99Tc(VII) Retardation, Reduction, and Redox Rate Scaling in Naturally

Subscriber access provided by NEW YORK MED COLL

Article

99Tc(VII) Retardation, Reduction, and Redox Rate Scaling in Naturally Reduced Sediments Yuanyuan Liu, Chongxuan Liu, Ravi Kukkadapu, James McKinley, John M. Zachara, Andrew Plymale, Micah D. Miller, Tamas Varga, and Charles T. Resch Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b03273 • Publication Date (Web): 15 Oct 2015 Downloaded from http://pubs.acs.org on October 18, 2015

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Environmental Science & Technology is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 28

Environmental Science & Technology

1 2

99

3 4

Yuanyuan Liu, Chongxuan Liu*, Ravi K. Kukkadapu, James P. McKinley, John Zachara, Andrew E. Plymale, Micah D. Miller, Tamas Varga, Charles T. Resch

Tc(VII) Retardation, Reduction, and Redox Rate Scaling in Naturally Reduced Sediments

5 6

Pacific Northwest National Laboratory, Richland, WA 99354

7 8 9 10 11 12 13

Submitted to Environmental Science and Technology

14 15 16 17 18 19

Corresponding author, Chongxuan Liu, Pacific Northwest National Laboratory, K8-96,

20

Richland, WA 99354, (509)371-6350, Fax(509)371-6354; email:

21

[email protected]

22 1 ACS Paragon Plus Environment


23

Abstract: An experimental and modeling study was conducted to investigate pertechnetate

24

(Tc(VII)O4-) retardation, reduction, and rate scaling in three sediments from Ringold formation

25

at U.S. Department of Energy’s Hanford site, where 99Tc is a major contaminant in groundwater.

26

Tc(VII) was reduced in all the sediments in both batch reactors and diffusion columns, with a

27

faster rate in a sediment containing a higher concentration of HCl-extractable Fe(II). Tc(VII)

28

migration in the diffusion columns was reductively retarded with retardation degrees correlated

29

with Tc(VII) reduction rates. The reduction rates were faster in the diffusion columns than those

30

in the batch reactors, apparently influenced by the spatial distribution of redox-reactive minerals

31

along transport paths that supplied Tc(VII). X-ray computed tomography and autoradiography

32

were performed to identify the spatial locations of Tc(VII) reduction and transport paths in the

33

sediments, and results generally confirmed the newly found behavior of reaction rate changes

34

from batch to column. The results from this study implied that Tc(VII) migration can be

35

reductively retarded at Hanford site with a retardation degree dependent on reactive Fe(II)

36

content and its distribution in sediments. This study also demonstrated that an effective reaction

37

rate may be faster in transport systems than that in well-mixed reactors.

2 ACS Paragon Plus Environment

Page 2 of 28

Page 3 of 28

38


INTRODUCTION

39

Technetium-99 (99Tc) is a groundwater contaminant with a long radioactive decay half-

40

life (2.13 × 105 years).1 It exists as pertechnetate (TcO4-) in oxic environments.2, 3 Under anoxic

41

conditions, TcO4- can be reduced through both biotic4-14 and abiotic reaction pathways,15-20

42

forming sparingly soluble Tc(IV)O2·nH2O,3, 21 and other poorly crystalized Tc(IV) phases.4, 20, 22-

43

24

44

often dominate Tc(VII) reduction rates.20 Fe(II) is an important reductant for the abiotic Tc(VII)

45

reduction.16, 26 Tc(VII) can be reduced by various Fe(II) species including aqueous Fe(II),17

46

sorbed Fe(II),16, 26 , amorphous Fe(II) gel,27 Fe(II)-containing minerals such as green rust,23

47

magnetite,27-30 pyrite,30, 31siderite,16, 18, 27 vivianite,27 FeS,32-34 FeO,32 and Fe(II)-bearing granite35

48

and phyllosilicates such as montmorillonite, nontronite, rectorite, illite, chlorite, palygorskite.15,

49

26, 27, 36

50

37, 38

51

reduction.16 A kinetic model that integrates the contribution of multiple Fe(II) species is critically

52

needed for describing Tc(VII) reduction in sediments.

53

While biotic and abiotic reaction pathways can coexist in sediments,19, 25 the abiotic pathways

The rates of Tc(VII) reduction, however, vary with the form of Fe(II) species.16, 17, 20, 25, 26,

Different Fe(II) species can co-exist in sediments that may collectively affect Tc(VII)

Tc(VII) reduction is commonly investigated under well-mixed conditions. Limited

54

studies implied that Tc(VII) reduction may have contributed to the retardation of Tc(VII)

55

migration in granite,35, 39 bentonite,40 and deep fracture zone.41 Models to describe Tc(VII)

56

reductive migration have not been well studied. Little is known about the impact of transport on

57

the rate of Tc(VII) reduction and the scaling behavior of the reduction rate from well-mixed to

58

transport systems. Geochemical reaction rates can be affected by heterogeneous mineral

59

distribution in transport systems.42-49 Effective reaction rates may decrease in orders of

60

magnitude from well-mixed to heterogeneous systems.50-57 The decrease in reaction rate,

61

however, depends on specific geochemical reactions, pore structure and connectivity, and 3 ACS Paragon Plus Environment


62

statistical distributions of reactants and their spatial and temporal correlations. Reactive transport

63

studies with microscopic insights are thus needed to understand the Tc(VII) reduction in reactive

64

transport systems and scaling behavior of Tc(VII) reduction rate from well-mixed to transport

65

system.

66

The objectives of this study are to: 1) investigate 99Tc(VII) retardation in natural

67

sediments containing multiple Fe(II) species, 2) develop reactive transport models to describe

68

Tc(VII) reductive migration in the sediments, and 3) evaluate the scaling behavior of Tc(VII)

69

reduction rates from well-mixed to transport systems. The sediments were collected from the

70

Ringold formation at US Department of Energy’s Hanford site where over 400 Ci of 99Tc has

71

been released from radionuclide waste tanks to the vadoze zone at the site (The geology of

72

Hanford site and 99Tc plume profile are provided in SI).16 Currently, the released 99Tc has

73

migrated through the vadoze zone in the Hanford formation.58-60 The Ringold sediments locate

74

below the Hanford formation and contain multiple Fe(II)-containing minerals that can potentially

75

retard Tc migration.16 Batch and diffusion experiments were performed to measure Tc(VII)

76

reduction and retardation, effective kinetic and reactive transport models were evaluated to

77

simulate Tc(VII) reductive migration in the sediments, and the experimental and model results

78

were used to assess the effect of transport on the effective rate of Tc(VII) reduction. Mössbauer

79

spectroscopy, x-ray computed tomography (XCT), autoradiography and scanning electron

80

microscopy (SEM), as well as tracer Br diffusion were performed to provide physical and

81

chemical insights into the Tc(VII) reduction and retardation in the sediments.

82

MATERIALS AND METHODS

83 84

Sediments and Characterization. Sediments used in this study were collected from a 55 m deep borehole (borehole C6209) at depth of 30.8-31.1 m, 39.0-39.3 m and 51.5-51.8 m in the 4 ACS Paragon Plus Environment

Page 4 of 28

Page 5 of 28


85

uncontaminated Ringold formation at the downstream of 99Tc plume at Hanford Site.61 These

86

sediments have different grain size distribution and Fe(II)-content, and were named as sediment

87

A, B and C, respectively hereafter. The collected sediments were stored at -80 oC, and thaw

88

before usage in an anaerobic chamber filled with N2 at room temperature. All experiments were

89

conducted in the anaerobic chamber. The sediments were dried at room temperature to measure

90

moisture content, and then wet-sieved through 2, 0.5 and 0.053 mm meshes to determine the

91

grain size distribution.62 Fe(II) content and mineralogy in the sediments was determined by acid-

92

extraction (0.5 M HCl) and Mössbauer spectroscopy following the methods described

93

elsewhere.26, 63 The details of these methods were provided in supporting information (SI). The

94

Fe(II) contents in the sediments were used as the initial Fe(II) concentrations for both the batch

95

and column experiments.

96

Tc(VII) Reduction In Batch Reactors. Sediments were mixed with 100 mL Hanford

97

synthetic groundwater (SGW)47 containing 10 µM TcO4- in 150 mL serum bottles.

98

Sediment/SGW ratio was varied for different sediments (18-63 g soil/1 L water) with a smaller

99

sediment/SGW ratio for the sediment containing more HCl-extractable Fe(II). The pH of the

100

SGW was stable (8.6 ± 0.1) during the entire experiments. The sediment suspensions were mixed

101

on a shaker at 200 rpm. Periodically, the suspensions were collected and filtered (0.2 µm mixed

102

cellulose ester, MCE, syringe filters), and 0.5 mL filtrate was added to 10 mL Opti-Fluor

103

cocktail (Perkin-Elmer) to quantify Tc(VII) concentration on a Packard 2500TR Scintillation

104

Counter.16 A parallel set of experiments using ground sediments (i.e., the sediments were ground

105

with a agate mortar until passing through 0.5 mm mesh) were also performed and compared with

106

experiments using the pristine sediments to investigate potential Fe(II) reactivity associated with



107

large particles. Ground sediments were used previously to investigate Tc(VII) reduction in

108

sediments.16

109

At the end of the experiments, the residual sediment in the suspension was collected by

110

filtration. The collected sediment (1 g) was mixed with 4 mL DI water for 1 h and then filtered,

111

and Tc in the filtrate was determined. This part of Tc was assumed to be Tc(VII) in the residual

112

sediment.16, 64 The total Tc(IV+VII) concentration in the residual sediment was determined using

113

a strong acid-extraction method (provided in SI) modified from previous studies.65, 66 The

114

insoluble Tc(IV) in the residual sediment was calculated by the difference between total

115

Tc(IV+VII) and Tc(VII) concentrations determined from the strong acid and DI-water extraction

116

methods.

117

Tc Retardation Experiments. Tc retardation in the sediments was assessed using

118

diffusion columns (10 cm long × 2.5 cm inner diameter). The diffusion columns instead of

119

traditional flow-through systems were used to minimize producing large amount of high

120

radioactive wastes. The sediments in the field-collected intact cores (10 cm diameter) were

121

extracted using a soil collection tube (2.5 cm inner diameter). Five replicates were extracted from

122

each intact sediment core, and were immediately transferred to the diffusion columns in the

123

anaerobic chamber for the retardation experiments. The two ends of the columns were equipped

124

with 0.45 µm MCE membranes supported by stainless steel meshes (Fig. SI1). The sediments in

125

the diffusion columns were first saturated with SGW. The porosity (θ) in the columns was

126

calculated as the moisture content in the sediments plus the weight difference before and after

127

water saturation in the columns. The SGW-saturated columns were submerged in 1.5 L SGW

128

containing ~10 µM TcO4- and ~33 mg/L Br- in a 2.7 L Flip-Tite storage tank (Fig. SI1). The bulk

129

solution in the tank was continuously mixed with a magnetic stir bar. Aqueous solution samples


Page 6 of 28

Page 7 of 28


130

(2.4 mL) were periodically collected and filtered to monitor the concentrations of Tc(VII) and

131

Br– (ion chromatography, Dionex ICS-2500). Occasionally, the bulk solution was sampled, and

132

Tc(VII) and Tc(IV) in the samples were separated by adding tetraphenyl arsonium chloride

133

(TPAC), a reagent that selectively forms a complex with Tc(VII), and the formed

134

Tc(VII)−TPAC complex was extracted using chloroform. The Tc in the remaining solution and

135

Tc in the chloroform were determined as Tc(IV) and Tc(VII), respectively. The extraction

136

procedure was described elsewhere14, 20 and provided in SI. Tc(IV) was not detected throughout

137

the experiment in the bulk solution.

138

After 1, 2, 4, and 8 weeks of diffusion, one column for each sediment was retrieved from

139

each bulk solution tank, and the sediment in the column was sectioned to measure the diffusion

140

profiles of dissolved Tc(VII) and Br-, and total Tc(IV+VII) concentrations. To section the

141

sediment, the column was frozen at -35 oC in an anaerobic freezer overnight. The frozen

142

sediments were pushed out and sectioned into 10 to 12 increments along column longitudinal

143

direction. The dissolved Tc(VII) and Br- in the sediment increments were extracted using DI

144

water (SI). Independent measurements and calculations of Tc(VII) sorption to the sediments in

145

the batch reactors indicated that sorbed Tc(VII) was negligible, and DI-extracted Tc was

146

dissolved Tc(VII) in the pore water. The total Tc(IV+VII) concentration in the sediment

147

increments was determined using the strong acid-extraction method. The concentrations of HCl-

148

extractable Fe(II) in the sediments were also measured after 1 and 8 weeks of Tc diffusion and

149

reduction using the Ferrozine method. All the extraction methods were the same as described

150

before.

151 152

After 8 weeks’ diffusion, the sediments in the columns were scanned using XCT (Xtek XT H 320) at voxel resolution of 28 µm.67 Then, the columns were sectioned into five 2-cm



Page 8 of 28

153

increments and embedded in epoxy resin (PELCO 24-Hour Epoxy Mount Kit). The epoxy-

154

embedded sediments were then cut with a diamond saw (TED PELLA) and the surfaces of the

155

cross section were polished and used for digital autoradiography68 and SEM scanning (JEOL

156

6340 field emission SEM with backscattered electron (BSE) detector). The SEM images were

157

used as the reference to superimpose the autoradiography images over the XCT images (Fig. SI2)

158

using Adobe Photoshop to determine residual Tc distribution and its correlation with the

159

distribution of pores/grains in the sediment (Fig. SI2D and Fig. 1E). The details of XCT and

160

digital autoradiography analysis were provided in SI. Multi-Rate Reaction Model. The reduction of TcO4- by sediment-associated Fe(II) is

161 162

generally described using the following reaction:25, 36 TcO4- + 3Fe(II)−sediment → TcO2·nH2O(s) + 3Fe(III)−sediment

163 164

1)

The rate of Tc(VII) reduction may be described using a 2nd order rate expression:28

r=

165

∂CTc (VII ) ∂t

N

i = −∑ piα i C Fe ( II ) CTc (VII ) i =1

2)

166

i where αi and C Fe ( II ) are the rate constant and reactive Fe(II) concentration at rate site i; CTc(VII) is

167

the aqueous concentration of TcO4-, pi is the fraction of rate site with rate constant αi, and N is

168

the number of rate sites. Modeling effort as described in the result section indicated that a single

169

rate model (i.e., N =1 and pi = 1 in Eq 2) was not able to describe Tc(VII) reduction in the

170

sediments. Consequently the multi-rate reaction model (Eq 2)51, 69 was adopted in this study to

171

account for the potential roles of multiple Fe(II)-minerals in the sediments for reducing Tc(VII).

172

To minimize the number of fitting parameters, the rate constants αi (i = 1, 2, … , N) were

173

assumed to follow a lognormal probability distribution.69

p(α ) =

174

1  (ln α − µ ) exp − 2 2π ασ  2σ  1

3)

175

where p(α) is the probability density function of a rate site which has a corresponding rate

176

constant of α; parameters µ and σ are the mean and deviation defining the probability function.

177

Once µ and σ are known, the rate constants can be calculated from the probability function (Eq

178

3). 8 ACS Paragon Plus Environment

Page 9 of 28


179

The initial reactive Fe(II) concentration at each reduction site was assumed to be

180

proportional to the site density (pi in Eq 2). HCl-extractable Fe(II) was used as the initial reactive

181

Fe(II) concentration, which was later adjusted to match experimental results.

182 183

Reductive Diffusion Model. A dual domain diffusion model in linking with Tc(VII) reduction was used to describe Tc(VII) migration in the diffusion columns:69

∂C jf 184

∂t

=

i= N ∂C jf  θ s ∂  Df − ω C jf − C sj + ∑ν ji ri f ∂x  ∂x  θ f i =1  

(

s i=N ∂  ∂C j  = Ds + ω C jf − C sj + ∑ν ji ris ∂t ∂x  ∂x  i =1  

∂C sj 185

186

)

V

(

 ∂C jf = 2n  Aθ f D f  ∂t ∂x 

∂C bj

x =0 + Aθ s Ds

)

∂C sj x =0

∂x

  

4)

5)

6)

187

where the superscript and subscript “f”, “s” and “b” denotes the fast diffusion domain, slow

188

diffusion domain and bulk solution, respectively, V (m3) is the volume of the bulk solution, A

189

(m2) is the area of the column cross section, D (m2/h) is the effective diffusion coefficient, θ is the

190

porosity, ω (h-1) is mass transfer coefficient between the fast and slow diffusion domains, vji is

191

the stoichiometric coefficient of chemical component j in Tc(VII) reduction reaction at rate site i

192

(ri, Eq 1), n is the number of columns in contact with the same bulk solution, and number 2

193

before n in Eq 6 accounts for diffusion from two ends of each column. Aqueous species (Br- and

194

TcO4-) and solid species (sediment-associated Fe(II) and TcO2·nH2O(s)) were considered in the

195

modeling. By ignoring the reaction term, the model can be used to describe Br- diffusion. By

196

setting θs to zero and ignoring equation 5, the dual-domain model becomes a single-domain

197

model. Modeling results, however, found that the single-domain diffusion model failed to

198

simultaneously describe the measured Br- concentration profiles obtained at different times for



199

each sediment (Fig. SI3). Consequently, a dual domain model was adopted here to describe Br

200

diffusion in the columns.

201

RESULTS AND DISCUSSION

202

Sediment Properties. Grain size distribution and Fe(II) mineralogy vary among the three

203

sediments used in the experiments (Table 1 and Fig. SI4). All the sediments are, however,

204

dominated by C>B, and silt/clay size fraction is in the reverse order. The mineralogy in

206

sediments A and C is dominated by quartz, cristobalite, and feldspar, with minor Fe(II)-

207

containing minerals including siderite, magnetite, Fe(II)-pyroxene, and Fe(II)-phyllosilicates.

208

Sediment A also contains trace amount of pyrite. The mineralogy of sediment B is dominated by

209

quartz and feldspar, with minor magnetite and Fe(II)-phyllosilicates. All the Fe(II)-containing

210

minerals in the sediments can potentially reduce Tc(VII).17, 38, 70 The amount of HCl-extractable

211

Fe(II) follows the decreasing order of sediment A>C>B, showing that a sediment with more finer

212

grain materials contains less HCl-extractable Fe(II) in the sediments.

213

Tc(VII) Reduction in Well-mixed Reactors. Tc(VII) concentrations slowly decreased

214

with time in all the sediment suspensions (Fig. 2A-C, circles). Extraction analysis of the

215

sediments after batch experiments using DI water and strong acid extraction indicated that >97%

216

of solid phase Tc existed as sparingly soluble Tc(IV). The reduction rate was relatively faster

217

initially and decreased with time in all the sediments, and was faster in the sediment containing a

218

higher HCl-extractable Fe(II) (sediment A>C>B). Sediment grinding enhanced Tc(VII)

219

reduction in the first 2 to 3 days, indicating that the fresh surface areas created by grinding the

220

large particles (>0.5mm) were more reactive to Tc(VII) reduction. After 2 to 3 days, however,

221

the reduction rates slowed in all the sediments and were in approximately parallel to those 10 ACS Paragon Plus Environment

Page 10 of 28

Page 11 of 28


222

without grinding, indicating that the new reactive surface area generated by the grinding was

223

small. The faster rate in the ground sediments was consistent with the previous observations

224

using the ground materials.16

225

Tc(VII) Reduction in Diffusion Columns. In this study, the diffusion profiles of Br

226

and Tc in the left half and right half of the columns were treated as replicates. Figure 3 showed

227

their averaged concentrations and variations as a function of distance from the bulk solution

228

toward the column center. Tc(VII) diffusion profiles (Fig. 3A2-C2) were steeper than tracer Br-

229

profiles (Fig. 3A1-C1), indicating Tc(VII) diffusion was retarded in all the sediments. The

230

retardation was stronger in the sediment with a faster reaction rate (A>C>B). The total

231

Tc(IV+VII) concentrations (Fig. 3A3-C3) had relatively steeper diffusion profiles as compared

232

to Tc(VII) as a result of local Tc(VII) reduction and Tc(IV) accumulation along diffusion paths.

233

Locations near the bulk solution had higher Tc(VII) concentrations and longer duration of

234

Tc(VII) contact with sediment-associated Fe(II), leading to higher Tc(IV) concentrations, and

235

steeper total Tc(IV+VII) concentration profile. The total Tc concentrations had larger variations

236

as compared to the dissolved Tc(VII) profiles, apparently caused by the heterogeneity of the

237

sediment redox properties that affected local Tc(VII) reduction rate and Tc(IV) accumulation

238

along the diffusion paths. Most of the Tc along the diffusion paths was associated with the solid

239

phase, given that the highest possible concentration of Tc(VII) in the pore water (i.e., 10 µM)

240

was equivalent to only 0.002-0.003 µmol/g after normalizing to sediment mass. The total Tc

241

concentrations in the sediments were much lower than the HCl-extractable Fe(II) concentrations.

242

As a result, the HCl-extractable Fe(II) concentration profiles had no detectable change during 8

243

weeks of experimental duration (Fig. 3D3). The Tc(VII) diffusion and reduction in the sediments

244

led to the decrease in Tc(VII) concentration in the bulk solutions (Fig. 3D2). Compared with Br-



245

concentration, the decrease in Tc(VII) concentration in the bulk solution was much faster as a

246

result of faster diffusion into the columns forced by the steeper concentration gradient at the bulk

247

solution side (Fig. 3A2-C2). As expected, Tc(VII) concentrations in the bulk solution decreased

248

more quickly for the sediment with a faster Tc(VII) reduction rate (A>C>B).

249

Modeling. The batch results (Fig. 2) were used to estimate rate constants in Eq 2 for

250

Tc(VII) reduction by the sediments. The Br- data (Fig. 3A1-D1) were used to determine physical

251

transport parameters in the columns. These parameters were used in the reactive diffusion model

252

(Eq 4-6) to predict Tc(VII) reductive diffusion in the columns. The measured column data (Fig.

253

3A2-D2 and Fig. 3A3-C3) were used to evaluate the model prediction and rate changes from the

254

well-mixed to diffusion systems.

255

The Tc(VII) reduction in the batch reactors was well described using the multi-rate model

256

(Fig. 2A-C) with fitted rate parameters (µ and σ) provided in Table 1. A single rate model,

257

which assumes that each sediment contains only one reactive Fe(II) mineral or site, was tried and

258

found not able to simultaneously describe Tc(VII) reduction in all three sediments (Fig. SI5).

259

The multi-rate model was then adopted by considering that the sediments contain multiple

260

reactive sites contributed from different Fe(II)-containing minerals (Table 1). The multi-rate

261

model did not distinguish whether the reactive sites were contributed from different surfaces on

262

individual minerals or from different Fe(II)-containing minerals. The total reactive Fe(II)

263

଴ concentration (‫ܥ‬ி௘(ூூ) ), which was initially assumed to be the HCl-extractable Fe(II) (Table 1),

264

was adjusted to match the Tc(VII) reduction profile for each sediment. The fitted reactive Fe(II)

265

concentrations were 0.20, 0.03, and 0.09 µmol/g for sediment A, B, and C, respectively, which

266

were much smaller than the HCl-extractable Fe(II) in the sediments. The result indicated that

267

most HCl-extractable Fe(II) was not reactive toward Tc(VII) reduction. However, the fitted


Page 12 of 28

Page 13 of 28


268

reactive Fe(II) concentration was positively correlated with the HCl-extractable Fe(II)

269

concentration in the sediments (i.e., sediment A>C>B). Using the estimated rate parameters (µ

270

and σ), the second-order rate constants were calculated using Eq 3. The rate constants calculated

271

using the estimated rate parameters (µ and σ, Eq 3) had a wide distribution (Fig. SI5, A3−C3),

272

with a mean of 6.5×10-4, 5.1×10-4, and 6.8×10-5 µM-1·h-1 for sediment A, B, and C, respectively.

273

Tc(VII) reduction not only depended on rate constant, but also Fe(II) concentration (Eq 2). The

274

much higher Fe(II) concentration in sediment C led to a higher effective Tc(VII) reduction rate

275

in sediment C than that in sediment B.

276

The smaller rate constants in the rate constant distribution profiles (Fig. SI5) are not

277

reliable because these rate sites did not have time to contribute to Tc(VII) reduction during the

278

batch experiment duration. A previous statistical analysis indicated that only larger rate constants

279

can be reliably estimated.71 Grinding sediments consistently shifted those larger rate constants

280

toward right (Fig. SI5) and resulted in a higher mean of rate constants (8.5×10-3, 2.9×10-3, and

281

1.2×10-3 µM-1·h-1 for sediment A, B, and C, respectively).

282

XCT results (Fig. 1D) revealed that the sediment in each column had a complex pore

283

structure. Some pores are well connected and others are not, suggesting that a dual or multiple

284

domain diffusion model is needed to fully describe the tracer transport. The dual-domain

285

diffusion model, which considers a fast domain to represent transport in well-connected pores

286

and a slow domain to represent transport in not well-connected pores,48, 50, 72 provided a good

287

description of the experimental results of Br- diffusion (Fig. 3A1-D1). The estimated values of Df

288

in the fast diffusion domain (Table 1) were comparable to the reported apparent diffusion

289

coefficients in soils with similar water content: 2.3-6.5×10-6 m2·h-1 at θ = 0.41-0.56.73 The fitted

290

diffusion coefficient in the slow diffusion domain was comparable to matrix diffusion coefficient



291

in soils and sediments: 1.1×10-8 m2·h-1.72 These parameters in the dual diffusion domain model

292

were used to predict Tc(VII) reductive diffusion transport in the columns.

293

Predicting Tc(VII) Reductive Diffusion. The results simulated using the reductive

294

diffusion model with the rate parameters independently determined from the batch reactors and

295

physical transport parameters from Br- diffusion profiles generally matched with the

296

experimental results of Tc(VII) profiles in the columns (Fig. 3A2-D2, and Fig.3A3-C3). The

297

minor variation in diffusion profiles with time was attributed to large Fe(II) availability relative

298

to Tc(VII) in the diffusion columns, leading to a quasi-steady-state of Tc(VII) supply and

299

reduction at the local scale. Discrepancy, however, existed. In the bulk solutions, Tc(VII)

300

concentrations were slightly over-predicted for all three sediments. In the pore water, Tc(VII)

301

concentrations matched well with the experimental results for sediments A and B for the first 4

302

weeks, but were slightly over-predicted at the 8th week. For sediment C, Tc(VII) concentrations

303

were over-predicted at all the time. The discrepancy between the predicted and measured total

304

Tc(IV+VII) was not obvious due to the large data variability as discussed before. The over-

305

prediction of Tc(VII) concentrations in both the bulk solution and pore water indicated that the

306

rate of Tc(VII) reduction in the columns was under-predicted, and was faster than that estimated

307

from the batch reactors. Using sediment C as an example, the multi-rate reaction parameters µ

308

and σ were refitted to match the Tc(VII) concentrations in the bulk solution and in the pore water

309

(Fig. SI6). The fitted rate constants were larger than those estimated from the well-mixed batch

310

reactor (Fig. SI6D); and the mean of the fitted rate constants was three times larger than that

311

estimated from well-mixed system (2.3×10-4 vs. 6.8×10-5 µM-1·h-1). The larger rate constants

312

estimated from the transport system is contradictory to the general trend of rate constant changes


Page 14 of 28

Page 15 of 28


313

in other rate scaling observations,51-54, 74 where the reaction rates in columns were smaller than in

314

batch reactors due to the pore-scale mass transfer effect.

315

A recent study,44 however, established the following mathematical relationship that links

316

the rate constants derived from the well-mixed to those in the transport systems after modified

317

for Tc(VII) reduction case (SI Eq 1-7): 

318

α ieff = α iins 1 +  

i ′   CT O − ′  CFe ( II )  1 + c 4  i CFe ( II )   CTcO4−   

7)

319

where αieff and α iins are the effective rate constant in transport and well-mixed systems,

320

respectively , Ci is the pore scale concentrations of reactive Fe(II) and Tc(VII), overhead bars

321

represent average operation over a certain volume of porous media in the transport system, and C’

322

denotes the relative deviation of the pore-scale concentration from their average value. Eq 7

323

indicated that if pore scale concentrations of reactive Fe(II) and Tc(VII) were positively

324

correlated, the effective rate in the transport system can be larger than that estimated from the

325

batch reactor. The results from Tc(VII) reactive transport in sediment C apparently reflected this

326

scenario, likely resulting from the preferential association of reactive Fe(II) with the faster

327

diffusion paths so that the rate constants became larger in the column systems.

328

Microscopic Insights: XCT and autoradiography images were superimposed to identify

329

the spatial correlation between Tc(VII) reduction locations and well-connected pore paths in

330

sediments to provide insights into the rate scaling behavior as discussed above (Fig. 1E and F).

331

Overlapping XCT and autoradiography images found that Tc, showing as bright spots, was

332

accumulated at the locations where coarse/medium sand (~0.5 mm) and well-connected pores

333

concurrently existed (red squares). These accumulated Tc was attributed to Tc(IV) as a result of

334

local Tc(VII) reduction by sediment-associated Fe(II), and consequently was indicative of



335

reactive Fe(II) locations. Little Tc was detected at the locations where silt/clay co-existed with

336

well-connected pores (Fig. SI7, blue circles) and where coarse sand coexisted with poor-

337

connected pores (Fig. SI7, green circles). Eq 7 indicates that the positive concurrent existence of

338

reactive Fe(II) and well-connected pores will lead to a larger effective rate constant in the

339

columns than that in the well-mixed reactors (Fig. SI6D). Most current studies focused on the

340

effect of transport property distribution on the scaling of reaction rates.44, 49, 75 The result here

341

demonstrated that the correlation of physical transport properties with reactive mineral

342

distributions is more important than the physical distribution only for controlling rate scaling

343

behavior.

344

Environmental Implications. TcO4- is highly mobile in groundwater that poses a long-

345

term health risk to human and ecological lives. Reduction of Tc(VII) to sparingly soluble

346

TcO2.nH2O has been proposed as a technique to remediate, contain, or retard Tc dispersion in

347

subsurface environments.14, 17, 18, 20, 32, 38, 76, 77 This type of techniques typically relied on the

348

injection of chemical reductants or stimulation of microbial activities to enzymatically reduce

349

Tc13, 14, 17, 32 or indirectly reduce Tc by biogenic Fe(II).18, 20 This study demonstrated that 99Tc

350

migration can be reductively retarded by the natural Fe(II)-containing sediments. Although the

351

reactive Fe(II) amount may be much lower than the total Fe(II) in the sediments (Table 1), the

352

vast amount of geological materials can provide a large capacity of reactive Fe(II) retarding Tc

353

migration. As an example, the Tc plume at Hanford site was estimated to be 16 km from the

354

Columbia River with a cross section of 10,000 m2.78 Ignoring dispersion, the reactive Fe(II) on

355

the path of the plume to Columbia River was estimated to be 9 × 105 – 6 × 106 kg based on the

356

estimated reactive Fe(II) content in the three sediments (Table 1). This amount of reactive Fe(II)

357

can treat 5 × 105 – 3 × 106 kg of Tc, which is equivalent to 9 × 106 – 6 × 107 Ci of 99Tc. Using


Page 16 of 28

Page 17 of 28


358

the averaged Fe(II) concentration and rate constants, the Damköhler number ( Da = kCFe0 ( II )τ ) was

359

estimated to be 7.4×104 – 1.6×106 in the Ringold formation. The large Damköhler number and a

360

large capacity of reactive Fe(II) implied that Tc will be strongly retarded once entering into the

361

geological formation.

362

This study also revealed that the effective rate constants of Tc reduction may be larger

363

than those estimated from the batch reactor. The large rate in the sediments would enhance the

364

retardation of Tc migration. Most current studies indicated that reaction rate constants would

365

decrease with increasing scale.50-57 The result in this study implied that effective rate or rate

366

constants may increase or decrease with scale depending on the correlation between reactive

367

sites or hot spots and preferential transport paths.

368

ACKNOWLEDGEMENT

369

This research is supported by the U.S. DOE, Office of Science, Biological and Environmental

370

Research (BER) as part of the Subsurface Biogeochemical Research (SBR) Program through

371

Pacific Northwest National Laboratory (PNNL) SBR Science Focus Area (SFA) Research

372

Project. Mössbauer spectroscopy, XCT, Autoradiography and SEM were performed using

373

facilities of the Environmental Molecular Science Laboratory (EMSL), a DOE Office of Science

374

user facility. We also thank the anonymous reviewers for their careful reading and constructive

375

comments.

376

Supporting Information. Additional method details, schematic experimental setup, Mössbauer

377

spectra, single domain and single rate modeling results, dual domain model fitting results, and

378

mathematical calculation for rate scaling theory. This information is available free of charge via

379

the Internet at http://pubs.acs.org/ . 17 ACS Paragon Plus Environment


Page 18 of 28

380

REFERENCES

381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423

1. Zachara, J. M.; Serne, J.; Freshley, M.; Mann, F.; Anderson, F.; Wood, M.; Jones, T.; Myers, D., Geochemical processes controlling migration of tank wastes in Hanford's vadose zone. Vadose Zone J. 2007, 6, (4), 985-1003. 2. Wildung, R. E.; Li, S. W.; Murray, C. J.; Krupka, K. M.; Xie, Y.; Hess, N. J.; Roden, E. E., Technetium reduction in sediments of a shallow aquifer exhibiting dissimilatory iron reduction potential. FEMS Microbiol. Ecol. 2004, 49, (1), 151-162. 3. Wildung, R. E.; McFadden, K. M.; Garland, T. R., Technetium sources and behavior in the environment. J. Environ. Qual. 1979, 8, (2), 156-161. 4. Abdelouas, A.; Fattahi, M.; Grambow, B.; Vichot, L.; Gautier, E., Precipitation of technetium by subsurface sulfate-reducing bacteria. Radiochim. Acta 2002, 90, (9-11), 773-777. 5. Baldwin, B. R.; Peacock, A. D.; Park, M.; Ogles, D. M.; Istok, J. D.; McKinley, J. P.; Resch, C. T.; White, D. C., Multilevel samplers as microcosms to assess microbial response to biostimulation. Ground Water 2008, 46, (2), 295-304. 6. Fredrickson, J. K.; Kostandarithes, H. M.; Li, S. W.; Plymale, A. E.; Daly, M. J., Reduction of Fe(III), Cr(VI), U(VI), and Tc(VII) by Deinococcus radiodurans R1. Appl. Environ. Microbiol. 2000, 66, (5), 2006-2011. 7. Istok, J. D.; Senko, J. M.; Krumholz, L. R.; Watson, D.; Bogle, M. A.; Peacock, A.; Chang, Y. J.; White, D. C., In situ bioreduction of technetium and uranium in a nitratecontaminated aquifer. Environ. Sci. Technol. 2004, 38, (2), 468-475. 8. Liu, C. X.; Gorby, Y. A.; Zachara, J. M.; Fredrickson, J. K.; Brown, C. F., Reduction kinetics of Fe(III), Co(III), U(VI), Cr(VI) and Tc(VII) in cultures of dissimilatory metal-reducing bacteria. Biotechnol. Bioeng. 2002, 80, (6), 637-649. 9. Lloyd, J. R.; Macaskie, L. E., A novel PhosphorImager-based technique for monitoring the microbial reduction of technetium. Appl. Environ. Microbiol. 1996, 62, (2), 578-582. 10. Lloyd, J. R.; Cole, J. A.; Macaskie, L. E., Reduction and removal of heptavalent technetium from solution by Escherichia coli. J. Bacteriol. 1997, 179, (6), 2014-2021. 11. Lloyd, J. R.; Harding, C. L.; Macaskie, L. E., Tc(VII) reduction and accumulation by immobilized cells of Escherichia coli. Biotechnol. Bioeng. 1997, 55, (3), 505-510. 12. Lloyd, J. R.; Ridley, J.; Khizniak, T.; Lyalikova, N. N.; Macaskie, L. E., Reduction of technetium by Desulfovibrio desulfuricans: Biocatalyst characterization and use in a flowthrough bioreactor. Appl. Environ. Microbiol. 1999, 65, (6), 2691-2696. 13. Lloyd, J. R.; Sole, V. A.; Van Praagh, C. V. G.; Lovley, D. R., Direct and Fe(II)mediated reduction of technetium by Fe(III)-reducing bacteria. Appl. Environ. Microbiol. 2000, 66, (9), 3743-3749. 14. Wildung, R. E.; Gorby, Y. A.; Krupka, K. M.; Hess, N. J.; Li, S. W.; Plymale, A. E.; McKinley, J. P.; Fredrickson, J. K., Effect of electron donor and solution chemistry on products of dissimilatory reduction of technetium by Shewanella putrefaciens. Appl. Environ. Microbiol. 2000, 66, (6), 2451-2460. 15. Jaisi, D. P.; Dong, H.; Morton, J. P., Partitioning of Fe(II) in reduced nontronite (NAu-2) to reactive sites: Reactivity in terms of Tc(VII) reduction. Clay Clay Miner. 2008, 56, (2), 175189. 16. Peretyazhko, T. S.; Zachara, J. M.; Kukkadapu, R. K.; Heald, S. M.; Kutnyakov, I. V.; Resch, C. T.; Arey, B. W.; Wang, C. M.; Kovarik, L.; Phillips, J. L.; Moore, D. A., Pertechnetate 18 ACS Paragon Plus Environment

Page 19 of 28

424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469


(TcO4−) reduction by reactive ferrous iron forms in naturally anoxic, redox transition zone sediments from the Hanford site, USA. Geochim. Cosmochim. Acta 2012, 92, (0), 48-66. 17. Zachara, J. M.; Heald, S. M.; Jeon, B.-H.; Kukkadapu, R. K.; Liu, C.; McKinley, J. P.; Dohnalkova, A. C.; Moore, D. A., Reduction of pertechnetate [Tc (VII)] by aqueous Fe (II) and the nature of solid phase redox products. Geochim. Cosmochim. Acta 2007, 71, (9), 2137-2157. 18. Fredrickson, J. K.; Zachara, J. M.; Kennedy, D. W.; Kukkadapu, R. K.; McKinley, J. P.; Heald, S. M.; Liu, C. X.; Plymale, A. E., Reduction of TcO4- by sediment-associated biogenic Fe(II). Geochim. Cosmochim. Acta 2004, 68, (15), 3171-3187. 19. Fredrickson, J. K.; Zachara, J. M.; Plymale, A. E.; Heald, S. M.; McKinley, J. P.; Kennedy, D. W.; Liu, C.; Nachimuthu, P., Oxidative dissolution potential of biogenic and abiogenic TcO2 in subsurface sediments. Geochim. Cosmochim. Acta 2009, 73, (8), 2299-2313. 20. Plymale, A. E.; Fredrickson, J. K.; Zachara, J. M.; Dohnalkova, A. C.; Heald, S. M.; Moore, D. A.; Kennedy, D. W.; Marshall, M. J.; Wang, C.; Resch, C. T.; Nachimuthu, P., Competitive reduction of pertechnetate (99TcO4−) by dissimilatory metal reducing bacteria and biogenic Fe(II). Environ. Sci. Technol. 2011, 45, (3), 951-957. 21. Meyer, R. E.; Arnold, W. D.; Case, F. I.; Okelley, G. D., Solubilities of Tc(IV) oxides. Radiochim. Acta 1991, 55, (1), 11-18. 22. Eagling, J.; Worsfold, P. J.; Blake, W. H.; Keith-Roach, M. J., Mobilization of technetium from reduced sediments under seawater inundation and intrusion scenarios. Environ. Sci. Technol. 2012, 46, (21), 11798-11803. 23. Pepper, S. E.; Bunker, D. J.; Bryan, N. D.; Livens, F. R.; Charnock, J. M.; Pattrick, R. A. D.; Collison, D., Treatment of radioactive wastes: An X-ray absorption spectroscopy study of the reaction of technetium with green rust. J. Colloid. Interf. Sci. 2003, 268, (2), 408-412. 24. Lee, J.-H.; Zachara, J. M.; Fredrickson, J. K.; Heald, S. M.; McKinley, J. P.; Plymale, A. E.; Resch, C. T.; Moore, D. A., Fe(II)- and sulfide-facilitated reduction of 99Tc(VII)O4- in microbially reduced hyporheic zone sediments. Geochim. Cosmochim. Acta 2014, 136, 247-264. 25. Peretyazhko, T.; Zachara, J. M.; Heald, S. M.; Jeon, B. H.; Kukkadapu, R. K.; Liu, C.; Moore, D.; Resch, C. T., Heterogeneous reduction of Tc(VII) by Fe(II) at the solid–water interface. Geochim. Cosmochim. Acta 2009, 72, (6), 1521-1539. 26. Peretyazhko, T.; Zachara, J. M.; Heald, S. M.; Kukkadapu, R. K.; Liu, C.; Plymale, A. E.; Resch, C. T., Reduction of Tc(VII) by Fe(II) sorbed on Al (hydr)oxides. Environ. Sci. Technol. 2008, 42, (15), 5499-5506. 27. McBeth, J. M.; Lloyd, J. R.; Law, G. T. W.; Livens, F. R.; Burke, I. T.; Morris, K., Redox interactions of technetium with iron-bearing minerals. Mineral. Mag. 2011, 75, (4), 24192430. 28. Cui, D.; Eriksen, T. E., Reduction of pertechnetate in solution by heterogeneous electron transfer from Fe (II)-containing geological material. Environ. Sci. Technol. 1996, 30, (7), 22632269. 29. Farrell, J.; Bostick, W. D.; Jarabek, R. J.; Fiedor, J. N., Electrosorption and reduction of pertechnetate by anodically polarized magnetite. Environ. Sci. Technol. 1999, 33, (8), 1244-1249. 30. Geraedts, K.; Bruggeman, C.; Maes, A.; Van Loon Luc, R.; Rossberg, A.; Reich, T., Evidence for the existence of Tc(IV) – humic substance species by X-ray absorption near-edge spectroscopy. Radiochim. Acta 2002, 90, (12/2002), 879. 31. Maes, A.; Geraedts, K.; Bruggeman, C.; Vancluysen, J.; Rossberg, A.; Hennig, C., Evidence for the interaction of technetium colloids with humic substances by X-ray absorption spectroscopy. Environ. Sci. Technol. 2004, 38, (7), 2044-2051. 19 ACS Paragon Plus Environment


470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515

Page 20 of 28

32. Fan, D.; Anitori, R. P.; Tebo, B. M.; Tratnyek, P. G.; Pacheco, J. S. L.; Kukkadapu, R. K.; Engelhard, M. H.; Bowden, M. E.; Kovarik, L.; Arey, B. W., Reductive sequestration of pertechnetate (99TcO4-) by nano zerovalent iron (nZVI) transformed by abiotic sulfide. Environ. Sci. Technol. 2013, 47, (10), 5302-5310. 33. Liu, Y.; Terry, J.; Jurisson, S., Pertechnetate immobilization with amorphous iron sulfide. Radiochim. Acta 2008, 96, (12), 823-833. 34. Wharton, M. J.; Atkins, B.; Charnock, J. M.; Livens, F. R.; Pattrick, R. A. D.; Collison, D., An X-ray absorption spectroscopy study of the coprecipitation of Tc and Re with mackinawite (FeS). Appl. Geochem. 2000, 15, (3), 347-354. 35. Liu, D.; Fan, X.; Yao, J., Diffusion of 99Tc in granite under aerobic and anoxic conditions. J. Radioanal. Nucl. Chem. 2006, 268, (3), 481-484. 36. Bishop, M. E.; Dong, H.; Kukkadapu, R. K.; Liu, C.; Edelmann, R. E., Bioreduction of Fe-bearing clay minerals and their reactivity toward pertechnetate (Tc-99). Geochim. Cosmochim. Acta 2011, 75, (18), 5229-5246. 37. Jaisi, D. P.; Dong, H.; Plymale, A. E.; Fredrickson, J. K.; Zachara, J. M.; Heald, S.; Liu, C., Reduction and long-term immobilization of technetium by Fe(II) associated with clay mineral nontronite. Chem. Geol. 2009, 264, (1–4), 127-138. 38. Kobayashi, T.; Scheinost, A. C.; Fellhauer, D.; Gaona, X.; Altmaier, M., Redox behavior of Tc(VII)/Tc(IV) under various reducing conditions in 0.1 M NaCl solutions. Radiochim. Acta 2013, 101, (5), 323-332. 39. Kumata, M.; Vandergraaf, T. T., Technetium behavior under deep geological conditions. Radioact. Waste Manag. 1993, 17, (2), 107-117. 40. Rameback, H.; Albinsson, Y.; Skalberg, M.; Eklund, U. B.; Kjellberg, L.; Werme, L., Transport and leaching of technetium and uranium from spent UO2 fuel in compacted bentonite clay. J. Nucl. Mater. 2000, 277, (2-3), 288-294. 41. Byegard, J.; Albinsson, Y.; Skarnemark, G.; Skalberg, M., Field and laboratory studies of the reduction and sorption of technetium(VII). Radiochim. Acta 1992, 58-9, 239-244. 42. Benner, S. G.; Hansel, C. M.; Wielinga, B. W.; Barber, T. M.; Fendorf, S., Reductive dissolution and biomineralization of iron hydroxide under dynamic flow conditions. Environ. Sci. Technol. 2002, 36, (8), 1705-1711. 43. Liu, C.; Shang, J.; Shan, H.; Zachara, J. M., Effect of subgrid heterogeneity on scaling geochemical and biogeochemical reactions: A case of U(VI) desorption. Environ. Sci. Technol. 2014, 48, (3), 1745-1752. 44. Liu, C.; Liu, Y.; Kerisit, S.; Zachara, J., Pore scale process coupling and effective surface reaction rates in heterogeneous subsurface materials. Rev. Mineral. Geochem. 2015, 80, 191-216. 45. Maher, K.; Steefel, C. I.; DePaolo, D. J.; Viani, B. E., The mineral dissolution rate conundrum: Insights from reactive transport modeling of U isotopes and pore fluid chemistry in marine sediments. Geochim. Cosmochim. Acta 2006, 70, (2), 337-363. 46. Malmstrom, M. E.; Destouni, G.; Martinet, P., Modeling expected solute concentration in randomly heterogeneous flow systems with multicomponent reactions. Environ. Sci. Technol. 2004, 38, (9), 2673-2679. 47. Shang, J.; Liu, C.; Wang, Z.; Zachara, J. M., Effect of grain size on uranium (VI) surface complexation kinetics and adsorption additivity. Environ. Sci. Technol. 2011, 45, (14), 60256031. 48. Shang, J.; Liu, C.; Wang, Z.; Zachara, J., Long-term kinetics of uranyl desorption from sediments under advective conditions. Water Resour. Res. 2014, 50, (2), 855-870. 20 ACS Paragon Plus Environment

Page 21 of 28

516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560


49. Zhang, C.; Liu, C.; Shi, Z., Micromodel investigation of transport effect on the kinetics of reductive dissolution of hematite. Environ. Sci. Technol. 2013, 47, (9), 4131-4139. 50. Lichtner, P. C.; Kang, Q., Upscaling pore-scale reactive transport equations using a multiscale continuum formulation. Water Resour. Res. 2007, 43, (12), W12S15. 51. Liu, C.; Shang, J.; Kerisit, S.; Zachara, J. M.; Zhu, W., Scale-dependent rates of uranyl surface complexation reaction in sediments. Geochim. Cosmochim. Acta 2013, 105, (0), 326-341. 52. Maher, K., The dependence of chemical weathering rates on fluid residence time. Earth Planet. Sci. Lett. 2010, 294, (1–2), 101-110. 53. Meile, C.; Tuncay, K., Scale dependence of reaction rates in porous media. Adv. Water Resour. 2006, 29, (1), 62-71. 54. Miller, A. W.; Rodriguez, D. R.; Honeyman, B. D., Upscaling sorption/desorption processes in reactive transport models to describe metal/radionuclide transport: A critical review. Environ. Sci. Technol. 2010, 44, (21), 7996-8007. 55. Navarre-Sitchler, A.; Brantley, S., Basalt weathering across scales. Earth Planet. Sci. Lett. 2007, 261, (1), 321-334. 56. Swoboda-Colberg, N. G.; Drever, J. I., Mineral dissolution rates in plot-scale field and laboratory experiments. Chem. Geol. 1993, 105, (1-3), 51-69. 57. Li, L.; Peters, C. A.; Celia, M. A., Upscaling geochemical reaction rates using pore-scale network modeling. Adv. Water Resour. 2006, 29, (9), 1351-1370. 58. Murray, C. J.; Bott, Y.-J. Spatial analysis of contaminants in 200 west area groundwater in support of the 200-ZP-1 operable unit pre-conceptual remedy design; Pacific Northwest National Laboratory (PNNL), Richland, WA (US): 2008. 59. Serne, R. J.; Bjornstad, B. N.; Horton, D. G.; Lanigan, D. C.; Lindenmeier, C. W.; Lindberg, M. J.; Clayton, R. E.; LeGore, V. L.; Geiszler, K. N.; Baum, S. R. Characterization of vadose zone sediments below the T tank farm: Boreholes C4104, C4105, 299-W10-196 and RCRA borehole 299-W11-39; Pacific Northwest National Laboratory (PNNL), Richland, WA (US): 2004. 60. Serne, R. J.; Bjornstad, B. N.; Horton, D. G.; Lanigan, D. C.; Lindenmeier, C. W.; Lindberg, M. J.; Clayton, R. E.; LeGore, V. L.; Orr, R. D.; Kutnyakov, I. V., Characterization of vadose zone sediments below the TX tank farm: Boreholes C3830, C3831, and C3832 and RCRA borehole 299-W10-27. Pacific Northwest National Laboratory (PNNL), Richland, WA (US): 2004. 61. Bjornstad, B. N.; Horner, J. A.; Vermeul, V. R.; Lanigan, D. C.; Thorne, P. D. Borehole completion and conceptual hydrogeologic model for the IFRC well field, 300 Area, Hanford site: Integrated Field Research Challenge Project; Pacific Northwest National Laboratory (PNNL), Richland, WA (US): 2009. 62. Stoliker, D. L.; Liu, C.; Kent, D. B.; Zachara, J. M., Characterizing particle-scale equilibrium adsorption and kinetics of uranium(VI) desorption from U-contaminated sediments. Water Resour. Res. 2013, 49, (2), 1163-1177. 63. Rancourt, D. G.; Ping, J. Y., Voigt-based methods for arbitrary-shape static hyperfine parameter distributions in Mössbauer spectroscopy. Nucl. Instr. Meth. Phys. Res. B 1991, 58, (1), 85-97. 64. Liu, J.; Pearce, C. I.; Qafoku, O.; Arenholz, E.; Heald, S. M.; Rosso, K. M., Tc(VII) reduction kinetics by titanomagnetite (Fe3−xTixO4) nanoparticles. Geochim. Cosmochim. Acta 2012, 92, (0), 67-81.



561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593

65. Zhao, Y.; Guo, Z.; Xu, J., 99TcO4− diffusion and sorption in compacted GMZ bentonite studied by capillary method. J. Radioanal. Nucl. Chem. 2013, 298, (1), 147-152. 66. Abdelouas, A.; Grambow, B.; Fattahi, M.; Andres, Y.; Leclerc-Cessac, E., Microbial reduction of 99Tc in organic matter-rich soils. Sci. Total Environ. 2005, 336, (1-3), 255-268. 67. Yang, X.; Liu, C.; Shang, J.; Fang, Y.; Bailey, V. L., A unified multiscale model for pore-scale flow simulations in soils. Soil Sci. Soc. Am. J. 2014, 78, (1), 108-118. 68. McKinley, J. P.; Zachara, J. M.; Smith, S. C.; Liu, C., Cation exchange reactions controlling desorption of 90Sr2+ from coarse-grained contaminated sediments at the Hanford site, Washington. Geochim. Cosmochim. Acta 2007, 71, (2), 305-325. 69. Liu, C.; Zachara, J. M.; Qafoku, N. P.; Wang, Z., Scale-dependent desorption of uranium from contaminated subsurface sediments. Water Resour. Res. 2008, 44, (8), W08413. 70. DeLaune, R.; Reddy, K., Redox potential. Encyclopedia of Soils in the Environment 2005, 3, 366-371. 71. Zhang, X.; Liu, C.; Hu, B. X.; Zhang, G., Uncertainty analysis of multi-rate kinetics of uranium desorption from sediments. J. Contam. Hydrol. 2014, 156, 1-15. 72. Hay, M. B.; Stoliker, D. L.; Davis, J. A.; Zachara, J. M., Characterization of the intragranular water regime within subsurface sediments: Pore volume, surface area, and mass transfer limitations. Water Resour. Res. 2011, 47, (10), W10531. 73. Shackelford, C. D.; Daniel, D. E., Diffusion in saturated soil. I: Background. J. Geotech. Eng. 1991, 117, (3), 467-484. 74. White, A. F.; Brantley, S. L., The effect of time on the weathering of silicate minerals: why do weathering rates differ in the laboratory and field? Chem. Geol. 2003, 202, (3), 479-506. 75. Liu, Y.; Liu, C.; Zhang, C.; Yang, X.; Zachara, J. M., Pore and continuum scale study of the effect of subgrid transport heterogeneity on redox reaction rates. Geochim. Cosmochim. Acta 2015, 163, (0), 140-155. 76. Blowes, D. W.; Ptacek, C. J.; Benner, S. G.; McRae, C. W. T.; Bennett, T. A.; Puls, R. W., Treatment of inorganic contaminants using permeable reactive barriers. J. Contam. Hydrol. 2000, 45, (1-2), 123-137. 77. Cui, D. Q.; Eriksen, T., Reactive transport of Sr, Cs and Tc through a column packed with fracture-filling material. Radiochim. Acta 1998, 82, 287-292. 78. Freedman, V. L.; Williams, M. D.; Cole, C. R.; White, M. D.; Bergeron, M. P. 2002 initial assessments for B–BX-BY field investigation report (FIR): Numerical simulations; Pacific Northwest National Laboratory (PNNL), Richland, WA (US): 2002.

594 595


Page 22 of 28

Page 23 of 28

596 597

598 599 600 601 602 603 604 605 606 607 608 609


Table 1. Properties of the sediments, parameters for the multi-rate reduction kinetic model, column porosities, and parameters for the reactive transport model. 30.8-31.1 m 39.0-39.3 m 51.5-51.8 m a Prodominant Mineralogy Q, Cri, F Q, F Q, Cri, F, Cal, H, M S; M; S; M; Pyr Fe(II); Pyro Fe(II) & Fe(III); M; Iron phases b Pyro Fe(II) & Fe(III); PS Fe(II) & Fe(III); PS Fe(II) & Fe(III) G, M(t+o), I, H and PS Fe(II) & Fe(III) sp-oxide Fe(III) Fe(II)HCl (µmol/g) c 287.8 ± 22.3 52.6 ± 5.3 156.3 ± 37.0 < 0.053 mm 34.8% 57.8% 40.7% Wet 0.053 – 0.5 mm 52.2% 28.7% 26.1% Sieving Size mass 0.5 – 2 mm 13.0% 9.8% 17.6% fraction d > 2 mm 0% 3.7% 15.6% ଴ ‫ܥ‬ி௘(ூூ) (µmol/g) 0.20 0.03 0.09 µp -8.8 -8.5 -9.9 σ 1.8 1.4 0.8 Reaction rate p -1 -1 -4 -4 6.5×10 5.1×10 6.8×10-5 parameters (µM ·h ) ଴ from batch ‫ܥ‬ி௘(ூூ) (µmol/g) 0.23 0.05 0.13 e reactors µg -9.6 -8.5 -9.9 3.6 2.5 2.8 σg -1 -1 -3 -3 (µM ·h ) 8.5×10 2.9×10 1.2×10-3 Column Porosity θ 0.418 0.564 0.440 θf 0.251 0.395 0.220 θs 0.167 0.169 0.220 Transport Df (m2·h-1) parameters in 3.7×10-6 1.5×10-6 3.4×10-6 the columns f Ds (m2·h-1) 7.5×10-8 7.5×10-9 5.0×10-8 ω (h-1) 0.0001 0.00015 0.00006 a

: Data from previous X-ray Diffraction (XRD) analysis: Q is quartz; Cri is cristobalite; F is feldspar; Cal is calcite; H is hematite; and M is magnetite.15 b : Iron phases were characterized by Mössbauer spectroscopy: G is goethite, H is hematite, I is ilmenite (FeTiO3), M is magnetite, M(t+o) is tetrahedral and octahedral Fe in magnetite, S is siderite, PS is phyllosilicate or clay Fe, Pyr is pyrite, and Pyro is M1 and M2 non-equivalent Fe(II) sites in pyroxene. c : Mean and standard deviations of HCl-extractable Fe(II) content for triplicate experiments. d : Wet sieving size distribution fractions in weight. e : The parameters were fitted from Tc(VII) reduction in the batches by multi-rate reaction model. The subscript “p” and “g” referred to experiments with pristine and ground sediments, respectively. is the mean of reaction rates. f : The parameters were fitted from Br- diffusion in the columns by dual-domain diffusion model.



610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649

A) Sed. A

C) Sed. C

B) Sed. B

D) Pores for sed. C

Page 24 of 28

8

1

7

3

Well-connected pores

9

4 Poor-connected pores

10 5 2

6

0.5 mm

E) XCT and autoradiography for sed. C

0.5 mm F) XCT for sed. C Figure 1. XCT images (top three named A, B, and C) are the cross sections in the columns (diameter of 2.54 cm) packed with sediments from depths of 30.8 − 31.1 m (A), 39.0 − 39.3 m (B), and 51.5 − 51.8 m (C). Binary image (image D and F) illustrates the distribution of pore spaces in the sediment (showing example for the sediment from 51.5 − 51.8 m), where yellow denotes pores and grey indicates the mixture of solids and fine pores as identified by XCT. Image E is the superimposed XCT and autoradiography images of the sediment from 51.5 − 51.8 m depth, showing Tc as bright spots (in image E). Image F illustrates the distribution of pores spaces (yellow area) at the same area of image E. 24 ACS Paragon Plus Environment

Page 25 of 28


PS_Exp. PS_Model

1.00

GS_Exp. GS_Model

0.95 C/C0

17 g/L 0.90 0.85 44 g/L 0.80 A) 30.8-31.1 m 0

20

40 60 Time (d)

PS_Exp. PS_Model

1.00

80

GS_Exp. GS_Model

C/C0

60 g/L 0.95 52 g/L

0.90 B) 39.0-39.3 m 0

40 60 Time (d)

PS_Exp. PS_Model

1.00

C/C0

20

80

GS_Exp. GS_Model

0.95 43 g/L 43 g/L 0.90 C) 51.5-51.8 m 0

650 651 652 653 654

20

40 60 Time (d)

80

Figure 2. Experimental (symbols) and calculated (lines) Tc(VII) concentrations in the batch reactors containing pristine sediments (PS, blue) and ground sediments (GS, red). The numbers next to the data are soil/water ratios for each experiment. The symbols and bars are the mean and variation of the results from duplicate experiments.

655



20 10 0

A1) 30.8 − 31.1 m 0

1

2 3 L (cm)

40

1 week 4 week

10 B1) 39 − 39.3 m 0

1

2 3 L (cm) 1 week 4 week

40

C1) 51.5 − 51.8 m 1 2 3 L (cm)

2 3 L (cm)

4

5

4 2 0

1

2 3 L (cm)

4

4 2

5

0

1

2 3 L (cm)

0.04 0.02 0.00

0

4

5

0.01

10 D1) Bulk 0

656 657 658 659 660 661 662 663

0

10

20 30 40 Time (d)

4

0

60

10

20 30 40 Time (d)

50

2 3 L (cm)

4

5

C3) 51.5 − 51.8 m 1 week 2 week 4 week 8 week

0.02 0.01 0.00

0

100

D2) Bulk 0

1

1

2 3 4 5 L (cm) A: 30.8 − 31.1 m

200

2 0

50

A: 30.8 − 31.1 m B: 39.0 − 39.3 m C: 51.5 − 51.8 m

6

5

0.03

Fe(II)HCl (µ µmol/g)

Tc(VII) (µ µ M)

Br- (mg/L)

A: 30.8 − 31.1 m B: 39.0 − 39.3 m C: 51.5 − 51.8 m

20

4

1 week 2 week 4 week 8 week

0.02

300

8

2 3 L (cm)

B3) 39.0 − 39.3 m

10

30

1

0.04 1 week 2 week 4 week 8 week

6


0.06

0.00

5

C2) 51.5 − 51.8 m

8

A3) 30.8 − 31.1 m

0.08

0.03 1 week 2 week 4 week 8 week

6

0

4

1

B2) 39.0 − 39.3 m

10

2 week 8 week

10

0

0

8

5

20

0

2

0

4

Tc(VII) (µ µ M)

Br- (mg/L)

30

4

10

2 week 8 week

20

0


6

5

Tc(VII) (µ µ M)

Br- (mg/L)

30

8

0

4

Tc(IV+VII) (µ µmol/g)

Tc(VII) (µ µ M)

Br- (mg/L)

30

0.10

10 A2) 30.8 − 31.1 m

2 week 8 week

Tc(IV+VII) (µ µ mol/g)

1 week 4 week

Tc(IV+VII) (µ µmol/g)

40

Page 26 of 28

60

C: 51.5 − 51.8 m

D3) Fe(II) B: 39.0 − 39.3 m 0 0 1 2 3 4 5 L (cm)

Figure 3. Experimental (symbols) and model simulated (lines) Br- (A1−C1), dissolved Tc(VII) (A2−C2), and total Tc(IV+VII) (A3−C3) concentrations in the diffusion columns at 1−8 weeks. Figure D1 and D2 are variations of Br- and Tc(VII) concentrations in the bulk solution. Brdiffusion was simulated using the dual-domain diffusion model; Tc(VII) and Tc(IV+VII) concentration profiles were predicted using the dual domain reactive diffusion model (see text). Figure E is the comparison between initial HCl-extractable Fe(II) concentrations (lines) and HClextractable Fe(II) concentrations in the columns at 1 (open symbols: □, ○, and ∆) and 8 (solid


Page 27 of 28

664 665


symbols: ■, ♦, and ▼) weeks. The points and bars are mean and variation of the results from the two half columns.


34

Environmental Science & Technology Page 28 of 28 5

17

0

0

CDF

1

0

Br- (mg / L)

Tc(VII) (M)

10

Batch ACS ParagonColumn Plus Environment -5

-4 log (, M-1h-1)

-3

99Tc(VII) Retardation, Reduction, and Redox Rate Scaling in Naturally

Recommend Documents