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Role of Immobile Kaolinite Colloids in the Transport of Heavy Metals Jongmuk Won, and Susan E. Burns Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b05631 • Publication Date (Web): 05 Feb 2018 Downloaded from http://pubs.acs.org on February 11, 2018

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Environmental Science & Technology

Role of Immobile Kaolinite Colloids in the Transport of Heavy Metals

1 2

Jongmuk Won*,1 and Susan E. Burns1

3 4 5 6 7 8

1

9

Drive, N.W. Atlanta, GA 30332-0355

School of Civil and Environmental Engineering, Georgia Institute of Technology, 790 Atlantic

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* Corresponding author

12 13 14 15 16 17 18 19

Submitted to:

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1 ACS Paragon Plus Environment


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TOC Art

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ABSTRACT

35 36 37

Predicting the transport of contaminants in porous media is crucial to protecting public

38

health and remediating contaminated soil and groundwater. However, the prediction of

39

contaminant transport is challenging due to the presence of mobile and immobile colloids. The

40

work performed in this experimental investigation quantified the role of immobile clay colloids

41

on metal transport through sets of column breakthrough experiments under varying solution

42

chemistry, clay content, and flow rate. Georgia kaolinite was chosen as the colloidal material and

43

Pb(II) was chosen as the dissolved contaminant. The silica sand used as the bed material was

44

sized to ensure that the kaolinite colloids remained stationary during the column experiments.

45

Results indicated that retardation of the Pb(II) breakthrough curve was observed as ionic strength

46

decreased and kaolinite content and pH increased, while no significant variation of Pb(II)

47

breakthrough was observed at any kaolinite content as flow rate decreased. This work

48

demonstrated that in the presence of immobile kaolinite colloids, Pb(II) breakthrough curves

49

strongly depended on the pH and ionic strength, which controlled the charge on the surface

50

functional groups and the surface availability of metal adsorption sites on immobile kaolinite

51

colloids. In addition, the evaluation of unknown first-order coefficients in the continuum

52

governing equation, bed efficiency, and Pb(II) saturation provided a quantitative description of

53

Pb(II) breakthrough curves.

54 55

Keywords: metal transport; kaolinite content; solution chemistry; breakthrough curve

56 57



58

1

INTRODUCTION

59

Contaminants originating from human activities can be introduced into the subsurface

60

through a variety of different sources ranging from stormwater events, leakage from waste

61

disposal facilities, mining activities, to various other industrial activities. Those contaminants can

62

subsequently transport to groundwater where they can pose a threat to public health.

63

Consequently, significant research effort has focused on developing methods to adequately

64

predict and assess contaminant transport in subsurface environments with the goal of protecting

65

human health and ecosystems.1

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Notably, in the past few decades, many laboratory and field studies have determined that

67

the presence and transport of colloidal particles in the subsurface can facilitate or enhance

68

contaminant transport: the contaminant transports faster than the groundwater flow because of

69

colloidal particles serve as a carrier of contaminant.2–7 Many laboratory studies have

70

demonstrated that predicting the distance of contaminant transport without taking mobile

71

colloids into account could result in an inaccurate estimate3,8–11. For instance, transport of

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contaminants such as heavy metals or radionuclides can be facilitated by the presence of charged

73

inorganic colloids including clay and oxide particles12–14; however, it is important to note that

74

colloids do not always pass through porous media easily and they may be retained, which they

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can accumulate in pore space (i.e., clogging) due to pore size restriction, van der Waals attraction

76

or electrostatic attraction.15–18 Occasionally, colloids are generated within the subsurface geology

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due to geochemical alternation and breakdown of parent geologic material, and they remain

78

stationary even under the groundwater flow condition of high hydrodynamic force. In these

79

conditions when colloids are relatively immobile, it is predictable that contaminant transport is


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likely to be retarded, rather than facilitated, if the contaminant is favorably adsorbed by the

81

colloid surface.

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Colloidal particles consist of a variety of different substances, including mineral and

83

organic phases; however, aluminosilicate clay minerals represent one of the most prevalent types

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of colloids found in groundwater. The mobility of these colloids is a function of the prevailing

85

geochemical conditions, and they may be mobilized in the short term due to the alternation of the

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hydrogeological condition and aqueous chemistry, or they can be stationary in a nearly immobile

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state in the short to long terms. Most importantly, the immobility of clay colloids can

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significantly retard the transport of contaminants that are favorably adsorbed by the clay surface,

89

which can have a measurable impact in contaminant transport. In spite of prevalence of clay

90

colloids in subsurface, the impact of immobile clay colloids on contaminant transport has not

91

been well documented to date.

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The objective of the work performed in this experimental study is to investigate

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contaminant transport in a sand medium in the presence of immobile kaolinite clay colloids.

94

Lead (Pb(II)) was selected as the model contaminant to represent heavy metal species that are

95

not easily degradable biologically and originate from human activities (e.g., industry emission,

96

wastewater irrigation, solid waste disposal, mine tailings).19–21 The variation of the clay colloidal

97

fraction in the sand medium was selected as the primary variable to observe the degree of Pb(II)

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transport retardation as a function of the mass of immobile clay colloids. Additionally, the

99

solution chemistry (pH and ionic strength) and flow rate were varied in order to investigate the

100

impact of a surface charge of the clay colloidal particles and kinetic rate of adsorption of Pb(II)

101

on the breakthrough curve. Finally, optimization analysis was performed on the measured



102

breakthrough curves to evaluate first-order coefficients embedded in the advection-dispersion

103

type governing equation to determine adsorption and desorption rates of Pb(II) onto clay colloids.

104 105

2

106

2.1

Materials and Methods Materials

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Georgia kaolinite (Wilkinson Kaolin Associate) and ASTM-graded sand (U.S. Silica)

108

were selected as the clay colloids and sand medium, and characterization data were measured for

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both soils (Table S1). The liquid limit (LL) was measured by the fall cone method (British

110

Standard 1377) and the specific surface (Ss) was measured by the methylene blue method.22 The

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hydrometer test and the sieve analysis in ASTM D422 were performed to measure median

112

particle sizes (d50) of the kaolinite and the sand. The maximum and minimum void ratios (emax

113

and emin, respectively) of the sand were measured according to ASTM D4253 and ASTM D4254,

114

respectively, and the specific gravity (Gs) of both materials was measured according to ASTM

115

D854. The zeta potential of the kaolinite particles was measured at varied pH using a zeta

116

potential analyzer (Zetaplus, Brookhaven Instruments Corporation). All chemicals in the

117

experiments (Pb(NO3)2, NaOH, HNO3, and CaCl2, Sigma Aldrich Corporation and Fisher

118

Scientific) were used as received, and deionized water (Barnstead E-pure, electrical conductivity

119

~ 0.8 µS/cm and pH ~ 5.6) was used in all experiments.

120

To ensure the immobility of kaolinite colloids in the sand medium during the column

121

experiment, the retention profile of kaolinite colloids was first obtained after the injection of 10

122

pore volumes (PV) of 1 g / L kaolinite suspension through the ASTM-graded sand (Figure S1).

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The hyperexponential retention profile in Figure S1 indicated that pore sizes of ASTM-graded

124

sand were not sufficiently large for kaolinite colloids to penetrate deeply into the sand column. A


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surface filter cake was formed at the inlet of the sand medium, and the kaolinite colloids were

126

trapped after initial placement in the small pore spaces within the sand. No kaolinite colloids

127

were observed in the effluent after 10 pore volumes of flow, and kaolinite mass recovery after

128

soil column extraction was approximately 100%.

129 130

2.2

Sample preparation and soil-column experiment

131

The soil columns were prepared for experimentation as follows: to remove any impurities

132

from the sand, deionized water was used to rinse the sand three to four times, after which the

133

sand was submerged it in an ultrasonic bath for 1 hour, followed by drying in an oven at a

134

temperature of 105±5 °C. Then the given mass of kaolinite was mechanically mixed for 1 hour

135

with a given mass of sand, chosen to form a sample with a corresponding Dr = 70% (i.e., n =

136

0.37). The sand-kaolinite sample was placed into the test column using wet pluviation (column

137

dimensions = 5.08 cm in diameter and 4.61 cm in height). A perforated round metal plate was

138

placed at the top and bottom of the column to ensure even distribution of flow, and a # 200

139

plastic mesh (75 µm opening size) was placed at each end of the column to retain the sand grains.

140

After the sand was placed, the column was submerged and assembled inside a water bath with

141

the background solution to obtain saturation. The background solution (without Pb(II)) was

142

injected into the column at a flowrate roughly 1.5 times higher than test velocity in order to

143

dislodge loosely bound colloidal particles until the sample reached the equilibrium. A

144

turbidimeter (Orbeco-Hellige Inc., TB200) and a conductivity meter (Accumet Excel XL20)

145

were utilized to monitor for the presence of kaolinite colloids and the stabilization of solution

146

chemistry in the effluent. A strong positive correlation between the concentration of kaolinite

147

colloids and turbidity (Figure S2) indicated that turbidity reliably estimated the concentration of



148

kaolinite colloids in the effluent. To ensure the system reached to the equilibrium, turbidity and

149

electrical conductivity for 15 pore volumes of flow were measured (Figure S3). The initial

150

injection of the background solution led to a small amount of kaolinite colloids detachment from

151

the sand medium. The measured turbidities demonstrated that the amount of detached kaolinite

152

colloids was less than 0.5 % of initial immobile kaolinite colloids in the column. After the

153

turbidity and the electrical conductivity of effluent stabilized to background values (dotted line

154

on Figure S3), Pb(II) was injected along with the background solution. Almost no kaolinite

155

colloid was observed at the outlet during Pb(II) injection in all cases.

156

Concentrations of Pb(II) in the effluent were measured using a fraction collector to sample flow

157

at the outlet of the column in each pore volume. In all experiments, a rate-adjustable peristaltic

158

pump (Fisher Scientific) was used to inject the lead solution. Experiments were performed at two

159

constant flow rates, three pH levels, and four levels of ionic strength (Table 1) to investigate the

160

impact of the reaction rate, the surface charge of kaolinite colloids, and the presence of other ions

161

on the Pb(II) breakthrough curve. The Pb(II) concentration in the influent was 5.0±0.1 mg/L for

162

13 experiments, and 1.0 mg/L for two experiments. The influent was flowed through the column

163

for 100 pore volumes, and the concentration of the effluent was measured by inductively-coupled

164

plasma optical emission spectrometry (ICP-OES, PerkinElmer Optima 8000) at the outlet every

165

5 pore volumes of flow.


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Table 1. Experimental Conditions for Lead Sorption Column Tests

166

Kaolinite content by mass (KC) Variables 1%

3%

5%

Chemical used

C0 (mg/L)

1, 5

1, 5

5

Pb(NO3)2

pH

4, 5.6, 9

4, 5.6, 9

4, 5.6, 9

70% HNO3, 1N NaOH

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0.001, 0.005, CaCl2 0.01 vs 0.0136 (low), 0.0141 (low), 0.0146 (low), (cm / s) 0.0452 (high) 0.0469 (high) 0.0488 (high) Note: IS = ionic strength, C0 = inlet Pb(II) concentration. Note that porosity variations in the

168

column setup resulted in slight variations in vs.

IS (M)

-

169 170

2.3

Equilibrium and kinetic adsorption test

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Equilibrium and kinetic adsorption tests were conducted for the sand and kaolinite to

172

determine the maximum adsorption capacities (qmax) and the first-order rate constant (ω)

173

(Equation (S5) and Equation (S9) in supporting information). For both the equilibrium and

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kinetic tests, 3 g of solids were mixed with 30 ml solutions in a series of 50 ml tubes, and the

175

tubes were rotated at 30 rpm for 24 hours for the equilibrium test, and for intervals of 5, 10, 15,

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20, 30, 60, 120, 240, 360, and 1440 minutes for the kinetic test. After the tubes were removed

177

from the shaker, they were centrifuged at 3000 rpm and the supernatant was filtered through a

178

0.45 µm filter prior to ICP-OES analysis. All batch tests were performed at the background

179

solution of pH ~ 5.6 without adding any chemicals but Pb(NO3)2. Sorption results were fitted to a

180

linearized Langmuir isotherm expressed as23:



Ce C 1 , = e + qe q max K d q max

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(1)

181

where Ce is the equilibrium concentration of Pb(II) (mg / cm3), qe is the amount of Pb(II)

182

adsorbed per unit mass of the sand or the kaolinite at equilibrium (mg / g), and Kd is the

183

distribution coefficient (cm3 / g). The first-order kinetic equation was expressed as24: log(qe − q) = log(qe ) −

ωt 2.303

,

(2)

184

where q (mg / g) was the amount of Pb(II) adsorbed per unit mass of sand or kaolinite at time t

185

(sec).

186 187

2.4

Optimized first-order coefficients, bed efficiency and Pb(II) saturation

188

An optimization analysis was performed to evaluate the three unknown first-order

189

coefficients (ka, kd and kc, Supporting Information) associated with reactions between immobile

190

kaolinite colloids and Pb(II) species. Implicit finite difference method was used to solve the

191

governing equation and the trust region algorithm was used for the analysis. In addition to

192

optimization analysis, quantitative comparison of the Pb(II) breakthrough curve in each

193

experimental condition was achieved by determining the calculated bed efficiency (β) and Pb(II)

194

saturation (Supporting Information).

195 196

3

197

3.1

RESULTS AND DISCUSSION Adsorption equilibrium and kinetic adsorption test

198

Uptake of lead by kaolinite was well modeled with the Langmuir isotherm; however, as

199

was anticipated, Pb(II) adsorption by sand was essentially negligible (Figure S4) (Table 2). The

200

specific surface (Ss) of kaolinite was roughly 1200 times larger than that of the sand (based on


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201

d50 and Gs, Table S1); therefore, it can be implied that Pb(II) adsorption during transport

202

dominantly took place at adsorption sites on the immobile kaolinite colloids. Equilibrium

203

sorption occurred in less than 10 min (Figure S5), and the determined values of qmax, Kd, and ω

204

(Table 2) were used in the optimization analysis. Kd, and ω of kaolinite were presented here for

205

information and qmax of kaolinite was used in the calculation of and Pb(II) saturation in the later

206

section. Table 2. Equilibrium and Kinetic Parameters Measured for Tested Soils

207

Kinetic (Equation (2))

Equilibrium (Langmuir) Material qmax (mg / g)

Kd (L / mg)

R2

ω (/ s)

Sand

1.081 × 10-3

2.202 × 10-3

0.045

1.859 × 10-3

Kaolinite

2.854

6.102 × 10-3

0.986

4.258 × 10-3

208 209 210

3.2

211

3.2.1

Soil-column experiment Impact of inlet Pb(II) concentration (Ci)

212

At low concentrations of colloids and lead (kaolinite = 1 % and Ci = 1 mg/L), almost no

213

Pb(II) breakthrough was observed, indicating there were enough available sorption sites on the

214

kaolinite to retard transport of the metal. In contrast, increasing Pb(II) concentration to 5 mg/L

215

led to rapid breakthrough with C / Ci > 0.9 after 20 pore volumes (Figure 1). For KC = 3%, no

216

Pb(II) was observed in effluent until 100 pore volumes for Ci = 1 mg/L, while the breakthrough

217

of Pb(II) was initiated at roughly 30 pore volumes for Ci = 5 mg/L. The plateau concentration

218

between 0.6 and 0.7 for KC = 3% and Ci = 5 mg/L indicated that Pb(II) adsorption still occurred

219

after 100 PVs of flow. In deionized water at pH ~ 5.6, Pb2+ was the dominant dissolved species 11 ACS Paragon Plus Environment


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and the kaolinite was still predominantly negatively charged, suggesting most Pb(II) adsorption

221

occurred through electrostatic attraction (Figure 1). 1 0.9

5mg/L

0.8 0.7

C / Ci

0.6 0.5 KC=1%, Ci=1mg/L KC=3%, Ci=1mg/L KC=1%, Ci=5mg/L KC=3%, Ci=5mg/L

0.4 0.3 0.2 0.1 0 0

20

40

60 PV

80

100

120

222 223

Figure 1. Pb(II) Breakthrough curves as a function of immobile kaolinite colloids and inlet lead

224

concentration (deionized water).

225 226

3.2.2

Impact of flow rate (Q) and kaolinite content

227

An increase in the concentration of kaolinite colloids led to the slower breakthrough and

228

lower peak concentrations in the breakthrough curve (Figure 2) and an increase in the

229

concentration of kaolinite colloids increased retardation of Pb(II), which demonstrates that the

230

colloids were immobile within the sand bed. If kaolinite colloids were highly mobile and

231

released from the bed4,8,25,26, transport would be facilitated because lead favorably sorbs to

232

colloids.27–29 Additionally, the flow rate (Darcy velocity), which ranged between 0.3 ~ 1 cm/min

233

(typical of groundwater velocity30), was not significant in Pb(II) transport, with breakthrough

234

times that were similar in all kaolinite content levels, regardless of flow rate. The similar shapes 12 ACS Paragon Plus Environment

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of the breakthrough curves indicated rapid sorption of Pb(II) (Figure S5), which resulted in the

236

similar masses of sorbed Pb(II) despite differences in flow rate. Very high flow rates can shear

237

and detach immobile colloids from the sand bed by large hydrodynamic force12,31,32; however,

238

that was not observed at the levels tested in this work. 1 1% KC 3% KC 5% KC

0.9 0.8 0.7 C / Ci

0.6 0.5 0.4 0.3 0.2

Q = 6 cm3 / min

0.1

Q = 20 cm3 / min

0 0

20

40

60 PV

80

100

120

239 240

Figure 2. Pb(II) breakthrough curves under two flow rates and three KC: Q = 6 and 20 cm3 / min

241

are corresponding to low and high vs for each KC in Table 1, elapsed time for Q = 6 and 20 cm3 /

242

min were roughly 9.5 hrs and 2.8 hrs, and Ci ≈ 5 mg/L and deionized water was used for all cases.

243 244

β values for the breakthrough curves demonstrated that more Pb(II) was removed by the

245

bed as the kaolinite content increased (Figure 5(a)), and, Pb(II) saturation decreased as the

246

kaolinite content increased, implying that many available adsorption sites were still available in

247

the sand-kaolinite bed at kaolinite content = 5 % after 100 pore volumes of flow for the Pb(II)

248

solution. This means that roughly 50 % of the sorption sites remained unbound when the

249

kaolinite content was 5 %. Lead saturation was approximately 1 for kaolinite content equal to 13 ACS Paragon Plus Environment


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1 %, meaning that the adsorption of Pb(II) in the bed would not occur at any significant level

251

after 100 pore volumes of flow due to the low maximum adsorption capacity. High Pb(II)

252

saturation led to C / Ci ~ 1 in the breakthrough curve after 100 pore volumes, which would

253

remain true unless solution chemistry was changed. β and Pb(II) saturation also showed the

254

insignificance of flow rate in Pb(II) transport (Figure 5(a)), which was consistent with the

255

breakthrough curves exhibited in Figure 2. Overall, the immobile kaolinite content retained in

256

the sand medium was more crucial than flow rate in Pb(II) transport.

257 258

3.2.3

Impact of pH

259

Kaolinite has a 1:1 clay structure with one alumina octahedral sheet (i.e., gibbsite) and

260

one silica tetrahedral sheet (i.e., silica sheet) held together through hydrogen bonding. The

261

permanent negative charges of kaolinite colloids are attributed to isomorphous substitution in the

262

mineral structure and uncompensated charge at the edge of the colloids.33 Because the hydroxyl

263

groups (≡SOH) located on the surface and edge of the kaolinite particles are amphoteric, the

264

surface charges are highly sensitive to pH. At high pH, H+ ions release into solution from surface

265

hydroxyl groups (≡SOH → ≡SO- + H+), a process that is known as deprotonation of surface

266

groups. Negatively charged ≡SO- sites result in an increase in the adsorption of metal species,

267

forming metallic surface complexes such as ≡SOMe+ or ≡SOMeOH. In contrast at low pH, the

268

surface hydroxyl groups sorb a proton to become ≡SOH2+ through protonation (≡SOH + H+ →

269

≡SOH2+), which leads to a decrease in adsorption of metal species.34 This trend is reflected to the

270

experimental Pb(II) breakthrough curves measured in this work (Figure 3).

271

Pb(II) breakthrough curves were significantly impacted by the variation of pH due to the

272

change in surface charge: protonation at low pH (pH = 4.0) and deprotonation at high pH (pH = 14 ACS Paragon Plus Environment

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9.0). Extremely early breakthrough was observed in the experiments conducted for a kaolinite

274

content equal to 1 % at pH = 4.0, while almost no breakthrough was observed in experiments

275

conducted at a kaolinite content of 5 % at pH = 9.0. Notably delayed Pb(II) breakthrough was

276

observed at pH = 5.6 and kaolinite content equal to 1 % when compared to all kaolinite contents

277

at pH = 4.0. This implies that a change in the pH of the solution more significantly impacted the

278

Pb(II) transport than kaolinite content when concentration was approximately = 1 ~ 5 %. In

279

addition, higher pH increased the impact of kaolinite content on the Pb(II) breakthrough curve

280

due to deprotonation of the kaolinite surface groups. The trend of breakthrough curves presented

281

in Figure 3 is consistent with batch adsorption tests of heavy metals as a function of pH.35–38

282

Except in the presence of ligands in solution, heavy metal species are generally more preferably

283

adsorbed by the clays at high pH, as observed in the breakthrough curves in Figure 3. 1 0.9 0.8 0.7 C / Ci

0.6 0.5 0.4

1% KC 3% KC 5% KC pH = 9.0 pH = 5.6 pH = 4.0

0.3 0.2 0.1 0 0

20

40

60 PV

80

100

120

284 285

Figure 3. Pb(II) breakthrough curves according to pH at three different values of kaolinite

286

content: Q = 20 cm3 / min, Ci ≈ 5 mg/L and IS ≈ 0 for all experiments.

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All experiments were conducted above the point of zero charge (Figure S6), which

289

resulted in negative values of zeta potential in all three experimental conditions (pH = 4, 5.6 and

290

9), with the zeta potential becoming more negative as pH increased. Consequently, the transport

291

of Pb(II) was retarded at high pH due to the favorable adsorption of Pb species by immobile

292

kaolinite colloids.

293

The Pb(II) saturation is indicative of the percentage of occupied sorption sites on the

294

colloidal surfaces. At pH = 9 and kaolinite content equal to 1 % (Figure 5(b)), beta is larger than

295

one because the baseline calculation was based on qmax of the sand and the kaolinite in deionized

296

water at pH ~ 5.6, which indicated that the adsorption capacity of the bed substantially increased

297

as pH increased. Less variation of β and Pb(II) saturation in Figure 5(b) indicates that KC is not a

298

critical factor in the transport of lead at low pH.

299 300

3.2.4

Impact of ionic strength (IS)

301

The impact of ionic strength on the deposition of negatively charged colloids on the sand

302

medium has been well established in the literature, with generally more favorable attachment of

303

colloids with an increase in ionic strength32,39,40, as is predicted by Derjaguin-Landau-Verwey-

304

Overbeek (DLVO) theory. This behavior facilitates contaminant transport at relatively low ionic

305

strength due to the high repulsive force between colloids and sand grains at low ionic strength,

306

which results in mobile colloids with sorbed contaminants.25,41 However, for immobile colloids

307

permanently retained in the sand bed (independent of ionic strength), retardation of Pb(II)

308

transport increased as ionic strength decreased (Figure 4). This resulted from competitive

309

adsorption between Pb(II) and Ca2+ on the immobile kaolinite colloids. Increased sorption of


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310

Ca2+ ions on kaolinite resulted in less availability of adsorption sites for Pb(II), leading to earlier

311

Pb(II) breakthrough (Figure 4), lower β, and lower Pb(II) saturation (Figure 5). 1 0.9 0.8 0.7 C / Ci

0.6 0.5 0.4

0.05 M 0.01 M 0.001 M ~ 0 M (DI)

0.3 0.2 0.1 0 0

20

40

60 PV

80

100

120

312 313

Figure 4. Pb(II) breakthrough curves at four different levels of ionic strength: Q = 20 cm3 / min,

314

Ci ≈ 5 mg/L, pH ≈ 5.6 and kaolinite content equal to 3 % for all experiments.

315 316 317 318 319 320 321 322 323 324 17 ACS Paragon Plus Environment

1

1

0.8

0.8

β or Pb(II) Saturation



0.6

0.4 β Pb(II) saturation Low Q High Q

0.2

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0.6

0.4

β Pb(II) Saturation

0.2

pH = 9.0 pH = 5.6 pH = 4.0

(a)

(b)

0

0

0

1

2

3 KC (%)

4

5

6

0

1

2

3

4

5

6

7

KC (%)

1 β


0.8

IS ≈ 0 (DI water)

Pb(II) Saturation

0.6

0.4

0.2 (c) 0 -4

-3

-2

-1

log IS (M)

325 326

Figure 5. Calculated β and Pb(II) saturation as a function of (a) kaolinite content and flowrate, (b)

327

kaolinite content and pH, and (c) ionic strength. Note that Pb(II) saturation at pH = 9 and KC = 1%

328

is 2.2 (data not shown).

329 330

3.2.5

Optimization analysis

331

The result of optimization analysis for the first-order coefficients is presented in Table S3,

332

with the parameters used in the analysis summarized in Table S2. Because the algorithm used in

333

the optimization analysis automatically gives optimized coefficients after satisfying the stop

334

criteria, quantitative comparison of the breakthrough curve in each condition was not feasible in

335

the second scenario because both ka and kc are coefficients associated with the adsorption of

336

Pb(II), and they balance each other with different magnitude. Nevertheless, by restricting the 18 ACS Paragon Plus Environment

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337

range of coefficient, the ka / kd ratio in the first scenario allowed comparison of each

338

breakthrough curve, even though the same ka / kd did not necessarily give an identical result. The

339

ka / kd ratio was not sensitive to the flow rate, but it increased as ionic strength decreased and

340

kaolinite content increased. This was consistent with the experimental results presented in Figure

341

2, Figure 3 and Figure 4. Notably, an increase in ka / kd ratio along with an increase in kaolinite

342

content implied that an increase in immobile kaolinite not only increased the amount of adsorbed

343

Pb(II), but also increased adsorption rate, assuming the desorption rate was constant. The

344

optimization analysis of the experimental Pb(II) breakthrough curves might be translatable to

345

contaminant transport at large scales, based on the results obtained at the laboratory scale.

346 100

180 Q = 6 cm3 / s Q = 20 cm3 / s

80

160

pH = 4.0 pH ≈ 5.6 pH = 9.0

140 120 IS ≈ 0 M

100

ka / kd

ka / kd

60

IS ≈ 0.001 M 40

IS ≈ 0.01 M

80 60

IS ≈ 0.05 M

40

20

20

(a) 0

(b)

0 0

1

2

3 KC (%)

4

5

6

0

1

(a) Flow rate and IS

2

3 KC (%)

4

5

6

(b) pH

347

Figure 6. ka / kd ratio according to kaolinite content based on optimization analysis as a function

348

of (a) flow rate and ionic strength and (b) pH.

349 350

In summary, this experimental study investigated the transport behavior of Pb(II) in the

351

presence of immobile kaolinite colloids in a sand medium. The transport was measured as a

352

function of ionic strength, pH, and immobile kaolinite content. Experimental observation,



353

calculated β and Pb(II) saturation, and optimized first-order coefficients revealed that the degree

354

of Pb(II) transport retardation can be varied as a function of kaolinite content, ionic strength, and

355

pH while the impact of flow rate was not significant. The results presented in this paper showed

356

only trace amount of (< 1%) immobile kaolinite colloids can result in significant retardation of

357

Pb(II) transport. Further investigation can be made under an unsaturated condition, transient flow

358

rate, and chemical perturbation to demonstrate and quantify the retardation of metal transport

359

under the presence of immobile clay colloids.

360 361

ASSOCIATED CONTENT

362

Supporting Information

363

Summary of Kaolinite and Sand Properties; the retention profile of kaolinite on ASTM-graded

364

sand; turbidity versus kaolinite suspension; turbidity and electrical conductivity measured during

365

injection of first 15 pore volumes; Pb(II) equilibrium isotherms; Pb(II) kinetic adsorption; zeta

366

potential of kaolinite as a function of pH; transport parameters used in optimization analysis;

367

results of optimization analysis; governing equations for colloid associated contaminant transport;

368

bed efficiency and Pb(II) saturation

369 370 371

AUTHOR INFORMATION

372

Corresponding Author

373

*Fax: (404) 894-2281; e-mail: [email protected]

374

Notes

375

The authors declare no competing financial interest.


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376 377

ACKNOWLEDGEMENT

378

This material is based upon work supported by the Georgia Department of Transportation. Any

379

opinions, findings, and conclusions or recommendations expressed in this material are those of

380

the writers and do not necessarily reflect the views of the Georgia Department of Transportation.

381

Special thanks is given to Mr. J.D. Griffith for his contributions to the research project.

382 383

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