In-situ determination of current density distribution and fluid modeling of an electrocoagulation process and its effects on natural organic matter removal for drinking water treatment

Journal Pre-proof In-situ determination of current density distribution and fluid modeling of an electrocoagulation process and its effects on natural organic matter removal for drinking water treatment Sean T. McBeath, Amin Nouri-Khorasani, Madjid Mohseni, David P. Wilkinson PII:

S0043-1354(19)31178-9

DOI:

https://doi.org/10.1016/j.watres.2019.115404

Reference:

WR 115404

To appear in:

Water Research

Received Date: 14 June 2019 Revised Date:

27 October 2019

Accepted Date: 15 December 2019

Please cite this article as: McBeath, S.T., Nouri-Khorasani, A., Mohseni, M., Wilkinson, D.P., In-situ determination of current density distribution and fluid modeling of an electrocoagulation process and its effects on natural organic matter removal for drinking water treatment, Water Research (2020), doi: https://doi.org/10.1016/j.watres.2019.115404. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

Electrocoagulation Reactor

Electrode Surface

24

16

8

0

Water Flow Variations in Electrochemical Reactor

Current Density Distribution on Dissolving Anode

Current Density, mA/cm2

32

1 2 3

In-situ determination of current density distribution and fluid modeling of an electrocoagulation process and its effects on natural organic matter removal for drinking water treatment

4 5

Sean T. McBeath, Amin Nouri-Khorasani, Madjid Mohseni, *David P. Wilkinson

6 7 8

Department of Chemical and Biological Engineering, University of British Columbia, Vancouver, BC, Canada V6T 1Z3

9 10

*[email protected]

11 12 13

ABSTRACT

14

Electrocoagulation is a burgeoning technology now being considered for niche water treatment

15

applications. Although much research has been conducted to determine the efficacy of

16

electrocoagulation to remove various contaminants, the more fundamental electrochemical

17

aspects of the technology are often overlooked. This research provides insight into the

18

fundamental relationship of water flow, electrochemical metal dissolution and current density

19

distribution through computational fluid dynamic (CFD) models, mathematical models and in-

20

situ current density distribution identification experiments. Theoretically, it was determined that

21

current distributed along the electrode was inversely proportional to the water flowrate. The

22

turbulent flow through the EC reactor was simulated with varying inter-electrode gaps and

23

flowrates, while the average velocity segments across the electrode surface was calculated,

24

corresponding to the same segments used to experimentally determine the current distribution.

25

Through the CFD models and current distribution determining technique, it was observed that

26

current density was distributed unevenly and followed the trend predicted by theory. Areas of

27

lower current density were generally accompanied by higher velocity flow. More uniform

28

current was yielded with larger inter-electrode gaps, due to the greater flow uniformity. While

29

operating with a 1 mm gap, the current and water velocity varied across the electrode by Δ27.6 1

30

mA/cm2 and Δ0.220 m/s, and was minimized to Δ3.6 mA/cm2 and Δ0.062 m/s at a 10 mm gap.

31

Although current uniformity was increased, the overall current density decreased significantly

32

due to the greater ohmic resistance associated with the larger gap. The removal of natural organic

33

matter was reduced as much as 79% when the inter-electrode gap was reduced from 10 to 1 mm.

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Keywords: Electrocoagulation; current distribution determination; computation fluid dynamic

36

model; water treatment; natural organic matter; electrochemical process

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1.

Introduction

39

Many electrochemical technologies for water treatment applications are beginning to gain

40

momentum for future integration into mainstream water treatment processes (Radjenovic and

41

Sedlak, 2015). Electrocoagulation (EC) has shown promise as an alternative treatment process to

42

conventional chemical coagulation for certain drinking water, municipal and industrial

43

wastewater treatment applications. EC eliminates the chemical supply chain required for

44

conventional coagulation, as coagulant chemicals are electrochemically synthesized in-situ and

45

on-demand. By applying current with an external power supply to an electrochemical cell, the

46

two half-cell reactions of anodic metal dissolution and cathodic reduction of water facilitate the

47

overall production of metal hydroxide and metal oxide species; i.e., the coagulant chemicals. As

48

current provided to the cell increases, the rate of anodic metal dissolution and water reduction at

49

the cathode surface increases, thereby resulting in the increased formation of coagulant. To date,

50

much of the EC research has concentrated on the technology’s ability to remove various target

51

contaminants, including both organic and inorganic compounds, while investigating the effect of

52

various process variables such as metal loading (coagulant dose) (Delaire et al., 2017; Kristian L

2

53

Dubrawski et al., 2013; Dubrawski and Mohseni, 2013a; Fuente et al., 2019), charge loading

54

(Addy, 2008; Fuente et al., 2019; Holt et al., 2002; Vik et al., 1984; Zhu et al., 2007), pH

55

(Delaire et al., 2017; Gilhotra et al., 2018; Mameri et al., 2001, 1998; Pan et al., 2016), anode

56

metal material (typically aluminum or iron) (Kristian L. Dubrawski et al., 2013; Flores et al.,

57

2018; Liu et al., 2018; Müller et al., 2019; Papadopoulos et al., 2019), reactor design (Dubrawski

58

and Mohseni, 2013b; Graça et al., 2019; Kobya et al., 2016; Mameri et al., 2001, 1998; Vik et

59

al., 1984), initial contaminant concentrations (Fuente et al., 2019; Heffron et al., 2019; Jiang et

60

al., 2002; Papadopoulos et al., 2019; Vik et al., 1984) and scale-up (Hakizimana et al., 2017;

61

McBeath et al., 2018).

62

An additional variable that has been widely investigated is the effect of current density on

63

the efficacy of the EC process. Many researchers have investigated the effect of current density

64

on the removal of various wastewater contaminants during an EC process. The effect of current

65

density on the removal of organic dyes found in textile wastewaters was found to be minimal,

66

but a proportional increase of dye removal and current density increase was yielded (Kim et al.,

67

2002). Other researchers observed a significant increase in dye removal with increasing current

68

density (Papadopoulos et al., 2019). The increased reduction of sulfide and chemical oxygen

69

demand from spent caustic wastewater was also observed with an increase of current density

70

(Ben Hariz et al., 2013). In both studies, current density was controlled by changing the applied

71

current, as opposed to changing the electrode surface area at constant current operation. Because

72

of this, the implications of increased coagulant formation and dosing on greater contaminant

73

removal at higher current densities is unknown.

74

The effect of current density on the EC process has also been widely investigated for

75

drinking water treatment applications. Researchers Mameri et al. (Mameri et al., 2001, 1998) and

3

76

Zhu et al. (Zhu et al., 2007) found that current density had little effect on the removal of fluoride

77

from groundwater. In both studies, researchers attributed the increased reduction of fluoride at

78

greater current densities to the increased coagulant formation at the higher metal loading

79

associated with greater current density. Current density was also found to greatly affect the

80

efficacy of EC to remove arsenic from groundwater, but in this case arsenic removal capacity

81

decreased with increasing current density (Addy, 2008). Other research has observed the

82

opposite effect for arsenic removal, however this was once again likely due to the increased

83

metal loading that accompanied the increase in applied current (Kobya et al., 2016). Some

84

batch-scale experiments have shown that the removal of natural organic matter from synthetic

85

and raw surface water also increased when current density was reduced (Dubrawski, 2012;

86

Dubrawski and Mohseni, 2013b). When a similar process was scaled-up to a continuous flow

87

operation, the effect was minimized and no clear trend was observed between current density and

88

the removal capacity of natural organic matter (McBeath et al., 2015). Current density has also

89

been found to have an effect on local pH near the electrode, as well as dissolved oxygen (DO)

90

concentration, subsequently effecting the speciation of iron hydroxide coagulants which are

91

formed during the EC process (Dubrawski and Mohseni, 2013a).

92

Although the effect of current density has been extensively investigated, along with other

93

process variables, not a lot of efforts have been directed towards understanding the fundamental

94

electrochemical and transport phenomena ultimately governing the distribution of current on the

95

electrode surface. In particular, there has been a lack of research to understand the relationship

96

between the variable movement of water across an EC electrode surface and its subsequent effect

97

on the current density distribution. In nearly all prior EC research, it is assumed that current

98

density remains constant over the entire electrode surface during galvanostatic operation. Like

4

99

other electrochemical processes, under most conditions this is likely not realized due to many

100

factors including electrolyte (water) velocity variations across the electrode surface. The

101

degradation of the sacrificial anode can occur due to three main reasons: electrochemical

102

oxidation (discussed here), chemical dissolution, and mechanical erosion. In the presence of an

103

oxidation current, the rate of the two other phenomena are negligible when compared to

104

electrochemical oxidation. Therefore, we associate the distribution of the anode degradation to

105

the inhomogeneity in the electric current distribution.

106

In some previous studies, current density has been modeled for an EC process and was

107

determined to be an important factor for evaluating the electrode arrangement and geometry for

108

energy consumptions, as it was not uniformly distributed (Vázquez et al., 2014). It has also been

109

previously shown through modeling, that this uneven distribution of current and potential across

110

an EC electrode can impact coagulant formation, ultimately affecting the performance of EC

111

(Vázquez et al., 2012a). Computational fluid dynamic (CFD) modeling has also been used for

112

the determination of electrolyte flow variations within an EC reactor, observing high variations

113

of fluid velocity within the reactors, as a result of many factors including cell geometry and

114

configuration (Martinez-Delgadillo et al., 2012; Vázquez et al., 2014). In general, CFD modeling

115

is a widely used tool in electrochemical engineering to understand electrolyte mass transport

116

phenomena. Phenomenological research on the EC processes have shed light on the mixing

117

(Choudhary and Mathur, 2017) and process (Gilhotra et al., 2018; Safonyk et al., 2019)

118

optimization approaches. Recent numerical studies on electrocoagulation have focused on the

119

role of the reactor configuration on the electric field and mass transport, and the role of local

120

reaction conditions on the same electrode plate has not been investigated (Song et al., 2018).

5

121

In order to understand the variation of current distribution across an electrode surface, this

122

research employed an in-situ technique to measure and map current density distribution.

123

Additionally, water flow patterns through the EC reactor were obtained through CFD modeling,

124

in order to provide insight towards the fluid and current flow relationship. Aside from yielding a

125

fundamental understanding of current and mass transport considerations for improved and

126

predictable EC operations, as well as providing a novel process application for identifying

127

current distribution in an EC reactor, results could lead to improved current density distribution

128

and consequently improved reactor design; a key factor for the design of an energy efficient and

129

consequently more economical EC reactor and process (Vázquez et al., 2012b). Without evenly

130

distributed current on the electrode surface, premature exhaustions at areas characterized by high

131

current density will occur (and relatively under-used portions in areas of low current density). In

132

order for EC to be considered and adopted as a potential alternative water treatment technology,

133

optimum electrode performance at an industrial scale needs to be demonstrated, and efficient and

134

optimized utilization of the entire electrode is required. Finally, EC’s ability to remove natural

135

organic matter (NOM), a common drinking water contaminant in surface water supplies, was

136

evaluated at the same conditions investigated with CFD and current distribution experiments.

137

138

2.

Material and methods

139

2.1 Materials

140

Anode electrodes were made of A1008 cold-rolled steel iron containing trace amounts of

141

carbon, manganese, phosphorus and sulfur. Cathode electrodes were made of austenitic, face

142

centered cubic crystal stainless steel alloy, containing trace amounts of chromium and nickel.

143

Both the anode and cathode electrodes were 16-gauge thickness (1.519 mm) and had a single

6

144

side active surface area of 310.8 cm2 (250 x 124.3 mm). Distilled water with dissolved NaCl to a

145

concentration of 0.3225 g/L was used for the inlet waters for all current density distribution

146

experiments (for all conditions tested). This water matrix was chosen in order to match the

147

synthetic surface water used in the subsequent electrocoagulation treatment experiments,

148

described in section 3.3. All experiments were investigated at 1.35 and 10 L/min for three

149

different inter-electrode gaps (1, 2 and 10 mm).

150

151

2.2 Electrocoagulation reactor and process

152

The EC reactor used was originally designed to maximize flow distribution across the

153

electrode surface and used for pilot-scale research investigating NOM, arsenic and manganese

154

removal from raw surface and groundwater supplies. To promote water flow uniformity, a baffle

155

was integrated into the inlet of the reactor whereby liquid entering the EC unit must first rise and

156

fall over a baffle spanning the entire width of the reactor. Upon passing over the inlet baffle,

157

water enters the main chamber of the reactor where the electrodes are housed. The main section

158

of the reactor accommodates removable electrode holders, which have machined slits with varied

159

spacing, corresponding to the inter-electrode gaps required when electrodes are installed into the

160

reactor. Depending on the number of cells to be used during EC operation, ‘flow blockers’ can

161

be inserted between the outermost electrodes and the walls of the reactor, to direct water solely

162

through the electro-active volumes of the reactor [see Figure S1]. Brass busbars are used for

163

configurations implementing two or more cells, in order to have a single electrical connection to

164

all electrodes. Water travels upwards through the electrodes and spills over an additional baffle

165

prior to exiting the EC reactor [see Figure S2].

7

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The reactor, electrode holder inserts and flow blockers were constructed entirely of inert

167

acrylic. Inlet water was pumped to the reactor using a Masterflex I/P Drive and I/P High

168

Performance Head peristaltic pump. Experiments were performed at potentiostatic conditions

169

(constant voltage) until a stable current was reached and stabilized for at least 30 seconds, using

170

a Keithley 2260B-30-72 DC Power Supply. During EC operations, voltage and current data were

171

displayed and collected via a custom LabView program at a sampling rate of 5.8 Hz. Although

172

the EC reactor was designed to accommodate various cell configurations, all current density

173

determination experiments were single-cell conditions using the partial electrode approach.

174 175

2.3 Partial electrode approach

176

To determine the variation of current over the electrode surface area during EC operation, a

177

method utilized for the determination of current distribution in proton exchange membrane fuel

178

cells was utilized, i.e., the partial membrane electrode assembly approach (Stumper et al., 1998).

179

With this partial electrode current determination method, portions of the electrode surface were

180

masked using an electrically inert polyimide adhesive membrane (Kapton) to test independent

181

segments of the electrode. Potentiostatic (constant voltage) electrolysis is performed in order to

182

generate polarization curves for each individually unmasked segment of the electrode. The

183

specific performance of the various regions tested could be determined through the difference of

184

each polarization curve generated. The intervals between each potential tested depended on the

185

linearity of the polarization curve; non-linear regions of the polarization curve were examined at

186

small voltage intervals, while linear regions of the curve could be tested at larger voltage

187

intervals. In this investigation, both vertical and horizontal segments of the electrodes were

188

investigated at three inter-electrode gaps (1, 2 and 10 mm) and two flow rates (1.35 and 10

8

189

L/min), using the same synthetic water matrix (described previously in section 2.1) for all

190

conditions investigated. The potentiostatic experiments were performed for seven different

191

electrode configurations for each condition investigated. One configuration included the

192

utilization of the entire electrode area, i.e., the standard single-cell EC configuration. For the six

193

other configurations, electrodes were masked vertically and horizontally to expose equal ¼, ½,

194

and ¾ segments of the electrode as shown in Figure 1. For all segments tested, both the anode

195

and cathode were masked symmetrically (mirror images), to ensure the same exposed surface

196

area on both electrodes.

197

198 199

Fig. 1. Seven partial electrode approach configurations implemented.

200

201

All configurations and potentials were tested in duplicates. At each voltage, a constant

202

current was reached. Polarization data for iron dissolution was collected using the two electrode

203

cell setup, under the assumption that cathodic potential (due to hydrogen evolution) is negligible

9

204

especially at low current densities. This is because the exchange current density for iron

205

oxidation is known to be more than three orders of magnitude smaller than the hydrogen

206

evolution reaction. The near negligible overpotential associated with hydrogen evolution has

207

been evidenced in previous work, which generated Tafel plots for a similar EC setup (Dubrawski

208

et al., 2014), as well as other modeling work which demonstrated that cell potential was largely

209

due to the anodic metal dissolution reaction (Mechelhoff, 2009). The voltage and current data

210

were used to generate polarization curves for each electrode configuration, yielding average

211

current densities for each exposed segment (¼, ½, ¾ vertical and horizontal). The individual

212

performance for each horizontal and vertical quarter segments of the electrode could then be

213

determined by the difference of each polarization curve. All current density and water velocity

214

distribution figures appearing in the following sections will follow the convention shown in

215

Figure 1, whereby the reactor’s water inlet is found in the bottom left corner of the electrode and

216

the water outlet is situated at the top right corner of the electrode.

217

218

2.4 Computational fluid dynamic model

219

To compliment experimental current density data obtained from the partial electrode

220

approach, CFD models were constructed to understand water flow variations in the EC reactor at

221

1.35 and 10 L/min flow rates for the 1, 2 and 10 mm inter-electrode gap settings. The 3-

222

dimensional water velocity distribution was simulated in the reactor using the CFD module in

223

COMSOL Multiphysics® software. The flow turbulence was modeled using the

224

(Launder and Spalding, 1974). The reactor entrance was modeled as an inlet with known mass

225

226

− method

flow rate and the outlet was modeled as an outlet with constant hydrostatic pressure ( =

ℎ).

The reactor walls were modeled as a no-slip boundary (u=0, where u is the velocity vector). The

10

227

open boundary of water with air was modeled as a slip boundary (n.u = 0, i.e. tangential flow

228

velocity along the water-air boundary). The water hydrodynamics were assumed to be

229

independent of the electrostatic interactions with the charged walls, because the electrostatic

230

interaction of the walls with polar, uncharged water is limited to the 10-nm layer adjacent to that

231

(Nouri-Khorasani et al., 2014), a distance 6 orders of magnitude smaller than the inter-electrode

232

gap. Therefore, no electrostatic simulation was performed or coupled to the CFD simulation. The

233

presence of ions and hydrogen gas have a negligible influence on the water velocity distribution.

234

Two possible effects of ions present in water include the effect on the viscosity, and the local

235

charge-ion interactions in the electrolyte. Since the total ion concentration in drinking water is

236

low, both of these effects can be neglected. The effect of hydrogen bubbles on the water velocity

237

distribution has also been neglected. Whereas the presence of bubbles can cause turbulence in an

238

otherwise laminar flow, in the presence of turbulence the momentum of hydrogen bubbles would

239

be small compared to water eddies. Furthermore, from a computational perspective, simulating

240

two-phase flow between two real-size electrodes describing the growth and detachment of

241

hydrogen bubbles on the cathode, and coupling to the water flow between the two electrodes is

242

both computationally demanding and physically incompletely-defined. Several parameters such

243

as the nucleation site density of the cathode, the onset of hydrogen supersaturation before bubble

244

nucleation, the shape and detachment size of the growing bubble make it very difficult to

245

explicitly simulate the effect of hydrogen bubbles in this system. For these reasons, we limited

246

the scope of simulation to the distribution of liquid water between two vertically oriented

247

electrodes.

248

249

2.5 Electrocoagulation water treatment process

11

250

EC water treatment experiments for NOM removal [Section 3.3] were undertaken using the

251

same reactor and conditions (i.e. flow rate, electrode surface area and materials, inter-electrode

252

gaps) used in the current density distribution determination experiments. The effectiveness of the

253

EC to remove NOM was evaluated by monitoring the reduction of dissolved organic carbon

254

(DOC) pre- and post-EC electrolysis. During laboratory-scale low flow rate (1.35 L/min)

255

experiments, synthetic surface water was used with a technical grade humic acid (Sigma-

256

Aldrich) surrogate in place of NOM. Synthetic waters were used for laboratory scale experiments

257

in order to maintain controlled conditions for a better analysis and understanding of the process.

258

In order to evaluate EC performance at a high flow rate (10 L/min), field studies were performed

259

using a mobile water treatment plant. Raw water from a small community’s water supply, Priest

260

Lake, located on Texada Island, British Columbia (Canada) was treated. This surface water

261

supply is characterized by high NOM concentrations [see Table 1]. Real waters were utilized for

262

high flow rate experiments for two primary reason: (1) to deal with the extremely large volumes

263

of water required to properly assess the steady-state performance of the electrocoagulation

264

process, and (2) to assess the technologies viability in a real applied context. Prior to DOC

265

analysis, both synthetic and raw water samples (untreated and treated) were filtered using a 0.45

266

µm PVDF syringe filter. DOC was analyzed using a Shimadzu ASI-V Total Organic Carbon

267

Analyzer, utilizing the non-purgeable organic carbon method. No pre-treatment to raw or

268

synthetic waters were conducted prior to the EC process.

269 270 271

Table 1 Water quality characteristics for low (1.35 L/min) and high (10 L/min) flow EC treatment experiments

DOC pH

Low Flow

High Flow

Synthetic Water

Raw Water

10.72 ± 1.64 mg/L 6.61 ± 0.22

6.036 ± 0.2 mg/L 7.87 ± 0.09

12

Conductivity

568 ± 28 μS/cm

236 ± 6 μS/cm

272

273

All of the same conditions used for the current distribution determination experiments were

274

investigated for NOM removal (1, 2 and 10 mm inter-electrode gaps), except for 10 mm gap

275

experiments at 10 L/min, as the power required exceeded the limitations of the DC power

276

supply. This problem affected high flow rate experiments because conductivity of the raw

277

surface water was lower than that of the synthetic water used in low flow rate laboratory

278

experiments using synthetic water [see Table 1]. Unlike the current distribution experiments, EC

279

water treatment experiments were conducted under galvanostatic operations (constant current),

280

in order to operate under constant metal loading conditions. The metal loading conditions tested

281

during EC water treatment experiments were consistent within the voltage range investigated

282

during current distribution tests. The same metal loading conditions were analyzed at both low

283

and high flow rates. A full analysis of results at various other conditions for low and high flow

284

rate have been described and published elsewhere (McBeath et al., 2018, 2015).

285

286

3.

Results and discussions

287

3.1 Theoretical current density distribution

288

The inherent rate of the hydrogen evolution reaction (HER) in the electrocoagulation cell,

289

exhibited by the exchange current density, is 4 times faster than that in iron reduction (Anson,

290

1961; Zeng and Zhang, 2010). The inherent HER rate is also faster than that of the coagulation

291

reaction rate constant (Vasudevan and Oturan, 2014). Since the OH- production in the cell is fast

292

compared to both iron oxidation and coagulation, one can estimate that the distribution of OH- is

293

equal to its equilibrium value at the anode reaction plane, and the coagulation reaction would be

294

first-order with respect to Fe2+ concentration. For this reason, we can correlate the local rate of 13

295

water treatment to the local Fe2+ concentration. Current density inhomogeneity in the

296

electrocoagulation cell stems from the variation in the electrochemical equilibrium potential

297

across the electrode. Non-uniform distribution of Fe2+ ions in the reactor leads to a variation in

298

the galvanic anode potential (

299

Nernst equation for the half-cell reaction in the reduction direction:

) across the anode electrode. This variation is described by the

=

+

ln

2

(1)

300

where [Fe2+] is the iron cation concentration on the anode reaction plane (mol.L-1),

301

standard half-cell potentials for the anodic reaction (-0.44 V (Bard et al., 1985)), R is the ideal

302

gas constant (8.314 J.mol-1.K-1), T is temperature (K), and F is Faraday’s constant (96485 C.mol-

303

1

is the

). Both anode and cathode potentials can be assumed constant across the electrodes, because

304

both electrodes are thick solid conductive metals. The variation in

305

the local overpotential on the anode electrode, despite the anode potential being constant: =

−

−( −

) =

−

=

+

2

leads to a distribution in

ln

−



(2)

306

Equation (2) shows that the local overpotential of an electrolytic cell such as an

307

electrocoagulation cell is directly related to the local Fe2+ concentration. A mole balance over

308

[Fe2+] at steady state in the cell reveals the relationship between the operational conditions and

309

the exit [Fe2+]:

#$ %& − #$ '() + #$ *

%& -ℎ%& .

−

− #$ '&+ = 0 /0 -ℎ%& . + − .0 2 &

=0

(3) (4)

310

where the subscripts denote the [Fe2+] inlet (in untreated water), outlet (from the reactor),

311

generation (from Fe oxidation reaction) and consumption (by the coagulation reaction, first-order

312

kinetics). u is the flow velocity (m.s-1) and ℎ%& is the reactor inlet height (m). k is the coagulation 14

313

314

rate constant (s-1), . is the inter-electrode gap (m), and A is the electrode area (m2). Solving equation (4) for [Fe2+] yields:

/ 0 1 1 23 5 2 ℎ%& . 0 1 1+ 3 5 ℎ%& -

%&

=

+

(5)

315

Equation (5) shows the dependence of the [Fe2+] in the reactor to the reactor structure and

316

operating conditions. Substituting equation (5) in equation (1) shows the relation between the

317

shift in local equilibrium potential and the operating conditions: = −0.44 +

2

ln 8

/ 0 1 1 23 5 2 ℎ%& . 9 0 1 1+ 3 5 ℎ%& -

%&

+

(6)

318

Figure 2 shows that increasing the flow velocity in the cell to 1 m.s-1 decreases the [Fe2+] and the

319

galvanic anode potential to 10-5 M, and -0.57 V, respectively. Consequently, the overall cell

320

overpotential required to achieve a given current increases, as shown in equation (2). Similar

321

mole balance can be applied to different segments in the cell; however, the local [Fe2+] depends

322

on the local [Fe2+]in from the neighboring sub-cell components.

15

323 324 325 326 327

Fig. 2. Inverse relationship between the flow velocity and a) the [Fe2+] and in the cell, and b) the anode equilibrium potential. Faster coagulation process (larger k) reduces the sensitivity to the velocity. Sensitivity of the anode galvanic potential to c) the average current density, and d) the inter-electrode gap, with k=0.001 s-1. Parameters are set at j= 25 mA.cm-2, δ=1 mm if not stated.

328

329

3.2 Water velocity and current density distribution

330

Equation (6) shows that water flow velocity across the electrode surface is inversely

331

proportional to the equilibrium anode potential and local Fe2+ concentration. While the absolute

332

flow rate of the process may remain constant (i.e., 1.35 L/min or 10 L/min), local fluid velocity

333

variations across the electrode surface will exist due to reactor design. Fundamentally, it is areas

334

of the electrode which are dominated by higher current density that will have lower

335

concentrations of Fe2+, as described by the Le Chatelier principle. It is therefore expected that

336

local variations of current density across the electro-active area of the electrocoagulation reactor

337

will exist, whereby certain areas of the electrode may be dominated by higher or lower current

338

(and iron dissolution). 16

339

CFD simulation results show that the flow pattern across the electrode is in the turbulent

340

flow region. This observation validates our assumption of the negligible effect of hydrogen

341

bubbles on the hydrodynamics in the system, due to the bubbles’ relatively smaller momentum

342

compared to turbulent water eddies. In general, current density data collected using the partial

343

electrode approach at 1.35 L/min flow rates agreed well with the local water velocity variations

344

generated with the CFD models. At an equal applied cell potential, the average velocity

345

decreases with an increasing inter-electrode gap. Similarly, the average current density decreases

346

with inter-electrode gap. Current is expected to decrease at a constant voltage when the inter-

347

electrode gap increases, due to ohmic losses as a result of the increased resistance associated

348

with the electrolyte (water). However a direct relationship between the average current density

349

and velocity agrees with the predictions of equations (5) and (6). Water velocity variations

350

decreased with increasing inter-electrode gap, as did the variations associated with current

351

density. The absolute range in variation of both current density and water velocity greatly

352

reduced with an increasing inter-electrode gap; Δ27.6, Δ13.7 and Δ3.6 mA/cm2 range from the

353

minimum and maximum recorded current densities and Δ0.220, Δ0.123 and Δ0.062 m/s range in

354

water velocity for 1, 2 and 10 mm inter-electrode gaps, respectively [see Figure 3].

355

356

17

357 358

Fig. 3. Average (•), minimum (⊥) and maximum (⊤) current density and water velocity for 1, 2 and 10 mm inter-electrode gaps at 1.35 L/min.

359

360

It can be observed that current density is greater in the top left corner area of the electrode

361

(current density versus minimum current density) where velocity is seen to be minimized (flow

362

rate versus maximum flow rate) and a general trend of higher current density inversely related to

363

water velocity was observed [see Figure 4]. The discrepancy between the trends in local and the

364

average current density distribution in the cell likely stems from the contribution of the inlet

365

local [Fe2+]in in the cell, shown in equation (5). Higher up sub-cell components have Fe2+ carried

366

over with the water convection, whereas sub-cell elements closer to the inlet have lower [Fe2+]in.

367

368 369 370

Fig. 4. Current density and water velocity variations, obtained with the partial electrode approach and CFD models respectively, for 1.35 L/min flow and 1 mm gap.

371

372

With slightly decreased absolute variations in both current density and water velocity, the

373

same trends observed at 1 mm gap existed with a 2 mm inter-electrode gap. Like 1 mm gap,

374

some outliers existed at 2 mm; however, electrode segments with higher current densities were

18

375

observed to be accompanied decreasing water velocity [see Figure 5]. One potential reason for

376

discrepancy between the CFD and experimental results could be the changing nature of the areas

377

of electrode with low flow rate. In these areas, a layer of oxide can grow on the surface, change

378

the inherent Fe oxidation reaction rate, and lead to additional mass transport resistance for Fe2+

379

inside the oxide layer.

380

381 382 383

Fig. 5. Current density and water velocity (inverse) data for 1.35 L/min and 2 mm gap for electrode segments.

384

385

When the inter-electrode gap was increased to 10 mm, water flow variations were greatly

386

reduced. Similarly, current density variations over the active area were also greatly reduced,

387

yielding a much more uniform current density distribution [see Figure 6]. Although current

388

density was more uniformly distributed at an inter-electrode gap of 10 mm, it was at the expense

389

of significantly reduced current densities and consequently higher energy requirements. Table 2

390

shows the range of potentials and currents investigated and the electrolyte resistance associated

391

with each inter-electrode gap (1, 2 and 10 mm), as well as the process energy requirements per

392

cubic meter of water being treated. The current density data obtained for the three inter-electrode

19

393

gaps investigated can be used for further analysis and understanding of local Fe2+ dissolution

394

rates. This information could be useful for all EC research, as metal loading is always reported

395

generally, as the overall metal dissolution rate under the assumption of evenly distributed current

396

across the electrode surface, which as been demonstrated to not be valid.

397 398 399 400

Table 2 Operating potentials and measured current, resistant and energy requirements for 1.35 and 10 L/min electrocoagulation experiments.

401

Potential 1 mm 2 mm

0 - 10 V

10 mm Potential, V 1 mm 2 mm 10 mm

0 - 29 V

Low Flow - 1.35 L/min Current Resistance

Energy (2 A)

0 - 12.4 A

0.81 Ω

0.066 kW/m3

0 - 11.3 A

0.88 Ω

0.074 kW/m3

0 - 2.8 A

3.57 Ω

0.191 kW/m3

High Flow - 10 L/min Current, I Resistance, R

Energy (7 A)

0 - 57.7 A

0.50 Ω

0.063 kW/m3

0 - 32.2 A

0.90 Ω

0.091 kW/m3

0 - 7.5 A

3.87 Ω

0.318 kW/m3

402

403

404

405

As the inter-electrode gap increases, the cell potential increases significantly as a result of

increased electrolyte resistance, as described by Ohm’s Law (< = = × ). As the gap increases from 1, 2 to 10 mm, the electrolyte resistance increases from 0.81, 0.88 to 3.57 Ω, respectively.

406

Although a more uniform current density distribution would be preferred in practice, the

407

increased resistance and consequently lower current density associated with the larger inter-

408

electrode gap results in a much more energy intensive process. At a constant current (2 A), and

409

therefore a constant metal loading (e.g., coagulant dosing rate), the energy required to treat a

410

cubic meter of water increases from 0.066 kWh/m3 at 1 mm to 0.191 kWh/m3 at 10 mm.

411

Consequently, electrocoagulation reactor design would require the consideration of the inter20

412

electrode to minimize both current/water velocity variations and ohmic losses; a design

413

incorporating evenly distributed flow, consequentially resulting in decreased current density

414

variations, while minimizing the inter-electrode gap for reduced resistance. When large

415

variations within the electrode exist, areas characterized by high current density will be depleted

416

at an increased rate, thereby minimizing the lifetime of an electrode, as holes, failures or losses

417

to the power supply connection points could arise.

418

419 420 421

Fig. 6. Current density (partial electrode approach) and water velocity profiles (CFD models) for 1.35 L/min flow at 1, 2 and 10 mm gaps.

422

423

In general, current density distribution was observed to become more uniformly distributed

424

as the inter-electrode gap increased. The same trend was seen with water flow velocity,

425

indicating that uniform use of the sacrificial anode in a water treatment process would be greatly

426

affected by reactor design parameters. An ideal and economical process would have even

427

dissolution of the electrode, thereby maximizing the usage of the sacrificial anode material. 21

428

Higher operating costs would be associated with the aforementioned localized and premature

429

failure points, as large underutilized areas of the electrode would remain at the end of an anode’s

430

lifetime.

431

When the flow rate was increased to 10 L/min, current density and water velocity

432

relationships were not as evident as those yielded during 1.35 L/min experiments. One clear

433

trend consistent with 1.35 L/min experiments was the increase of water flow uniformity and the

434

consequentially improved current density distribution with increasing inter-electrode gaps. Once

435

again, this was observed when analyzing the absolute variation of both current density and water

436

velocity at 1, 2 and 10 mm inter-electrode gaps [see Figure 7]. The absolute range of current

437

density and water velocity variations for 1, 2 and 10 mm gaps was 75.0, 31.7 and 6.5 mA/cm2

438

and 3.5, 1.7 and 0.5 m/s, respectively; clearly highlighting the greatly increased uniformity of

439

both current and flow as the inter-electrode gap increases.

440

441 442 443 444

Fig. 7. Average (•), minimum (⊥) and maximum (⊤) current density and water velocity for 1, 2 and 10 mm inter-electrode gaps at 10 L/min.

445

As is the case with 1.35 L/min flow rate experiments, this phenomenon can be attributed to

446

the chamber volumes (volume within the electro-active area of the reactor). When operating at a

447

1 mm inter-electrode gap, the chamber volume is 31.1 cm3. As the inter-electrode gap increases 22

448

to 2 and 10 mm, the volume increases to 62.2 and 310.8 cm3, respectively. Because of the

449

different chamber volumes, there is an average reactor residence time of 0.187, 0.373 and 1.865

450

seconds for 1, 2 and 10 mm inter-electrode gap conditions, respectively [see Table S1]. At larger

451

inter-electrode gaps with greater reactor chamber volumes and residence times, improvement in

452

current distribution will be achieved due to more uniform velocity profiles. It should also be

453

noted that the increase in inter-electrode gap also increases the electrical resistance (as described

454

by Ohm’s law), accounting for the decrease in current density despite improved current

455

uniformity, as previously described for low flow operation [see Table 2].

456

In addition to the inverse relationship between flow velocity and Fe2+ concentrations,

457

reductions in current density performance at a high flow rate may also suggest a reduction in the

458

current due to increased resistance. Increased resistance loss can be due to a number of variables,

459

but those that may be more likely to occur during higher flow rate experiments include a

460

decrease in the active electrode area and/or the increase of ‘gas blinding’ (Walsh, 1993). Gas

461

bubbles may enter the electro-active area of the reactor through the electrochemical synthesis of

462

H2 and/or O2 at the cathode and anode respectively, or enter with the water being pumped into

463

the reactor. The introduction of gas into the reactor may be more likely to happen at a higher

464

flow rate due to aeration, as water travels through the reactor inlet channel, baffle and electro-

465

active area much more vigorously when compared to the fully developed laminar flow observed

466

in the low flow rate experiments.

467

A simple way of avoiding increased resistance and consequently decreased current density at

468

greater inter-electrode gaps would be to increase the conductivity of the water by salt addition

469

thereby lowering electrolyte resistance, however this would be impractical in a drinking water

470

treatment process, as the ions would have to be removed in downstream processing (typically an

23

471

energy and economically expensive process). Therefore, in order to maximize the operating

472

efficiency of EC, the process must place high importance on two reactor design considerations:

473

(i) homogeneous flow across the electrode surfaces, and (ii) maximizing current density (and

474

consequently energy efficiency). Homogeneous flow across the electrode surface will increase

475

current density distribution uniformity, which promotes the even dissolution of iron and

476

maximizes the lifetime of consumable electrodes. While increasing the inter-electrode gap was

477

found to increase current density distribution homogeneity, it also yielded decreases in overall

478

current density (and therefore iron dissolution) through increased electrolyte resistance, making

479

the process much more energy intensive. Once again, when the reactor design accounts for

480

evenly distributed flow, minimization of electrical resistance with electrode configuration and

481

decreased inter-electrode gaps can be implemented without sacrificing current density

482

distribution and energy consumption.

483

484

3.3 Electrocoagulation drinking water treatment

485

Metal loading has been shown to be an important factor dictating the effectiveness of EC to

486

remove a number of contaminants (Holt et al., 2002; Kim et al., 2002; Mameri et al., 2001, 1998;

487

Zhu et al., 2007), including NOM (Dubrawski and Mohseni, 2013b; Jiang et al., 2002; Vik et al.,

488

1984). Experiments at both low and high flow rates were conducted at very similar metal

489

loadings. At an operating current of 2.0 and 16.0 A, metal loading values of 25.7 and 27.8 mg/L

490

were achieved at 1.35 and 10 L/min, respectively. Although two different water matrices were

491

used during low and high flow rate experiments respectively [see section 2.5], the same trends in

492

contaminant removal were observed at both conditions. DOC reductions were observed to

493

significantly increase with decreasing inter-electrode gap for both 1.35 and 10 L/min operations

24

494

[Figure 8]. While local variations of both current density and fluid velocity were observed to

495

greatly increase with decreasing inter-electrode gaps, indicating more unfavorable process

496

conditions with respect to the electrochemical efficiency of electrode exhaustion, these

497

conditions provided greater removal of organic matter. As the inter-electrode gap decreased from

498

10, 2 and 1 mm, the DOC was observed to increase 16, 29 and 46%, respectively. While areas on

499

the electrode with greater current density will be more rapidly exhausted, leading to uneven

500

electrode dissolution, conditions provided a greater capacity to reduce DOC, which can be

501

attributed to the effect of current density on the speciation of iron hydroxide coagulants, which

502

have varying affinities to function as coagulants (Dubrawski and Mohseni, 2013a). Other

503

variables that will differ when changing the inter-electrode gap that can influence the selectivity

504

of iron hydroxide species synthesis include anode potential and [Fe(II)]:[Fe(III)] ratio, as well as

505

the pH and concentration of dissolved oxygen (Cornell and Schwertmann, 2003). The DO can

506

vary even in synthetic water matrices during experimental investigations due to both atmospheric

507

influx, as well as the oxygen evolution reaction at the anode surface. Localized pH can also vary

508

due to current density, whereby higher current results in greater pH. Previous studies have been

509

conducted by this group investigating the iron speciation under a 99.99% N2 blanket to prevent

510

an atmospheric influx of DO, while monitoring it’s concentration in the water (Dubrawski and

511

Mohseni, 2013a). In low DO conditions, green rust was found to form resulting in favorable

512

NOM removal, while higher DO conditions led to lepidocrocite (γ-FeOOH) and decreased NOM

513

removal. While the current study did not include a speciation analysis, it would be important to

514

control and monitor DO and pH for such an investigation.

515

25

516 517 518 519

Fig. 8. DOC reductions of 1, 2, 10 mm inter-electrode gap EC operations at similar metal loadings (1.35 L/min → 25.7 mg/L – synthetic waters, 10 L/min → 27.8 mg/L – raw waters).

520

The same trends in DOC reduction, with respect to the inter-electrode gaps, were yielded

521

when varying the metal loading. In addition to 25.7 mg/L, metal loadings of 38.3 and 51.1 mg/L

522

were investigated by applying a constant current of 3.0 and 4.0 A, respectively. As expected,

523

DOC was observed to reduce as the dosing of coagulant (metal loading) increased, however

524

greater reductions were yielded when operating at smaller inter-electrode gaps [see Figure 9].

525

Particularly for higher metal loadings of 38.3 and 51.1 mg/L, 1 mm inter-electrode gap

526

experiments yielded DOC reductions 79 and 59% greater, respectively, and 75 and 56% greater

527

at 2 mm, respectively.

528

529

26

530 531 532

Fig. 9. DOC reductions of 1, 2, 10 mm inter-electrode gap EC operations at 25.7, 38.3 and 51.1 mg/L metal loadings (1.35 L/min flow rate, synthetic waters).

533

534

Again, while larger inter-electrode gaps did provide greater current distribution and water

535

velocity distribution, it resulted in greatly decreased pollutant removal. As seen in Figure 9, at all

536

three metal loadings investigated, significant decreases in DOC were achieved as the inter-

537

electrode gap decreased from 10 to 2 and 1 mm. This difference in contaminant removal was

538

particularly evident at greater metal loadings experiments, whereby a 10 mm gap yielded less

539

than 10 and 30% reductions of DOC when operating at 38.3 and 51.1 mg/L dosing, respectively.

540

When inter-electrode gaps were decreased to 1 and 2 mm, these same metal loading conditions

541

provided over 80% reductions of DOC. These results highlight the tradeoff that arises when

542

increasing the inter-electrode gap; although larger gaps provide more evenly distributed fluid

543

flow and consequently more homogeneously distributed current density, natural organic matter

544

removal is significantly hindered, like due to lower current density and iron dissolution.

545

Moreover, this increased current distribution was at the expense of a greatly decreased overall

546

current density, resulting in a much more energy intensive process. The combination of the 27

547

current density, fluid dynamics and treatment investigations highlights the importance of further

548

research to refine the EC process. While treatment results highlight EC’s efficiency of removing

549

NOM from surface waters, the electrochemical and transport phenomena studies emphasize the

550

importance of reactor design; a paradox can exist in the conditions which yield the required

551

pollutant removal at low energy requirements, with those that provide a robust system which

552

maximizes the efficient utilization of the entire electrode surface. Although the latter is

553

overlooked by most EC research to date, its consideration will be required in order for the

554

technology to be widely considered by industry for a drinking water treatment application.

555

556

4.

Conclusion

557

In summary, an in-situ technique for the determination of current density distribution for an EC

558

process was employed, in conjunction with mathematical and computational fluid dynamic

559

modeling for iron dissolution and water velocity variation analysis, respectively. The current

560

density data agreed well with the models, whereby areas of high current density were inversely

561

correlated to areas of low velocity fluid flow and consequently, increased Fe2+ dissolution. As

562

the inter-electrode gap increased, water velocity variations significantly decreased, resulting in

563

significantly increased current density uniformity. From the current distribution data, a more

564

accurate view of iron dissolution performance is attained, whereby local Fe2+ dissolution rates

565

could be determined (as opposed to overall metal loading rates typically reported in EC

566

literature). During 1 mm inter-electrode gap operations, current and water velocity variations

567

were ∆27.6 mA/cm2 and ∆0.220 m/s respectively. When the inter-electrode gap increased to 10

568

mm, this variance decreased to ∆3.6 mA/cm2 and ∆0.062 m/s. This increased current uniformity

569

did have consequences on the overall achievable current density however, due to the greatly

28

570

increased ohmic resistance associated with the larger gap. In addition to decreased current

571

density, the associated increase in electrical potential greatly increases operating energy

572

requirements. Furthermore, NOM removal suffered at larger inter-electrode gaps, whereby DOC

573

removal was observed to increase from 16, 29 and 46%, during 10, 2 and 1 mm operations.

574

575

Acknowledgments

576

The authors would like to acknowledge RES’EAU-WaterNET for financial support, CMC

577

Microsystems for the provision of COMSOL Multiphysics license, as well as Van Anda

578

Improvement District for their hospitality during our on-site pilot research within their

579

community and water supply.

580

29

581

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582

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Highlights • • • • •

Parametric analysis of an electrocoagulation reactor for water treatment In-situ technique for determining current density distribution is demonstrated CFD and theoretical models support experimental water flow and current distributions Localized water flow and electrode gap strongly effect metal dissolution uniformity Electrocoagulation reactor design considerations discussed for contaminant removal

Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: