Additive Surface Complexation Modeling of Uranium(VI) Adsorption


Additive Surface Complexation Modeling of Uranium(VI) Adsorption...

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Additive Surface Complexation Modeling of Uranium(VI) Adsorption onto Quartz-Sand Dominated Sediments Wenming Dong* and Jiamin Wan Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States S Supporting Information *

ABSTRACT: Many aquifers contaminated by U(VI)-containing acidic plumes are composed predominantly of quartz-sand sediments. The F-Area of the Savannah River Site (SRS) in South Carolina (USA) is an example. To predict U(VI) mobility and natural attenuation, we conducted U(VI) adsorption experiments using the FArea plume sediments and reference quartz, goethite, and kaolinite. The sediments are composed of ∼96% quartz-sand and 3−4% fine fractions of kaolinite and goethite. We developed a new humic acid adsorption method for determining the relative surface area abundances of goethite and kaolinite in the fine fractions. This method is expected to be applicable to many other binary mineral pairs, and allows successful application of the component additivity (CA) approach based surface complexation modeling (SCM) at the SRS F-Area and other similar aquifers. Our experimental results indicate that quartz has stronger U(VI) adsorption ability per unit surface area than goethite and kaolinite at pH ≤ 4.0. Our modeling results indicate that the binary (goethite/kaolinite) CA-SCM under-predicts U(VI) adsorption to the quartz-sand dominated sediments at pH ≤ 4.0. The new ternary (quartz/goethite/kaolinite) CA-SCM provides excellent predictions. The contributions of quartz-sand, kaolinite, and goethite to U(VI) adsorption and the potential influences of dissolved Al, Si, and Fe are also discussed.



INTRODUCTION Groundwaters contaminated by acidic radioactive wastewater plumes are common in many of the U.S. Department of Energy (DOE)’s nuclear materials processing sites and uranium mining and milling sites, especially from activities during the Cold War.1−7 Many of these contaminated aquifers and other depleted uranium weapon testing sites are composed predominantly of quartz-sand sediments.4−10 The F-Area in the Savannah River Site (SRS) in South Carolina (USA) is an example where a large volume of (∼ 7 × 106 m3) of acidic radioactive wastewaters was released into seepage basins after acid-extraction of plutonium from 1955 to 1988, resulting in a large, persistent U(VI) containing acidic groundwater plume.3,4,11,12 The SRS F-Area was selected by the DOE as a study site for understanding and predicting long-term groundwater plume mobility and natural attenuation. U(VI) mobility is controlled by adsorption and greatly affected by groundwater pH.8,13,14 Although U(VI) adsorption has been studied extensively,8,14−19 the understanding of mechanisms governing U adsorption under acidic conditions is still incomplete. Surface complexation modeling (SCM) has emerged as powerful tool for describing adsorption processes, mechanisms, and the effects of varying geochemical conditions.8,13,20−22 There are two major approaches for applying the SCM to sediments: the component additivity (CA) and generalized composite (GC) approaches.13,20 The CA-SCM approach assumes that the sediment can be considered as a mineral assemblage and composed of a mixture of reference minerals whose surface reactions/constants are known from independ© 2014 American Chemical Society

ent studies of each mineral or from the literature. If the reactive surface area of each mineral component present in the sediment can be estimated, adsorption by the sediment can be predicted by a simple sum of adsorption from each component, without any fitting of experimental data for the sediment. The GC-SCM approach assumes that the sediment presents “generic” surface functional groups (e.g., strong and weak binding sites) which are responsible for the adsorption, and adsorption can be described by fitting experimental data by optimizing the proposed surface adsorption models and parameters. The GC-SCM has been widely applied to complex aquifer systems because it requires less geochemical characterization and easier computation compared to the CASCM.13,20,22,23 The disadvantage of the GC-SCM is that the model parameters are site-specific and cannot be applied to other field sites.13 The advantages of the CA-SCM are that (i) the surface adsorption models and parameters can be developed from reference minerals or obtained from the literature,13 (ii) the model parameters are transferable from one field site to another,13 and (iii) the modeling results can be useful for understanding the relative contributions of each mineral components for the overall adsorption. However, applications of the CA-SCM approach to aquifer sediments have been limited due to the difficulty in Received: Revised: Accepted: Published: 6569

May May May May

19, 23, 27, 27,

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plasma emission standard (10 g/L) with deionized water while adjusting the pH to 3.0 with 0.1 M HNO3 to prevent U(VI) precipitation. Other stock solutions were prepared using chemicals of ACS reagent grade or higher. HA and U(VI) Adsorption Experiments. The HA adsorption capacities onto reference goethite, kaolinite, three goethite/kaolinite mixtures with known relative surface area ratios (10%:90%, 30%:70%, and 50%:50%) of goethite to kaolinite, and three fine fractions of sediments A, B, and C were investigated at pH 3.5 ± 0.1 with an initial HA concentration range of 10−400 mg/L and a sorbent concentration of 5 g/L. U(VI) adsorption experiments were performed under varied pH (3.0−9.5) and a total U(VI) ≈ 1 μM with a sorbent concentration of 100 g/L for quartz, 5 g/L for goethite and kaolinite, and 20 g/L for sediments. Use of different solid concentrations was necessary to compensate for different adsorption capacities, thereby allowing accurate quantification of adsorption from measurements of aqueous U(VI) concentration after adsorption. For the sediments, extractable U by pH 9.5 carbonate buffer solution26 was included in the calculations of U adsorption and modeling. All HA and U(VI) batch experiments were conducted in duplicate using polypropylene centrifuge tubes under atmospheric pressure (PCO2 = 10−3.5 atm) and room temperature (22.5 °C). All solutions contained 0.01 M NaNO3, which was selected to be similar to that of the background groundwater in the F-Area.4 Prior to addition of U(VI), a calculated amount of NaHCO3/Na2CO3 was added to the solution of pH > 5.0 to accelerate the equilibrium process with atmospheric CO2(g). To make a solution of pH ≤ 5.0, small amounts of HNO3/ NaOH were used to adjust pH. All samples were maintained in equilibrium with atmospheric CO2 by frequent exposure to air. A small volume of U(VI) stock solution was then added to achieve the desired initial [U(VI)]. A small volume of NaOH solution was immediately added to neutralize the acidity introduced by the U(VI) stock solution. The pH values were monitored and adjusted daily until pH shifts were 45 μm) fraction contents, morphology, mineralogy, specific surface areas (SSA), and elemental composition. The fine and quartz-sand fractions were separated via wet-sieving using deionized water. Polished thin sections were made from epoxy-embedded whole sediment samples and studied with a petrographic microscope. Minerals in fine fractions were identified using powder X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive X-ray spectrometry (EDS). The SSA was measured using N2−BET analysis (Quantachrome). Sediment elemental analysis was obtained using X-ray fluorescence (XRF). Reference quartz, goethite, and kaolinite were used as model minerals. Goethite and kaolinite were purchased from Alfa Aesar (Ward Hill, MA) without further treatment. Quartz was obtained from the Unimin Corporation (New Canaan, CT) and the 250−355 μm size range was selected via dry-sieving. The quartz was washed with 50% HNO3 and sonicated in deionized water for removal of attached impurities.13,24 A standard soil HA (Elliott) was purchased from the International Humic Substances Society and its chemical properties are reported elsewhere.25 Stock Suspensions and Solutions. Prior to batch experiments, the fine fractions of samples A, B, and C, and reference goethite and kaolinite were suspended in deionized water as stock suspensions (25 g/L). HA stock solution (1000 mg/L) was prepared by dissolving in deionized water by adjusting pH to 6.5 and shaking overnight, and then passed through a 0.2-μm polysulfone filter. The difference of HA concentrations before and after filtration were measured to be negligible, indicating that all HA was dissolved in the solution. U(VI) stock solution (25 μM) was prepared by dilution of a U 6570

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Other adsorption methods using methylene blue (MB),27,28 ethylene glycol monoethyl ester (EGME),29 and protein30 can only determine the overall SSA of clay fractions. The phosphate method31 can only determine the overall reactive surface area of Fe/Al oxide fraction in soils. Therefore, the existing methods cannot determine the SSAs of individual minerals in sediments with mixed mineralogy. HAs are negatively charged natural organic polyelectrolytes at all environmentally relevant pH conditions,32 and have strong adsorption affinity toward positively charged mineral surfaces including goethite and kaolinite via the formation of inner sphere surface complexes or via ligand exchange mechanisms under acidic pH conditions.25,33,34 HA adsorption shows a maximum adsorption capacity per unit surface area (Qmax),25,34 indicating the existence of a finite supply of reactive surface area or sites for each sorbent.35 Under the same experimental conditions, the maximum HA adsorption capacity onto a mixed mineral assemblage (Qmix max) can be considered as the sum of individual contributions from each component surface: mix Q max =

i fi ∑ Q max

Modeling Approach. The discussion of the reactions/ constants describing U(VI) adsorption onto goethite and kaolinite was provided in our earlier paper.8 The stability constants for U(VI) adsorption onto quartz were determined from this work by fitting experimental data with proposed surface reactions. The CA-SCM approach is then applied with goethite, kaolinite, and quartz as adsorbing components, to predict U(VI) adsorption to the sediments using PHREEQC (V2).37 The diffuse layer model (DLM)21 was used, with aqueous U(VI) and other relevant reactions/constants in Table SI-1 in the Supporting Information (SI). We assumed that all sorbent surfaces have the same thickness of electrostatic diffuse layer (10 nm) and the surface charges were counterbalanced in the diffuse layer with the counterions only.37 The Davies equation is used in PHREEQC for ionic strength activity corrections. As pointed out recently by Wang and Giammar for the bidentate surface complexation,22 it is important to note that PHREEQC (V2) uses mole coverage fraction concentrations for all surface species in the mass action expressions.



RESULTS AND DISCUSSION Sediment Properties. Photographs of a typical plume sediment sample and its quartz-sand and fine fractions are shown in Figure 1a. The fine fraction is loosely associated with

(1)

i

Qimax 2

where and f i are the maximum adsorption capacity of HA (mg/m ) onto individual mineral component i, and its relative surface area abundance in the mixed mineral assemblage, i respectively. Qmix max and Qmax can been experimentally determined and the f i can be then estimated from eq 1 for binary mineral systems. For example, once the overall SSAfine of a fine fraction of sediment is determined by N2−BET, the SSA of goethite and kaolinite in the fine fractions can be calculated: SSA goe =

Ffine goe

SSA fine·fgoe fine Fgoe

;

SSA kao =

SSA fine·fkao fine Fkao

(2)

Ffine kao

where and are the relative mass abundances of goethite and kaolinite in the fine fractions, respectively. It should be pointed out that the HA method has the following limitations: (i) It is conducted at low pH (e.g., 3.5− 5.5) where HA have a large adsorption capacity.25,34,36 High pH would generate large uncertainties due to the weak adsorption of HA.25,34,36 HA adsorption is pH-dependent (decrease with increasing pH), and the relative surface area abundances should be independent of pH. (ii) It assumes the configuration of the HA adsorbed onto the same surface is identical under the same experimental conditions, regardless of whether the mineral is the reference or from the sediments. (iii) It currently can only be applied to binary mineral systems and extension to systems containing more minerals will require combination with other approaches. For example, the sediments we used are ternary mineral systems (quartz/goethite/kaolinite). The quartz-sand can be separated to leave the fine fractions as binary systems. (iv) Potential precipitation of HA at low pH needs to be avoided. In this work, our HA control experiments indicate that no recordable precipitation was observed with HA concentration up to 400 mg/L at pH 3.5. (v) It may be limited to the sediments with low contents of natural organic matter. When applied to other aquifer sediments containing high-solubility minerals, the potential effects of dissolved cations needs to be tested. It is also worth noting that no other independent experimental approach is currently available, such that use of the CA-SCM approach in this relatively simple system would not otherwise be possible.

Figure 1. Solid phase of F-Area sediments. (a) Typical F-Area sediments: fine particles associated with coarse quartz-sand that can be easily separated by wet-sieving. (b) Pore-scale microscopic image of the whole sediments. (c, d) SEM microphotographs of the coatings showing kaolinite and goethite are the dominant minerals with the SEM/EDS chemical composition analyses.

the quartz-sand that can be readily removed by water-rinsing for the moisture-preserved sediments. If the sediments were dried, significant fine-grain coatings13,38,39 would be observed on the quartz-sand surfaces and could not be removed by water rinsing. A microphotograph of a polished section (Figure 1b), illustrates spatial relations between quartz-sand grains and fine particles. SEM photographs (Figure 1c, d) show the morphology of the fine fraction, well-crystallized kaolinite and goethite, confirmed by XRD (SI Figure SI-1) and SEM/EDS elemental analysis (Figure 1c, d). The mineral composition (Table 1) estimated by XRF indicates that the bulk sediments were composed predominantly of quartz (SiO2, 95.9−96.2%) with small fractions of kaolinite (Al2Si2O5(OH)4), 2.2−2.6%) and goethite (FeO(OH), 1.0−1.2%). The quartz mass fraction estimated by XRF is consistent with the coarse fraction data 6571

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Table 1. Properties of Plume Sediment Samples from SRS FArea A specific surface area (SSAbulk) (m2/g) pHa U in solid sediment (μg/g)b quartz sand (wt %)c kaolinite (wt %)d goethite (wt %)e fine fraction (wt %, ≤ 45 μm)f coarse fraction (wt %, > 45 μm)f SSAfine (m2/g) g goethite (Ffine goe , wt %) fine kaolinite (Fkao , wt %)g SSAquartz‑sand (m2/g)

SSAref (m2/g)

B

Whole Sediment 1.90 ± 0.20 1.69 ± 0.20

C 1.44 ± 0.20

3.9 ± 0.1 1.68 96.2% 2.2% 1.1% ∼ 4.8%

4.0 ± 0.1 1.52 95.9% 2.6% 1.2% ∼ 3.8%

4.9 ± 0.1 0.26 96.2% 2.5% 1.0% ∼ 3.8%

∼ 95.2%

∼ 96.2%

∼ 96.2%

Fine Fraction 36.5 ± 2.5 39.3 ± 3.6 32.7 ± 2.8 33.8% 32.5% 29.6% 66.2% 67.5% 70.4% Coarse Fraction 0.20 ± 0.10 0.23 ± 0.10 0.18 ± 0.10 Reference Mineral goethite kaolinite quartz 16.2 ± 1.0 20.6 ± 1.2 0.036 ± 0.020

Figure 2. HA sorption isotherms to (a) reference goethite, kaolinite, and the mixtures of reference goethite/kaolinite with an overall surface area ratio = 10%:90% for mixture-1, 30%:70% for mixture-2, and 50%:50% for mixture-3, and (b) the fine fractions of sediments A, B, and C under conditions of 5 g solid/L, pH = 3.5 ± 0.1, and 0.01 M NaNO3. Symbols are experimental data representing a mean of duplicate samples with standard deviation bars. The solid lines are Langmuir modeling results.

a

Table 2. Determining the Relative Reactive Surface Area Abundances of Goethite and Kaolinite within the Mixtures of Reference Goethite/Kaolinite and the Fine Fractions of Sediments A, B, and C Using the HA Adsorption Method (pH = 3.5 ± 0.1, Sorbent Concentration = 5 g/L)

Measured with 1:1 ratio of fresh sediment to deionized water. Extractable U by pH = 9.5 carbonate buffer solution.19 cEstimated by assuming that the Si in quartz-sand (SiO2) was from the difference between all measured Si using XRF (X-ray fluorescence) and the Si from kaolinite (Al2Si2O5(OH)4). dEstimated by assuming that all measured Al using XRF was from kaolinite (Al2Si2O5(OH)4). e Estimated by assuming that all measured Fe using XRF was from goethite (FeO(OH)). fDetermined via wet-sieving using deionized water. gCalculated using XRF data by assuming that the fine fraction was composed of kaolinite and goethite only. b

relative surface area abundancec sorbent goethite kaolinite goe/kao mixture-1a goe/kao mixture-2a goe/kao mixture-3a fine fraction A fine fraction B fine fraction C

(>45 μm) determined by wet-sieving (95.2−96.2%). Measured SSA is in the range of 1.44−1.90 m2/g for the bulk sediments, 32.7−39.3 m2/g for the fine fractions, and 0.18−0.23 m2/g for the coarse fractions. As shown in Table 1, U concentrations are higher (0.26−1.68 μg/g) and pH values are lower (3.9−4.9) in the plume samples compared to U concentrations (0.006− 0.014 μg/g) and pH (5.3−5.4) in the background sediment samples.4,8 More information on the plume chemistry is provided in Wan et al.4 Relative Surface Area Abundances of Goethite and Kaolinite in the Fine Fractions of Sediments. As shown in Figure 2, the per unit surface area based maximum adsorption capacity of HA to the mixed mineral assemblages (Qmix mas) at pH = 3.5 can be considered as the sum of goethite (Qgoe max) and kao kaolinite (Qmax ). The relative surface area abundance of goethite (fgoe) in the mixtures can be estimated as fgoe =

mix kao − Q max Q max goe kao − Q max Q max

Qkao max,

2 b

(mg/m )

2.4 1.00 1.13 1.40 1.70 1.5 1.4 1.15

± ± ± ± ± ± ± ±

0.1 0.02 0.02 0.04 0.02 0.1 0.1 0.02

goethite (fgoe)

kaolinite ( f kao)

9.3% 28.6% 50.0% 35.7% 28.6% 10.7%

90.7% 71.4% 50.0% 64.3% 71.4% 89.3%

a

Mixtures of reference goethite/kaolinite with an overall surface area ratio = 10%:90% for mixture-1, 30%:70% for mixture-2, and 50%:50% for mixture-3. bObtained by fitting experimental data (Figure 2) to the Langmuir adsorption isotherm equation: Qx = b·C·Qxmax/(1 + b·C), where Qx is the adsorbed HA mass weight by per unit surface area (mg/m2) of sorbent x, C is the aqueous HA concentration at equilibrium (mg/L), b is a constant (L/mg), and Qxmax is the maximum adsorption capacity of HA by per unit surface area (mg/m2) of sorbent x. cCalculated using eq 3.

area ratios of goethite to kaolinite. The values of fgoe determined for the fine fractions of A, B, and C are 35.7%, 28.6%, and 10.7%, respectively. The fgoe shows a trend of A > B ≫ C, which is consistent with the relative intensities of goethite peaks (∼ 21.2 deg) in XRD patterns (SI Figure SI-1). The values of fgoe and f kao are also consistent with the mass percentages of goethite and kaolinite estimated by XRF (Table 1) for the fine fractions A and B. However, the value of fgoe is significantly smaller than its mass percentage (10.7 ± 1.4% vs 29.6 ± 0.9%) for fraction C. The values of fgoe should be attributed to the overall active goethite surface areas in the fine fractions, including the surfaces from the discrete particles and/or the coated goethite. If the goethite surfaces were coated more by

× 100 (3)

where and can be obtained by fitting the Langmuir equation to the HA adsorption data (Figure 2). The obtained Qmix max, fgoe, and f kao = 100 − fgoe for the goethite/ kaolinite mixture-1, mixture-2, and mixture-3, and the fine fractions of A, B, and C are listed in Table 2. As shown in Table 2, the experimentally determined values of fgoe:f kao are 9.3%:90.7% for mixture-1, 28.6%:71.4% for mixture-2, and 50%:50% for mixture-3, which are in good agreement with the experimentally designed relative surface Qgoe max,

Qxmax

Qmix max

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Figure 3. Comparison of U(VI) adsorption onto reference goethite, kaolinite and quartz (a). Surface complexation modeling of U(VI) adsorption onto goethite (b), kaolinite (c), and quartz (d). Symbols are experimental data points with estimated uncertainties. The solid lines are the overall model fits and the dashed lines are the fitted distribution of specific surface species: 1 = (>FeOH)2UO2+, 2 = (>FeOH)2UO2CO3−, 3 = >X2UO2, 4 = (>SOH)2UO2+, and 5 = (>SOH)2UO2CO3−, 6 = (>QOH)2UO22+, and 7 = (>QOH)2UO2CO3.

kaolinite has the PZC at pH ≈ 4.0−5.047 and goethite has a PZC at pH 9.2.46,48 Thus, goethite and kaolinite surfaces are net positively charged at pH < 4.0, which can depress UO22+ adsorption. This result indicates that quartz is an important U(VI) sorbent under acidic pH conditions. The relative strong U(VI) adsorption by quartz-sand at pH ≤ 4.0 was also observed in our earlier work.8 Similar U(VI) adsorption behavior by quartz and silica has been also reported by Pabalan et al.49 and McKinley et al.50 Huber et al.51 and Stamberg et al.52 also reported that quartz and silica can adsorb U(VI) at pH 3.0−4.0, but decreased with decreasing pH. Although adsorption by quartz is small at pH 3.0−4.0 (6.9− 9.0% in Figure 3d), it cannot be ignored because of its large abundance (∼ 96%) in the sediments. Comparison of U(VI) Adsorption onto Quartz-Sand Dominated Sediments. The distribution coefficients of U(VI) adsorption onto sediments A, B, and C are compared in SI Figure SI-2. Similar U(VI) adsorption to all three samples is observed at pH ≤ 4.0, while adsorption is stronger to A than to B and C at pH 4.0−7.0. The small adsorption at pH ≤ 4.0 can be attributed to the relative contributions from kaolinite and quartz due to their stronger adsorption ability at acidic conditions (Figure 3a) and their larger mass/surface abundances (Tables 1 and 2). The stronger adsorption by A at pH = 4.0−7.0 is attributed to its larger fgeo (Figure 2). Surface Complexation Modeling. To illustrate the relative contributions of individual minerals and specific surface species to the overall adsorption of U(VI), the experimental data and modeling results are presented in percentages (Figures 3b−d and Figure 4). Modeling of U(VI) Adsorption onto Quartz, Goethite, and Kaolinite. A detailed description for modeling U(VI) adsorption to goethite and kaolinite (Table 3 and Figure 3b, c) has been discussed in our previous paper8 and can be summarized briefly as (i) U(VI) species are adsorbed via

kaolinite, the values of fgoe would be smaller than those of fgoe if goethite and kaolinite exist as the discrete particles alone, and vice versa. The results demonstrate that HA adsorption method is capable of determining the relative surface area abundances of goethite and kaolinite in their assemblages. It is expected that HA method can apply to many other binary mineral pairs of goethite, hematite, magnetite, gibbsite, silica, manganese-oxides, kaolinite, montmorillonite, and imogolite, etc. because HA adsorption to all these minerals increases with decreasing pH, and shows existence of specific maximum adsorption capacities at constant pH conditions.33,34,40−45 U(VI) Adsorption Data. U(VI) adsorption was calculated from the difference of aqueous U(VI) concentrations before and after adsorption. Our control experiments indicate that U(VI) adsorption by the vial walls was negligible. To directly compare the adsorption ability by various sorbents, the experimental data are reported as per unit surface area based distribution coefficients Ka (mL/m2) (Figure 3a and SI Figure SI-2). Comparison of U(VI) Adsorption onto Quartz, Goethite, and Kaolinite. The new adsorption data of U(VI) on quartz are compared with those by goethite and kaolinite (reported elsewhere8) in Figure 3a. The data show that the quartz surface has stronger adsorption ability than the goethite and kaolinite at pH ≤ 4.0. For example, at pH ≈ 3.0, Ka = 18.9 ± 11.4 mL/ m2 for quartz, 2.4 ± 0.2 mL/m2 for kaolinite, and 0.73 ± 0.06 mL/m2 for goethite. At pH > 4.0, goethite becomes the more important sorbent, and quartz and kaolinite show almost identical adsorption ability. This observation can be explained by the amphoteric nature of the minerals.46 Quartz has the point of zero charge (PZC) at pH 2.0−3.0,35,46 and quartz surfaces are net negatively charged at pH > 3.0, such that adsorption of the positively charged UO22+ species (SI Figure SI-3a) is enhanced by electrostatic attraction. In contrast, 6573

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Table 3. Surface Reactions and Formation Constants for Goethite, Kaolinite, and Quartza Log K Goethite 1. 2 >FeOH−0.5 + UO22+ = (>FeOH)2UO2+ 2. 2 >FeOH−0.5 + UO22+ + H2CO3 = (>FeOH)2UO2CO3− + 2 H+ 3. >FeOH−0.5 + H+ = >FeOH2+0.5 4. 2 >FeOH−0.5 + H2CO3 = (>FeO)2CO2−1 + 2H2O 5. >FeOH−0.5 + H2CO3 + Na+ = >FeOCO2−1.5Na+ + H+ + H2O 6. >FeOH−0.5 + Al3+ + H2O = (>FeOH)Al(OH)+1.5 + H+ 7. >FeOH−0.5 + Al3+ + 2H2O = (>FeOH)Al(OH)2+0.5 + 2H+ Kaolinite 8. 2 >SOH−0.5 + UO22+ = (>SOH)2UO2+ 9. 2 >SOH−0.5 + UO22+ + H2CO3 = (>SOH)2UO2CO3− + 2 H+ 10. >SOH−0.5 + H+ = >SOH2+0.5 11. >SOH−0.5 + Na+ = >SOH-Na+0.5 12. >SOH−0.5 + H+ + NO3− = >SOH2−NO3− 13. 2 >X− + UO22+ = (>X)2UO2 14. >X− + Na+ = >XNa 15. >X− + H+ = >XH 16. 2 >X− + Ca2+ = (>X)2Ca 17. 3 >X− + Al3+ = (>X)3Al Quartz 18. 2 >QOH + UO22+ = (>QOH)2UO22+ 19. 2 >QOH+ UO22+ + H2CO3 = (>QOH)2UO2CO3 + 2 H+ 20. >QOH = >QO− + H+ 21. >QOH + Al3+ + 3 H2O = (>QOH)Al(OH)3 + 3 H+

Figure 4. Binary mineral (goethite/kaolinite, Model-1) and ternary mineral (quartz/goethite/kaolinite, Model-2) CA-SCM approach predicted U(VI) adsorption onto bulk sediments of A (a, b), B (c, d), and C (e, f). The black solid lines are the overall model fits and the colored lines with numbers are the fitted distribution of specific surface species: 1 = (>FeOH)2UO2+, 2 = (>FeOH)2UO2CO3−, 3 = >X2UO2, 4 = (>SOH)2UO2+, and 5 = (>SOH)2UO2CO3−, 6 = (>QOH)2UO22+, and 7 = (>QOH)2UO2CO3.

14.11b 4.35b 9.18b 5.93b −3.02b 7.00c −0.61c 5.3d −0.1d 4.9e −2.1e 4.9e 7.1d 2.9e 4.5d 6.8d 8.0d 5.12f 0.26f −7.20g −9.00h

a

Based on the overall surface area, goethite site (>FeOH) density = 3.0/nm2 from Sherman et al.,48 kaolinite exchange site (>X−) density = 0.28/nm2 and the edge site (>SOH) density = 2.3/nm2 from Heidmann et al.,47,68 and quartz-sand site (>QOH) density = 2.3 from Pabalan et al.49,57 bSherman et al.48 cModified from Lovgren et al.62 d Dong et al.8 eHeidmann et al.47,68 fThis work. gPabalan et al.49 h Modified from Charlet et al.63

formation of two bidentate surface complexes to goethite and kaolinite edge sites, which are supported by spectroscopic investigations;48,53,54 (ii) for kaolinite, ion exchange reactions of exchange sites with UO22+ and coexisting cations must be included under our experimental conditions. U(VI) adsorption and SCM onto quartz/silica have been extensively studied.13,49,51,52,55−58 In these studies, monodentate surface complexes were usually proposed via reactions of silanol surface sites with major aqueous U(VI) species. However, these studies did not provide direct spectroscopic evidence supporting the formation of the proposed surface complexes. Recent X-ray absorption spectroscopy (XAS) studies on U(VI) coordination environments at the surfaces of quartz, silica, and aluminosilicates demonstrated that all U(VI) species adsorbed via formation of inner-sphere bidentate complexes.53,54,59 More importantly, U(VI) in air CO2equilibrated systems was identified to form ternary uranyl− carbonato surface complexes.53,54,59−61 On the basis of these spectroscopic observations, we hypothesize that two bidentate U(VI) surface complexes are formed with the quartz surface sites (Table 3). The surface site density (2.3/nm2) and the deprotonation constant (Table 3) for quartz were obtained from Pabalan et al.49 Constrained by these minimum numbers of reactions and parameters combined with the SSA of quartz, modeling of U(VI) adsorption to quartz (Figure 3d) was completed. The reaction constants (Table 3) for U(VI) surface species (>QOH)2UO22+ and (>QOH)2UO2CO3 were obtained by overall tests to fit experimental data using PHREEQC. Figure 3d shows that the one type of

surface site with two bidentate surface complexes can reasonably predict U(VI) adsorption onto quartz. Modeling of U(VI) Adsorption onto Quartz-Sand Dominated Sediments. The total mole number of each binding site and the SSA of each mineral are important input parameters for CA-SCM. The total mole numbers of binding sites on quartz, goethite, and kaolinite surfaces in each sediment sample was calculated from the total mass of bulk sediment used (20 g), the mass percentages and SSAs of its fine and coarse fractions (Table 1), the relative surface area abundances of goethite and kaolinite (Table 2), and the site density for goethite, kaolinite, and quartz (Table 3). These parameters were combined with the surface reactions/constants (Table 3), the aqueous reactions/constants (SI Table SI-1) and the DLM, in order to simulate U(VI) adsorption to the quartz-sand dominated sediments using the CA-SCM approach (Figure 4). The dissolved Fe, Al, and Si from sediments (SI Table SI-2) could affect U(VI) adsorption via competitive adsorption and complexation. A comparison and discussion of calculated solubility of goethite, kaolinite, and quartz using the solubility constants in SI Table SI-3 with experimentally determined data are presented in SI Figure SI-4. The dissolved Fe was below its effective detection limit (∼10−7 M) and its effect is expected to be negligible. The dissolved Al (0.004−0.063 mM) increased with deceasing pH (≤ 4.5). The surface reactions/constants of dissolved Al with goethite and quartz (Table 3) were modified from Lovgren et al.62 and Charlet et al.,63 respectively, and have been found capable of describing their Al adsorption data (SI 6574

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Figure SI-5). Detailed modification can be found in the SI. Prior to modeling U(VI) adsorption onto sediments, the total initial Al concentrations were adjusted until the calculated equilibrium Al concentrations approximately equaled the experimentally determined Al data throughout preliminary CA-SCM modeling of Al adsorption to the sediments. The results show that dissolved Al can suppress U(VI) adsorption to kaolinite exchange sites. For sediment A as an example, if equilibrium [Al] = 0.021, 0.036, and 0.063 mM at pH = 4.18, 3.57, and 3.05 (SI Table SI-2) were not considered, predicted U(VI) adsorption could increase from 40% to 45%, 15% to 18%, and 9.2% to 9.4%, respectively. The small impact at pH 3.05 is due to competition from high [H+]. The effect of dissolved Al on U(VI) adsorption to goethite and quartz was predicted to be small (≤ 1%) under our experimental conditions. The dissolved Si decreased slightly with increasing pH, consistent with observations by Turner et al.58 and William et al.64 for silica phases. Hiemstra et al.65 reported that dissolved Si can adsorb onto goethite and adsorption decreased with decreasing pH at pH < 9.0. Ulrich et al. also reported that the influence of dissolved Si on U(VI)−ferrihydrite surface complexation in Fe(III)-rich acidic mine water was not detectable in slightly acidic conditions using XAS.66 However, understanding of how adsorbed Si affects U(VI) adsorption is currently unclear and needs further study. In this work, only the aqueous complexation of U(VI) with dissolved Si67 was considered (SI Figure SI-3b). With the considerations above, model simulations were completed first by using the binary CA approach (Model-1, Figure 4a, c, e) in terms of SCMs for U(VI) with goethite and kaolinite only. It is apparent that this binary CA-SCM underpredicted U(VI) adsorption at pH ≤ 4.0. By using ternary CA approach (Model-2, Figure 4b, d, f) in terms of SCMs for U(VI) with quartz, goethite, and kaolinite provides an excellent fit to U(VI) experimental data for all the tested sediment samples, particularly at acidic pH conditions. It should be noted that the binary CA-SCM model was able to predict U(VI) adsorption to the SRS F-Area background sediments successfully.8 The difference between the plume and background sediments is their contents of quartz-sand fractions. The plume sediments contain larger contents of quartz-sand than the background sediments (e.g., plume ∼96% vs background 87%). This difference can increase the quartzsand’s contribution to the overall surface area in sediments (e.g., 3.5% to 11.6%). The results (Figure 4) indicate that although U(VI) adsorption to quartz is small, inclusion of quartz improves modeling of U(VI) adsorption under acidic conditions. As illustrated in Figure 4b, d, f, the quartz, goethite, and kaolinite cocontribute to U(VI) adsorption at pH < 5.0. Specifically, quartz adsorbs more at pH near 3.0 (species 6), kaolinite (exchange sites) contributes more at pH near 4.0 (species 3), while goethite dominates at pH > 4.5 (species 1−2). At near neutral and weakly alkaline pH conditions, the goethite uranyl− carbonato surface complex (>FeOH)2UO2CO3− (species 2) becomes the only species dominating U(VI) adsorption. The strong adsorption by ∼1% goethite mass weight in all sediments (Table 1) at near neutral and alkaline pH conditions is consistent with many observations in the literature, where iron (oxy)hydroxides such as amorphous/microcrystalline ferrihydrite, goethite, and hematite in aquifer sediments have been identified as major sinks for U(VI) uptake.14,16,21,48

This work demonstrates how the CA-SCM approach can be used as a tool to predict U(VI) adsorption in acidic aquifers. The HA adsorption method developed in this work plays a key role in successful application of the CA-SCM. It should be noted that further studies are needed on (1) application of HA method for multimineral systems, and (2) the effects of dissolved Al and Si on U(VI) adsorption at acidic conditions.



ASSOCIATED CONTENT

S Supporting Information *

Aqueous reactions/constants, XRD analysis, U(VI) adsorption to sediments, aqueous U(VI) species distribution, dissolved ions concentrations, solubility calculations, modeling Al(III) adsorption to goethite/silica, and a modeling input file. This material is available free of charge via the Internet at http:// pubs.acs.org/.



AUTHOR INFORMATION

Corresponding Author

*Phone: 510-486-7499; fax: 510-486-5686; e-mail: [email protected]. Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS The work reported here is supported as part of the Sustainable Systems (SS) Scientific Focus Area (SFA) program at LBNL, supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Subsurface Biogeochemical Research Program, through Contract DEAC02-05CH11231 between Lawrence Berkeley National Laboratory and the U.S. Department of Energy. We thank Dr. Miles Denham (SRNL) for providing us the sediment samples from SRS, and the anonymous reviewers for their helpful comments.



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