Integration of ferrate (VI) pretreatment and ceramic membrane reactor for membrane fouling mitigation in reclaimed water treatment

Journal of Membrane Science 552 (2018) 315–325

Contents lists available at ScienceDirect

Journal of Membrane Science journal homepage: www.elsevier.com/locate/memsci

Integration of ferrate (VI) pretreatment and ceramic membrane reactor for membrane fouling mitigation in reclaimed water treatment

T

⁎

Jing Liua,b,c, Zhenghua Zhanga,b,c, , Zhenyang Liua,b,c, Xihui Zhanga,b,c,d a

Research Institute of Environmental Engineering & Nano-Technology, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, Guangdong, China School of Environment, Tsinghua University, Beijing 100084, China c Guangdong Provincial Engineering Research Center for Urban Water Recycling and Environmental Safety, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, Guangdong, China d Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen 518055, Guangdong, China b

A R T I C L E I N F O

A B S T R A C T

Keywords: Reclaimed water Ferrate (VI) Membrane fouling Redundancy analysis Clustering correlation analysis

Ferrate (VI) is a unique and “green” chemical that can be utilized for oxidation, disinfection and coagulation simultaneously in a single unit without producing by-product. Herein, for the first time, we reported the integrated process of ferrate (VI) pretreatment coupled with ceramic membrane reactor for mitigating membrane fouling in natural reclaimed water treatment. Membrane fouling was effectively mitigated by ferrate pretreatment with the maximum trans-membrane pressure (TMP) reduction of 81.8% achieved at ferrate dosage of 0.15 mM. Moreover, the fouling mechanism changed from intermediate-standard blocking to cake-intermediate blocking with ferrate pretreatment and the contribution of cake layer fouling was significantly diminished with increase of ferrate dosage (≤ 0.15 mM). Statistical analysis including redundancy analysis and clustering correlation analysis showed that chemical oxygen demand (COD), dissolved organic carbon (DOC) and polysaccharide were the most important positive factors to Rt with their correlation coefficients above 0.92 while SS and turbidity were the most important negative factors to Rt with their correlation coefficients below − 0.87. Long-term filtration experiments also confirmed the membrane fouling control performance by ferrate with the significant extension of the onset of membrane fouling.

1. Introduction Nowadays, municipal wastewater reclamation has been attracting more and more attentions due to the increasing severe water scarcity problem [1]. Ultrafiltration (UF) membrane has been applied widely for reclaimed water treatment with the main advantages of better water quality and less footprint compared to the conventional processes such as sedimentation and sand-filtration processes [2,3]. Compared to polymeric UF membrane, ceramic UF membrane has many advantages including robust mechanical, thermal and chemical stability, long lifespan and high hydrophilicity [4–6]. However, membrane fouling is still a big issue limiting the wide applications of membrane technologies. For reclaimed water treatment, natural organic matters (NOM) and suspended solids (SS) in the secondary effluent would be the main foulants for membrane fouling [7–9]. Coagulants have been widely used in the pretreatment process of membrane filtration to mitigate fouling and improve general water quality [10–13]. However, not all organics can be fully removed by

coagulants as coagulants usually have limited removal performance of organics with low and medium molecular weight (MW) and the remaining organics in water would still induce membrane fouling [14]. As such, the combined pretreatment processes of oxidation and coagulation has been of particular interest to further remove organics and control membrane fouling in water treatment. For instance, the combination of permanganate oxidation and aluminum coagulation as the pretreatment processes prior to membrane filtration facilitated the removal of algal extracellular organic matters (EOM) and membrane fouling control [15]. Meanwhile, the combination of ozone and coagulation hindered the accumulation of organic matters in membrane pores with the dramatically lower membrane fouling rate [16]. Ferrate (VI) is a unique and “green” chemical that can be utilized for oxidation, disinfection and coagulation simultaneously in a single unit without producing by-product [17]. Ferrate (VI) has a superior oxidation and reduction capacity especially at acidic conditions (E0=2.20 V) [18] and ferric hydroxide, a strong coagulant, is in-situ formed during the oxidation and disinfection processes of ferrate (VI) [19]. In recent

⁎ Corresponding author at: Research Institute of Environmental Engineering & Nano-Technology, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, Guangdong, China. E-mail address: [email protected] (Z. Zhang).

https://doi.org/10.1016/j.memsci.2018.02.031 Received 16 December 2017; Received in revised form 10 February 2018; Accepted 11 February 2018 Available online 14 February 2018 0376-7388/ © 2018 Elsevier B.V. All rights reserved.

Journal of Membrane Science 552 (2018) 315–325

J. Liu et al.

Nomenclature COD DOC E0 EDX EEM EOM KMO MW NOM PFS

RDA SS SEM SSE

chemical oxygen demand dissolved organic carbon redox potential energy-dispersive X-ray excitation-emission matrix spectra extracellular organic matters Kaiser-Meyer-Olkin molecular weight natural organic matters polyferric sulfate

SMP TN TP TMP ΔTMP UF WWTP

redundancy analysis suspended solid scanning electron microscopy sum of squares of difference between experimental data and fitted values soluble microbial products total nitrogen total phosphorus transmembrane pressure normalized transmembrane pressure ultrafiltration wastewater treatment plant

2. Materials and methods

years, ferrate (VI) has gained increasing attention in water and wastewater treatment partially due to the recent advances of synthesis. It was reported that ferrate (VI) has the extraordinarily strong capability in removing organic matters in water and wastewater (not involving membrane filtration) [19–22]. In terms of the performance of ferrate (VI) for UF membrane fouling control, there were only two studies up to now in which polymeric UF membrane filtration was used for synthetic water and wastewater treatment. One study reported that the combined usage of polyferric sulfate (PFS) (1.2 mM) and ferrate (0.5 mM) for Reactive Black W-2N removal in synthetic wastewater also alleviated membrane fouling [23]. The other study demonstrated that the combined usage of FeCl3 (0.12 mM) and ferrate (0.03 mM) effectively mitigated membrane fouling in synthetic drinking water treatment [14]. In natural reclaimed water treatment, however, utilization of ferrate (VI) coupled with ceramic membrane reactor for ceramic membrane fouling mitigation has not been evaluated up to now. In this study, for the first time, the effect of ferrate (VI) on membrane fouling in natural reclaimed water treatment using the integrated process of ferrate (VI) pretreatment coupled with ceramic membrane reactor was investigated by assessing 1) membrane fouling control performance; 2) fouling layer characteristics; 3) characterization of influent and effluent; 4) quantitatively statistical analysis between membrane foulants and fouling resistances; 5) modeling analysis for membrane fouling mechanism; and 6) long-term operation performance.

2.1. Chemical and feed water sampling Potassium ferrate (K2FeO4) (90.4%, analytical grade) used in the study was purchased from Huayueyang Biotechnology Co., Ltd., China. The feed for ferrate pretreatment was collected from the secondary effluent after disinfection of Xili Wastewater Treatment Plant (WWTP) in Shenzhen, China, in which biological aerated filter was applied to treat the municipal wastewater without any coagulants dosing. Note that the Fe concentration in the feed before ferrate pretreatment can be neglected with the value below 0.01 mg/L. 2.2. Experimental set-up and procedure The schematic diagram of the integrated process of ceramic membrane reactor coupled with ferrate pretreatment is show in Fig. 1. Ferrate pretreatment of feed with different dosages of 0, 0.05, 0.065, 0.1, 0.15, 0.2 mM (one-off dosing) was implemented with stirring at 200 rpm for 30 min prior to pumping to the ceramic membrane reactor. The cubic plexiglass ceramic membrane reactor has two units, stirring unit (5 L) and ceramic membrane separation unit (10 L). The stirring unit has an inner dimension of 112.8 mm (length) × 80 mm (width) × 500 mm (height) with the stirring speed of 200 rpm to ensure that the influent entering to the ceramic reactor was well mixed. The cubic membrane separation unit has an inner dimension of 250 mm

Fig. 1. Schematic diagram of the integrated process of ferrate pretreatment coupled with ceramic membrane reactor. Note that the feed for ferrate pretreatment was collected from the secondary effluent after disinfection of local WWTP.

316

Journal of Membrane Science 552 (2018) 315–325

J. Liu et al.

(length) × 80 mm (width) × 500 mm (height) and a flat sheet Al2O3 ceramic UF membrane module (120 mm (length) × 9 mm (width) × 280 mm (height)) with an average pore size of 100 nm and active area of 0.0425 m2 (Meidensha Corporation, Japan) was vertically fixed in the membrane separation unit. An intermittent mode with on/ off ratio of 9 min: 1 min was adopted by the peristaltic pump to withdraw the effluent from the membrane module under a constant flux of 90 L/(m2 h). A pressure gauge (GC31-180, Nagano Keiki, Japan) was placed between the membrane reactor and the suction pump to keep track of the trans-membrane pressure (TMP) with the pressure gauge connecting to a computer with a data acquisition system which recorded the TMP data every ten seconds. Under constant flux, membrane fouling can be evaluated by the increase of TMP. Herein, normalized TMP (ΔTMP) was used to indicate the gap between the final TMP and the initial baseline. All filtration experiments were run in triplicate under room temperature ranging from 22 to 25 °C.

cake layer and was calculated by the resistances before and after physical cleaning. Rgel is the resistance of gel layer and was calculated by the resistances before and after chemical cleaning. Rpore is the resistance of pore blocking and was calculated based on Eq. (2). 2.4. Water quality analysis Water samples were filtered through 0.45 µm membrane filters (MICROPES, JINTENG, China) before analysis. The size fractionated (≤ 0.45 µm) dissolved organic carbon (DOC) and total nitrogen (TN) were analyzed by a total organic carbon analyzer (TOC-VCSH, Shimadzu, Japan). Chemical oxygen demand (COD) based on standard potassium dichromate method and total phosphorus (TP) based on molybdenum-antimony anti-spectrophotometric method were measured by the APHA Standard Method [25]. UV254 adsorption was measured by the UV spectroscopy (UV-1700, Shimadzu, Japan) at wavelength of 254 nm. Protein concentration was measured by the modified Lowery method using bovine serum albumin (BSA) as the standard [26,27]. Polysaccharide concentration was measured using sulfuric acid and phenol with D-glucose as the standard. Turbidity was measured by a turbidimeter (2100Q, Hach, USA) [28]. SS was measured based on the oven-drying method using an electro-thermostatic blast oven at 105 °C (DHG-9141A, Shanghai Honghua Instruments Co. Ltd, China). The particle size of flocs was measured by Nanosight (NS300, Malvern Instruments Ltd, UK). Zeta potential was determined by Zeta Sizer (Nano-Z, Malvern Instruments Ltd, UK). Fluorescence excitation-emission matrix (EEM) spectra were measured using a fluorescence spectrometer (F-7000, Hitachi, Japan). The excitation spectra was scanned from 220 to 450 nm at 5 nm increment and the emission spectra was scanned from 240 to 600 nm at 1 nm increment. Five regions of the EEM spectra can be divided including region I (Ex/Em: 220–250/280–330 nm) and region II (Ex/Em: 220–250/330–380 nm) (aromatic protein), region III (Ex/Em:

2.3. Membrane cleaning strategy and resistance calculation Physical cleaning (rinsed by 100 mL Milli-Q water) followed by chemical cleaning (soaked in 500 mL NaOH solution (0.1 mM) for 24 h and then 500 mL HCl (0.1 mM) for 12 h) were conducted for the fouled ceramic membrane after each filtration test. The resistances of cake layer, gel layer and pore blocking were calculated from TMP and flux data using Darcy's Law [24]:

Rtotal =

TMP μJ

(1)

Rtotal = R cake + Rgel + Rpore + Rm

(2)

where J is the permeate flux (90 L/(m h)); μ is the viscosity of water at 25 °C (0.8949 × 10−3 N s/m2). Rtotal is the total ceramic membrane resistance after filtration and was determined by the final TMP (Eq. (1)). Rm is the intrinsic membrane resistance. Rcake is the resistance of 2

a

1.8

0 mM 0.05 mM 0.065 mM 0.1 mM 0.15 mM 0.2 mM

30 25 20

Resistance (1012 m-1)

Normalised TMP (kPa)

35

15 10

b

1.6 1.4

0 0

Rgel

Rpore

1.2 1.0 0.8 0.6 0.4

1

2

3

4

5

6

7

8

0.005 0.000

0

Time (h)

c

0.05 0.065

0.1

0.15

0.2

Ferrate dosage (mM)

Cake layer

10

Gel layer

Concentration (mg/L)

DOC concentration (mg/L)

Rcake

0.2

5

18

Rtotal

15 12 9 6 3

d

Protein

Polysaccharide

8 6 4 2 0

0

0

0.05 0.065

0.1

0.15

0

0.2

0.05

0.065

0.1

0.15

0.2

Ferrate dosage (mM)

Ferrate dosage (mM)

Fig. 2. Effect of ferrate dosage on normalized TMP (a), fouling resistance (b), DOC of cake and gel layers (c), and concentrations of protein and polysaccharide in cake layer (d).

317

Journal of Membrane Science 552 (2018) 315–325

J. Liu et al.

Fig. 3. SEM images of the ceramic membrane surface after filtration with different dosages of ferrate pretreatment. (a) virgin membrane surface; (b) magnified virgin membrane surface; (c) fouled membrane surface without ferrate; (d) fouled membrane surface with 0.05 mM ferrate; (e) fouled membrane surface with 0.065 mM ferrate; (f) fouled membrane surface with 0.1 mM ferrate; (g) fouled membrane surface with 0.15 mM ferrate; (h) fouled membrane surface with 0.2 mM ferrate.

More operational conditions were described in our previous studies [30,31].

Table 1 Porosity of the ceramic membrane surface with different dosages of ferrate pretreatment. Virgin membrane

0 mM

0.05 mM

0.065 mM

0.1 mM

0.15 mM

0.2 mM

40.05%

3.92%

8.83%

11.13%

17.24%

20.42%

12.29%

2.5. Surface characteristics of membrane fouling layer The surface morphology and element components of the virgin and fouled ceramic membranes were analyzed by scanning electron microscopy (SEM) (SU8010, HITACHI, Japan) and energy-dispersive X-ray (EDX) spectroscopy (550i, IXRF, America), respectively. Moreover, the surface porosity of the virgin and fouled ceramic membranes was determined by Image-Pro plus software based on the SEM images [32].

220–250/380–480 nm) (fulvic acid-like substances), region IV (Ex/Em: 250–440/280–380 nm) (soluble microbial products (SMP)) and region V (Ex/Em: 250–400/380–540 nm) (humic-like substances) [29]. The MW distribution was determined using a high performance liquid chromatography system (LC-20AT, Shimadzu, Japan) coupled with an on-line UV detector (SPD-M20A, Shimadzu, Japan) with the wavelength of 254 nm using an exclusion column (TSK-Gel G3000PWXL, Japan). The column temperature was set at 40 °C. Sodium polystyrene sulphonate standards (208 Da, 4230 Da, 6430 Da, 10,000 Da, 14,900 Da, 75,600 Da, German Polymer Standards Service GmbH) were adopted to calibrate the MW distribution of UV254.

2.6. Statistical analysis for membrane fouling Statistical analysis including redundancy analysis (RDA) and clustering correlation analysis were adopted to analyze the quantitative correlation between membrane fouling resistances (total resistance, cake resistance and gel resistance) and influent characteristics (COD, 318

Journal of Membrane Science 552 (2018) 315–325

20

Influent Effluent

a

DOC concentration (mg/L)

COD concentration (mg/L)

J. Liu et al.

18 16 14 12

5.0

Influent Effluent

b 4.5

4.0

3.5

3.0

10 0.00

0.05

0.10

0.15

0.00

0.20

0.07

TP concentration (mg/L)

UV254 (cm-1)

0.15

0.20

Influent Effluent

d

0.06

0.05

0.04

0.03

0.3

0.2

0.1

0.0 0.00

0.05

0.10

0.15

0.00

0.20

Influent Effluent

e 3.0

2.5

2.0

1.5 0.00

0.05

0.10

0.15

0.20

Polysaccharide concentration (mg/L)

3.5

0.05

0.10

0.15

0.20

Ferrate dosage (mM)

Ferrate dosage (mM)

Protein concentration (mg/L)

0.10

0.4

Influent Effluent

c

0.05

Ferrate dosage (mM)

Ferrate dosage (mM)

5

Influent Effluent

f 4

3

2

1 0.00

0.05

0.10

0.15

0.20

Ferrate dosage (mM)

Ferrate dosage (mM)

Fig. 4. Effect of ferrate dosage and ceramic membrane filtration on the concentrations of COD (a), DOC (b), UV254 (c), TP (d), protein (e), and polysaccharide (f).

individual fouling models (standard blocking, intermediate blocking, cake blocking and complete blocking) and five combined fouling models (cake-standard, cake-intermediate, cake-complete, completestandard, intermediate-standard) were utilized to fit the experimental data [34–36] with SSE (sum of squares of difference between experimental data and fitted values) indicating the modeling fitting performance.

DOC, EEM, polysaccharide, protein, SS, turbidity, particle size, zeta potential and UV254) by software CANOCO version 4.5. There was only one principal component extracted, which could explain 95.8% of the total variance and represent the linear combination for the influent characteristics (COD, DOC, EEM, polysaccharide, protein, SS, turbidity, particle size, zeta potential and UV254) (Table S1) according to KMO (Kaiser-Meyer-Olkin)-statistic (0.905) and spherical validation of Bartlett (0.001) attained by principal component analysis using software IMB SPSS Statistics version 20.0. Therefore, a linear model was adopted for RDA analysis and more details of RDA analysis could be found in our most recent study [33]. Meanwhile, clustering correlation analysis was further performed to quantitatively analyze the correlation between fouling resistances and influent characteristics (COD, DOC, EEM, polysaccharide, protein, SS, turbidity, particle size, zeta potential and UV254) by software Language R and thus the dominating foulants could be identified.

2.8. Long-term operation Long-term filtration experiments were implemented at the low filtration flux of 30 L/(m2 h) to further verify the ceramic membrane fouling control performance by ferrate with ferrate pretreatment at the optimum dosage of 0.15 mM and without ferrate pretreatment. Once the normalized TMP reached 30 kPa, the fouled ceramic membrane was rinsed by MQ-water to restore the membrane filterability. After MQwater rinsing, the ceramic membrane was continuously running and the irreversible fouling including gel layer and pore blocking kept on increasing. The long-term filtration experiments lasted for 15 days for the control sample without ferrate pretreatment and 60 days for the sample

2.7. Modeling analysis for membrane fouling Nine constant flow fouling models (Table S2) including four 319

Journal of Membrane Science 552 (2018) 315–325

Turbidity

10

10

8

8

6

6

4

4

2

2

0

5

12

0 0.00

0.05

0.10

0.15

b

Influent

5 4

3

3

2

2

1

1 0

0

0.20

0.00

0.05

0.10

0.15

0.20

Ferrate dosage (mM) -8

Average particle size

Zeta potential (mv)

Average particle size (nm)

c

Turbidity

4

Ferrate dosage (mM) 260

SS

Effluent

240 220 200 180

d Influent

Zeta potential

pH

7.6 7.4

-9

7.2 -10

7.0 6.8

-11

pH

SS

SS concentration (mg/L)

a Influent

Turbidity (NTU)

SS concentration (mg/L)

12

Turbidity (NTU)

J. Liu et al.

6.6

-12

160

6.4 -13

140 0.00

0.05

0.10

0.15

6.2 0.00

0.20

0.05

0.10

0.15

0.20

Ferrate dosage (mM)

Ferrate dosage (mM)

Fig. 5. Effect of ferrate dosage and ceramic membrane filtration on the properties of reclaimed water: SS and turbidity – Influent (a), SS and turbidity – Effluent (b), the average particle size – Influent (c), and zeta potential and pH – Influent (d).

fouled ceramic membrane surfaces were covered with a thick layer of foulants. Meanwhile, the porosity of the ceramic membrane surface decreased from 40.1% (virgin ceramic membrane) to 3.9% (fouled ceramic membrane without ferrate pretreatment) (Table 1), which would induce the remarkable reduction of membrane filterability and the sharp increase of TMP (Fig. 2a). However, the fouling layer deposited on the membrane surface became porous with ferrate pretreatment (Fig. 3) and the porosity increased from 3.9% (0 mM) to 20.4% (0.15 mM) (Table 1), which was in line with the TMP reduction results that the ΔTMP decreased from 30.8 kPa (0 mM) to 5.6 kPa (0.15 mM) (Fig. 2a). Moreover, the further increase of ferrate dosage (0.2 mM) resulted in a lower porosity (12.3%), which was in line with the results of TMP, resistances and concentrations of organics in the fouling layer (Fig. 2) and was further discussed in the later section.

with 0.15 mM ferrate pretreatment with the resistances of irreversible fouling after filtration contributing over 50% of the total resistance, which required chemical cleaning.

3. Results and discussion 3.1. Membrane fouling control performance Fig. 2 shows the ceramic membrane fouling control performance and characteristics of fouling layers with ferrate pretreatment during the filtration experiment. As shown in Fig. 2a, the control sample without ferrate pretreatment had the fastest fouling rate (dTMP/dt) with the ΔTMP (the gap between the final TMP and the initial baseline) of 30.8 kPa after 7.5 h filtration. In contrast, membrane fouling was significantly alleviated with ferrate pretreatment and the best fouling control performance was achieved at ferrate dosage of 0.15 mM with the maximum ΔTMP reduction of 81.8%. The ΔTMP decreased to 24.6, 15.5, 7.3, 5.6, 11.5 kPa after 7.5 h filtration with ferrate dosages of 0.05, 0.065, 0.1, 0.15, 0.2 mM, respectively. The fouling resistances of different fouling layers with different dosages of ferrate pretreatment are shown in Fig. 2b. Cake layer and gel layer resistances primarily dominated the membrane fouling resistances. All resistances including the resistances of cake layer, gel layer and pore blocking decreased significantly with increase of ferrate dosage (≤ 0.15 mM). The maximal reductions of cake layer resistance of 77.6% and gel layer resistance of 91.3% were achieved at ferrate dosage of 0.15 mM. Meanwhile, the concentrations of DOC, protein and polysaccharide in cake layer and gel layer decreased with increase of ferrate dosage (≤ 0.15 mM) as shown in Figs. 2c and 2d. It is interesting to note that the concentrations of these organics in cake layer and gel layer were higher at ferrate dosage of 0.2 mM compared to the case with 0.15 mM ferrate, which was in line with the TMP results (Fig. 2a) and was further discussed in the later section. The SEM images of the ceramic membrane surface after filtration with different dosages of ferrate pretreatment are shown in Fig. 3. Compared to the porous surface of the virgin ceramic membrane, the

3.2. Characterization of influent and effluent The effect of the integrated process of ferrate (VI) pretreatment coupled with ceramic membrane reactor with different ferrate dosages of 0, 0.05, 0.065, 0.1, 0.15, 0.2 mM on influent and effluent is shown in Fig. 4. The concentrations of COD, DOC, UV254, protein and polysaccharide effectively decreased with increase of ferrate dosage and the maximal removal efficiencies of 30.8% (COD), 25.5% (DOC), 46.1% (UV254), 60.2% (polysaccharide) and 18.7% (protein) in the influent were achieved at ferrate dosage of 0.2 mM. Chemical oxidation and coagulation are the main mechanisms for organics removal by ferrate. The generation of Fe(V) and Fe(IV) with strong oxidation capacity via 1-e- (Fe(VI) → Fe(V) → Fe(III)) and 2-e- transfer processes (Fe(VI) → Fe (IV) → Fe(II)) during ferrate-organics reactions would facilitate the removal of organics [37]. Meanwhile, reactive oxygen species produced from self-decomposition of ferrate could also easily react with organics [38]. Moreover, ferric hydroxide, a strong coagulant, would be in-situ formed during the oxidation and disinfection processes of ferrate [19], which also further removed organics. However, it is technically difficult to discern the contributions of oxidation and coagulation in organics removal with ferrate dosing [39]. The above results indicated that 320

Journal of Membrane Science 552 (2018) 315–325

J. Liu et al.

420

420

380

b

0.000 200.0

Ferrate: 0 mM

400.0 600.0

Excitation (nm)

Excitation (nm)

a

800.0 1000

340

1200 1400 1600

300

1800 2000 2200

260

380

0.000 200.0

Ferrate: 0.05mM

400.0 600.0 800.0 1000

340

1200 1400 1600

300

1800 2000 2200

260

2400

2400

2600

2600

2800

220 280

320

360

400

440

480

520

560

2800

220 280

3000

320

Emission (nm) 420

c

0.000 200.0

Ferrate: 0.065mM

Excitation (nm)

400

440

480

520

560

380

400.0

380

600.0 800.0 1000

340

1200 1400 1600

300

1800

d

0.000 200.0

Ferrate: 0.1 mM

400.0 600.0 800.0 1000

340

1200 1400 1600

300

1800 2000

2000 2200

260

2200

260

2400

2400 2600

2600 2800

220 280

320

360

400

440

480

520

560

2800

220 280

3000

320

400

440

480

520

560

f

0.000 200.0

380 Ferrate: 0.15mM

400.0 600.0 800.0 1000

340

1200 1400 1600

300

1800

380

0.000 200.0

Ferrate: 0.2mM

400.0 600.0 800.0 1000

340

1200 1400 1600

300

1800

2000

2000

2200

260

2200

260

2400

2400

2600

220 280

3000

420

e

Excitation (nm)

Excitation (nm)

360

Emission (nm)

Emission (nm) 420

3000

Emission (nm)

Excitation (nm)

420

360

2600

2800

320

360

400

440

480

520

560

220 280

3000

Emission (nm)

2800

320

360

400

440

480

520

560

3000

Emission (nm)

Fig. 6. Effect of ferrate dosage on fluorescence EEM spectra of the influent. (a) without ferrate; (b) with 0.05 mM ferrate; (c) with 0.065 mM ferrate; (d) with 0.1 mM ferrate; (e) with 0.15 mM ferrate; and (f) with 0.2 mM ferrate. (I: Ex/Em = 220–250/280–330 nm; II: Ex/Em = 220–250/330–380 nm; III: Ex/Em = 220–250/380–480 nm; IV: Ex/Em = 250–440/ 280–380 nm; V: Ex/Em = 250–400/380–540 nm).

ferrate significantly improved the TP removal with the minimum TP concentration of 0.03 mg/L in the effluent achieved at ferrate dosage of 0.2 mM. However, ferrate had negligible effect on TN removal (Fig. S1), and the similar results were also reported in other studies [42,43]. Meanwhile, both SS and turbidity in the influent increased with increase of ferrate dosage (Fig. 5a). After ceramic membrane filtration, however, the concentration of SS remained below 1.2 mg/L and turbidity was under 0.3 NTU in the effluent (Fig. 5b). Additionally, both the average particle size and zeta potential of the influent increased with increase of ferrate dosage. The particle size at ferrate dosage of 0.2 mM was almost doubled compared to that of the control sample without ferrate dosage (Fig. 5c), which was in line with the zeta

ferrate had higher removal efficiency on UV254 than DOC and similar removal results were also reported in the case of synthetic drinking water treatment with ferrate dosage [40]. As an efficient oxidant, ferrate preferentially attacks electron-rich organic moieties in NOM such as conjugated C˭C double bounds and aromatic structures by electrophilic oxidation [41], as such, significant reduction of UV254 was achieved [40]. Moreover, as an efficient coagulant, ferrate could destabilize colloidal particles in less than 1 min, which would also facilitate the removal of organics especially polysaccharide in this case [19]. Additionally, ceramic membrane also facilitated the further removal of organics with the further decrease of the concentrations of COD, DOC, UV254, protein and polysaccharide in the effluent. Moreover, 321

Journal of Membrane Science 552 (2018) 315–325

UV254 abs intensity (×103 AU)

J. Liu et al.

10

Ferrate dosage 0 mM 0.05 mM 0.065 mM 0.1 mM 0.15 mM 0.2 mM

a

8 Humic like substance

6 4

Low MW organic matter

Biopolymer

2 0 10

100

1000

10000 100000 1000000

Molecular weight (Da)

Removal efficiency (%)

100

b

Ferrate dosage

80 60

0.05 mM 0.065 mM 0.1 mM 0.15 mM 0.2 mM

40 20 0

0.005-0.35

0.35-20

20-2000

Molecular weight (kDa) Fig. 7. Effect of ferrate dosage on molecular weight (MW) distribution (a) and removal efficiency (b) of UV254 of the influent.

potential results (Fig. 5d) that the zeta potential increased from − 13.6 mV (control sample) to − 8.3 mV (ferrate dosage of 0.2 mM). The fluorescence EEM spectra results of the influent with different dosages of ferrate pretreatment are shown in Fig. 6. The control sample without ferrate dosage consisted of aromatic protein (region I and region II) (46.6%), fulvic acid-like substances (region III) (16.6%), SMPlike substances (region IV) (25.3%) and humic-like substances (region V) (11.5%) (Fig. S2). With increase of ferrate dosage, the fluorescent intensity of regions III, IV and V effectively decreased while limited intensity reduction of regions I and II was achieved. Ferrate at 0.2 mM had the greatest removal efficiency of SMP (region IV) (25.1%), fulvic acid-like substances (region III) (20.0%), humic-like substances (region V) (15.8%) and aromatic protein-like substances (regions I and II) (7.0%) (Fig. S2). The poor EEM removal performance of aromatic protein was consistent with the results in previous studies [22,40] that ferrate (VI) oxidation showed high selectivity in removing two-ring and three-ring fluorescing aromatics such as fulvic acid-like substances (region III) and humic-like substances (region V) while ferrate (VI) had limited oxidation of aromatic protein-like substances especially in region I. The MW distribution of UV254 of the influent without and with ferrate dosage is shown in Fig. 7. The control sample without ferrate dosage mainly contained very high MW biopolymers (20,000–2000,000 Da), medium MW substances (350–20,000 Da) and low MW substances (below 350 Da) (Fig. 7a). With increase of ferrate dosage, significant reduction of very high MW biopolymers was achieved compared to the limited reduction of low and medium MW substances with the maximal removal efficiency of very high MW biopolymers (20,000–2,000,000 Da) of 98.9% achieved at 0.2 mM (Fig. 7b). These very high MW biopolymers might

Fig. 8. The statistical correlation of membrane fouling resistances (total resistance, cake resistance and gel resistance) and influent characteristics (COD, DOC, EEM, polysaccharide, protein, SS, turbidity, particle size, zeta potential and UV254). Redundancy analysis (a) and clustering correlation analysis (b).

belong to the SMP with conjugated C˭C double bounds and/or aromatic structures (Fig. 6) and ferrate preferentially attacks electron-rich organic moieties in NOM such as conjugated C˭C double bounds and aromatic structures by electrophilic oxidation [41] with the significant reduction of UV254 achieved [40]. It is interesting to note that low and medium MW substances rather than very high MW biopolymers of UV254 are more easily to be removed by ferrate (VI) in the case of synthetic drinking water treatment with ferrate dosage [14]. This is understandable in their case because there was negligible UV254 adsorption for the very high MW biopolymers while extremely high UV254 adsorption for the low and medium MW substances in the synthetic drinking water [14]. 3.3. Statistical analysis of membrane fouling The quantitative correlation between membrane fouling resistances (total resistance, cake resistance and gel resistance) and influent characteristics (COD, DOC, EEM, polysaccharide, protein, SS, turbidity, particle size, zeta potential and UV254) with ferrate pretreatment was further elucidated by redundancy analysis (RDA) (Fig. 8a) and clustering correlation analysis (Fig. 8b). As shown in Fig. 8a, the first axis and second axis of RDA explained 99.1% and 0.9% of the total variance, 322

Journal of Membrane Science 552 (2018) 315–325

J. Liu et al.

5.5 5.0 4.5

P/P0

4.0 3.5 3.0 2.5 2.0

a

Experimental data 0 mM 0.05 mM 0.065 mM 0.1 mM 0.15 mM 0.2 mM Model fit 0 mM 0.05 mM 0.065 mM 0.1 mM 0.15 mM 0.2 mM

of the effective decrease of organics (Figs. 4, 6 and 7) and the increased particle size of SS (Fig. 5c) in the influent. 3.4. Modeling of membrane filtration process In order to further understand the fouling mitigation mechanism with ferrate pretreatment, modeling including four constant flow single fouling models and five constant flow combined fouling models (Table S2) was utilized to fit the P/P0 versus time data for the membrane filtration process with different dosages of ferrate pretreatment (Fig. 9a). For the control sample without ferrate dosage, intermediate-standard model best fitted the experimental data with the SSE of 0.04 and R2 of ~ 1 (Tables S3 and S4). Additionally, the contributions of intermediate and standard blockings can be evaluated from the magnitude of the fitted parameters [34]. For the control sample, the ratio of Ki/Ks was ~ 10.5, indicating that intermediate blocking played a much more important role during the filtration process without ferrate pretreatment. With ferrate pretreatment, the fouling mechanism changed from intermediate-standard blocking to cake-intermediate blocking with the SSE less than 0.19 and R2 of ~ 1 (Tables S3 and S4). Moreover, the contribution of cake layer fouling was significantly diminished with increase of ferrate dosage as indicated by the ratio of Kc*J/Ki (Fig. 9b). The lowest ratio of Kc*J/Ki was achieved at 0.15 mM and the further increase of ferrate dosage (0.2 mM) resulted in a higher ratio of Kc*J/Ki, which was in line with the results of TMP and resistances (Fig. 2). The increased particle size of SS (Fig. 5) and the effective decrease of organics (Figs. 4, 6 and 7) in the influent after ferrate pretreatment (≤ 0.15 mM) would facilitate the reduction of pore blocking (Figs. 2 and 9) and formation of a more porous cake layer (Table 1).

1.5 1.0 0

1

2

3

4

5

6

7

8

Time (h)

Kc*J/Ki

0.00

b

Kc*J/Ki

-0.05

-0.10

-0.15 0.00

0.05

0.10

0.15

0.20

0.25

Ferrate dosage (mM) 3.5. Discussion of membrane fouling mitigation

Fig. 9. TMP (P/P0) vs. time with the combined cake-intermediate fouling model (a) and fitting parameters as a function of ferrate dosage (b). Symbols represent the experimental data and solid lines represent the model fit using the combined cake-intermediate fouling model (a) and the trend of Kc*J/Ki (b).

Membrane fouling was significantly alleviated with ferrate pretreatment and the best fouling control performance was achieved at ferrate dosage of 0.15 mM with the maximum ΔTMP reduction of 81.8% (Fig. 2). However, the further increase of ferrate dosage (0.2 mM) resulted in more severe membrane fouling (Fig. 2). As suggested by the statistical analysis results (Fig. 8), COD, DOC and polysaccharide were the most important positive factors to Rt with the correlation coefficients above 0.92 while particle size, turbidity, SS and zeta potential were the most important negative factors to Rt with the correlation coefficients below − 0.82. As such, the effective decrease of organics (Figs. 4, 6 and 7) and the significant increase of the average particle size of SS (Fig. 3c) in the influent after ferrate pretreatment (≤ 0.15 mM) would be the main contributors for the mitigation of membrane fouling. SS with the average particle size of 145 nm (Fig. 3c) and organics especially the very high MW biopolymers (20,000–2000,000 Da) (Fig. 7a) in the influent would be the main foulants for the control sample without ferrate pretreatment as the ceramic membrane used in this study could intercept the biopolymers with the MW above 30,000 Da [45]. With ferrate pretreatment, the concentrations of organics effectively decreased (Figs. 4, 6 and 7) and the average particle size of SS significantly increased (Fig. 3c) with increase of ferrate dosage, which facilitated the formation of a more porous fouling layer (Figs. 3, 9 and Table 1), the reduction of pore blocking (Figs. 2 and 9) and thus the significant reduction of TMP and resistances (Fig. 2). The increased TMP at 0.2 mM (Fig. 2a) was in line with the porosity results that the porosity of the fouling layer decreased from 20.4% to 12.3% when the ferrate dosage increased from 0.15 mM to 0.2 mM (Table 1). Meanwhile, the concentrations of organics in the fouling layers also increased at 0.2 mM compared to the case at 0.15 mM (Figs. 2c and d), which might facilitate the formation of a more dense fouling layer and thus reduce the porosity of the fouling layer at 0.2 mM. This is more likely because significantly more iron oxyhydroxides accumulated on the membrane surface at 0.2 mM with more

Table 2 The percentage of different elements on the membrane surface after filtration with different dosages of ferrate pretreatment. Ferrate dosage/mM

Virgin membrane 0 0.05 0.065 0.1 0.15 0.2

Element percentage/% C

O

Al

Si

P

Ca

Fe

– 43.27 33.99 31.13 20.61 15.35 23.16

58.23 41.67 49.37 53.78 60.54 65.92 56.69

41.77 7.5 6.12 4.21 4.12 3.63 3.03

– 1.16 2.07 3.05 3.08 2.75 2.53

– 0.55 1.56 2.23 2.53 2.74 3.01

– 0.22 0.56 0.63 0.93 1.02 1.21

– 0.05 0.83 1.43 2.81 3.37 6.52

respectively. Six components including EEM, COD, DOC, polysaccharide, protein, UV254 showed an apparently positive correlation with membrane fouling resistances (Fig. 8a) and the correlation coefficients were above 0.77 (Fig. 8b). COD, DOC and polysaccharide were the most important positive factors to Rt with the correlation coefficients above 0.92 (Fig. 8b), which was consistent with the conclusion in other study [44] in which statistical analysis was applied to determine the correlation between organic matter characteristics and fouling potential in the advanced treatment of five secondary effluents. In contrast, there was a completely negative correlation between the other four components (particle size, turbidity, SS, zeta potential) and membrane fouling resistances with the correlation coefficients below − 0.82 (Fig. 8b), indicating that they had the significantly inverse influence on membrane fouling. Herein, the statistical analysis results (Fig. 8) suggested that ferrate pretreatment (≤ 0.15 mM) facilitated significant reduction of TMP and resistances (Fig. 2) mainly as a result 323

Journal of Membrane Science 552 (2018) 315–325

J. Liu et al.

35

5

a

b Resistance (1012m-1)

Normalized TMP (kPa)

40 30 25 20 15 10 5

Without ferrate With ferrate

0 0

10

20

30

40

50

60

70

4

Rcake Rgel + Rpore

0 mM

0.15 mM

3 2 1 0

1

2

Time (d)

3

4

5

1

2

Rinsing frequency

Fig. 10. Effect of ferrate dosage on normalized TMP (a) and fouling resistance (b) with ferrate dosages of 0 and 0.15 mM in a long-term operation at the filtration flux of 30 L/(m2•h). Arrow represents when rinsing was undertaken.

pretreatment coupled with ceramic membrane reactor was systematically investigated in this study. The following conclusions can be drawn:

organics adsorbing to the preformed iron oxyhydroxides or coprecipitating with the iron oxyhydroxides on the membrane surface. Moreover, the increase in the extent of fouling associated with iron oxyhydroxides deposition on the membrane surface would outweigh the mitigation in the extent of membrane fouling associated with the accumulation of organic matters at high dosage of iron [46,47]. This is indeed the case in this study and the EDX results bear this out. Fe on the membrane surface after filtration remarkably increased with increase of ferrate dosage (Figs. S3 and S4) and the percentage of Fe significantly increased from 0.05% (0 mM) to 3.4% (0.15 mM) and 6.5% (0.2 mM) while the percentage of C effectively decreased from 43.3% (0 mM) to 15.3% (0.15 mM) and 23.2% (0.2 mM) (Table 2).

1. Membrane fouling was effectively mitigated by ferrate pretreatment with the maximum ΔTMP reduction of 81.8% achieved at ferrate dosage of 0.15 mM. The fouling layer deposited on the membrane surface became porous with ferrate pretreatment and the porosity increased from 3.9% (0 mM) to 20.4% (0.15 mM). 2. The fouling mechanism changed from intermediate-standard blocking to cake-intermediate blocking with ferrate pretreatment. Moreover, the contribution of cake layer fouling was significantly diminished with increase of ferrate dosage (≤ 0.15 mM). 3. COD, DOC and polysaccharide were the most important positive factors to Rt with their correlation coefficients above 0.92 while SS and turbidity were the most important negative factors to Rt with their correlation coefficients below − 0.87. 4. Ferrate pretreatment (≤ 0.15 mM) facilitated the significant reduction of TMP and resistances mainly as a result of the effective decrease of organics and the increased particle size of SS in the influent. 5. The long-term filtration experiments also confirmed the effect of ferrate on membrane fouling control with the significant extension of the onset of membrane fouling.

3.6. Long-term operation To further verify the ceramic membrane fouling control performance by ferrate, a comparable long-term operation at the low filtration flux of 30 L/(m2 h) was implemented with ferrate pretreatment at the optimum dosage of 0.15 mM and without ferrate pretreatment. Once the normalized TMP reached 30 kPa, MQ-water rinsing was undertaken to restore the membrane filterability. As shown in Fig. 10a, the onset of membrane fouling was significantly delayed with 0.15 mM ferrate pretreatment that the first rinsing was not undertaken until operation for 54 days. In contrast, much more severe membrane fouling occurred within 4 days for the control sample without ferrate pretreatment. Moreover, 5 times of rinsing were undertaken within 15 days for the control sample, whereas only 2 times of rinsing were undertaken within 60 days for the sample with 0.15 mM ferrate pretreatment. Meanwhile, the irreversible fouling resistance of the control sample gradually increased from 0.87 × 1012 m−1 (1st rinsing) to 2.44 × 1012 m−1 (5th rinsing) within 15 days which was even larger than that of the sample (2.34 × 1012 m−1) with 0.15 mM ferrate pretreatment after operation for 60 days (Fig. 10b). As such, it can be concluded that ferrate can remarkably mitigate membrane fouling with the significant extension of the onset of membrane fouling. The Fe-related foulants contributing for gel layer and pore blocking with ferrate pretreatment might be a potential issue in an even longer term operation, which however will be investigated in the future work and is out of the scope of this study. Moreover, the comparable study of Fe(VI), Fe (II) and Fe(III) on membrane fouling control in reclaimed water treatment will also be investigated in the future work.

Acknowledgements This research was supported by the National Natural Science Foundation of China (51708325), the Committee of Science and Technology Innovation of Shenzhen (JCYJ20160331185156860), the Development and Reform Commission of Shenzhen Municipality (urban water recycling and environment safety program) and Guangdong Science and Technology Department Industry-Education-Research Project (2013B090500132). The authors are particularly thankful to MEIDENSHA CORPORATION for provision of the ceramic membranes. Appendix A. Supplementary material Supplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.memsci.2018.02.031. References

4. Conclusions

[1] B.J. Blunt, A. Singh, L. Wu, M.G. El-Din, M. Belosevic, K.B. Tierney, Reuse water: exposure duration, seasonality and treatment affect tissue responses in a model fish, Sci. Total Environ. 607 (2017) 1117–1125. [2] C.W. Lee, S.D. Bae, S.W. Han, L.S. Kang, Application of ultrafiltration hybrid

The effect of ferrate (VI) on membrane fouling in natural reclaimed water treatment using the integrated process of ferrate (VI) 324

Journal of Membrane Science 552 (2018) 315–325

J. Liu et al.

[3]

[4]

[5]

[6]

[7]

[8]

[9]

[10]

[11] [12]

[13]

[14]

[15]

[16]

[17]

[18] [19]

[20]

[21] [22]

[23]

[24]

treatment of wastewaters, J. Membr. Sci. 475 (2015) 9–21. [25] American Public Health Association (APHA), Standard Methods for the Examination of Water and Wastewater, 21st ed., APHA, Washington, DC, USA, 2005. [26] O.H. Lowry, N.J. Rosebrough, A.L. Farr, R.J. Randall, Protein measurement with the Folin phenol reagent, J. Biol. Chem. 193 (1951) 265–275. [27] G.L. Peterson, A simplification of the protein assay method of Lowry et al. which is more generally applicable, Anal. Biochem. 83 (1977) 346–356. [28] M. DuBois, K.A. Gilles, J.K. Hamilton, P.T. Rebers, F. Smith, Colorimetric method for determination of sugars and related substances, Anal. Chem. 28 (1956) 350–356. [29] W. Chen, P. Westerhoff, J.A. Leenheer, K. Booksh, Fluorescence excitation–emission matrix regional integration to quantify spectra for dissolved organic matter, Environ. Sci. Technol 37 (2003), pp. 5701–5710. [30] D. Wei, Y. Tao, Z. Zhang, X. Zhang, Effect of pre-ozonation on mitigation of ceramic UF membrane fouling caused by algal extracellular organic matters, Chem. Eng. J. 294 (2016) 157–166. [31] S. Tang, Z. Zhang, X. Zhang, New insight into the effect of mixed liquor properties changed by pre-ozonation on ceramic UF membrane fouling in wastewater treatment, Chem. Eng. J. 314 (2017) 670–680. [32] P. Park, C. Lee, S. Lee, Determination of cake porosity using image analysis in a coagulation-microfiltration system, J. Membr. Sci. 293 (2007) 66–72. [33] S. Tang, Z. Zhang, J. Liu, X. Zhang, Double-win effects of in-situ ozonation on improved filterability of mixed liquor and ceramic UF membrane fouling mitigation in wastewater treatment? J. Membr. Sci. 533 (2017) 112–120. [34] G. Bolton, D. LaCasse, R. Kuriyel, Combined models of membrane fouling: development and application to microfiltration and ultrafiltration of biological fluids, J. Membr. Sci. 277 (2006) 75–84. [35] Q. Liu, S. Kim, Evaluation of membrane fouling models based on bench-scale experiments: a comparison between constant flowrate blocking laws and artificial neural network (ANNs) model, J. Membr. Sci. 310 (2008) 393–401. [36] J.A. Suarez, J.M. Veza, Dead-end microfiltration as advanced treatment for wastewater, Desalination 127 (2000) 47–58. [37] V.K. Sharma, R. Zboril, R.S. Varma, Ferrates: greener oxidants with multimodal action in water treatment technologies, Acc. Chem. Res. 48 (2015) 182–191. [38] Y. Lee, R. Kissner, U. von Gunten, Reaction of ferrate (VI) with ABTS and self-decay of ferrate (VI): kinetics and mechanisms, Environ. Sci. Technol. 48 (2014) 5154–5162. [39] N.J. Graham, T.T. Khoi, J.Q. Jiang, Oxidation and coagulation of humic substances by potassium ferrate, Water Sci. Technol. 62 (2010) 929–936. [40] Y. Song, Y. Deng, C. Jung, Mitigation and degradation of natural organic matters (NOMs) during ferrate(VI) application for drinking water treatment, Chemosphere 146 (2016) 145–153. [41] Y. Lee, S.G. Zimmermann, A.T. Kieu, U. von Gunten, Ferrate (Fe(VI)) application for municipal wastewater treatment: a novel process for simultaneous micropollutant oxidation and phosphate removal, Environ. Sci. Technol. 43 (2009) 3831–3838. [42] M. Feng, L. Cizmas, Z. Wang, V.K. Sharma, Synergistic effect of aqueous removal of fluoroquinolones by a combined use of peroxymonosulfate and ferrate (VI), Chemosphere 177 (2017) 144–148. [43] É.C. Vizsolyi, P. Dobosy, G.G. Láng, I. Varga, J. Varga, G. Záray, Laboratory scale study for remediation of polluted groundwater by ferrate treatment, Microchem. J. 133 (2017) 231–236. [44] E. Filloux, J. Labanowski, J.P. Croue, Understanding the fouling of UF/MF hollow fibres of biologically treated wastewaters using advanced EfOM characterization and statistical tools, Bio Resour. Technol. 118 (2012) 460–468. [45] D. Wei, Y. Tao, Z. Zhang, L. Liu, X. Zhang, Effect of in-situ ozonation on ceramic UF membrane fouling mitigation in algal-rich water treatment, J. Membr. Sci. 498 (2016) 116–124. [46] Z. Zhang, M.W. Bligh, T.D. Waite, Ascorbic acid-mediated reductive cleaning of iron-fouled membranes from submerged membrane bioreactors, J. Membr. Sci. 477 (2015) 194–202. [47] Z. Zhang, Y. Wang, G.L. Leslie, T.D. Waite, Effect of ferric and ferrous iron addition on phosphorus removal and fouling in submerged membrane bioreactors, Water Res. 69 (2015) 210–222.

membrane processes for reuse of secondary effluent, Desalination 202 (2007) 239–246. J.L. Acero, F.J. Benitez, A.I. Leal, F.J. Real, F. Teva, Membrane filtration technologies applied to municipal secondary effluents for potential reuse, J. Hazard. Mater. 177 (2010) 390–398. X. Fan, Y. Tao, L. Wang, X. Zhang, Y. Lei, Z. Wang, H. Noguchi, Performance of an integrated process combining ozonation with ceramic membrane ultra-filtration for advanced treatment of drinking water, Desalination 335 (2014) 47–54. B. Düppenbecker, M. Engelhart, P. Cornel, Fouling mitigation in Anaerobic Membrane Bioreactor using fluidized glass beads: evaluation fitness for purpose of ceramic membranes, J. Membr. Sci. 537 (2017) 69–82. W. Zhang, X. Liu, D. Wang, Y. Jin, Effects of bamboo charcoal on fouling and microbial diversity in a flat-sheet ceramic membrane bioreactor, Bio Resour. Technol. 243 (2017) 1020–1026. M. Ben-Sasson, Y.M. Lin, A. Adin, Electrocoagulation-membrane filtration hybrid system for colloidal fouling mitigation of secondary effluent, Sep. Purif. Technol. 82 (2011) 63–70. C. Ayache, M. Pidou, J. Croue, J. Labanowski, Y. Poussade, A. Tazi-Pain, J. Keller, W. Gernjak, Impact of effluent organic matter on low-pressure membrane fouling in tertiary treatment, Water Res. 47 (2013) 2633–2642. X. Zheng, M.T. Khan, J. Croué, Contribution of effluent organic matter (EfOM) to ultrafiltration (UF) membrane fouling: isolation, characterization, and fouling effect of EfOM fractions, Water Res. 65 (2014) 414–424. T. Matsushita, Y. Matsui, N. Shirasaki, Y. Kato, Effect of membrane pore size, coagulation time, and coagulant dose on virus removal by a coagulation-ceramic microfiltration hybrid system, Desalination 178 (2005) 21–26. K. Konieczny, D. Sąkol, J. Płonka, M. Rajca, M. Bodzek, Coagulation-ultrafiltration system for river water treatment, Desalination 240 (2009) 151–159. R. Bergamasco, L.C. Konradt-Moraes, M.F. Vieira, M.R. Fagundes-Klen, A.M.S. Vieira, Performance of a coagulation–ultrafiltration hybrid process for water supply treatment, Chem. Eng. J. 166 (2011) 483–489. Y. Rasouli, M. Abbasi, S.A. Hashemifad, Investigation of in-line coagulation-MF hybrid process for oily wastewater treatment by using novel ceramic membranes, J. Clean. Prod. 161 (2017) 545–559. W. Yu, Y. Yang, N. Graham, Evaluation of ferrate as a coagulant aid/oxidant pretreatment for mitigating submerged ultrafiltration membrane fouling in drinking water treatment, Chem. Eng. J. 298 (2016) 234–242. Z. Yan, B. Liu, F. Qu, A. Ding, H. Liang, Y. Zhao, G. Li, Control of ultrafiltration membrane fouling caused by algal extracellular organic matter (EOM) using enhanced Al coagulation with permanganate, Sep. Purif. Technol. 172 (2017) 51–58. W. Yu, N.J. Graham, G.D. Fowler, Coagulation and oxidation for controlling ultrafiltration membrane fouling in drinking water treatment: application of ozone at low dose in submerged membrane tank, Water Res. 95 (2016) 1–10. X. Sun, Q. Zhang, H. Liang, L. Ying, M. Xiangxu, V.K. Sharma, Ferrate(VI) as a greener oxidant: electrochemical generation and treatment of phenol, J. Hazard. Mater. 319 (2016) 130–136. R.H. Wood, The heat, free energy and entropy of the ferrate (VI) ion, J. Am. Chem. Soc. 80 (1958) 2038–2041. A. Talaiekhozani, M.R. Talaei, S. Rezania, An overview on production and application of ferrate (VI) for chemical oxidation, coagulation and disinfection of water and wastewater, J. Environ. Chem. Eng. 5 (2017) 1828–1842. J. Jiang, S. Wang, A. Panagoulopoulos, The exploration of potassium ferrate(VI) as a disinfectant/coagulant in water and wastewater treatment, Chemosphere 63 (2006) 212–219. B. Lan, Y. Wang, X. Wang, X. Zhou, Y. Kang, L. Li, Aqueous arsenic (As) and antimony (Sb) removal by potassium ferrate, Chem. Eng. J. 292 (2016) 389–397. C. Wang, N. Klamerth, S.A. Messele, A. Singh, M. Belosevic, M.G. El-Din, Comparison of UV/hydrogen peroxide, potassium ferrate(VI), and ozone in oxidizing the organic fraction of oil sands process-affected water (OSPW), Water Res. 100 (2016) 476–485. J. Li, D. Wang, J. Liu, D. Yu, P. Zhang, Y. Li, Removal of reactive black W-2N from synthetic wastewater by an integrated membrane coagulation reactor, Sep. Purif. Technol. 141 (2015) 48–52. Z. Zhang, M.W. Bligh, Y. Wang, G.L. Leslie, H. Bustamante, T.D. Waite, Cleaning strategies for iron-fouled membranes from submerged membrane bioreactor

325