Ferrous iron sorption by hydrous metal oxides

Journal of Colloid and Interface Science 297 (2006) 443–454 www.elsevier.com/locate/jcis

Ferrous iron sorption by hydrous metal oxides Genevieve Villaseñor Nano, Timothy J. Strathmann ∗,1 Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA Received 13 September 2005; accepted 14 November 2005 Available online 9 December 2005

Abstract Ferrous iron is critical to a number of biogeochemical processes that occur in heterogeneous aquatic environments, including the abiotic reductive transformation of subsurface contaminants. The sorption of Fe(II) to ubiquitous soil minerals, particularly iron-free mineral phases, is not well understood. Colloidal TiO2 , γ -AlOOH, and γ -Al2 O3 were used as model hydrous oxides to investigate Fe(II) sorption to iron-free mineral surfaces. Rapid Fe(II) sorption during the first few hours is followed by a much slower uptake process that continues for extended periods (at least 30 days). For equivalent solution conditions, the extent of Fe(II) sorption decreases in the order TiO2 > γ -Al2 O3  γ -AlOOH. Short-term equilibrium sorption data measured over a wide range of conditions (pH, ionic strength, Fe(II)-to-sorbent ratio) are well described by the diffuse double layer model. Fe(II) sorption to TiO2 is best described by a single-site model that considers formation of two surface complexes, ≡SOFe+ and ≡SOFeOH0 . For γ -AlOOH and γ -Al2 O3 , sorption data are best described by a two-site model that considers formation of ≡SOFe+ complexes at weak- and strong-binding surface sites. Accurate description of sorption data for higher Fe(II) concentrations at alkaline pH conditions requires the inclusion of a Fe(II) surface precipitation reaction in the model formulation. The presence of common groundwater constituents (calcium, sulfate, bicarbonate, or fulvic acid) had no significant effect on Fe(II) sorption. These results demonstrate that iron-free soil minerals can exert a significant influence on Fe(II) sorption and speciation in heterogeneous aquatic systems. © 2005 Published by Elsevier Inc. Keywords: Ferrous iron; Sorption; Surface complexation; Metal oxide; Titanium dioxide; Aluminum oxide; Anoxic environments

1. Introduction Ferrous iron, Fe(II), is abundant in many suboxic and anoxic environments (e.g., sediments, water-logged soils, and aquifers) and plays a critical role in a number of important biogeochemical processes [1–4]. Fe(II) concentrations exceeding 1 mM (56 mg/L) have been reported in some environments [1,2,5]. Fe(II) is generated by microbial utilization of Fe(III)-bearing mineral phases and dissolved Fe(III)–organic complexes as alternative terminal electron acceptors [6–9], and via abiotic Fe(III) reduction by extracellular reducing agents of biological origin (e.g., quinones, thiols, bisulfide) [10–12].

* Corresponding author. Fax: +1 217 333 6968.

E-mail address: [email protected] (T.J. Strathmann). 1 Department of Civil and Environmental Engineering, University of Illinois,

3209 Newmark Civil Engineering Laboratory, 205 N. Mathews Ave, MC-250, Urbana, IL 61801, USA. 0021-9797/$ – see front matter © 2005 Published by Elsevier Inc. doi:10.1016/j.jcis.2005.11.030

In recent years there has been a growing interest in the genesis, speciation, and redox activity of Fe(II) in heterogeneous aquatic systems [1,4,5,8,13–16]. Recent studies report that a number of contaminants of concern (e.g., Cr(VI), U(VI), organohalogens) are abiotically reduced by Fe(II), and that reaction rates are heavily dependent upon Fe(II) speciation [17–26]. A number of recent reports demonstrate that sorption of Fe(II) to mineral surfaces markedly enhances the metal’s redox reactivity with contaminants [23–33]. Furthermore, some reports suggest that observed reaction rates correlate with the concentration of individual surface-complexed Fe(II) species (e.g., hydrolyzed species like ≡SOFeOH0 ), as opposed to the total concentration of sorbed Fe(II) [25,33]. Finally, because Fe(II) reaches appreciable concentrations in some environments, it can affect the sorption and distribution of trace metal contaminants (e.g., As, Cd, Zn) [34,35]. Therefore, development of models that accurately predict both the extent of Fe(II) sorption and the distribution of sorbed Fe(II) species is of great interest.

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Because of the need for strict anoxic laboratory procedures, only a limited number of studies have reported on Fe(II) sorption to environmentally-relevant mineral surfaces [23–33,36– 39], and most of these did not attempt to model the sorption processes (typically, Fe(II) sorption measurements were conducted as part of studies that focus on Fe(II) redox reactivity [23–33]). Furthermore, the bulk of literature reports pertain to Fe(II) sorption to Fe(III) oxide minerals (e.g., ferrihydrite, goethite, hematite, etc.). These studies show that the extent of Fe(II) sorption is affected by a number of variables, including the identity and concentration of Fe(III) minerals present, the composition of the aqueous solution (e.g., pH), and the equilibration time [25,28,29,36–38]. In comparison to what has been reported for Fe(III) oxides, very little is known about Fe(II) sorption to other important classes of soil minerals (e.g., Al and Si oxides, aluminosilicate clays). Surface complexation models (SCMs) have been highly successful in describing the sorption of metal ions by hydrous metal oxide surfaces [40–43]. These models assume that sorption occurs by metal complexation with hydrated surface functional groups in an analogous manner to metal–ligand complexation reactions that occur in the solution phase [40]. A number of SCMs have been proposed for metal ion sorption that make varying assumptions about surface acid–base chemistry, electrostatic description of the solid–water interface, heterogeneity of surface sites, and surface precipitation processes. A few studies have interpreted Fe(II) sorption to Fe(III) oxides using SCMs that assume Fe(II) uptake solely via formation of innersphere complexes with surface hydroxyl groups [25,28,33,39]. However, these interpretations are called into question by recent reports that Fe(II)-to-Fe(III) electron transfer processes are contributing to the observed sorption phenomena at aqueousFe(III) oxide interfaces [37,38,44,45]. To our knowledge, there are no previous reports of the application of SCMs to describe Fe(II) sorption to other classes of soil minerals. This work focuses on quantification and surface complexation modeling of Fe(II) sorption processes in aqueous suspensions of hydrous metal oxides (TiO2 , γ -AlOOH, and γ -Al2 O3 ) that are representative of common iron-free soil minerals. The extent of Fe(II) sorption was quantified as a function of several variables, including reaction time, solution composition (e.g., pH, ionic strength, presence of other groundwater constituents), and the identity and concentration of the sorbing mineral surface. For each oxide mineral, Fe(II) sorption is well described at a wide range of conditions (pH, I , total Fe(II)) by a generalized two-layer surface complexation model that uses a single set of equilibrium constant values for two Fe(II) surface complexation reactions (either two-reaction stoichiometries binding at a single surface site or one-reaction stoichiometry binding to two types of surface sites). By focusing on iron-free metal oxides, we are able to neglect Fe(II) uptake via interfacial electron transfer processes [37,38,44], and identify how important geochemical parameters affect Fe(II) surface complexation processes. This work is part of an ongoing effort to characterize the mechanisms controlling Fe(II) formation, speciation and abiotic redox reactivity in anoxic aquatic systems.

2. Materials and methods 2.1. Chemical reagents All chemicals were of >95% purity and were used without further purification. FeCl2 ·4H2 O, NaCl, NaOH, Na2 SO4 , CaCl2 ·2H2 O, 3-(2-pyridyl)-5,6-diphenyl-1,2,4-triazine-4 ,4 disulfonic acid sodium salt (ferrozine), 2-morpholinoethanesulfonic acid (MES buffer, pKa = 6.1), 3-[N-morpholino]propanesulfonic acid (MOPS buffer, pKa = 7.2), and MOPS sodium salt were obtained from Sigma–Aldrich (St. Louis, MO). NaHCO3 , N-[tris(hydroxymethyl)methyl]-3-aminopropanesulfonic acid (TAPS buffer, pKa = 8.4), and concentrated (∼12.1 M) HCl were obtained from Fisher Scientific (Fair Lawn, NJ). Standard grade Suwannee River fulvic acid was purchased from the International Humic Substances Society (St. Paul, MN). 2.2. Mineral phases Three synthetic nanoparticulate metal (hydr)oxide phases were used as model Fe(II)-sorbing minerals. TiO2 (P25 form) and γ -Al2 O3 (Alumina-C form) were provided by Degussa. γ -AlOOH (boehmite) was obtained from Sasol North America. Titanium and aluminum oxides were chosen as model Fe(II)-sorbing oxides because previous work by one of the authors showed that the extent of sorption to these solids is much greater than to other iron-free oxides (e.g., amorphous SiO2 ) [29]. The high-purity mineral phases were used as received, and have been extensively characterized [29,46–50]. Table 1 lists some relevant mineral properties and the experimental conditions used in this work. The designated crystal structures of γ -AlOOH and γ -Al2 O3 were verified previously using powder X-ray diffraction [29,50]. The TiO2 powder was reported to be mainly anatase (rutile amounts to ca. 10%) [48]. Table 1 Hydrous metal oxide properties and experimental conditions Specific surface area (m2 /g) pHzpc c Primary particle size Mineral loading (g/L) Total Fe(II) concentration (µM) pH range Ionic strength (M) Equilibration time (h)f

TiO2

γ -AlOOH

γ -Al2 O3

50a 6.3a 30 nm 0–15 (2)e 20–500 4–9 0.001–0.1 2

85.6b 8.6d 35 nm 0–10 (5)e 20–500 4–9 0.001–0.1 6

92.8a 9.0a 20 nm 0–10 (5)e 20–500 4–9 0.001–0.1 6

a Ref. [46]. b Ref. [50]. c pH zpc values determined by potentiometric titrations under an inert at-

mosphere (nitrogen or argon) in 0.1 M NaNO3 (TiO2 ), 0.1 M NaCl (γ AlOOH), or 0.01 M NaNO3 (γ -Al2 O3 ). d Ref. [71]. e Number in parentheses represents mineral loading used in pH-edge sorption experiments and kinetic sorption experiments. f Reaction time used in short-term equilibrium sorption experiments.

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2.3. Experimental setup Strict oxygen exclusion is necessary to prevent Fe(II) oxidation at circum-neutral pH [51]. Thus, all experiments were conducted inside a controlled-atmosphere glovebox (96% N2 , 4% H2 with Pd catalysts; Coy Laboratory Products, Grass Lake, MI). The temperature of the glovebox was maintained at 25 ± 1 ◦ C and chamber gases were continuously bubbled through a 1 M NaOH solution to remove CO2 . All reactors, equipment, and dry reagents were also pre-equilibrated inside the glovebox for several hours prior to use. With the exception of experiments conducted using natural groundwater, all solutions were prepared with anoxic reagent-grade water (18 M cm; Millipore Corporation, Billerica, MA) that was boiled for >30 min and then sparged with ultra-high purity N2 before and after transferring into the glovebox. All glassware and plasticware were washed in 1 M HCl and rinsed with water several times prior to use. Fe(II) stock solutions were prepared by the following procedure. First, 0.22 mol of FeCl2 ·4H2 O was added to 0.2 L of deoxygenated water and pH was adjusted to 4.0 using NaOH. After stirring for 30 min, the solution was filtered to remove any Fe(III) impurities that are much less soluble than Fe(II) at this pH [52]. As an added precaution to ensure removal of all Fe(III) solids, filtration was accomplished using two syringe filters attached in series: 0.2 µm mixed cellulose ester (Fisherbrand) followed by 0.02 µm aluminum oxide (Whatman Scientific). The filtrate was then acidified to pH 2.0 with HCl and quantified by comparison with Fe(II) standards. Aqueous stock suspensions of each mineral phase (20 or 30 g/L) were allowed to hydrate for at least one day prior to use. Special care was taken to exclude light from TiO2 suspensions to prevent unwanted photochemical reactions, even though tests demonstrated that exposure to laboratory lighting had no effect on experimental results. A natural groundwater was collected from beneath the Newmark Civil Engineering Laboratory in Urbana, IL. The groundwater possesses the following characteristics: pH 7.3, 290 mg/L alkalinity as CaCO3 , 1.1 mg/L Fe, 0.02 mg/L Mn, 60 mg/L Ca, 38 mg/L Mg, 1.1 mg/L NH4 , 1.2 mg/L SO4 , and 3.0 mg/L total organic carbon [53]. Prior to use, the groundwater was sparged with compressed air for >1 h to oxidize the Fe(II) already present in the water. The groundwater was then filtered (0.2 µm aluminum oxide) to remove the resulting Fe(III) oxide precipitates and any other solids, and then deoxygenated by sparging with ultra-high purity N2 . 2.4. Sorption kinetics Kinetic sorption experiments were first conducted to quantify the dynamics of Fe(II) uptake by mineral surfaces, and to select appropriate reaction times to use for subsequent “equilibrium” sorption experiments. Continuously-stirred aqueous suspensions were prepared in 125-mL polypropylene bottles by adding appropriate volumes of water, MOPS buffer (used to fix both the pH and ionic strength), and mineral stock suspension. Suspension pH was then adjusted as necessary (pH 7 for TiO2 ;

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pH 7.5 for γ -AlOOH and γ -Al2 O3 ) and allowed to equilibrate overnight. A small volume of Fe(II) stock solution was then added to initiate the kinetic reactions and achieve an overall Fe(II) concentration of 100 µM in the suspensions. Aliquots of suspension were then regularly collected for a period of ∼30 days, and were immediately filtered through 0.2-µm mixed cellulose ester filters, and the acidified filtrates were analyzed for Fe(II). The amount of Fe(II) sorbed to the metal oxide solids was calculated by difference. Although loss of Fe(II) by adsorption to the syringe filters was not observed, the first 1–2 mL of filtrate were always discarded to prevent any such experimental artifacts. Suspension pH was monitored throughout each experiment, and small volumes of 0.1 M HCl or NaOH were added to readjust pH when necessary. Dilution effects were assumed negligible since the total volume of acid/base added was <1% of the reactor volume. 2.5. Sorption equilibrium Equilibrium sorption experiments were conducted to determine the effects of important geochemical parameters—pH, ionic strength, total Fe(II) concentration, mineral identity and loading, and the presence of bulk groundwater constituents − (Ca2+ , SO2− 4 , HCO3 , fulvic acid)—on the extent of Fe(II) sorption. For comparison, Fe(II) sorption was also measured in TiO2 suspensions prepared in a natural groundwater containing several of these same constituents. First, a series of pH-variation experiments were carried out in which all other constituents were held fixed. For each experiment, three continuously-stirred “master” reactors corresponding to different pH ranges were prepared in 200-mL polypropylene bottles. Appropriate volumes of water and stock solutions of NaCl, pH buffer (see below), and mineral phase were added to the master reactors, and HCl was used to adjust the pH of the three master reactors to pH 4.0, 6.4, and 7.6, respectively. After equilibrating overnight, stock solutions of Fe(II) and any competing/co-sorbing groundwater constituents were added to each master reactor. 0.1 M NaOH was then slowly added to increase the pH of each master reactor, and 10-mL aliquots of suspension were removed at desired pH intervals and placed in 15-mL centrifuge tubes. The centrifuge tubes were then placed on a rotating mixer, and allowed to equilibrate for either 2 h (TiO2 ) or 6 h (γ -Al2 O3 and γ -AlOOH). After equilibration, the final pH of each suspension aliquot was recorded before filtering and acidifying. Dilution effects were assumed negligible because the total added NaOH volume was <1% of the volume of each master reactor. A second series of equilibrium experiments was conducted to quantify Fe(II) sorption as a function of mineral loading (g/L) at a fixed pH. A series of 30-mL suspensions was prepared with varying amounts of each mineral phase (0–15 g/L), and 0.015 M MOPS buffer was used to buffer pH at 7.5 and ionic strength at 0.01 M (∼66% of MOPS is present in the ionized form at this pH). After pre-equilibrating overnight, 100 µM Fe(II) were added to each suspension and allowed to equilibrate for the same time period used in pH-variation experiments. Suspensions were then filtered and acidified as described above.

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pH stability of individual suspensions was verified by periodic measurement. pH 7.5 was chosen for these experiments because it falls on the pH sorption edges observed for all three mineral phases.

would have rapidly oxidized Fe(II) to insoluble Fe(III) precipitates [51].

2.6. pH buffers

Solution and suspension pH values were measured using an Orion 290 Aplus pH meter equipped with an Orion semimicro pH probe that was calibrated against pH 4.0, 7.0, and 10.0 standard buffers prior to each use. The ferrozine colorimetric method was used to quantify aqueous Fe(II) concentrations [56]; spectrophotometric measurements were made using a double-beam Shimadzu UV-2401PC spectrophotometer. A ferrozine-reacted water blank was used for background correction.

Low concentrations of pH buffers were added to help stabilize the pH of suspensions; Good’s buffers were used because they interact weakly with metal ions [54]. For pH-variation studies, 1 mM MES (pH 4.0–6.8), MOPS (pH 6.4–7.8), or TAPS (pH 7.4–9.0) buffer was added to each of the three master reactors to help prevent large pH decreases associated with proton release during surface complexation reactions. In kinetic experiments and mineral loading-variation experiments, higher buffer concentrations (up to 15 mM) were used to ensure pH stability. Tests carried out in buffer-free suspensions demonstrated that the extent of Fe(II) sorption is not affected by buffer addition at these concentrations. Furthermore, comparable Fe(II) sorption was observed in pH-variation experiments where different buffers were used to set the same pH (e.g., MOPS and TAPS buffer present used for pH 7.8), and equivalent results were obtained at corresponding conditions in kinetic, pH-variation, and loading-variation experiments (e.g., after 6 h equilibration in 5 g/L γ -Al2 O3 suspension at pH 7.5, 100 µM total Fe(II), and 0.01 M ionic strength), even though buffer concentrations differed by more than a factor of 10 in these different experiments. 2.7. Fe(II) sorption reversibility and solubility Tests were also carried out to evaluate the reversibility of Fe(II) sorption processes, and to ensure that minimal Fe(II) oxidation occurred during equilibrium sorption experiments. Fe(II) desorption was accomplished by acidifying suspensions with HCl (equilibrium sorption experiments indicated minimal sorption at pH < 4.5). Fe(II) desorption was measured for two different scenarios: (1) after allowing Fe(II) to react with mineral surfaces for the same length of time used in short-term equilibrium sorption experiments (i.e., after 2 or 6 h), and (2) after reacting suspensions for 30 days (i.e., at the end of the kinetic sorption experiments). Comparing results from these two scenarios enabled us to evaluate the effects of system aging on the reversibility of Fe(II) sorption processes. A series of batch tests were also conducted to evaluate whether Fe(II) precipitation occurs at the pH and Fe(II) concentrations examined in sorption experiments. Fe(II) solubility was operationally defined by passage through the same 0.2-µm filters used in sorption experiments. For 100 µM Fe(II) solutions, no precipitation was observed for the entire pH range examined. For 500 µM Fe(II) solutions, precipitation was only observed when pH > 8.5. These results agree closely with model predictions using solubility constants for amorphous Fe(OH)2 (s) [55]. The lack of any significant iron removed from solutions equilibrated at neutral pH also validated the integrity of the anoxic laboratory procedures used here; exposure to O2 at neutral pH

2.8. Analytical methods

2.9. Surface complexation modeling The generalized diffuse double layer (DDL) surface complexation model was used to interpret Fe(II) sorption trends [40], and the Davies equation was used to calculate activity coefficients for aqueous species. Oxides were assumed to contain either one or two types of amphoteric surface sites (so-called weak-binding and strong-binding sites) that possess similar acid–base characteristics (i.e., the same protonation and deprotonation constants were assumed to apply to both site types). Equilibrium constants for aqueous-phase reactions and surface protonation and deprotonation reactions were fixed at previously reported values (Table 2). Optimization of intrinsic Fe(II) surface complexation constants was performed using a nonlinear least squares optimization algorithm in the computer program FITEQL 4.0 [57]. For each mineral, attempts were made to fit sorption data with individual surface complexation reactions and combinations of surface complexation reactions possessing different reaction stoichiometries, x≡SOH +yFe2+ + zH2 O ↔ 2y−x−z + (x + z)H+ , (≡SO)x Fey (OH)z

(1)

where ≡SOH represents an amphoteric surface site, and x, y, and z are reaction stoichiometries. Both single-site and two-site models were considered, where ≡Sw OH and ≡Ss OH were used to represent the so-called weak-binding and strong-binding surface species, respectively [40]. The majority of the acid–base labile surface groups were assumed to be weak-binding, so weak site densities (Nw , sites nm−2 ) were fixed at values previously reported for each mineral phase (Table 2). Single-site models assumed that reactions take place only at these sites. Two-site models assumed that mineral surfaces also contain a much lower concentration of strong-binding surface sites (Ns < 5%Ntot ), and Ns was determined by optimization in the iterative fitting procedure. The quality of model fits is indicated by visual inspection of the fits and the overall variance (Vy ), which is the weighted sum of the squares of the residuals divided by the degrees of freedom; values of Vy between 0.1 and 20 indicate reasonably good fits [57]. Multiple reaction stoichiometries or site types were only considered when their inclusion decreased Vy

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Table 2 Aqueous reactions and intrinsic surface complexation reactionsa Aqueous reactionsb H2 O ↔ OH− + H+ Fe2+ + H2 O ↔ FeOH+ + H+ Fe2+ + 2H2 O ↔ Fe(OH)02 + 2H+ + Fe2+ + 3H2 O ↔ Fe(OH)− 3 + 3H

+ Fe2+ + 4H2 O ↔ Fe(OH)2− 4 + 4H

log K −13.997 −9.397 −20.494 −28.991 −45.988 TiO2 2.5d

γ -AlOOH 1.7e

γ -Al2 O3 2.3d

n/a

0.045 ± 0.007

0.079 ± 0.004

log K 3.9d

log K 7.48e

log K 7.7d

−8.7d

−9.80e

−10.2d

log K −2.87 ± 0.02 −10.92 ± 0.03

log K −4.59 ± 0.05

log K −3.70 ± 0.03

−2.24 ± 0.09 69 3 7.16

−0.66 ± 0.03 96 3 5.13

Surface reactions N w (sites/nm2 )c Ns (sites/nm2 )f Surface acid–base reactionsg ≡SOH + H+ ↔ ≡SOH+ 2

≡SOH + H2 O ↔ ≡SO− + H+

Fe(II) sorption reactions ≡Sw OH + Fe2+ ↔ ≡Sw OFe+ + H+ ≡Sw OH + Fe2+ + H2 O ↔ ≡Sw OFeOH0 + 2H+ ≡Ss OH + Fe2+ ↔ ≡Ss OFe+ + H+ Number of data points used in overall fit Number of adjustable fitting parameters Vy a b c d e f g

113 2 1.80

All log K values corrected to I = 0 M using the Davies equation. Uncertainties represent one standard deviation. Stability constants for aqueous reactions from Ref. [55]. Density of weak-binding surface sites reported previously. Ref. [46]. Ref. [71]. Density of strong-binding Al oxide surface sites determined from the overall fit of the entire pH-variation Fe(II) sorption data set. Stability constants for protonation and deprotonation of weak-binding and strong-binding sites assumed to be the same.

considerably and resulted in visually improved model predictions of entire data set for a given mineral (pH-variation and mineral loading-variation data). To prevent artifacts caused by Fe(II) precipitation processes, data at pH > 8.5 was excluded from 20 and 100 µM Fe(II) data sets, and data at pH > 8.0 was excluded from 500 µM Fe(II) data sets when performing model fits (measured data are still shown for comparison with model predictions). In addition, only data points corresponding to Fe(II) sorption from 5 to 95% were used for model fitting purposes. Data outside this range are considered less accurate for Fe(II) species present in the phase that is not dominant (e.g., there is high uncertainty in the concentration of sorbed species when [Fe(II)]aq approaches 100% of total Fe(II)). For fitting data, experimental errors for pH and [Fe(II)]sorbed measurements were assumed to be 0.02 pH units and 0.05[Fe(II)]tot , respectively, and an absolute error of 1×10−6 M was assumed for [Fe(II)]sorbed . Model predictions using fit-optimized parameters were performed using the computer program MINEQL+ [58]. 3. Results and discussion 3.1. Sorption kinetics Fe(II) sorption kinetics is summarized in Fig. 1. In general, Fe(II) sorption to the metal oxide surfaces follows a two-phase process. An initial phase characterized by rapid sorption during the first few hours is followed by a much slower uptake process that continues for the duration of the kinetic experi-

Fig. 1. Fractional sorption of Fe(II) onto hydrous metal oxides as a function of time at a fixed pH. Reaction conditions: 100 µM Fe(II), pH 7.0 (TiO2 ) or pH 7.5 (γ -AlOOH and γ -Al2 O3 ), I = 0.01 M. Lines connecting the data points are included only as a visual guide and do not indicate a model fit.

ments. For TiO2 , the majority of the total sorption observed (70% of the added Fe(II)) occurs within the first few hours, but the extent of Fe(II) sorption increases slightly to 74% during the subsequent 30 days. The two-phase Fe(II) sorption behavior is much more pronounced in aluminum oxide suspensions. For γ -Al2 O3 , 40% of Fe(II) sorbs during the first few hours, but the extent of sorption increases to 67% during the subsequent month. For γ -AlOOH, 30% of Fe(II) sorbs during the first few hours, increasing to 46% over the following month. Jeon and co-workers recently reported similar slow uptake of

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Fig. 2. Fractional sorption of Fe(II) onto TiO2 (A, D), γ -AlOOH (B, E), and γ -Al2 O3 (C, F) as a function of pH. Panels (A)–(C) illustrate the effect of varying total Fe(II) concentration at a fixed ionic strength and mass loading of each mineral. Panels (D)–(F) show the effects of varying ionic strength at a fixed total Fe(II) concentration and mass loading of each mineral. Lines represent model predictions using overall best-fit parameters listed in Table 2.

Fe(II) by α-Fe2 O3 and α-Al2 O3 at pH 6.8 [38]. The slow uptake by α-Fe2 O3 was attributed to interfacial electron transfer and formation of a mixed Fe(II)–Fe(III) phase (e.g., magnetite). No mechanism was postulated for slow uptake by α-Al2 O3 . Numerous studies have reported two-phase metal sorption kinetics in mineral suspensions, and several mechanisms have been postulated to account for this behavior [38,59–61]: (1) parallel multiple-site adsorption where different sites possess differing activation energies, (2) rapid uptake by adsorption at low activation energy sites followed by slow surface diffusion to higher activation energy surface sites, and (3) rapid adsorption to particle surfaces followed by a slower process that causes additional uptake from solution, such as solid-state diffusion to adsorb at internal binding sites or to form a new structural phase involving the adsorbate and adsorbent, surfacepromoted precipitation of the adsorbate, or interfacial electron transfer. Since this work focuses on characterization of Fe(II) surface complexation processes, which can be expected to occur during the rapid uptake phase, subsequent short-term “equilibrium” sorption experiments were conducted using either

a 2-h (TiO2 ) or a 6-h (γ -Al2 O3 , γ -AlOOH) equilibration time. 3.2. Sorption equilibrium Equilibrium sorption measurements were carried out to quantify the effects of environmental variables that are important in saturated subsurface environments. Fig. 2 shows the effects of pH, total Fe(II) concentration, and ionic strength on the extent of Fe(II) sorption in titanium and aluminum oxide suspensions. As expected, Fe(II) sorption increases with increasing pH. Typical pH-edge sorption behavior is observed for all three mineral phases, where the extent of Fe(II) sorption increases from 0 to nearly 100% over a narrow pH window. The extent of Fe(II) sorption at equivalent solution conditions follows 2 g/L TiO2 > 5 g/L γ -Al2 O3  5 g/L γ -AlOOH. For example, at pH 7 and 0.01 M ionic strength, the extent to which 100 µM Fe(II) sorbs is 57% (TiO2 ), 38% (γ -Al2 O3 ) and 7% (γ -AlOOH). For each mineral surface, as the sorbate-to-sorbent ratio (i.e., total Fe(II)/total ≡SOH) increases, sorption edges shift

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Fig. 3. Fractional sorption of Fe(II) as a function of metal oxide mass loading in suspensions of (") TiO2 , (2) γ -Al2 O3 , and (Q) γ -AlOOH. Lines represent model predictions using overall best-fit parameters listed in Table 2.

to higher pH (Figs. 2A–2C). This trend is commonly reported for cation sorption onto hydrous metal oxides, and is consistent with Fe(II) binding to a fixed number of surface sites [40, 62]. As total Fe(II) concentration increases, fractional sorption to each oxide at a given pH decreases while sorption density (Γ Fe(II) ; µmol/m2 ) increases. Increasing ionic strength from 0.001 to 0.1 M has no significant effect on Fe(II) sorption (Figs. 2D–2F), a feature also commonly observed for divalent transition metal ion sorption to metal oxides [40,63]. This observation indicates that the contribution of coulombic forces to the overall free energy change associated with Fe(II) sorption is minimal, and it can be inferred that Fe(II) sorption occurs predominantly by formation of inner-sphere complexes with specific surface sites (as opposed to solvent-separated ion pairs) [63]. It is also noteworthy that the Fe(II) sorption edges observed for TiO2 occur mostly in the pH range where the surface is negatively charged (i.e., pH > pHzpc ), while the sorption edges observed for the aluminum oxides occur at pH conditions where the surfaces are positively charged (i.e., pH < pHzpc ). In comparison, sorption edges previously reported for Fe(III) oxide surfaces demonstrate Fe(II) sorption at pH < pHzpc [25,36,39]. It should be kept in mind, however, that the positions of the sorption edges are dependent upon the sorbate-to-sorbent ratio, so higher TiO2 mass loadings would be expected to shift the Fe(II) sorption edge to pH < pHzpc . Fig. 3 shows the effect that mineral loading has on the extent of Fe(II) sorption when pH is fixed at 7.5. These experiments were carried out in lieu of typical isotherm experiments to avoid high Fe(II) concentrations where precipitation is favorable. For TiO2 , the extent of sorption increases from 0 to 80% in a roughly linear fashion from 0 to 2 g/L mineral loading, and then increases more gradually to 100% when loading is increased from 2 to 8 g/L. For the aluminum oxides, sorption also increases in a linear fashion, but the maximum extent of Fe(II) sorption reaches only 41% for γ -AlOOH and 86% for γ -Al2 O3 at the highest mass loadings examined (10 g/L). The relative extent of Fe(II) sorption for the three mineral phases is unchanged when data is normalized to mineral surface area

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loading (m2 /L) of the suspensions (TiO2 > γ -Al2 O3 > γ AlOOH). Although the observed Fe(II) sorption trends are qualitatively similar for all three minerals, the differing positions of the pH sorption edges and mass loading dependencies of each mineral demonstrate that the strength of Fe(II)–metal oxide interactions are highly dependent upon the identity of the sorbing surface. Greater sorption to TiO2 than to either of the aluminum oxide surfaces is consistent with expected trends for hard Lewis acid–base interactions (i.e., stronger interactions with increasing charge of the sorbate or sorbent-derived metal ions) [64]. The large difference in Fe(II) sorption behavior observed for the two aluminum oxides is more difficult to interpret. For comparable sorbent mass or surface area, Fe(II) sorbs to a much greater extent to γ -Al2 O3 than γ -AlOOH. The position of the sorption edge measured for γ -Al2 O3 is roughly 1 pH unit lower than the edge position measured for γ -AlOOH. Wide variations in the extent of Fe(II) sorption to different ferric oxide minerals have also been reported [25,39,65]. 3.3. Sorption reversibility The reversibility of Fe(II) sorption was evaluated in metal oxide suspensions following both short-term equilibration (at the end of equilibrium sorption experiments; 2 h for TiO2 , 6 h for γ -AlOOH and γ -Al2 O3 ) and long-term equilibration (at the end of the 30-day sorption kinetics experiments). Desorption of Fe(II) was accomplished by acidifying suspensions to pH 4.5 where minimal Fe(II) sorption is observed in equilibrium experiments (Fig. 2). Complete Fe(II) desorption is achieved for all three metal oxides following short-term sorption (sampled after mixing acidified suspensions overnight). This observation indicates that the rapid uptake process observed during the first few hours (see Fig. 1) results primarily from an easily reversible sorption process. This finding also confirms that negligible Fe(II) oxidation occurs during equilibrium sorption experiments. Following long-term equilibration of TiO2 suspensions, >90% of Fe(II) desorption is still achieved by acidifying the suspension and mixing overnight. This indicates that Fe(II) speciation in TiO2 suspensions is not significantly modified following the initial sorption process. The static nature of Fe(II) speciation on TiO2 surfaces is further supported by very little change in the extent of Fe(II) sorption after the first few hours of equilibration (see Fig. 1). In contrast, incomplete Fe(II) desorption is observed following long-term equilibration of aluminum oxide suspensions. Only 75–80% and 80–85% of Fe(II) is desorbed in aqueous suspensions of γ -AlOOH and γ -Al2 O3 , respectively, even after mixing the acidified suspensions for up to 4 months. The low Fe(II) recovery suggests that the slow uptake phase observed during long-term kinetic experiments leads to Fe(II) fixation at aluminum oxide surfaces. Jeon and co-workers reported nearly complete Fe(II) desorption from αAl2 O3 surfaces following a 30-day sorption process [38], but these authors used a harsher extraction procedure (3 N HCl) than that used here (suspensions acidified to pH 4.5). Fe(II) fixation at aluminum oxide surfaces after an extended period of

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3.5. Surface complexation modeling

Fig. 4. Fe(II) sorption onto TiO2 in suspensions prepared in laboratory water amended with selected bulk groundwater constituents and in natural groundwater. No pH buffer or electrolyte was added to suspensions prepared in natural groundwater.

uptake could be due to slow diffusion of Fe(II) ions from particle surfaces to strong internal binding sites [61], or to formation of a new mixed Fe(II)–Al(III) mineral phase by either surface precipitation or solid-state diffusion into the mineral matrix [60, 66]. Although Fe(II) oxidation by O2 contamination of our experimental system cannot be ruled out, it is not expected to be a factor because nearly complete desorption was observed in the equivalent TiO2 sorption/desorption experiment that was conducted at the same time using the same procedure. 3.4. Effects of groundwater constituents A series of sorption experiments were conducted to evaluate the effects of a number of bulk groundwater constituents on Fe(II) sorption reactions. TiO2 was used for these experiments because results described above indicate that it behaves most ideally with respect to metal ion surface complexation phenomena (i.e., rapid and reversible sorption behavior), which is the focus of this investigation. The results of these experiments, shown in Fig. 4, indicate that the extent of Fe(II) sorption is not − 2+ significantly affected by the presence of SO2− 4 , Ca , HCO3 , or fulvic acid at relevant groundwater concentrations (although higher concentrations may yield effects). Furthermore, identical Fe(II) sorption is observed in suspensions prepared in a natural groundwater and in reagent-grade water that is ionic strengthand pH-buffered (groundwater composition described in Section 2.3). The insensitivity of Fe(II) sorption to the presence of other groundwater constituents contrasts with previous reports of diminished Fe(II) sorption to α-FeOOH in the presence of carbonate [28] and enhanced Fe(II) sorption to α-Fe2 O3 in the presence of sulfate [37]. The contrasting results demonstrate the surface-specific nature of sorption processes in complex multiadsorbate systems like groundwater. The findings also highlight the need for further studies to characterize how individual mineral surface properties (e.g., pHzpc ) affect competitive and cooperative sorption mechanisms involving important ground– water constituents.

Fe(II) sorption data were interpreted using a generalized diffuse double layer model (DDL) [40]. While the literature is full of arguments in favor of particular surface complexation models, the DDL was chosen for this work because of its simplicity and need for few model input parameters. The goal of the modeling work was to obtain a single small set of model parameters that would best describe Fe(II) sorption under all conditions examined. Therefore, models that considered different reaction stoichiometries and surface site types were fit simultaneously to the entire pH-variation data set (pH 4–9, 3 different Fe(II) concentrations, 3 different ionic strengths) for a given mineral (see Fig. 2). In order to keep the models simple and minimize the number of adjustable fitting parameters, only the following scenarios were considered: 1. Single weak-site model with one reaction stoichiometry. 2. Single weak-site model with two distinct reaction stoichiometries. 3. Two-site model with equivalent reaction stoichiometries at both sites. The stoichiometries of the surface complexes and the estimated intrinsic stability constants that yielded the best fits of the overall data sets are provided in Table 2, and the predicted Fe(II) sorption trends using these model parameters are shown in Figs. 2–3. 3.5.1. Fe(II) sorption by TiO2 Fe(II) sorption onto TiO2 is best described by a model that assumes the simultaneous formation of two surface complexes at a single surface site: ≡SOH + Fe2+ ↔ ≡SOFe+ + H+ ,

(2)

≡SOH + Fe2+ + H2 O ↔ ≡SOFeOH0 + 2H+ .

(3)

Figs. 2A and 2D show that most of the pH-variation sorption data set is well described by as single set of equilibrium constants for formation of these two complexes. As an added test of the model robustness, Fe(II) sorption was calculated as a function of TiO2 loading and compared with measured sorption trends (Fig. 3). Even though the fitting procedure did not consider this data, model predictions are in good agreement with measured data. The underprediction of the sorption of 500 µM Fe(II) at pH > 8 is presumably due to surface precipitation processes that are not included in the model formulation (note that model fitting only considered 500 µM data at pH  8). Single-site models that considered a single reaction stoichiometry (≡SOFe+ , ≡SOFeOH0 , or (≡SO)2 Fe0 ) provide poor predictions of the sorption data set, particularly at lower and higher Fe(II) concentrations. A single-site model that considers ≡SOFe+ and (≡SO)2 Fe0 complexes accurately describes sorption trends observed at lower Fe(II) concentrations, but fails to accurately predict the sorption trend observed for 500 µM Fe(II). Attempts to fit a two-site model that considered both weak- and strong-binding surface sites did not converge in the FITEQL minimization algorithm.

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≡SOFe+ predominates at higher solid loadings. The variation in the relative concentration of the two surface species with increased TiO2 mass loading results from contributions of the coulombic terms in the formulations of the intrinsic surface complexation constants [40]. According to the equilibrium constants listed in Table 2, the pK1 value for homogeneous Fe(II) hydrolysis is 9.1 (Table 2). In comparison, the predicted Fe(II) surface species distribution in TiO2 suspensions indicates significant heterogeneous Fe(II) hydrolysis at neutral pH. This finding indicates that sorption to TiO2 promotes hydrolysis of Fe(II), as has been reported for a number of divalent metal ions [41]. Previous studies report that surface-enhanced Fe(II) hydrolysis promotes Fe(II) redox reactivity with O2 and a number of aquatic contaminants (e.g., U(VI), nitroaromatic contaminants) [25,33]. 3.5.2. Fe(II) Sorption by aluminum oxides As reported for TiO2 , single-site, single-stoichiometry models provided poor fits to Fe(II) sorption data for both γ -AlOOH and γ -Al2 O3 . In addition, model convergence was not achieved when considering two reaction stoichiometries (combinations of ≡SOFe+ , ≡SOFeOH0 , and (≡SO)2 Fe0 ) at a single surface site. The sorption data for both aluminum oxides is best described by a model that considers formation of surface complexes with the same stoichiometry depicted in Eq. (2) at both “weak” and “strong” sites (following the terminology of Dzombak and Morel [40]) Fig. 5. Calculated distribution of surface-complexed Fe(II) species as a function of pH and mineral loading in TiO2 suspensions. Speciation calculated using stability constants provided in Table 2. Symbols represent the measured sorption, solid lines the predicted total sorption, and dashed and dotted lines the predicted distribution of surface complexes.

Charlet and co-workers invoked the same two surface complexes to describe Fe(II) sorption on Fe(III) oxide minerals [25, 33,39]. The intrinsic stability constants obtained for formation of ≡SOFe+ ranged from log K = −2.98 (ferrihydrite) to 0.11 (goethite), and constants for formation of ≡SOFeOH0 ranged from log K = −11.96 (ferrihydrite) to −7.64 (goethite). The constants derived for the same complexes on the TiO2 surface lie towards the lower end of these ranges. It should be kept in mind, however, that Fe(II) sorption to Fe(III) oxides may include contributions from interfacial electron transfer processes [44,45], so stability constants derived from fits that assume only surface complexation on Fe(III) oxide surfaces may be artificially high. Fig. 5 shows the calculated distribution of Fe(II) surface complexes as a function of both pH and mineral loading. The relative contribution of ≡SOFe+ and ≡SOFeOH0 to overall sorption varies with solution composition. For 100 µM Fe(II), ≡SOFe+ predominates at pH < 8.6 and ≡SOFeOH0 predominates at higher pH (Fig. 5A). Similar trends are predicted for 20 and 500 µM Fe(II), except that the dividing line between ≡SOFe+ and ≡SOFeOH0 predominance occurs at pH 10.1 and 7.0, respectively. When TiO2 mass loading is varied at pH 7.5, ≡SOFeOH0 is predicted to predominate at <4 g/L solid, and

≡Sw OH + Fe2+ ↔ ≡Sw OFe+ + H+ ,

(4)

≡Ss OH + Fe2+ ↔ ≡Ss OFe+ + H+ ,

(5)

where ≡Sw OH and ≡Ss OH refer to the weak-complexing and strong-complexing surface sites, respectively. Strong sites were assumed to account for only a small fraction of the total surface sites (<5% Ntot ), so the weak site density (Nw ) was set equal to the total site density values used in the single-site models. The strong site density (Ns ) was then determined by optimization with FITEQL to find the value that produced the best fit of the experimental data. Similar two-site models have previously been used to describe the sorption of divalent metal ions onto hydrous metal oxide surfaces [40,67]. Model predictions shown in Figs. 2–3 demonstrate that the model adequately describes Fe(II) sorption to aluminum oxides under most conditions examined. Using a single set of equilibrium constants for each oxide (Table 2), the model accurately predicts the varying positions of the pH sorption edges measured for different total Fe(II) concentrations and ionic strength. As with TiO2 , the model underpredicts the sorption of 500 µM Fe(II) onto aluminum oxides at pH > 8. This can be attributed to surface precipitation processes that are not considered in the model. The underprediction of 20 µM Fe(II) sorption at low pH could be due to the presence of additional surface sites that are even more strongly binding than either of the two sites used here. The general trends observed for varying mineral loading are also accurately predicted for both minerals, although predictions for γ -AlOOH are slightly lower than measured.

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Fig. 7. Effect of adding a Fe(OH)2 (s) precipitation reaction on model-predicted sorption of 500 µM Fe(II) onto γ -AlOOH. Data points are the same as shown in Fig. 2B. Individual lines represent model predictions using different log K values for Eq. (6). All other model parameters the same as listed in Table 2.

for different Al(III) oxides and different Fe(III) oxides might be explained by differences in the distribution of surface-site types (e.g., mononuclear, binuclear, or trinuclear) on the exposed surfaces of each oxide mineral [68–70]. Further studies that combine detailed crystallographic data on mineral structure, microscopic data on oxide particle morphology, and spectroscopic data on the molecular structures of adsorbing surface complexes are needed to address this issue. Fig. 6. Calculated distribution of surface-complexed Fe(II) species as a function of pH and mineral loading in γ -AlOOH suspensions. Speciation calculated using stability constants provided in Table 2.

Fig. 6 shows representative plots of the calculated distribution of Fe(II) surface complexes in γ -AlOOH suspensions as a function of both pH and mineral loading. Both weak- and strong-site complexes contribute to Fe(II) sorption under most conditions. At conditions where the total sorbed Fe(II) is lower than the concentration of “strong” surface sites, the relative contribution of ≡Ss OFe+ and ≡Sw OFe+ is relatively constant. When the total sorbed Fe(II) is greater than the concentration of “strong” surface sites, the relative importance ≡Sw OFe+ increases. For example, when pH increases, ≡Ss OFe+ levels off at 30% (a value corresponding to saturation of strong sites) while the concentration of ≡Sw OFe+ continues to increase. The relative contribution of strong-site complexes is greater for γ -Al2 O3 than γ -AlOOH. As discussed earlier, when normalized for mineral surface area or mass, Fe(II) sorbs to a much greater extent to γ -Al2 O3 than γ -AlOOH. Likewise, the stability constants obtained for Eqs. (4)–(5) follow the same trend. The stability constant for Fe(II) complexation by “weak” and “strong” surface sites are, respectively, nearly one- and two-orders-of-magnitude larger for γ -Al2 O3 than γ -AlOOH. Similar large differences in surface complexation constants have been reported for Fe(II) sorption to Fe(III) oxides [25,39,65]. The large differences in magnitude of equivalent surface complexation constants obtained

3.6. Surface precipitation of Fe(II) As described above, model fitting only considered pH conditions where Fe(II) is significantly undersaturated with respect to Fe(OH)2 (s) [55], and Fe(II) precipitation reactions were not included in the surface complexation model formulations described above. With the exception of data reported for sorption of 500 µM Fe(II) at pH > 8, the SCMs described above provide good predictions of Fe(II) sorption trends. Under this limited set of conditions, the SCM parameters derived from fitting data at lower pH and Fe(II) concentrations underpredict the extent of sorption. Although surface-enhanced Fe(II) precipitation is not the focus of this study, the inclusion of a simple Fe(OH)2 (s) precipitation reaction Fe2+ + 2H2 O ↔ Fe(OH)2 (s) + 2H+

(6)

in the SCMs (all other model parameters fixed at values listed in Table 2) enabled description of the sorption data at pH > 8. For example, Fig. 7 shows the effect of assuming different log K values for Eq. (6) on model predictions of 500 µM Fe(II) sorption to γ -AlOOH. Using a log K value of −13.0 reproduced the measured sorption data most closely. This compares with a reported log K value of −13.56 for Fe(OH)2 (s) precipitation from homogeneous solution [55]. log K values of −12.9 and −12.2 best describe the sorption of 500 µM Fe(II) onto TiO2 and γ -Al2 O3 , respectively. The increased logK values for Eq. (6) inferred from these fits suggest that hydrous metal oxides may enhance Fe(II) precipitation, as has been reported for other divalent transition metals [60,66].

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Alternatively, the underprediction of SCM calculations can be attributed to the surface site density values that were used as fixed model parameters during model fits. The fixed site densities, which were reported previously from experimental measurements [46,71], are less than would be predicted from crystallographic data. When surface site densities are arbitrarily fixed at higher values (e.g., 5–10 sites/nm2 ), the model is able to capture observed uptake trends for 500 µM Fe(II) at pH > 8 without invoking Fe(OH)2 (s) precipitation. However, model fits at these conditions are not significantly improved when surface site density is allowed to float as an adjustable parameter during model fits, and with the exception of γ -Al2 O3 , the (weak) site density values obtained in this process are lower than the values reported in Table 2. For γ -Al2 O3 , the fit-derived value of Nw is 4.3 sites/nm2 . Furthermore, precipitation of 500 µM Fe(II) is observed in homogeneous solution at pH  8.5, so ignoring the precipitation reaction in the model formulation is questionable. Additional in-depth studies need to be conducted over a wider range of conditions that approach or exceed Fe(OH)2 (s) saturation to establish the mechanism(s) controlling Fe(II) uptake from solution, and adequately model these processes. In situ spectroscopy techniques can also be used to differentiate between mononuclear surface complexes and three-dimensional surface precipitates [60,66,72]. 4. Conclusions Like other divalent cations, Fe(II) sorbs to hydrous metal oxide surfaces under a variety of environmental conditions. For each mineral sorbent examined here, the extent of Fe(II) sorption increases with increasing reaction time, pH, and decreasing Fe(II)-to-sorbent ratio, and is not significantly affected by changing ionic strength. These results suggest that noniron oxide surfaces are important sorbent phases for Fe(II) in groundwater. Although sorption trends reported here indicate that Fe(II) sorption to aluminum oxides is weaker than to equivalent Fe(III) oxides (e.g., γ -AlOOH vs γ -FeOOH), aluminumcontaining minerals (oxides and aluminosilicates) are often more abundant in temperate soils. It follows that geochemical models of Fe(II) speciation should also consider sorption to surfaces other than iron oxides. Similarly, the redox reactivity of aquatic contaminants with Fe(II) sorbed to non-iron oxide minerals should be quantified to establish the relative importance of these species to overall contaminant fate in complex heterogeneous systems. To date, most studies of contaminant reactivity with Fe(II) have focused exclusively on the reactivity of Fe(II) species sorbed to Fe(III) oxide surfaces. Sorption of Fe(II) onto hydrous metal oxide surfaces over a wide range of conditions, including variable pH, Fe(II) concentration, ionic strength, and mineral loading, is described reasonably well by the diffuse double layer model using a single set of mononuclear monodentate reaction stoichiometries and associated equilibrium constants for each mineral. Fe(II) sorption to TiO2 is best described by a single-site model that considers formation of two surface complexes, ≡SOFe+ and ≡SOFeOH0 . Fe(II) sorption to γ -AlOOH and γ -Al2 O3 is best described by a two-site model that considers formation of ≡SOFe+ complexes

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at both weak-binding and strong-binding sites. Modeling sorption of higher Fe(II) concentrations at alkaline pH conditions requires consideration of surface precipitation reactions. We recommend further studies to assess the relative contribution of surface complexation and surface precipitation processes at different environmental conditions. For aluminum oxides, rapid Fe(II) uptake that occurs on the timescale of hours is followed by a much slower process that results in formation of surface species that are not desorbed upon gentle acidification. This finding suggests that surface speciation of Fe(II) is not static, and dynamic models will be required to accurately predict the metal’s speciation in environmental systems where longer contact times are relevant. In contrast to earlier reports on Fe(II) sorption to Fe(III) oxide surfaces, the extent of Fe(II) sorption to TiO2 is not markedly affected by the presence of common groundwater constituents (calcium, sulfate, bicarbonate, fulvic acid) at concentrations relevant to groundwater systems. Furthermore, sorption measurements carried out in a natural groundwater are similar to measurements conducted in pH- and ionic strengthbuffered laboratory water. The differing trends reported for TiO2 versus Fe(III) oxides may be a by-product of the prevailing surface charges at pH conditions where the Fe(II) sorption edges are observed. Fe(II) sorption to Fe(III) oxides occurs at pH where the surface is positively charged, whereas TiO2 is negatively charged throughout most of the pH range where the Fe(II) sorption edge occurs. We recommend additional studies to elucidate the mechanisms by which relevant soil and groundwater constituents affect the sorption of Fe(II) to different mineral surfaces. Addressing these issues is necessary to evaluate Fe(II) speciation in complex natural environments that contain a mixture of sorbent phases and solution constituents. Application of modern in situ spectroscopic techniques is a promising approach to resolving these issues and others discussed in this paper, and we hope that this work serves to motivate future research into Fe(II) speciation in environmental systems. Acknowledgments Acknowledgment is made to the donors of the American Chemical Society Petroleum Research Fund for support of this research. The National Science Foundation provided a graduate fellowship for G.V.N. Degussa and Sasol are gratefully acknowledged for supplying high purity metal oxide powders. References [1] J.G. Hering, W. Stumm, in: M.F. Hochella, A.F. White (Eds.), Mineral– Water Interface Geochemistry, in: Reviews in Mineralogy, vol. 23, Mineralogical Society of America, Washington, DC, 1990, pp. 427–465. [2] W. Stumm, J.J. Morgan, Aquatic Chemistry: Chemical Equilibria and Rates in Natural Waters, third ed., New York, Wiley, 1996, 1022 p. [3] W.H. Schlesinger, Biogeochemistry—An Analysis of Global Change, second ed., Academic Press, San Diego, CA, 1997, 588 p. [4] D.R. Lovley, D.E. Holmes, K.P. Nevin, Adv. Microbiol. Physiol. (2004) 219–286. [5] G.W. Luther, P.A. Shellenbarger, P.J. Brendel, Geochim. Cosmochim. Acta 60 (1996) 951–960.

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