to constrain the NEM described above. The opti-mized binding constants for Pb and Cd surface complexa-tion and ion exchange reactions, and final set of surfacesites used in the model, are shown in Table 2. The finalset of reactions (Table 2) were the result of iterative fitting,starting with a larger set of surface complexation reactionsand surface sites, and progressively eliminating reactionsfor which optimized binding constants were either poorlyconstrained (large confidence limits) or which contributedinsignificantly to the overall variance. Comparison of differ-ent optimized models showed that >AlOH and >SOH sites

0.00 0.01 0.02 0.03 0.04 0.05

0.00

0.01

0.02

0.03

0.04

0.05

Cd (+ Pb)Pb (+ Cd)

Cd

Met

al s

orb

ed, m

od

el (

mm

ol g

-1)

Metal sorbed, experimental (mmol g -1) Metal sorbed, experimental (mmol g -1)

Soil 1 Soil 2 Soil 3

Pb

Met

al s

orb

ed, m

od

el (

mm

ol g

-1)

0.00 0.01 0.02 0.03 0.04

0.00

0.01

0.02

0.03

0.04

0.00 0.01 0.02

0.00

0.01

0.02

0.00 0.01 0.02

0.00

0.01

0.02

Fig. 1. Correlation of experimental Pb and Cd adsorption data and optimized model fit as a function of pH and initial metal concentrationfor both single and binary solutions in soils 1–3.



could be represented as a single component site (>SOH)with no significant loss of goodness-of-fit. This is probablybecause of the similarity in metal binding between >AlOHsites associated with Al-oxide phases and >AlOH sites onphyllosilicate edges (Zavarin and Bruton, 2004; Grafeet al., 2007). Thus, reactions associated with Al hydroxidesurface sites were removed from the final model and theconcentration of sites estimated for this mineral phasewas added to the total site concentration for >SOH (Table3). In addition, results from different model optimizationssuggested that Pb retention on both >FeOH and >SOHsites could be accounted for using only the bidentate com-plexes >(FeOH)2PbOH+ and >(SOH)2PbOH+, respec-tively, rather than both bidentate and monodentatereactions. Likewise, the overall Cd adsorption was well de-scribed through the formation of the bidentate surface com-plexes >(FeO)2Cd� and >(SO)2Cd� and monodentatecomplexes could be excluded without significant changeof the model fit (within 95% confidence interval). In the

same way, different models were tested using one, two, orthree cation exchange sites. Fit results showed that morethan two ion exchange sites were equally good at describingPb and Cd retention on the three soils. Thus, the final opti-mized model represents a minimum set of statistically sig-nificant reactions needed to describe the variation in thesorption data.

3.3. Metal ion sorption: single-metal systems

3.3.1. Lead

Lead uptake for all three soils, and model results as afunction of pH and concentration, are shown in Fig. 2.Common to the three soils, the fraction of sorbed Pb in-creased with pH following a sigmoid-type behavior(Fig. 2). In soil 3, Pb uptake reached its maximum sorptionat lower pH values than in the other two soils. This behav-ior agrees with a previous study (Serrano et al., 2005) indi-cating that the higher Pb sorption capacity of soil 3 is due

0.000

0.002

0.004

0.006

0.008Soil 1

Pb

so

rbed

(m

mo

l g-1)

Soil 2

Soil 1

0.000

0.005

0.010

0.015

0.020

0.025

Pb

0.000

0.002

0.004

0.006

0.008

Soil 2

Pb

so

rbed

(m

mo

l g-1)

0.000

0.005

0.010

0.015

0.020

0.025

2 3 4 5 6

0.000

0.003

0.005

0.007

0.010

0.97 mM Model

>(FeOH)2PbOH

+

>(SOH)2PbOH

+

PbX2

PbY2(just in Soil 3)

Soil 3

Pb

so

rbed

(m

mo

l g-1)

Soil 3

pH

2 3 4 5 6

0.00

0.01

0.02

0.03

0.04

0.05

0.35 mM 0.97 mM 1.95 mM 4.06 mM 6.07 mM

pH

a b

c d

e f

Fig. 2. Lead adsorption in single-metal systems (no Cd present). Experimental data (points) and model fit (lines) are shown in (a), (c) and (e)for soils 1–3, respectively. Model results for surface speciation of sorbed Pb at a total concentration of 0.97 mM are shown in (b), (d) and (f)for soils 1–3, respectively.



to its higher ECEC and clay content compared with soils 1and 2 (Table 1). The greatest deviation of the model fromthe experimental uptake data for all soils was observed athigh initial metal concentrations. However, the modelunderpredicts uptake in some cases and overpredicts in oth-ers (Fig. 2). Introducing additional surface complexation orexchange reactions in the model did not improve the fitresults.

Model results for Pb surface speciation (Fig. 2 b,d, andf) showed that sorbed Pb was distributed mainly on ion ex-change sites at low pH and >FeOH sites at higher pH. Onall three soils at pH 2 and 3, more than 99% of the sorbedPb was retained on ion exchange sites at all concentrations.As the pH increased, sorption on exchange sites decreased,reaching almost 0% at the lowest metal concentration forsoil 2 and 38% and 84% for soil 1 and soil 3, respectively,at the highest metal concentration at pH 6. The decreasein uptake on ion exchange sites as pH increased was re-placed by sorption on >FeOH. For example in soil 1 atthe lowest metal concentration, Pb retention on >FeOHsites increased from zero at pH 3 to �99% at pH 6. Leadsorption on >SOH sites was very low over the entire pHrange studied. The highest fraction of Pb sorbed on thesesites was 10% for soil 2 at the highest concentration atpH 6. These results corroborate previous studies showingthe high affinity of Pb for iron oxides and the differencein reactivity of Pb between >FeOH and >SOH surfacefunctional groups (McKenzie, 1980; Swallow et al., 1980;Christl and Kretzschmar, 1999; Scheinost et al., 2001).

In addition to changes in surface site reactivity as a func-tion of the pH, the NEM was able to capture differences insorption behavior due to the mineralogical composition ofthe soils. The modeling results showed less Pb sorbed on theion exchange sites in soil 2 with lowest CEC, and the mostPb sorbed on exchange sites in soil 3, with the highest CEC.Sorbed Pb concentrations were higher on Y� sites than onX� sites, consistent with the higher fraction of smectite thanillite in the clay fraction of soil 3. In contrast, Pb sorbed on>FeOH sites was highest in soil 1, with highest amount ofextractable Fe, compared to soils 2 and 3.

3.3.2. Cadmium

Sorption of Cd as a function of pH is shown for thethree soils in Fig. 3. As we saw for Pb, sorption of Cd onsoil 3 was higher than on soil 1 and soil 2, which reflectsthe higher cation exchange capacity of soil 3 (Serranoet al., 2005). Also, similar to the case of Pb, the model pro-vided a better fit to the sorption data at low metal concen-trations than at higher concentrations. However, Cdadsorption was generally overestimated at low pH (2–3)in all soils. The difference between model and experimentcan be attributed to Cd–Ca competitive sorption on perma-nent charge sites associated with 2:1 clay minerals (Cowenet al., 1991), to competition from aqueous Al from the dis-solution of Al-oxide phases, or to possible changes in thebinding constant from protonation of mineral surfaces(Kraepiel et al., 1998) at low pH.

The model speciation results showed that sorbed Cd wasdistributed between permanent charge sites at low pH andsurface hydroxyl sites at higher pH (Fig. 3 b, d and f).

The model showed important differences in Cd versus Pbsorption. For metal retention on ion exchange sites, a high-er fraction of Cd than Pb was retained on these sites overthe entire pH range. For example, most Pb sorption oc-curred on exchange sites over the pH range 2–3, but abovepH 3, Pb sorbed dominantly on >FeOH sites. For Cd, morethan 94% sorbed on ion exchange sites over the pH range2–4.5 for all three soils and all metal concentrations. Com-mon to the three soils and similar to Pb, Cd adsorption onexchange sites decreased with increasing pH for all initialmetal concentrations, and Cd uptake on hydroxyl sites in-creased at pH >4.5, particularly on soils 1 and 2, throughthe formation of the bidentate complex >(FeO)2Cd�. Thesurface speciation model showed very low Cd uptake on>SOH sites, with this site becoming important only at pH6 and high metal concentration.

The fraction of Cd retained on hydroxyl surface siteswas always lower than for Pb, particularly for >FeOH sites.Differences in the pH of sorption on hydroxyl sites betweenPb and Cd suggests that Pb adsorption involves significanthydrolysis and/or interaction with surface hydroxyls(>(FeOH)2PbOH+, >(SOH)2PbOH+) at pH values atwhich Cd interacts only with exchange sites (Srivastavaet al., 2005). This selectivity agrees with Forbes et al.(1976) who concluded that adsorption on goethite de-creased in the order Cu > Pb > Zn > Co > Cd. Also, Appeland Ma (2002) showed that Pb sorbed to tropical soils atlower pH than Cd. Studies of Pb and Cd competitiveadsorption in monomineralic systems showed that Pb hada higher affinity for the surface of amorphous iron oxyhy-droxide than Cd, and suggested the selectivity sequencePb > Cu > Zn > Cd for this phase (Benjamin and Leckie,1981b).

3.4. Bi-metal systems and competitive adsorption

Model results for Pb and Cd in binary systems and thesurface speciation for each soil are shown in Figs. 4 and5, respectively. For Pb, the model matched experimentaldata well over the range of concentration and pH studiedfor all three soils. However, it underestimated Cd sorptionon soils 1 and 2 at high metal concentrations (Fig. 5). Theseresults are discussed below in terms of competitive sorption.

The effect of competition in binary systems is that thesorption of one metal in the presence of another is reducedrelative to sorption in a single-metal system (Bradbury andBaeyens, 2005). In order to examine competitive sorptionbetween Pb and Cd on reactive sites defined in the model,site occupancy of Pb and Cd was compared between singleand binary systems at the same metal concentration(Fig. 6). Model results suggest that most competition oc-curred on the >FeOH sites. Cadmium occupancy in thesesites decreased significantly in the binary system comparedto Cd-only at the same concentration (Fig. 6d). However,because of its higher affinity for >FeOH sites and abilityto hydrolyze discussed above, Pb adsorption is not affectedby the presence of Cd (Fig. 6c). The percent of >FeOH sitesoccupied by Cd decreased considerably in all soils for thefive metal concentrations studied when Pb was present insolution. For instance, in soil 1 at pH 5, Cd site occupancy



decreased from 20% to 0%, from single to binary systems,respectively, at the highest metal concentration. At the low-est metal concentration, 3% of the >FeOH sites were occu-pied by Cd in the Cd-only case, but decreased to 0.8% withCd + Pb in solution. Since the only difference between Cd-only and Cd + Pb experiments was the presence of Pb,these results suggest competition for FeOH sites. Sorptioncompetition implies that the same sorption sites are in-volved in the uptake of metals of similar characteristics,and non-competitive sorption implies that different sitesare involved (Bradbury and Baeyens, 2005), either for a gi-ven solid phase or within a complex soil matrix. Based onour modeling results, Pb and Cd appear to access the sameset of >FeOH sites, such that Cd is displaced to lower affin-ity sites (see below), although the sensitivity to sorptioncompetition depends to some extent on the choice of sur-face sites in the model. Similar behavior has been described

for other strongly absorbing metals. For instance, Atanass-ova (1995) reported results showing that, in multi-compo-nent systems, an increase in Cu concentration reduced theuptake of Ni, Cd, and Zn.

Minor differences between single and binary systemswere found for Pb and Cd occupancy on >SOH sites andthus, competition appears to be limited for this type of site,although site occupancy was uniformly low in both singleand binary systems (<6%). The inherent surface heteroge-neity associated with edges of phyllosilicate minerals in nat-ural composite materials induces different affinities for agiven type of surface-reactive site in the soil solution(Balistrieri and Chao, 1990). Surface site heterogeneitymay come from natural structural irregularities within aclay mineral, or as a result of mixtures of phyllosilicate min-erals present in the soil matrix. Heterogeneity of the func-tional groups of the phyllosilicate edges could explain the

0.000

0.002

0.004

0.006

0.008Soil 1

Cd

Cd s

orbe

d (m

mol

g-1)

Soil 1

0.000

0.004

0.008

0.012

0.016

0.020

0.000

0.002

0.004

0.006

0.008Soil 2

Cd s

orbe

d (m

mol

g-1)

Soil 2

0.000

0.005

0.010

0.015

0.020

2 3 4 5 6

0.000

0.002

0.004

0.006

0.008 Soil 3

1.07 mM Model (FeO)2Cd (SO)2Cd CdX2 CdY2(just in Soil 3)

Cd s

orbe

d (m

mol

g-1)

Soil 3

2 3 4 5 60.00

0.01

0.02

0.03

0.46 mM 1.07 mM 2.28 mM 2.65 mM 5.56 mM

pHpH

a b

dc

e f

Fig. 3. Cadmium adsorption in single-metal systems (no Pb present). Experimental data (points) and model fit (lines) are shown in (a), (c) and(e) for soils 1–3, respectively. Model results for surface speciation of sorbed Cd at a total concentration of 1.07 mM are shown in (b), (d) and(f) for soils 1–3, respectively.



lack of evidence for sorption competition between Pb andCd on >SOH sites, but site occupancy was generally toolow to assess its importance for this site type.

On ion exchange sites, Pb and Cd retention decreasedslightly in binary systems compared to single systems atlow pH. Lead adsorption on ion exchange sites at highpH did not change in the presence or absence of Cd inthe solution (Fig. 6c). However, Cd retention on exchangesites increased in binary systems compared to single-metalsystems over the pH range 4.5–6 (Fig. 6d). Cadmium dis-placed from >FeOH sites noted above was distributed onion exchange sites, which reflects the tendency of Cd to sorbto permanent charge sites (Srivastava et al., 2005). In addi-tion, uptake data suggests the influence of the backgroundelectrolyte (CaCl2) on the Pb and Cd adsorption. Solutionanalyses showed a slightly higher Ca concentration in solu-tion after metal equilibration at low pH in Cd-only systemsthan in the Pb-only experiments (data not shown). Thisobservation suggests that the competition of Cd with Cafor ion exchange sites at low pH values was greater than

the competition of Pb with Ca, which is consistent withthe differences in chemical properties between Pb and Cddiscussed above. Based on results from the Cd single-metalsystem and the lower Ca sorption in binary-metal systems,adsorption competition between Cd and Ca, and possiblyfrom dissolved Al at low pH, may be a factor in the Pband Cd binary systems that the model was not able to cap-ture completely. Therefore, the better model fits for soil 3than soils 1 and 2 can be explained in terms of a lowerCa–Cd adsorption competition on soil 3 than in the othertwo soils, attributed to the higher concentration of ion ex-change sites in soil 3.

3.5. Test of the model with an unknown soil

Lead and cadmium sorption data for a fourth soil, notincluded in model development and calibration, was usedto test the transferability of the optimized reactions andconditional equilibrium constants (log Kcond) derived fromthe sorption data for soils 1, 2, and 3. This soil (T), whose

0.000

0.005

0.010

0.015

Pb

so

rbed

(m

mo

l g-1)

Soil 1

0.000

0.002

0.004

0.006

0.008Soil 1

Pb (+ Cd)

0.000

0.005

0.010

0.015

Soil 2

Pb

so

rbed

(m

mo

l g-1)

0.000

0.002

0.004

0.006

0.008Soil 2

2 3 4 5 6

0.000

0.005

0.010

0.015

0.020

0.025

(0.24 mM (+ 0.18mM Cd) 0.91 mM (+ 0.11mM Cd) 1.73 mM (+ 1.46mM Cd) 2.33 mM (+ 2.01mM Cd) 3.75 mM (+ 2.28mM Cd)

Pb

so

rbed

(m

mo

l g-1)

Soil 3

pH

2 3 4 5 6

0.000

0.002

0.004

0.006

0.008Soil 3

0.91 mM Model

>(FeOH)2PbOH

+

>(SOH)2PbOH

+

PbX2

PbY2(just in Soil 3)

pH

a b

c d

e f

Fig. 4. Lead adsorption in binary-metal systems (Cd present). Experimental data (points) and model fit (lines) are shown in (a), (c) and (e) forsoils 1–3, respectively. Model results for surface speciation of sorbed Pb at a total concentration of 0.91 mM are shown in (b), (d) and (f) forsoils 1–3, respectively.



chemical and mineralogical characteristics are shown inTable 1, was used in equilibrium and kinetic experimentsof Pb and Cd sorption in single and binary systems at thenatural pH of the soils (3.5–4.5) (Serrano et al., 2005).Sorption experiments were conducted in a concentrationrange similar to the ones used for soils 1–3. The NEMwas tested using the same set of surface complexation andion exchange reactions reactions with previously optimizedlog Kcond. Concentrations of >FeOH and >SOH surfacesites, and ion exchange sites (X� and Y�), were estimatedon the basis of the mineral composition of the soil usingthe same procedure described above (Table 3).

Experimental and modeled Pb and Cd sorption iso-therms for both single and binary solutions are shown inFig. 7. There was generally very good agreement betweenmodeled and observed Pb and Cd sorption over the rangeof metal concentrations studied. Only for Cd systems didthe model slightly underestimate the experimental data.

The site distribution in soil T was similar to that of soil 3,which had somewhat similar chemical, physical, and miner-alogical properties, with the exception of a higher ECEC insoil 3 (Table 1). Over the pH range (3.5–4.5) at which sorp-tion experiments were done, sorption of Pb on soil T wasdistributed between ion exchange sites and specific adsorp-tion on >FeOH sites in both single and binary systems. AtpH 3.5, most of the Pb was retained on ion exchange sitesbut as pH increased to 4.5, sorption on exchange sites de-creased and Pb retention on >FeOH increased. Cadmiumsorption occurred mostly on ion exchange sites over thispH range as noted for the other soils. As discussed above,competition between Cd and Ca on ion exchange sites atthe pH of these experiments may account for the slightlypoorer model performance for Cd in binary systems. Inaddition, chemical extraction of the poorly crystalline andamorphous fraction of the soils indicated a higher extractedMn concentration in this soil (765 mg kg�1) than in the

0.000

0.002

0.004

0.006

Cd (+ Pb)

Cd

sorb

ed (m

mol

g-1)

Soil S1

0.000

0.002

0.004

0.006

0.008 Soil S1

0.000

0.002

0.004

0.006

Cd

sorb

ed (m

mol

g-1)

Soil S3

Soil S2

0.000

0.002

0.004

0.006

0.008 Soil S2

0.005

0.010

0.015

0.18 mM (+0.24mM Pb) AAA1.11 mM (+0.91mM Pb) 1.46 mM (+1.73mM Pb) 2.01 mM (+2.33mM Pb) 2.88 mM (+3.75mM Pb)

pH

Cd

sorb

ed (m

mol

g-1)

2 3 4 5 6 2 3 5 6

0.000

0.002

0.004

0.006

0.008 Soil S3

1.11 mM Model >(FeO)2Cd >(SO)2Cd CdX2 CdY2(Just in Soil 3)

pH

a b

dc

e f

4

Fig. 5. Cadmium adsorption in binary-metal systems (Pb present). Experimental data (points) and model fit (lines) are shown in (a), (c) and(e) for soils 1–3, respectively. Model results for surface speciation of sorbed Cd at a total concentration of 1.11 mM are shown in (b), (d) and(f) for soils 1–3, respectively.



other soils (12, 276, and 10 mg kg�1 for soil 1–3, respec-tively). Manganese oxides have a high affinity for metaladsorption (Anderson and Christensen, 1988; Xu et al.,2006), but this mineral phase was not included in the modelbecause of its low abundance in soils 1–3. The presence ofMn-oxides may account for some of the differences betweenthe experimental data and model prediction for soil T.

Although the metal sorption data for the test soil waslimited to a relatively narrow pH range, the good agree-ment between experimental data and model suggests thata mineralogy-based NEM with few adjustable parametersmay be useful in describing metal uptake in a variety of soiltypes. It is encouraging that sorption data for soil T exper-iments could be modeled simply by adjusting concentra-tions of surface sites using constraints from the soilmineralogy, but without any adjustment of model sorptionconstants or inclusion of additional reactions. However, wenote that additional sorption reactions may be warrantedfor model application to soils with distinctly different min-eralogy or a high concentration of surface-reactive organicmatter.

4. CONCLUSIONS

A non-electrostatic surface equilibrium model con-strained by the mineralogical properties of natural soilswas formulated to describe Pb and Cd adsorption and com-petition on soils. A minimum set of surface complexationand ion exchange reactions were generated to describe Pband Cd retention on Fe- and Al-oxyhydroxide phases andphyllosilicate clay minerals, representing the most reactivemineral phases in the soils considered in this study. Thestoichiometry of surface reactions was in general agreementwith surface complexes inferred from published XAS stud-

ies for Pb and Cd sorbed on Fe-oxyhydroxide and phyllo-silicates (Spadini et al., 1994; Bargar et al., 1997; Randallet al., 1999; Strawn and Sparks, 1999; Dyer et al., 2003;Trivedi et al., 2003).

The resulting NEM showed that Pb and Cd sorptionwas dominated by exchange reactions on permanent chargesites at low pH, with a greater tendency of Cd than Pb tosorb on ion exchange sites (Srivastava et al., 2005) and topossibly compete with Ca (the background electrolyte) forexchange sites (Cowen et al., 1991). As pH increased, up-take of both Pb and Cd on >FeOH sites, and to a lesser ex-tent on >SOH sites, became more important, with Pbhaving a greater affinity than Cd for >FeOH sites (Benja-min and Leckie, 1981b). Modeling of Pb and Cd sorptionin binary systems showed a significant decrease in >FeOHsites occupied by Cd compared to Cd-only systems at thesame concentration. Model results suggest competitionfor >FeOH sites (Srivastava et al., 2005) and displacementof Cd from hydroxyl sites to ion exchange sites in the pres-ence of Pb. The model was successfully used to describe Pband Cd sorption on a fourth soil not used in the modelparameterization.

The modeling results from this study suggest that multi-ple metal sorption processes and site competition in com-plex soils may be adequately described by relativelysimple, non-adjustable surface complexation and ion ex-change models. Given the complexity of natural materials,the NEM has advantages over distribution coefficient (Kd)models by its ability to account for effects of pH, metal con-centration, and differences among soils through the choiceof surface sites that reflect soil chemistry, mineralogy, andphysical properties. The effects of ionic strength, however,were not investigated in this study. Large variation insolution ionic strength may require additional model

model Cd Cd 0.97mM exp. Cd 1.1mM model Cd Cd 0.97mM (+Pb 0.97mM) exp. Cd 1.1mM (+Pb 0.97mM)

total sorption

Met

al s

orb

ed (

mm

ol g

-1)

Met

al s

orb

ed (

mm

ol g

-1)

Cd sorption

0.002

0.004

0.006

0.008

total sorption

model Pb 0.97 mM exp. Pb 0.9mM model Pb 0.9mM (+Cd 1.1mM) exp. Pb 0.97 mM (+Cd 1.1mM)

>FeOH

Pb sorption

2 3 4 5 6

0.000

0.002

0.004

0.006

0.008

pH

X-

2 3 4 5 6

pH

X-

>FeOHX-

>FeOH

a b

c d

Fig. 6. Competitive adsorption between Pb (1 mM) and Cd (1 mM) on soil 1. Experimental data (points) and model fit (lines) are shown forbinary (Pb 1 mM + Cd 1 mM) and single (Pb 1 mM or Cd 1 mM) systems. (a) and (b): total metal adsorption, (c) and (d): metal adsorption on>FeOH and ion exchange sites (X�).



adjustments. It is important to note that no sorption modelis entirely unique and each depends on the choice of surfacereaction stoichiometry, site type and abundance, and chem-ical and electrostatic interactions between sorbate and sor-bent. A feature of our model that permits transferability isthe use of mineralogical and exchange properties of naturalsoils to constrain surface reactions and to estimate densitiesfor sorption sites, rather than treating them as adjustableparameters. Sources of error in the estimation of surfacesite densities include the uncertainty in using selectiveextractions as a proxy for reactive surface hydroxyl sites(Gruebel et al., 1988; Keon et al., 2001), and the quantifica-tion of minerals present in the clay fraction using mineralintensity factors from X-ray diffraction (Kahle et al.,2002). A challenge to improving and extending this model-ing approach is the need for better characterization of themost important mineral phases in soils responsible for me-tal sorption, and selection of appropriate surface reactionsfor soils of different chemical, physical and mineralogicalcomposition, including sorption reactions for clay andoxide minerals, and for organic matter.

ACKNOWLEDGEMENTS

The Spanish Ministry of Education and Science supported thiswork within the framework of the research project CTM2006-00884/TECNO. This study was partially supported by fundingfrom the US National Science Foundation (NSF-EAR 0409203to O’Day). We thank S.S. Papadopulos & Associates for additionalsupport.

REFERENCES

Anderson P. R. and Christensen T. H. (1988) Distributioncoefficients of Cd, Co, Ni, and Zn in soils. J. Soil Sci. 39, 15–22.

Appel C. and Ma L. (2002) Concentration, pH, and surface chargeeffects on Cadmium and Lead sorption in three tropical soils. J.

Environ. Qual. 31, 581–589.

Atanassova I. D. (1995) Adsorption and desorption of Cu at highequilibrium concentrations by soil and clay samples fromBulgaria. Environ. Pollut. 87, 17–21.

Balistrieri L. S. and Chao T. T. (1990) Adsorption of selenium byamorphous iron oxyhydroxide and manganese-dioxide. Geo-

chim. Cosmochim. Acta 54, 739–751.

Bargar J. R., Brown, Jr., G. E. and Parks G. A. (1997) Surfacecomplexation of Pb(II) at oxide–water interfaces: II. XAFS andbond-valence determination of mononuclear Pb(II) sorptionproducts and surface functional groups on iron oxides.Geochim. Cosmochim. Acta 61, 2639–2652.

Barnhisel R. and Bertsch P. M. (1982) Aluminium. In Methods of

Soil Analysis. Part 2. Chemical, Microbiological Properties (ed.A. L. Page). American Society of Agronomy, Madison, WI, pp.

275–300.

Benjamin M. M. and Leckie J. O. (1981a) Competitive adsorptionof Cd, Cu, Zn, and Pb on amorphous iron oxyhydroxide. J.

Colloid Interface Sci. 83, 410–419.

Benjamin M. M. and Leckie J. O. (1981b) Multiple-site adsorptionof Cd, Cu, Zn, and Pb on amorphous iron oxyhydroxide. J.


Bhattacharyya K. G. and Gupta S. S. (2007) Influence of acidactivation of kaolinite and montmorillonite on adsorptiveremoval of Cd (II) form water. Ind. Eng. Chem. Res. 46,

3734–3742.

Bradbury M. H. and Baeyens B. (2005) Experimental measure-ments and modeling of sorption competition on montmoril-lonite. Geochim. Cosmochim.Acta 69, 4187–4197.

Calvet R., Barriuso E. and Dubus I. G. (2007) Application of twosurface complexation models to the adsorption of weak organicacids by soil: an additive approach. Eur. J. Soil Sci. 58, 609–

624.

Choi J. (2006) Geochemical modeling of cadmium sorption tosoil as a function of soil properties. Chemosphere 63, 1824–

1834.

0 4 8 12 160.000

0.004

0.008

0.012

Pb exp.Pb model

Metal in solution (x 10-4mol l-1)

pH = 3.7 - 4.1

Metal in solution (x 10-5mol l-1)

Met

al s

orb

ed (

mm

ol g

-1)

0 5 10 15 20 25

0.002

0.004

0.006

0.008

pH = 4.0 - 4.2

Cd exp.Cd model

0 1 2 3 40.000

0.002

0.004

0.006

0.008

pH = 3.5 - 4.3

Pb(+Cd) exp.Pb(+Cd) model

Met

al s

orb

ed (

mm

ol g

-1)

0 2 4 6 80.000

0.001

0.002

0.003

0.004

pH = 3.5 - 4.3

Cd(+Pb) exp.Cd(+Pb) model

Fig. 7. Lead and Cd sorption isotherms from single (open symbols) and binary (closed symbols) systems in test soil (T). Solid lines are themodel fits. The pH shown is the measured natural soil pH of the experiment (no acid or base adjustment).



Christl I. and Kretzschmar R. (1999) Competitive sorption ofcopper and lead at the oxide–water interface. Implications forsurface site density. Geochim. Cosmochim. Acta 63, 2929–2938.

Coles C. A. and Yong R. N. (2002) Aspects of kaolinitecharacterization and retention of Pb and Cd. Appl. Clay Sci.

22, 39–45.

Cowen C. E., Zachara J. M. and Resch C. T. (1991) Cadmiumadsorption on iron oxides in the presence of alkaline-earthelements. Environ. Sci. Technol. 25, 437–446.

Davis J. A. and Kent D. B. (1990) Surface complexation modellingin aqueous geochemistry. In Mineral-Water Interface Geochem-

istry, Reviews in Mineralogy, vol. 23 (eds. M. F. Hochella andA. F. White). Mineralogical Society of America, pp. 177–260.

Davis J. A. and Leckie J. O. (1979) Speciation of adsorbed ions atthe oxide/water interface, Symposium Series 93. In Chemical

Modeling of Aqueous System (ed. E. A. Jenne). American

Chemical Society, p. 299.

Davis J. A., Coston J. A., Kent D. B. and Fuller C. C. (1998)Application of the surface complexation concept to complexmineral assemblages. Environ. Sci. Technol. 32, 2820–2828.

Doherty J. (2002) PEST: Model-independent Parameter Estimation,4th edn. Watermark Numerical Computing, Corinda, Australia.

Dyer J. A., Trivedi P., Scrivner N. C. and Sparks D. L. (2003) Leadsorption onto ferrihydrite. 2. Surface complexation modeling.Environ. Sci.Technol. 37, 915–922.

Dzombak D. A. and Morel F. M. M. (1990) Surface Complexation

Modeling: Hydrous Ferric Oxides. John Wiley & Sons, NewYork.

Forbes E. A., Posner A. M. and Quirk J. P. (1976) The specificadsorption of divalent Cd, Co, Cu, Pb, and Zn on goethite. J.

Soil Sci. 27, 154–166.

Gomes P. C., Fontes M. P. F., da Silva A. G., Mendoca E. S. andNetto A. R. (2001) Selectivity sequence and competitiveadsorption of heavy metals by Brazilian soils. Soil Sci. Soc.

Am. J. 65, 1115–1121.

Grafe M., Singh B. and Balasubramanian M. (2007) Surfacespeciation of Cd(II) and Pb(II) on kaolinite by XAFSspectroscopy. J. Colloid Interface Sci. 315, 21–32.

Gruebel K. A., Davis J. A. and Leckie J. O. (1988) The feasibilityof using sequential extraction techniques for arsenic andselenium in soils and sediments. Soil Sci. Soc. Am. J. 52, 390–

397.

Gu X. and Evans L. J. (2007) Modelling the adsorption of Cd(II),Cu(II), Ni(II), Pb(II) and Zn(II) onto Fithian illite. J. Colloid

Interface Sci. 307, 317–325.

Gunneriusson L., Lovgren L. and Sjoberg S. (1994) Complexationof Pb (II) at the goethite (a-FeOOH) water interface—theinfluence of chloride. Geochim. Cosmochim. Acta 58, 4973–

4983.

Harter R. D. (1992) Competitive sorption of cobalt, copper, andnickel ions by a calcium-saturated soil. Soil Sci. Soc. Am. J. 56,

444–449.

Hayes K. F. and Leckie J. O. (1987) Modeling ionic strength effectson cation adsorption at hydrous oxide/solution interfaces. J.


Hayes K. F., Redden G., Ela W. and Leckie J. O. (1990) Surfacecomplexation models: an evaluation of model parameterestimation using FITEQL and oxide mineral titration data. J.


Heidmann I., Christl I., Leu C. and Kretzschmar K. (2005)Competitive sorption of protons and metal cations ontokaolinite: experiments and modeling. J. Colloid Interface Sci.

282, 270–282.

Hiemstra T. and van Riemsdijk W. H. (1996) A surface structuralapproach to ion adsorption: the charge distribution (CD)model. J. Colloid Interface Sci. 179, 488–508.

Hiemstra T. and van Riemsdijk W. H. (1999) Surface structural ionadsorption modeling of competitve binding of oxyanions bymetal (hydr)oxides. J. Colloid Interface Sci. 210, 182–193.

Hizal J. and Apak R. (2006) Modeling of copper (II) and lead(II) adsorption on kaolinite-based clay minerals individuallyand in the presence of humic acid. J. Colloid Interface Sci.

295, 1–13.

Kahle M., Kleber M. and Jahn R. (2002) Review of XRD-basedquantitative analyses of clay minerals in soils: the suitability ofmineral intensity factors. Geoderma 19, 191–205.

Keon N. E., Swartz C. H., Brabander D. J., Harvey C. andHemond H. F. (2001) Validation of an arsenic sequentialextraction method for evaluating mobility in sediments. Envi-

ron. Sci. Technol. 35, 2778–2784.

Kraepiel A. M. L., Keller K. and Morel F. M. M. (1998) On theacid–base chemistry of permanently charged minerals. Environ.

Sci. Technol. 32, 2829–2838.

Kraepiel A. M. L., Keller K. and Morel F. M. M. (1999) A modelfor metal adsorption on montmorillonite. J. Colloid Interface

Sci. 210, 43–54.

Kretzschmar R. and Voegelin A. (2001) Modeling competitivesorption and release of heavy metals in soils. In Heavy Metal

Release in Soils (eds. H. M. Selim and D. L. Sparks). LewisPublishers, Boca Raton, FL, pp. 55–88.

Lackovic K., Angove M. J., Wells J. D. and Johnson B. B. (2004a)Modeling the adsorption of Cd(II) onto goethite in the presenceof citric acid. J. Colloid Interface Sci. 269, 37–45.

Lackovic K., Wells J. D., Johnson B. B. and Angove M. J. (2004b)Modeling the adsorption of Cd(II) onto kaolinite and Muloo-rina illite in the presence of citric acid. J. Colloid Interface Sci.

270, 86–93.

Lee S. Z., Allen H. E., Huang C. P., Sparks D. L., Sanders P. F.and Peijnenburg W. J. G. M. (1996) Predicting soil–waterpartition coefficients for cadmium. Environ. Sci.Technol. 30,

3418–3424.

McKeague J. A. and Day D. H. (1966) Dithionite- and oxalate-extractable Fe and Al as aids in differentiating various classes ofsoils. Can. J. Soil Sci. 46, 13.

McKenzie R. M. (1980) The adsorption of lead and other heavymetals on oxides of manganese and iron. Aust. J. Soil Res. 18,

61–73.

Nowack B., Lutzenkirchen J., Behra P. and Sigg L. (1996)Modeling the adsorption of metal–EDTA complexes ontooxides. Environ. Sci.Technol. 30, 2397–2405.

Pagnanelli F., Bornoroni L., Moscardini E. and Toro L. (2006)Non-electrostatic complexation models for proton and lead (II)sorption onto single minerals and their mixture. Chemosphere

63, 1063–1073.

Parkhurst D. L., Appelo C. A. J. (1999) User’s guide to PHREEQCVersion 2- A computer program for speciation, batch reaction,one-dimensional transport and inverse geochemical calcula-tions. In Water Resources Investigations, US Geological Survey,

Lakewood, Lakewood, CO, (Report 99–4259).Ponthieu M., Juillot F., Hiemstra T., Van Riemsdijk W. H. and

Benedetti M. M. (2006) Metal ion binding to iron oxides.Geochim. Cosmochim. Acta 70, 2679–2698.

Randall S. R., Sherman D. M., Ragnarsdottir K. V. and Collins C.R. (1999) The mechanism of cadmium surface complexation oniron oxyhydroxide minerals. Geochim. Cosmochim. Acta 63,

2971–2987.

Scheinost A. C., Abend S., Pandya K. I. and Sparks D. L. (2001)Kinetic controls on Cu and Pb sorption by ferrihydrite.Environ. Sci. Technol. 35, 1090–1096.

Schindler P. W., Liechti P. and Westall J. C. (1987) Adsorption ofcopper, cadmium and lead from aqueous-solution to thekaolinite water interface. Neth. J. Agric. Sci. 35, 219–230.



Schroth B. K. and Sposito G. (1998) Effect of landfill leachateorganic acids on trace metal adsorption by kaolinite. Environ.

Sci. Technol. 32, 1404–1408.

Schultz L. G. (1964) Quantitative interpretation of mineralogicalcomposition from X-ray and chemical data for the PierreShale. US Geological Survey Professional Paper 391-C, C1–

C31.

Serrano S., Garrido F., Campbell C. G. and Garcıa-Gonzalez M.T. (2005) Competitive sorption of cadmium and lead in acidsoils of Central Spain. Geoderma 124, 91–104.

Shuman L. M. (1990) Comparison of exchangeable Al, extractableAl, and Al in soil fractions. Can. J. Soil Sci. 70, 263–275.

Soil Survey Staff (1999) A basic system of soil classification formaking and interpreting soil surveys. In Agriculture Handbook

436, US Department of Agriculture, US Government PrintingOffice, Washington, DC.

Spadini L., Manceau A., Schindler P. W. and Charlet L. (1994)Structure and stability of Cd2+ surface complexes on ferricoxides.1. Results from EXAFS Spectroscopy. J Colloid Inter-

face Sci. 168, 73–86.

Sposito G. (1984) The Surface Chemistry of Soils. Oxford Univer-sity Press, Riverside, CA.

Srivastava P., Singh B. and Angove M. (2005) Competitiveadsorption behavior of heavy metals on kaolinite. J. Colloid


Strawn D. G. and Sparks D. L. (1999) The use of XAFS todistinguish between inner- and outer-sphere lead adsorptioncomplexes on montmorillonite. J. Colloid Interface Sci. 216,

257–269.

Stumm W., Huang C. P. and Jenkins S. R. (1970) Specific chemicalinteraction affecting the stability of dispersed systems. Croat.

Chem. Acta 42, 223–244.

Swallow K. C., Hume D. N. and Morel F. M. M. (1980) Sorptionof copper and lead by hydrous ferric oxide. Environ. Sci.

Technol. 14, 1326–1331.

Thomas G. W. (1982) Exchangeable cations. In Methods of Soil

Analysis. Part 2. Chemical, Microbiological Properties (ed. A. L.Page). American Society of Agronomy, Madison, WI, pp. 159–

164.

Trivedi P., Dyer J. A. and Sparks D. L. (2003) Lead sorption ontoferrihydrite. 1. A macroscopic and spectroscopic assessment.Environ. Sci. Technol 37, 908–914.

Tsang D. and Lo I. S. L. (2006) Competitive Cu and Cd sorptionand transport in soils: A combined batch kinetics, column andsequential extraction study. Environ. Sci. Technol. 40, 6655–

6661.

Van Benschoten J. E., Young W. H., Matsumoto M. R. and ReedB. E. (1998) A non-electrostatic surface complexation model forlead sorption on soils and mineral sufaces. J. Environ. Qual. 27,

24–30.

van Riemsdijk W. H., Bolt G. H., Koopal L. K. and Blaakmeer J.(1986) Electrolyte adsorption on heterogeneous surfaces:adsorption models. J. Colloid Interface Sci. 109, 219–228.

Veeresh H., Tripathy S., Chaudhuri D., Hart B. R. and Powell M.A. (2003) Sorption and distribution of adsorbed metals in threesoils of India. Appl. Geochem. 18, 1723–1731.

Voegelin A. and Kretzschmar R. (2003) Modelling sorption andmobility of cadmium and zinc in soils with scaled exchangecoefficients. Eur. J. Soil Sci. 54, 378–400.

Voegelin A., Vulava V. M. and Kretzschmar R. (2001) Reaction-based model describing sorption and transport of Cd, Zn, andNi in an acidic soil. Environ. Sci. Technol. 35, 1651–1657.

Walkley A. and Black A. I. (1934) An examination of theDegtjareff method for determining soil organic matter, and aproposed modification of the chromic acid titration method.Soil Sci. 37, 29–38.

Wang F., Chen J. and Forsling W. (1997) Modeling sorption oftrace metals on natural sediments by surface complexationmodel. Environ. Sci. Technol. 31, 448–453.

Weerasooriya R., Tobschall H. J. and Bandara A. (2007) Modelinginteraction of Hg(II) and bauxitic soils. Chemosphere 69, 1525–

1532.

Wen X. H., Du Q. and Tang H. X. (1998) Surface complexationmodel for the heavy metal adsorption on natural sediment.Environ. Sci. Technol. 32, 870–875.

Weng L. P., Temminghoff E. J. M. and van Riemsdijk W. H. (2001)Contribution of individual sorbents to the control of heavy metalactivity in sandy soil. Environ. Sci. Technol. 35, 4436–4443.

Westall J. C. (1986) Reactions at the oxide–solution interface:chemical and electrostatic models. In Geochemical Processes at

Mineral Surface, vol. 323 (eds. J. A. Davis and K. F. Hayes),pp. 54–78. ACS Symposium Series. American Chemical Soci-

ety, Washington, DC.

Westall J. and Hohl H. (1980) A comparison of electrostaticmodels for the oxide/solution interface. Adv. Colloid Interfac.

12, 265–294.

Xu Y., Boonfueng T., Axe L., Maeng S. and Tyson T. (2006)Surface complexation of Pb(II) on amorphous iron oxide andmanganese oxide: Spectroscopic and time studies. J. Colloid


Zavarin M., Bruton C. J. (2004) A non-electrostatic surfacecomplexation approach to modeling radionuclide migration atthe Nevada Test Site II. Aluminosilicates. Lawrence Livermore

National Laboratory. UCRL-TR-208672.Ziper C., Komarneni S. and Baker D. E. (1988) Specific cadmium

sorption in relation to the crystal-chemistry of clay minerals.Soil Sci. Soc. Am. J. 52, 49–53.

Associate editor: Dimitri A. Sverjensky


author's personal copy · author's personal copy a surface complexation and ion exchange...

Documents