Sludge characteristics and their contribution to microfiltration in submerged membrane bioreactors

Journal of Membrane Science 216 (2003) 217–227

Sludge characteristics and their contribution to microfiltration in submerged membrane bioreactors Wontae Lee a , Seoktae Kang b , Hangsik Shin c,∗ a

Department of Civil and Environmental Engineering, Arizona State University, Tempe, AZ 85287-5306, USA Department of Chemical and Environmental Engineering, University of California, Riverside, CA 92521, USA Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejon 305-701, South Korea b

c

Received 12 December 2002; received in revised form 16 December 2002; accepted 10 February 2003

Abstract This study focused on the physicochemical and biological characteristics of sludge in submerged membrane bioreactors (MBRs) at various sludge retention times (SRT) and their effect on microfiltration and membrane fouling. Three lab-scale submerged MBRs at SRT of 20, 40, and 60 days were performed at a constant permeate flux of 9 l/(m2 h) with hollow fiber microfiltration membranes (hydrophilized polypropylene; nominal pore size = 0.4 ␮m). In order to evaluate the relative contribution of microbial floc and supernatant to the membrane fouling, supernatant was separated from the sludge by centrifugation at 366 rad/s for 5 min. Batch filtration experiments with the same configuration showed that the relative contribution of supernatant to overall membrane fouling was higher at SRT of 20 days (37%) than at SRT of 40 (28%) and 60 days (29%), whereas the overall fouling resistance increased as SRT prolonged. Hydrophobicity (correlation coefficient, r = 0.86; significant value, P < 0.05), surface charge (r = 0.87, P < 0.05) and microbial activity (r = −0.87, P < 0.05), which were related to composition and properties of extracellular polymeric substances (EPS), appeared key parameters relating to fouling by microbial floc. However, no remarkable factor was found in fouling caused by supernatant. © 2003 Elsevier Science B.V. All rights reserved. Keywords: Membrane bioreactor; Microfiltration; Membrane fouling; SRT; Sludge characteristics

1. Introduction By replacing a secondary clarifier by a membrane separation unit in an activated sludge process, membrane bioreactor (MBR) technologies have emerged as one of the innovative and promising solutions for wastewater treatment and reclamation. MBRs use ultrafiltration and/or microfiltration membranes for the complete retention of sludge. This leads to an increased microbial concentration in the reactor ∗ Corresponding author. Tel.: +82-42-869-3613; fax: +82-42-869-3610. E-mail address: [email protected] (H. Shin).

and an improved biological reactor operation with reduced sludge production, persistence to high or shock loadings, and the effective separation of bacteria and viruses when ultrafiltration membranes are used [1,2]. However, membrane fouling is a main obstacle to the wide application of MBRs, which causes declining permeate flux and increasing operation costs [3]. Some previous investigators reported that the membranes in MBR were more fouled at higher sludge concentration [4,5], while others suggested that higher sludge concentration resulted in less fouling under certain conditions [6,7]. This conflict implies that membrane fouling is related to not only sludge quantity

0376-7388/03/$ – see front matter © 2003 Elsevier Science B.V. All rights reserved. doi:10.1016/S0376-7388(03)00073-5

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but also other parameters in MBR. Sludge is mixed liquor of two main fractions: microbial floc and supernatant containing colloids and solutes. Each has its own physicochemical and biological properties, affecting membrane fouling. Recently, several researchers have quantified the fouling caused by different fractions of the sludge. Defrance et al. [8] reported on the relative role of various sludge fractions in fouling on a ceramic microfiltration membrane (pore size = 0.1 ␮m). The sludge sample from an activate sludge process (sludge retention time (SRT) = 60 days; suspended solids (SS) = 4.5 g/l) to treat domestic wastewater showed that the supernatant had 35% of contribution to the total fouling resistance. Bouhabila et al. [9] reported that the supernatant contributed by 76% in a test with a hollow fiber membrane (pore size = 0.1 ␮m) and sludge sample (SS = 20.7 g/l) in an MBR (SRT = 20 days) fed with a synthetic wastewater. However, they did not consider the various characteristics and physiological state of sludge, which would be important to understand microfiltration and membrane fouling in MBR. In this study, the physicochemical and biological properties of both microbial floc and supernatant were investigated and dominant factors affecting membrane fouling in submerged MBR were evaluated though microfiltration of sludge in MBR at various SRTs. 2. Materials and methods 2.1. MBR system description Three submerged MBRs were operated at a constant permeate flux of 9 l/(m2 h) under the same hydraulic retention time (HRT) of 7.8 h, but different SRT of 20, 40, and 60 days. Each MBR consisted of an activated sludge bioreactor having an effective volume of 7 l, in which a U-shaped hollow fiber membrane module was placed (Fig. 1). The membranes (KMS, Korea) were made of polypropylene and hydrophilized. A nominal pore size was 0.4 ␮m (outside diameter = 520 ␮m; inside diameter = 360 ␮m) and an effective filtration area was 0.1 m2 . Initially, the bioreactor was filled with sludge acclimated to synthetic wastewater in a sequencing batch reactor (SBR) at SRT of 20 days. Synthetic wastewater having influent chemical oxygen demand (COD) of 300 mg/l

Fig. 1. Schematic diagram of the experimental system.

(COD:N:P = 100:10:2) was fed to avoid any fluctuation in the feed and provide a continuous source of completely biodegradable organic pollutants, of which composition is summarized in Table 1. NaHCO3 was added to the wastewater to maintain a constant pH for the nitrification in the bioreactors. 2.2. Filtration test Batch filtration tests were performed to investigate the contributions of various constituents in sludge to membrane fouling using sludge and supernatant samples from the three MBRs. The filtration set consisted of a cylindrical vessel (effective volume = 1 l), an air diffuser (air flow rate = 0.3 l/min) and a U-shaped membrane module (effective filtration area = 0.015 m2 ) with the same membrane used in the MBRs. All the operation conditions were seven times smaller than the lab-scale MBR in the same configuration. Prior to the filtration test, the concentration of sludge samples were adjusted to SS = 3.0 ± 0.1 g/l with supernatant of each MBR to avoid the concentration effect on membrane fouling. A supernatant, which contained colloids and solutes, was produced by centrifugation (366 rad/s for 5 min) from a sludge sample. The resistance-in-series model was used to analyze filtration resistances. Based on this model, the permeate flux on the applied transmembrane pressure (TMP)

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219

Table 1 Composition and concentration of the synthetic wastewater fed to the MBRs Compound

Chemical formula

Molecular weight (g/mol)

Concentration (mg/l)

Organics and nutrients Glucose Ammonium sulfate Potassium phosphate

C6 H12 O6 (NH4 )2 SO4 KH2 PO4

180.0 132.1 136.1

280 142 26

CaCl2 ·2H2 O MgSO4 ·7H2 O MnCl2 ·4H2 O ZnSO4 ·7H2 O FeCl3 CuSO4 ·5H2 O CoCl2 ·6H2 O Na2 MoO4 ·2H2 O

147.0 246.5 197.9 287.5 162.2 249.7 237.9 242.0

Trace nutrients Calcium chloride Magnesium sulfate Manganese chloride Zinc sulfate Ferric chloride anhydrous Cupric sulfate Cobalt chloride Sodium molybdate dihydrate Yeast extract

can be described by Darcy’s law as follows: J (t) =

P P 1 dV = = A dt µ(Rt ) µ(Rm + Rf )

(1)

where J is the permeate flux (m3 /(m2 h)), V the total volume of permeate (m3 ), A the membrane area (m2 ), P the TMP (Pa), µ the permeate viscosity (Pa s), Rt the total resistance (m−1 ), Rm is the intrinsic membrane resistance (m−1 ), and Rf the fouling resistance (m−1 ) due to cake layer formation, pore narrowing and blocking, and/or adsorption. All membrane modules were soaked and washed with ultrapure water several times to remove impurities on the membrane surface before filtration experiments. Rt was obtained by filtration of the sludge and supernatant samples from each MBR, which had been performed until the fractional reduction in retentate volume became 0.3; Rf could be estimated from Rt and Rm values. The filtration test was performed at a constant suction pressure of 27 kPa. 2.3. Analytical methods Microbial floc size and colloid size were measured by PAMAS-2120 (PAMAS, Germany) and ZetaPlus (Brookhaven, UK) using a particle sizing software, respectively. Molecular weight (MW) of soluble organic was evaluated using three ultrafiltration membranes of

0.368 5.07 0.275 0.44 1.45 0.391 0.42 1.26 30

different size (Amicon YM series; nominal molecular weight cut-off (MWCO) of 3, 30, and 100 kDa) in parallel processing after prefiltering with 0.45 ␮m membrane filters (Whatman® ). A permeation coefficient model was used to correct apparent size distributions for membrane rejection [10]. Contact angle and specific ultraviolet absorbance (SUVA) were used to estimate the hydrophobicity of microbial floc and supernatant, respectively. SUVA is the ratio of UV absorbance at 254 nm (UVA254 ) to dissolved organic carbon (DOC). High SUVA indicates high degree of hydrophobicity due to its high aromaticity. Contact angle was measured by modified axisymmetric drop shape analysis using a contact angle meter (KRUSS G2, GmbH, Germany) [11]. The surface charges of microbial floc and supernatant were determined by titration method [12] and zeta potential by using ZetaPlus (Brookhaven, UK), respectively. Polybrene and polyvinyl sulfate (PVSK) were used as the cationic and anionic standards, respectively, in the titration method. A known volume of sludge sample was diluted with ultrapure water and mixed with an excess amount of 0.001N polybrene standard solution. Standard solution of 0.001N PVSK was used to titrate against the excess amount of polybrene using a few drops of toluidine blue as an indicator; a subtle color change from blue to purple. An equal volume of polybrene diluted with the same amount of ultrapure water was used as a blank. The surface charge can then be determined from the fol-

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lowing equation:

Table 3 Microbial growths and activities in the MBRs at various SRTs

surface charge(meq./g VSS) (A − B) × N × 1000 = V ×M

Parameters

SRT

(2)

where A is the amount of PVSK (in ml) added to the sample; N the normality of PVSK; B the amount of PVSK (in ml) added to blank; V the amount of sample (in ml) used; M the amount of VSS (in g/l); VSS: volatile suspended solids. EPS was extracted from microbial floc using heat treatment [12]. The extracted solution was analyzed for total carbohydrate and proteins. The sum of the amounts of total carbohydrates and proteins represented the total amount of EPS, which are the dominant components typically found in EPS [13,14]. Carbohydrates in the EPS were determined according to the phenol–sulfuric acid method with glucose as standard [15]. Proteins were determined by the Folin method with bovine serum albumin (BSA) as standard [16]. Specific oxygen uptake rate (SOUR) was adopted to measure microbial activity. The value of OUR, which was obtained by a batch respirometry test using a respirometer (Challenge AER-200 system; Challenge Environment System, Inc.) over the concentration yielded a value termed SOUR. Statistical analysis of experimental data was carried out using SPSS V. 10.0.

3. Results and discussion 3.1. Overall performance of the MBRs COD and NH3 -N removals in the MBRs at steady state are summarized in Table 2. COD and NH3 -N concentrations in supernatant represented the removal

20 days Sludge concentration (VSS in g/l) Sludge production (g VSS/g CODremoved ) SOUR (mg O2 /g VSS h−1 )

40 days

60 days

2.8

4.4

5.5

0.16

0.12

0.10

14.6

12.4

11.7

efficiency in the bioreactors, while those in membrane permeate depicted the removal efficiency in the total MBR processes. The total COD removal efficiencies in three MBRs were over 95%. The bioreactors were responsible for 80–90% of the overall COD removal mainly due to biological degradation. A difference of 10–20% in COD removal between the bioreactors and the total processes inferred that a fraction of soluble COD could be removed by membrane rejection, plugging and/or adsorption. In case of NH3 -N removal, however, no significant difference between the bioreactors and the total processes appeared. This implied that NH3 -N was mostly removed by biological nitrification in the reactor. As the membrane completely kept the nitrifying microorganisms in the reactors, these autotrophic nitrifiers could proliferate without any loss. Consequently, a high nitrification could be achieved in the MBRs regardless of SRT. Table 3 lists sludge concentrations, yields and SOURs in the MBRs. As SRT increased, sludge concentration increased accordingly. Sludge concentration at SRT of 20 days maintained 2.8 g/l and reached 5.5 g/l at SRT of 60 days. On the other hand, specific sludge production decreased from 0.16 to 0.10 g VSS/g CODremoved as SRT increased from 20 to 60 days. This might be a consequence of the amplification

Table 2 COD and NH3 -N removal efficiencies in the MBRs at various SRTs SRT

20 days 40 days 60 days

COD (O2 in mg/l)

NH3 -N (N in mg/l)

Influent

Supernatant

Permeate

Influent

Supernatant

Permeate

300 (100) 300 (100) 300 (100)

42.3 ± 6.3 (85.9 ± 2.1) 38.5 ± 10.1 (87.2 ± 3.4) 35.8 ± 11.2 (88.1 ± 3.8)

11.5 ± 3.7 (96.2 ± 1.2) 9.0 ± 3.5 (97.0 ± 1.2) 7.6 ± 3.8 (97.5 ± 1.3)

30 (100) 30 (100) 30 (100)

2.6 ± 1.0 (91.4 ± 3.3) 2.0 ± 1.1 (93.4 ± 3.5) 2.0 ± 0.9 (93.5 ± 3.1)

1.3 ± 0.6 (95.7 ± 2.0) 1.1 ± 0.6 (96.6 ± 1.9) 0.9 ± 0.5 (97.1 ± 1.8)

Results are expressed as the average ± 1 standard deviation. Data in parenthesis are removal efficiency percentage; average ± 1 standard deviation.

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of the endogenous respiration at longer SRT. Longer sludge age also led to decreased microbial activity in the MBRs, as shown in Table 3. Brindle and Stephenson [1] also reported that prolonged SRT could result in lower microbial activity. However, as shown in Tables 2 and 3, the reduction of microbial activity and variation of microbial quantity had no significant effect on the COD removal and the nitrification in the MBRs. 3.2. Contribution of various constituents in sludge to fouling The membrane fouling is caused not only by microbial floc but also by supernatant containing colloids and solutes [8,9]. Sludge and supernatant samples from each MBR were filtrated using the batch scale filtration set, and resistances in microbial floc were quantified by the difference between resistances in sludge and supernatant. The Rf values of microbial floc and supernatant were presented in Fig. 2. Although solutes and colloids produced in microbial metabolism were considered to increase as SRT prolonged, the Rf values in supernatant had similar values regardless of SRT in the MBRs: 2.93, 2.56 and 3.09 × 1011 m−1 at SRT of 20, 40, and 60 days, respectively. On the contrary, the Rf of sludge enlarged as SRT increased: 7.91, 9.19 and 10.79 × 1011 m−1 at SRT

221

Table 4 Relative contribution (%) of various fractions in sludge to membrane fouling at various SRTs Fractions

Supernatant SS

Our results

[9]

[8]

20 days

40 days

60 days

20 days

60 days

37 63

28 72

29 71

76 24

35 65

of 20, 40, and 60 days, respectively. Furthermore, relative contributions of supernatant containing colloids and solutes to the total membrane fouling were 37, 28, and 29% at SRT of 20, 40, and 60 days, respectively. From the results, solutes and colloids mainly resulting from the lysis of bacteria were most likely to have no dominant fouling potential on microfiltration in submerged MBRs regardless of SRT, while the relative contribution of them to overall membrane fouling was higher at SRT of 20 days than SRT of 40 and 60 days. In Table 4, the study results were compared with recent researches, which quantified the membrane fouling caused by each fraction of the sludge. The differences were mostly due to the substrate characteristics, the physiological state of sludge and the membrane properties. Despite these differences, it is clear that supernatant and microbial floc partly have contribution to the fouling resistance increase during microfiltration, and the relative contribution of

Fig. 2. Resistances of various fractions in sludge samples at different SRTs.

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supernatant to membrane fouling was higher at shorter SRT in the MBRs. 3.3. Size characteristics of various constituents in sludge Microbial floc size was investigated in the range of 1–280 ␮m. As shown in Fig. 3, the floc size distributions in three sludges were similar, while mean floc sizes enlarged as SRT increased: 5.2 ± 0.3, 6.0 ± 0.2 and 6.6 ± 0.3 ␮m at SRT of 20, 40, and 60 days, respectively. The floc size is inversely proportional to the magnitude of the hydraulic stress and the operation [6]. Since the operation time and HRT of each MBR was fixed the same, the difference in size might be due to different physiological state of sludge and hydraulic stresses on microbial floc at various SRT. In a submerged MBR, a higher air supply is required than a conventional process not only for organics biodegradation but for generating a cross-flow stream over the membrane surface to prevent fouling [17]. In this study, air flow rate in each reactor kept 2.0 l/min, which might lead to higher hydraulic stress on microbial floc under lower SRT condition with lower sludge concentration. The microbial floc, which was made by physicochemical interactions between microorganisms, EPS, multivalent cations, and inorganic

particles, would be destructed by the incessant aeration. The rupture of floc resulted in a decrease in mean floc size. Mean colloid sizes at SRT of 20, 40, and 60 days were 349±14, 420±23 and 458±26 nm, respectively. Mean colloid size enlarged as SRT increased. High hydraulic strains and stresses might enhance cell and floc breakage under lower microbial concentration, favoring cell debris and macromolecules (i.e. colloids). In addition, the proportions of the particles whose size is smaller than the nominal pore size of the membrane (0.4 ␮m) were 68, 62, and 54% of the total colloids at SRT of 20, 40, and 60 days, respectively (Fig. 4). Despite the difference in the size characteristic of colloids along with SRT, colloids could not affect the overall fouling resistance as shown in Fig. 2. To compare soluble organic fractions at each SRT, mixed liquor from each reactor was filtered with 0.45 ␮m filter (Whatman® ). DOC values of the solutions were 18.3 ± 2.3, 19.6 ± 2.1 and 23.2 ± 3.1 mg/l at SRT 20, 40, and 60 days, respectively. The MW distributions of soluble organics at each SRT were evaluated using three UF membranes of different sizes in parallel processing. As shown in Fig. 5, all the solutions contained a wide distribution of MW; 70% of soluble organics were in the MW range larger than 3 kDa at the three SRTs, indicating that the majority

Fig. 3. Particle size distributions of sludge at various SRTs.

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Fig. 4. Intensity accumulation of colloids at various SRTs.

of the solutes have high MW, perhaps polymeric substances in nature. Furthermore, the distribution patterns were quite similar at each SRT, tending to be bimodal in shape. The quantitative and qualitative properties of the soluble organics in supernatant did not vary so much.

3.4. EPS composition EPS matrix is very heterogeneous, in which a variety of polymeric materials have been found: carbohydrates, proteins, lipids and nucleic acids. In this work, however, the sum of total carbohydrates and proteins

Fig. 5. MW distribution of soluble organics at various SRTs.

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Fig. 6. The concentration of EPS components at various SRTs.

was considered to represent the total amount of EPS because these are the dominant components typically found in extracted EPS [14,15]. Fig. 6 shows the concentrations of carbohydrate and protein in microbial floc at various SRTs. Comparing to EPS contents of microbial floc at SRT of 40 and 60 days, microbial floc at SRT of 20 days had a relatively high carbohydrate concentration but a low protein concentration. Carbohydrates are synthesized extracellularly for a specific function, while proteins can exist in the extracellular polymer network due to the excretion of intracellular polymers or cell lysis [14,15]. At higher SRTs and lower food to microorganism (F/M) ratios, the carbohydrate in microbial floc declined, which reflected the available carbon. On the other hand, the amount of protein on the cell surface increased probably due to cell lysis: 29.9 ± 2.4, 35.7 ± 2.5 and 35.5 ± 2.1 mg/g VSS at SRT of 20, 40, and 60 days. In general, larger amount of EPS would be produced as endogenous metabolism predominates at high SRT compared to conditions when rapid growth occurs [18]. In this study, however, the total amount of EPS was independent of the SRT: 62.8±4.9, 70.0±5.6 and 64.9 ± 4.8 mg EPS/g VSS at SRT 20, 40, and 60 days, respectively. This indicates that the production of total EPS is not limited only to the stationary and endogenous phases of sludge over SRT 20 days, whereas the excreted protein on the cell surface increased with

decrease in microbial activity as microorganism aged (Fig. 6). 3.5. Surface properties of microbial floc and supernatant To evaluate the surface properties of microbial floc and supernatant at each SRT, hydrophobicity and charge of both microbial floc and supernatant were measured (Table 5), which might influence the membrane fouling. Both microbial floc and supernatant appeared more hydrophobic at SRT 40 and 60 days than at SRT 20 days; more hydrophobic property is related to higher SRT. Table 6 presents a statistical analysis of linear correlations between contact angles and EPS components. It appears that the ratio of protein to carbohydrate (r = 0.77, P < 0.05) is more important than the quantity of total EPS. Different EPS components may have different effects resulting in the various physical and chemical properties of EPS. The EPS protein had a strong positive influence on the hydrophobicity of microbial floc (r = 0.81, P < 0.05), while EPS carbohydrate had no remarkable influence. This result was similar to the other study reporting that the hydrophobic fraction of EPS was made of only proteins but not carbohydrates. Amino acids at hydrophobic side groups contribute significantly to the hydrophobicity of microbial floc [19].

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Table 5 Surface properties of microbial floc and supernatant at various SRTs SRT

Microbial floc Contact angle

20 days 40 days 60 days a

Supernatant (◦ )

34.4 ± 40.6 ± 2.6 44.4 ± 3.0

3.4a

Surface charge (meq./g VSS)

SUVA (m−1 mg−1 l)

Zeta potential (mV)

−0.66 ± 0.07 −0.58 ± 0.04 −0.43 ± 0.04

0.357 ± 0.105 0.484 ± 0.098 0.481 ± 0.107

−9.84 ± 0.93 −10.06 ± 1.27 −9.98 ± 2.33

Results are expressed as the average ± 1 standard deviation.

Since SUVA value of influent was almost zero due to easily degradable carbon source having low MW, the rise in SUVA indicated the formation of aromatic and larger MW soluble organics in the MBRs. SUVA value of the supernatant was least at SRT of 20 days (Table 5). Higher values in SUVA imply the preferential presence of larger MW soluble organics as shown in Fig. 5. The portion of DOC larger than 30 kDa was smaller at SRT of 20 days (34%) than SRT of 40 (42%) and 60 days (40%). The increase in SUVA is also caused by accumulation of protein, lipids and nucleic acids [20]. As presented in Table 3, there were drop in SOUR and severe cell lysis at higher SRT, which caused excretion of intracellular polymers (i.e. protein-like materials). The negative correlation between microbial activity and hydrophobicity of supernatant (r = −0.49, P < 0.05) confirms this result (Table 6). The surface charges of microbial floc at various SRTs were listed in Table 5. A smaller value of surface charge was found for microbial floc at SRT 40 and 60 days, than at SRT of 20 days. However, the zeta potential of colloids in supernatant did not change significantly over the range of SRT since the processes were operated at neutral pH (Table 5). The

transition in surface charge of microbial floc had positive correlations with the variation of the contact angle (r = 0.75, P < 0.05) and the proportion of EPS proteins/carbohydrates (r = 0.80, P < 0.05), implying that the charge properties of proteins could affect the surface charge of microbial floc. Positively charged and non-polar amino acids in protein might be dominant in sludge samples. Microbial activity decreased from 14.6 to 11.7 mg O2 /g VSS h−1 as sludge aged (Table 3). Proteins that were excreted from the cell would neutralize some of the negative charge of microbial floc. These results suggest that the measurement of microbial activity by SOUR might be an indirect evaluation method of the relative hydrophobicity and surface charge of microbial floc. 3.6. Effect of surface properties on membrane fouling caused by various constituents in sludge To investigate the key contributors to membrane fouling caused by microbial floc and supernatant, statistical analysis of experimental data was performed as shown in Table 7. The amount of EPS protein (r = 0.74, P < 0.05), protein/carbohydrate ratio in EPS (r = 0.85, P < 0.05), hydrophobicity

Table 6 Correlation between physicochemical parameters and surface properties of microbial floc and supernatant Components

EPS carbohydrate EPS protein EPS protein/carbohydrate Total amount of EPS Supernatant DOC Activity a

Microbial floc

Supernatant

Contact angle

Surface charge

SUVA

Zeta potential

−0.18 0.81a 0.77a 0.39 – −0.71a

−0.51a 0.52a 0.80a −0.01 – −0.74a

– – – – −0.02 −0.49a

– – – – 0.03 0.08

Significant at 95% confidence level.

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Table 7 Correlation between prospective fouling-cause items and fouling resistance caused by microbial floc (RSS ) and supernatant (Rsupernatant ) Components

RSS

Rsupernatant

EPS carbohydrate EPS protein EPS protein/carbohydrate Total amount of EPS Supernatant DOC SUVA Contact angle Zeta potential Surface charge Microbial activity

−0.36 0.74a 0.85a 0.23 – – 0.86a – 0.87a −0.87a

– – – – 0.39 −0.09 – 0.04 – −0.37

a

Significant at 95% confidence level.

(r = 0.86, P < 0.05) and surface charge (r = 0.87, P < 0.05) of microbial floc demonstrated a strong positive correlation with the fouling resistance caused by microbial floc (RSS ), whereas microbial activity had a negative correlation (r = −0.87, P < 0.05). The protein/carbohydrate ratio in EPS appeared more significant than the quantities of EPS components in controlling RSS . The strong correlation between microbial activity and RSS indicates that microbial floc with lower activity has more fouling potential. Since hydrophobicity and surface charge had a strong correlation with EPS protein/carbohydrate ratio and microbial activity (Table 6), protein/carbohydrate ratio of EPS and microbial activity appeared the essential parameters to predict the RSS . In contrast, no remarkable parameter appeared for fouling resistance caused by supernatant (Rsupernatant ). A better understanding of dominant foulant in microfiltration of supernatant requires more fundamental information about the colloids and solutes.

4. Conclusions The physicochemical and biological characteristics of both microbial floc and supernatant in submerged MBRs were investigated and applied to elucidate the microfiltration behavior and membrane fouling. The following specific conclusions were obtained: (1) Although the microbial activity at long SRT revealed low values (11.7–14.6 mg O2 /g VSS h−1 ),

both the COD removal and the nitrification efficiency were kept over 95% in the MBRs. The high microbial concentration due to the complete separation enhanced the overall treatment performance. (2) The overall fouling resistance increased in the MBRs as SRT prolonged. Solutes and colloids appeared to have no dominant fouling potential on microfiltration membrane regardless of SRT, whereas the relative contribution of them to overall membrane fouling was higher at SRT 20 days than SRT 40 and 60 days. Relative contribution of supernatant to membrane fouling was higher at shorter SRT in the MBRs. (3) Hydrophobicity, surface charge and microbial activity could be the key factors to estimate microbial-floc-cause resistance. Furthermore, composition and properties of EPS appeared more important than the total quantity of EPS with respect to membrane fouling caused by microbial floc. It, therefore, would be desirable to gain the precise role of the EPS for better understanding of surface properties of microbial floc. On the other hand, no remarkable parameter was found for supernatant-cause resistance as it was difficult to describe prospective foulant in supernatant with a microfiltration filtration.

Acknowledgements This work was supported by the Brain Korea 21 project.

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