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Correlation between local TMP distribution and bio-cake porosity on the membrane in a submerged MBR
Journal of Membrane Science 332 (2009) 50–55
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Journal of Membrane Science journal homepage: www.elsevier.com/locate/memsci
Correlation between local TMP distribution and bio-cake porosity on the membrane in a submerged MBR Woo-Nyoung Lee, Won-Suk Cheong, Kyung-Min Yeon, Byung-Kook Hwang, Chung-Hak Lee ∗ School of Chemical and Biological Engineering, Seoul National University, Seoul 151-744, Republic of Korea
a r t i c l e
i n f o
Article history: Received 13 June 2008 Received in revised form 17 January 2009 Accepted 25 January 2009 Available online 5 February 2009 Keywords: Membrane bioreactor Membrane fouling Bio-cake porosity Local TMP distribution Local aeration method
a b s t r a c t In a submerged membrane bioreactor (SMBR) the spatial distribution of bio-cake porosity on the membrane module is very important in the detection of local membrane biofouling, which is directly related to efficient membrane-cleaning and energy consumption. In this study, the local bio-cake porosity was determined experimentally and correlated with the local flux measured by a newly developed experimental method. This exercise made it possible to suggest the optimum position of an aerator in the reactor to obtain minimal membrane biofouling. The local transmembrane pressure (TMP) on the membrane module became bigger and bigger as the distance from the local position to the suction pump became nearer and nearer owing to the pressure drop inside the hollow fiber lumen. A good correlation was found between the local TMP distribution and the local porosity of bio-cake formed on the membrane surface which was measured by a confocal laser scanning microscope (CLSM) and image analysis technique. The bio-cake formed on a local position of the membrane near the suction pump was more easily compressed by higher TMP, and thus its porosity became lower. From this local porosity distribution on the membrane the effect of aerator positions on the membrane biofouling was studied. Under identical mixing intensity, the positioning of a diffused aerator near the suction pump was the most effective location for the alleviation of the membrane fouling because the porosity of bio-cake at that location was the smallest, and thus the worst biofouling took place. © 2009 Elsevier B.V. All rights reserved.
1. Introduction It is widely known that the formation of bio-cake is one of the major hurdles to be overcome in a submerged membrane bioreactor (MBR) [1,2], because the filtration performance in MBR is closely related to bio-cake characteristics such as the porosity and amount of the attached bio-cake [3]. Many studies have been carried out to reduce or eliminate the bio-cake on the membrane surface in several ways, such as aeration, high-shear slug flow, module modification, and so on [4–6]. From a practical point of view, aeration has been the most useful operating parameter for the reduction of biofilm formation as well as the supply of dissolved oxygen in a submerged MBR. However, during the operation of MBR only the highest transmembrane pressure (TMP) or the average flux on a membrane module is monitored instead of spatial distribution of the TMP or flux. Consequently, the aeration is usually applied uniformly or monotonously to the entire membrane module without taking into account the difference in the extent of local biofouling developed on the membrane surface, which may result in inefficient membrane-cleaning and energy consumption. On the other hand,
it has been reported that the distribution of bio-cake porosity on which the hydraulic permeability through the membrane mostly depends is uneven along the length of a hollow fiber membrane in a submerged MBR [7]. The uneven distribution of bio-cake porosity on the membrane may be closely associated not only with the spatially uneven TMP distribution but also with the best positioning of an aerator to get the most efficient cleaning. However, few studies have reported on this issue. In this study, a new experimental method was developed to determine the local TMP profile on a hollow fiber membrane module in order to link it to the local porosity profile of bio-cakes which was measured by means of a confocal laser scanning microscope (CLSM) and image analysis technique [7,8]. Based on the profile of the local distribution of bio-cake porosity, the most probable position of the aerator in the bioreactor was predicted and confirmed experimentally in order to get the most efficient cleaning in a submerged MBR.
2. Materials and methods 2.1. Local flux measurement
∗ Corresponding author. Tel.: +82 2 880 7075; fax: +82 2 874 0896. E-mail address: [email protected] (C.-H. Lee). 0376-7388/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.memsci.2009.01.036
Fig. 1 shows the schematic diagram for local TMP measurement. The system consists of three reactors (R1–R3). A single hollow fiber
W.-N. Lee et al. / Journal of Membrane Science 332 (2009) 50–55
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Fig. 1. Schematic diagram for local TMP measurement.
(F1–F3, outer diameter D0 = 1.9 mm, ZeeWeed 500c, PVDF, Zenon) was put into each reactor, which was divided into five compartments (C1–C5). Actually, each compartment in Fig. 1 was replaced by a mass cylinder (Falcon tube) of 50 mL to prevent the fluid in each compartment from moving to other compartments as shown in Fig. 2. Each compartment (or cylinder) was filled with 50 mL D.I. water. The effective membrane surface area in each compartment was 1.5 cm2 . The left end of each fiber was sealed, and the other ends of three fibers were inter-connected by a silicon tube which extended to the suction pump. A permeate of D.I. water through the three fibers was continuously withdrawn at constant flux of 100 L/m2 h by a peristaltic pump. The smaller the number of compartments (e.g., C1) or the number of fibers (e.g., F1) the closer they are to the pump, i.e., [F3, C5] indicates the farthest part from the pump whereas [F1, C1] indicates the nearest one. The TMP measured using the pressure gauge was maintained at 24 kPa during the suction of D.I. water. Fig. 2 shows the variations in the water level before and after the operation of the suction pump depending on the compartment (C1–C5) or the position on a hollow fiber (it showed only one fiber). As soon as the suction pump ran, the hollow fiber membrane sucked up D.I. water, and thus the water levels went down at different rates depending on the compartment. The variations in permeate volume were measured to calculate the 15 (5 × 3) local permeate fluxes through the fraction of a fiber in each compartment (C1–C5) for all three fibers (F1–F3). 2.2. Calculation of TMP The local permeate flux at each compartment in Table 3 was calculated by Eq. (1): Ji =
Vi Ai
(1)
where Ji is the local permeate flux, Vi is the volume of local permeate accumulated for 1 h through a fraction of a fiber in each
Fig. 3. Schematic diagram of an MBR system.
compartment, and Ai is the effective surface area of membrane (1.5 cm2 ) submerged in each compartment. The local TMP applied to a fraction of a fiber in each compartment was calculated by Eq. (2) based on resistance-in-series model [9]: PTi = Rm Ji
(2)
where PTi is the local TMP at each compartment, is the viscosity of water, and Rm is the intrinsic membrane resistance (1.15 × 1012 m−1 ). 2.3. MBR system Fig. 3 shows the schematic diagram of MBR setup, and operating conditions are listed in Table 1. Compressed air (air flow rate = 1 L/min) was supplied through a bubble stone on the bottom of the reactor with a working volume of 2 L to provide dissolved oxygen and turbulence. Hydraulic retention time (HRT) and sludge retention time (SRT) were maintained at 10 h and 30 days, respectively. The main carbon and nitrogen sources in the synthetic wastewater were glucose and ammonium sulfate, respectively. Influent COD was 300 mg/L, whereas the effluent COD was less than 6 mg/L so that the treatment efficiency showed over 98% during the whole operation. The average particle size of sludge floc was around 60 (±5) m during the whole experiment. Soluble EPS concentration was showed 8.4 (±1.1) mg EPS/L. At steady state, the concentration of suspended biomass was kept constant at 4800 (±200) mg/L. As shown in Fig. 4, an I-shaped hollow fiber module, made of PVDF (ZeeWeed 500c, Zenon) with a pore size of 0.04 m and a Table 1 Operating conditions of an MBR system. Working volume (L) TMP (kPa) Constant flux (L/m2 h) Air flow rate (L/min) DO (mg O2 /L) pH Feed concentration (mg COD/L) HRT (h) SRT (day) MLSS (mg/L)
Fig. 2. Variations in the water level over a hollow fiber during suction.
( ) Standard deviation.
2 <30 15 1 >5 (±0.2) 6.5–7.5 300 (±10) 10 30 4800 (±200)
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W.-N. Lee et al. / Journal of Membrane Science 332 (2009) 50–55
Fig. 4. The hollow fiber module and sampling points for the bio-cake specimens.
surface area of 200 cm2 , was dipped vertically into the MBR. The top ends of fibers were sealed with epoxy resin, and suction was done through the potted end of fibers. A permeate through the submerged membrane module was continuously withdrawn at a constant flux of 15 L/m2 h. The TMP was continuously monitored until it reached 30 kPa. The average membrane operating time, i.e., the time required to reach TMP of 30 kPa, was about 5 days. The used membrane module was cleaned with 500 mg NaClO/L solution for 6 h and then reinstalled for the next run. 2.4. Determination of bio-cake porosity When the TMP reached 30 kPa, the membrane module was removed from the MBR for measurement of the local bio-cake porosity. In Fig. 4, F1 –F13 represent the horizontal location of 13 hollow fibers in a membrane module, whereas P1–P4 represent the vertical location of each fiber. Three fibers (F1 , F9 , and F13 ) were cut from the membrane module, and each one was further cut into four segments (P1–P4) with the same length of 3 cm, so 12 specimens (3 fibers × 4 specimens/fiber) in total were obtained for staining and CLSM. The smaller the number of F1 and P1 represents the closer to the pump, i.e., [F1 , P1] indicate the nearest segment to the pump whereas [F13 , P4] indicate the farthest one from the pump. The list of fluorescent dyes used in the bio-cake staining is given in Table 2. Cells and polysaccharides in the bio-cake were stained with SYTO9 and Concanavalin A (Molecular Probes, Eugene, USA), which is specific to nucleic acids and polysaccharides. SYTO9 and Concanavalin A were added to the bio-cake samples at the concentration of 1.67 M/mL and 0.1 mg/mL, respectively. After dye addition, the bio-cake was incubated for 30 min at room temperature in the dark and then washed with phosphate-buffered saline (PBS) solution. The stained bio-cake was immediately observed by
means of a CLSM (Radiance 2000, Bio-Rad, UK) which consisted of a microscope (Nikon, Japan) and krypton–argon mixed gas laser source. Signals were recorded in the green channel and the red channel. For the observation (magnification ×600), an oil lens with 40 × 1.3NA (numerical aperture) lens was used. A series of CLSM images of optical sections with a step size of 1 m were simultaneously taken for each specimen. The spatial resolutions of CLSM are 395 nm in the xy plane and 500 nm in the z direction. To check interferences from background fluorescence of the membrane, the fresh PVDF membrane followed the same procedure of staining as the used membrane with bio-cakes. But any fluorescence was not detected, indicating no background interference from the PVDF membrane. Two CLSM images based on cell and polysaccharide respectively were merged together by means of the IMARIS Program (v4.1.3, Bitplane AG, Zurich, Switzerland) [10] and then the merged images were used for calculation of the porosity of bio-cake with a software, Image Structure Analyzer-2 (ISA-2), developed by Beyenal et al. [11]. The relative standard deviations in determining the bio-cake porosity are in the range of 2.0–2.9%, indicating fairly good reproducibility for this analysis. Fig. 5a and b represents the merged CLSM images for the bio-cakes developed on the membrane module corresponding to the local points [F1 , P3] and [F13 , P3], respectively in Fig. 6a. 2.5. Analytical methods Mixed liquor suspended solids (MLSS) were measured according to the analytical methods described in the standard methods [12]. DO concentration and pH of a mixed liquor were measured with a multi-meter (Orion 1230, USA). COD was determined by the spectrophotometric method (DR 4000, HACH, USA). Particle size distributions were analyzed with a particle size analyzer, based on a laser scattering method (Mastersizer/E, Malvern, UK)
Table 2 Fluorescence probes used in bio-cake staining and their spectral characteristics. Probes
Label
Excitation (nm)
Emission (nm)
Specificity (target)
Channel
SYTO9 Concanavalin A
– TRITCa
488 568
515/30 600/50
Nucleic acids (Bacterial cell) ␣-Mannose, ␣-glucose (Polysaccharide)
Green Red
a
TRITC, tetramethylrhodamine isothiocyanate.
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Fig. 5. Merged CLSM images (Green; cells, Red; polysaccharides); (a) [F1 , P3] and (b) [F13 , P3] represent the local points in Fig. 6a from which two bio-cake specimens were taken respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)
Fig. 6. Vertical and horizontal distribution of (a) bio-cake porosity and (b) TMP.
which allows the measurement of particle size in the range of 0.1–600 m. The extraction of bound EPS from suspended microbial flocs was carried out through a heating method [13]. Proteins and polysaccharides were analyzed by spectrophotometric methods: protein concentration was determined according to the modified Lowry method with the Lowry reagent (P 5656, Sigma). A calibration curve was prepared with a solution of bovine serum albumin. For the quantitative analysis of polysaccharides, the phenol-sulfuric acid method was used with glucose as a standard [14]. 3. Results and discussion 3.1. Local distribution of permeate flux and TMP In a submerged MBR, the spatial distribution of bio-cake porosity and flux in the membrane module is vital in identifying local membrane biofouling which is directly related to efficient membrane-cleaning, energy consumption, and membrane life span. In operating the submerged MBR, however, we usually measure only the average flux or the highest TMP, neglecting their local distributions in the same membrane module. The TMP dis-
tribution of a submerged hollow fiber has been predicted via a model equation, but has not yet been determined experimentally [15,16]. The local flux distribution throughout the hollow fiber membrane module was measured with a new experimental method developed in this study, as described in Section 2. Using Eq. (2) we calculated local TMPs by measuring local permeate fluxes for D.I. water (Table 3). During the operation of a MBR system, however, bio-cakes continuously develop on the membrane surface and thus bio-cake resistances change along with the operation time. In this case, although we can measure local permeate fluxes for mixed liquor in an activated sludge reactor we cannot use any more Eq. (2) because the intrinsic membrane resistance (Rm ) should be replaced by resistances originated from not only the membrane itself (Rm ) but also the architecture of bio-cakes formed which we do not know. Therefore it is impossible to obtain the spatial distribution and temporal change of local TMPs on the membrane surface when the real feed, e.g., the mixed liquor is filtered. Consequently, the distribution of local TMPs shown in Fig. 3 does not represent those developed with the bio-cakes because the absolute values of local TMPs measured with D.I. water in Table 3 should be different from those measured with mixed liquor.
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Table 3 Local distributions of permeate volume, permeate flux, and TMP. C5
C4
C3
vations, comparisons between the local porosity and local TMP are made in the following section. C2
C1
V (mL)
Fiber 1 Fiber 2 Fiber 3
14.0 13.3 12.5
14.8 13.9 13.0
15.5 14.6 13.7
16.3 15.3 14.3
17.1 16.1 15.2
J (L/m2 h)
Fiber 1 Fiber 2 Fiber 3
93.3 88.7 83.3
98.7 92.7 86.7
103.3 97.3 91.3
108.7 102.0 95.3
114.0 107.3 101.3
PT (kPa)
Fiber 1 Fiber 2 Fiber 3
16.8 16.0 15.0
17.8 16.7 15.6
18.6 17.5 16.5
19.6 18.4 17.2
20.5 19.3 18.3
The bold values represents the nearest or the farthest position from the suction pump.
However, the suction pressure inside of hollow fiber lumens would be dropped along with the fiber length and the local TMPs are largely dependent on their relative positions to a suction pump in a submerged MBR. For example, TMP at C1 is certainly greater than that at C5 because C1 is closer to the suction pump than C5 for each fiber in Fig. 1. Accordingly the relative sizes of local TMPs were assumed to be consistent for both measurements with D.I. water and mixed liquor, respectively. Based on this assumption, we tried to compare the relative TMPs with the relative porosities of bio-cakes to identify the correlation between them which will be discussed in Section 3.3. Table 3 shows the permeate volume, permeate flux, TMP for various combinations of compartments (C1–C5) and fibers (F1–F3) depicted in Fig. 1. For the fixed filtration time of 1 h, the largest volume of water was permeated in F1 and C1 which were located at the nearest point to the suction pump, whereas the least volume of water was permeated in F3 and C5 which were located at the farthest point to the pump. The permeate volumes were gradually increased as the membrane fibers approached the suction pump, from F3 to F1 or from C5 to C1. The local permeate flux (Ji ) was calculated by use of Eq. (1) and the local permeate volume (Vi ). Just like the permeate volume, the local permeate flux changed from 83.3 to the maximum of 114.0 L/m2 h depending on the distance of a fiber fraction from the suction pump. It suggests a heterogeneous flow rate exists through the same membrane module. The distribution of local TMP (PTi ) was also calculated with Eq. (2) and the local permeate flux (Ji ). As expected, the local TMP also ranged from the minimum value of 15.0 kPa at the farthest point [F3, C5] to the maximum of 20.5 kPa at the nearest point [F1, C1] from the suction pump. This result coincides well with the report by Lee et al. [15] and Shao and Huang [16], where they predicted theoretically the greatest local TMP at the potted end [C1] of a hollow fiber and the lowest local TMP at the sealed end [C5]. 3.2. Local distribution of bio-cake porosity In the operation of MBR depicted in Fig. 3, when the TMP reached 30 kPa, the hollow fiber membrane module was taken out from the MBR to analyze the local porosities of bio-cakes formed on the membrane surface. Fig. 6a shows the vertical and horizontal distributions of bio-cake porosities formed on the surface of a hollow fiber membrane module. The bio-cake porosity was dependent on the position of bio-cake over the module. On the vertical level, e.g., for the same fiber, the bio-cake porosity near the potted end [P1] was lower than that near the sealed end [P4] for all fibers tested. In addition, on the horizontal level the bio-cake porosities from a fiber near the suction part [F1 ] were always lower than those from a fiber on the right parts (F9 and F13 ). To elucidate these obser-
3.3. Correlation between the local TMP distribution and the bio-cake porosity The distribution of local TMP along the vertical and horizontal position of hollow fibers was determined with a method described in Section 3.1 and shown in Fig. 6b. TMP was gradually increased as the location over the module approached horizontally or vertically nearer to the suction pump. As a result, the bio-cake formed on the nearest point to the suction pump (F1 , P1 in Fig. 6a) would be compressed most easily by the highest TMP, and thus its porosity should be lower than that of any other point over the module. In contrast, the bio-cake formed on the farthest point to the suction pump (F13 , P4 in Fig. 6a) would be compressed the least by the lowest TMP, and thus its porosity should be higher than that of any other point over the module. It was concluded that there is good correlation between local bio-cake porosity and local TMP over the membrane in a submerged MBR. These findings led us to a further study on the optimum position of an aerator inside the bioreactor to mitigate the membrane biofouling and thus to reduce energy consumption. 3.4. Optimum position of an aerator in a submerged MBR to reduce membrane biofouling We found that heterogeneous porosities of the bio-cake are generated over the same membrane module during the operation of a submerged MBR owing to the heterogeneous TMP development, depending on how far the zone on the module is located from the suction pump, the smallest porosity being at the nearest zone to the suction pump whereas the highest porosity is at the farthest zone from the suction pump. In other words, the extent of biofouling on the membrane module which is exposed to the identical mixed liquor of activated sludge could differ from place to place. This suggests that we should change the aeration strategy to mitigate the biofouling by aeration more efficiently. An additional filtration experiment was therefore carried out to confirm the best position of an aerator to achieve the least membrane biofouling. Fig. 7a shows a schematic diagram of an MBR with different locations of aerators. The bioreactor was divided into four compartments by means of baffles to minimize the effect of shear force generated by the aeration from the other compartments. The mixed liquor was, however, freely moved throughout the bioreactor so that all four membrane modules could be exposed to the same environment of activated sludge (MLSS = 4800 mg/L). Four hollow fiber membrane modules (ZeeWeed 500c, PVDF, Zenon) of the same size (fiber length = 20 cm; membrane area = 60 cm2 ) were dipped into each compartment. The aeration was done using a plate type aerator at the air supply of 1 L/min on the bottom of all four compartments (the plate type aerator was not depicted in Fig. 7a). And then, the same strength of aeration (air supply of 1 L/min) using a bubble stone was supplemented to three compartments (for M2–M4) where each bubble stone located at different position. For Membrane 1 (M1), no bubble stone was supplied. For M2, the bubble stone was located near the sealed end which is farthest to the suction pump. For M3, it was located in the middle of the part, whereas for M4 it was located near the potted end which is nearest from the suction pump. Filtration under the same constant flux (30 L/m2 h) was conducted simultaneously through four membrane modules and the variations in TMP for four submerged modules were also simultaneously monitored and plotted in Fig. 7b. To reach the same TMP of 30 kPa, it took about 8 h for M1. It showed the smallest membrane operation time than those of other membrane modules since the aeration was not supple-
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4. Conclusions In this study, the local bio-cake porosity was determined experimentally and correlated with the local TMPs measured by a newly developed experimental method. This exercise made it possible to suggest the optimum position of an aerator in MBR to obtain higher membrane-cleaning efficiency. The following conclusions can be drawn: (1) During the operation of submerged MBR under the constant flux, the distribution of local TMPs is developed depending on local positions on the membrane due to the pressure drop along the lumen of hollow fibers. (2) The distribution of local TMPs coincided well with the distribution of the bio-cake porosities. The bio-cake formed on the membrane near the suction pump would be more easily compressed by higher TMP, and thus its porosity should be lower than those at other locations. (3) The positioning of an aerator should be near to the part of the membrane module where a bio-cake with smaller porosity develops in order to increase membrane-cleaning efficiency through the aeration. Acknowledgements This work was supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the government (MOST) (No. R0A-2007-000-20073-0). The authors thank the National Instrumentation Center for Environment Management (NICEM) for the use of the confocal laser scanning microscope system. References
Fig. 7. Effect of the location of aerator on membrane filterability.
mented for M1. However, when the additional aeration (1 L/min) was added to the other three membranes using the bubble stones, the membrane operation time was elongated depending on the aerator position. It took about 14 and 20 h for M2 and M3, whereas it was elongated to about 27 h for M4. This demonstrated that the nearer the aerator to the suction pump, the more efficient the alleviation of membrane biofouling in a submerged MBR. It is because the nearer the bio-cakes to suction pump, the smaller the biocake porosities and thus the greater membrane biofouling. The results in Fig. 7b coincided well with the heterogeneous distribution of bio-cake porosities over the membrane module which was determined experimentally and described in the previous section. In real MBR plants, uniform aeration is usually applied throughout the entire membrane module. From a practical point of view, however, the results from this study suggest that in the design and operation of a submerged MBR the aeration should focus as much as possible on the part of the module where a bio-cake with smaller porosity develops in order to increase membrane-cleaning efficiency through the aeration.
[1] M.A. Yun, K.M. Yeon, J.S. Park, C.H. Lee, J. Chun, D.J. Lim, Characterization of biofilm structure and its effect on membrane permeability in MBR for dye wastewater treatment, Water Res. 40 (1) (2006) 45–52. [2] Y.L. Jin, W.N. Lee, C.H. Lee, I.S. Chang, X. Huang, T. Swaminathan, Effect of DO concentration on biofilm structure and membrane filterability in submerged membrane bioreactor, Water Res. 40 (15) (2006) 2829–2836. [3] S.H. Hong, W.N. Lee, H.S. Oh, K.M. Yeon, B.K. Hwang, C.H. Lee, I.S. Chang, S. Lee, The effects of intermittent aeration on the characteristics of bio-cake layers in a membrane bioreactor, Environ. Sci. Technol. 41 (17) (2007) 6270–6276. [4] I.S. Chang, P.L. Clech, B. Jefferson, S. Judd, Membrane fouling in membrane bioreactors for wastewater treatment, J. Environ. Eng. 128 (11) (2002) 1018–1029. [5] T. Ueda, K. Hata, Y. Kikuoka, O. Seino, Effects of aeration on suction pressure in an submerged membrane bioreactor, Water Res. 31 (3) (1997) 489–494. [6] S.H. Yoon, H.S. Kim, I.T. Yeom, Optimization model of submerged hollow fiber membrane modules, J. Membr. Sci. 234 (1–2) (2004) 147–156. [7] W.N. Lee, I.S. Chang, B.K. Hwang, P.K. Park, C.H. Lee, X. Huang, Changes in biofilm architecture with addition of membrane fouling reducer in a membrane bioreactor, Process Biochem. 42 (4) (2007) 655–661. [8] B.K. Hwang, W.N. Lee, P.K. Park, C.H. Lee, I.S. Chang, Effect of membrane fouling reducer on cake structure and membrane permeability in membrane bioreactor, J. Membr. Sci. 288 (2007) 149–156. [9] M. Mulder, Basic Principles of Membrane Technology, Kluer Academic Publishers, Nethelands, 1991, pp. 230–231. [10] C. Staudt, H. Horn, D.C. Hempel, T.R. Neu, Volumetric measurements of bacterial cells and extracellular polymeric substance glycoconjugates in biofilm, Biotechnol. Bioeng. 88 (5) (2004) 585–592. [11] H. Beyenal, C. Donovan, Z. Lewandowski, G. Harkin, Three-dimensional biofilm structure quantification, J. Microbiol. Methods 59 (2004) 395–413. [12] APHA, AWWA, WEF, Standard Methods for the Examination of Water and Wastewater, 22nd ed., American Public Health Association, Washington, DC, 2005. [13] I.S. Chang, C.H. Lee, Membrane filtration characteristics in membrane coupled activated sludge system—the effect of physiological states of activated sludge on membrane fouling, Desalination 120 (3) (1998) 221–233. [14] M. Dubois, K.A. Gilles, J.K. Hamilton, P.A. Rebers, F. Smith, Colorimetric method for determination of sugars and related substances, Anal. Chem. 28 (1956) 350–356. [15] H.M. Lee, C.H. Lee, K.Y. Chung, S.H. Lee, Prediction model for transmembrane pressure in a submerged hollow-fiber microfiltration membrane, Sep. Sci. Technol. 39 (8) (2004) 1833–1856. [16] P. Shao, R.Y.M. Huang, An analytical approach to the gas pressure drop in hollow fiber membranes, J. Membr. Sci. 271 (1/2) (2006) 69–76.
Contents lists available at ScienceDirect
Journal of Membrane Science journal homepage: www.elsevier.com/locate/memsci
Correlation between local TMP distribution and bio-cake porosity on the membrane in a submerged MBR Woo-Nyoung Lee, Won-Suk Cheong, Kyung-Min Yeon, Byung-Kook Hwang, Chung-Hak Lee ∗ School of Chemical and Biological Engineering, Seoul National University, Seoul 151-744, Republic of Korea
a r t i c l e
i n f o
Article history: Received 13 June 2008 Received in revised form 17 January 2009 Accepted 25 January 2009 Available online 5 February 2009 Keywords: Membrane bioreactor Membrane fouling Bio-cake porosity Local TMP distribution Local aeration method
a b s t r a c t In a submerged membrane bioreactor (SMBR) the spatial distribution of bio-cake porosity on the membrane module is very important in the detection of local membrane biofouling, which is directly related to efficient membrane-cleaning and energy consumption. In this study, the local bio-cake porosity was determined experimentally and correlated with the local flux measured by a newly developed experimental method. This exercise made it possible to suggest the optimum position of an aerator in the reactor to obtain minimal membrane biofouling. The local transmembrane pressure (TMP) on the membrane module became bigger and bigger as the distance from the local position to the suction pump became nearer and nearer owing to the pressure drop inside the hollow fiber lumen. A good correlation was found between the local TMP distribution and the local porosity of bio-cake formed on the membrane surface which was measured by a confocal laser scanning microscope (CLSM) and image analysis technique. The bio-cake formed on a local position of the membrane near the suction pump was more easily compressed by higher TMP, and thus its porosity became lower. From this local porosity distribution on the membrane the effect of aerator positions on the membrane biofouling was studied. Under identical mixing intensity, the positioning of a diffused aerator near the suction pump was the most effective location for the alleviation of the membrane fouling because the porosity of bio-cake at that location was the smallest, and thus the worst biofouling took place. © 2009 Elsevier B.V. All rights reserved.
1. Introduction It is widely known that the formation of bio-cake is one of the major hurdles to be overcome in a submerged membrane bioreactor (MBR) [1,2], because the filtration performance in MBR is closely related to bio-cake characteristics such as the porosity and amount of the attached bio-cake [3]. Many studies have been carried out to reduce or eliminate the bio-cake on the membrane surface in several ways, such as aeration, high-shear slug flow, module modification, and so on [4–6]. From a practical point of view, aeration has been the most useful operating parameter for the reduction of biofilm formation as well as the supply of dissolved oxygen in a submerged MBR. However, during the operation of MBR only the highest transmembrane pressure (TMP) or the average flux on a membrane module is monitored instead of spatial distribution of the TMP or flux. Consequently, the aeration is usually applied uniformly or monotonously to the entire membrane module without taking into account the difference in the extent of local biofouling developed on the membrane surface, which may result in inefficient membrane-cleaning and energy consumption. On the other hand,
it has been reported that the distribution of bio-cake porosity on which the hydraulic permeability through the membrane mostly depends is uneven along the length of a hollow fiber membrane in a submerged MBR [7]. The uneven distribution of bio-cake porosity on the membrane may be closely associated not only with the spatially uneven TMP distribution but also with the best positioning of an aerator to get the most efficient cleaning. However, few studies have reported on this issue. In this study, a new experimental method was developed to determine the local TMP profile on a hollow fiber membrane module in order to link it to the local porosity profile of bio-cakes which was measured by means of a confocal laser scanning microscope (CLSM) and image analysis technique [7,8]. Based on the profile of the local distribution of bio-cake porosity, the most probable position of the aerator in the bioreactor was predicted and confirmed experimentally in order to get the most efficient cleaning in a submerged MBR.
2. Materials and methods 2.1. Local flux measurement
∗ Corresponding author. Tel.: +82 2 880 7075; fax: +82 2 874 0896. E-mail address: [email protected] (C.-H. Lee). 0376-7388/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.memsci.2009.01.036
Fig. 1 shows the schematic diagram for local TMP measurement. The system consists of three reactors (R1–R3). A single hollow fiber
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Fig. 1. Schematic diagram for local TMP measurement.
(F1–F3, outer diameter D0 = 1.9 mm, ZeeWeed 500c, PVDF, Zenon) was put into each reactor, which was divided into five compartments (C1–C5). Actually, each compartment in Fig. 1 was replaced by a mass cylinder (Falcon tube) of 50 mL to prevent the fluid in each compartment from moving to other compartments as shown in Fig. 2. Each compartment (or cylinder) was filled with 50 mL D.I. water. The effective membrane surface area in each compartment was 1.5 cm2 . The left end of each fiber was sealed, and the other ends of three fibers were inter-connected by a silicon tube which extended to the suction pump. A permeate of D.I. water through the three fibers was continuously withdrawn at constant flux of 100 L/m2 h by a peristaltic pump. The smaller the number of compartments (e.g., C1) or the number of fibers (e.g., F1) the closer they are to the pump, i.e., [F3, C5] indicates the farthest part from the pump whereas [F1, C1] indicates the nearest one. The TMP measured using the pressure gauge was maintained at 24 kPa during the suction of D.I. water. Fig. 2 shows the variations in the water level before and after the operation of the suction pump depending on the compartment (C1–C5) or the position on a hollow fiber (it showed only one fiber). As soon as the suction pump ran, the hollow fiber membrane sucked up D.I. water, and thus the water levels went down at different rates depending on the compartment. The variations in permeate volume were measured to calculate the 15 (5 × 3) local permeate fluxes through the fraction of a fiber in each compartment (C1–C5) for all three fibers (F1–F3). 2.2. Calculation of TMP The local permeate flux at each compartment in Table 3 was calculated by Eq. (1): Ji =
Vi Ai
(1)
where Ji is the local permeate flux, Vi is the volume of local permeate accumulated for 1 h through a fraction of a fiber in each
Fig. 3. Schematic diagram of an MBR system.
compartment, and Ai is the effective surface area of membrane (1.5 cm2 ) submerged in each compartment. The local TMP applied to a fraction of a fiber in each compartment was calculated by Eq. (2) based on resistance-in-series model [9]: PTi = Rm Ji
(2)
where PTi is the local TMP at each compartment, is the viscosity of water, and Rm is the intrinsic membrane resistance (1.15 × 1012 m−1 ). 2.3. MBR system Fig. 3 shows the schematic diagram of MBR setup, and operating conditions are listed in Table 1. Compressed air (air flow rate = 1 L/min) was supplied through a bubble stone on the bottom of the reactor with a working volume of 2 L to provide dissolved oxygen and turbulence. Hydraulic retention time (HRT) and sludge retention time (SRT) were maintained at 10 h and 30 days, respectively. The main carbon and nitrogen sources in the synthetic wastewater were glucose and ammonium sulfate, respectively. Influent COD was 300 mg/L, whereas the effluent COD was less than 6 mg/L so that the treatment efficiency showed over 98% during the whole operation. The average particle size of sludge floc was around 60 (±5) m during the whole experiment. Soluble EPS concentration was showed 8.4 (±1.1) mg EPS/L. At steady state, the concentration of suspended biomass was kept constant at 4800 (±200) mg/L. As shown in Fig. 4, an I-shaped hollow fiber module, made of PVDF (ZeeWeed 500c, Zenon) with a pore size of 0.04 m and a Table 1 Operating conditions of an MBR system. Working volume (L) TMP (kPa) Constant flux (L/m2 h) Air flow rate (L/min) DO (mg O2 /L) pH Feed concentration (mg COD/L) HRT (h) SRT (day) MLSS (mg/L)
Fig. 2. Variations in the water level over a hollow fiber during suction.
( ) Standard deviation.
2 <30 15 1 >5 (±0.2) 6.5–7.5 300 (±10) 10 30 4800 (±200)
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Fig. 4. The hollow fiber module and sampling points for the bio-cake specimens.
surface area of 200 cm2 , was dipped vertically into the MBR. The top ends of fibers were sealed with epoxy resin, and suction was done through the potted end of fibers. A permeate through the submerged membrane module was continuously withdrawn at a constant flux of 15 L/m2 h. The TMP was continuously monitored until it reached 30 kPa. The average membrane operating time, i.e., the time required to reach TMP of 30 kPa, was about 5 days. The used membrane module was cleaned with 500 mg NaClO/L solution for 6 h and then reinstalled for the next run. 2.4. Determination of bio-cake porosity When the TMP reached 30 kPa, the membrane module was removed from the MBR for measurement of the local bio-cake porosity. In Fig. 4, F1 –F13 represent the horizontal location of 13 hollow fibers in a membrane module, whereas P1–P4 represent the vertical location of each fiber. Three fibers (F1 , F9 , and F13 ) were cut from the membrane module, and each one was further cut into four segments (P1–P4) with the same length of 3 cm, so 12 specimens (3 fibers × 4 specimens/fiber) in total were obtained for staining and CLSM. The smaller the number of F1 and P1 represents the closer to the pump, i.e., [F1 , P1] indicate the nearest segment to the pump whereas [F13 , P4] indicate the farthest one from the pump. The list of fluorescent dyes used in the bio-cake staining is given in Table 2. Cells and polysaccharides in the bio-cake were stained with SYTO9 and Concanavalin A (Molecular Probes, Eugene, USA), which is specific to nucleic acids and polysaccharides. SYTO9 and Concanavalin A were added to the bio-cake samples at the concentration of 1.67 M/mL and 0.1 mg/mL, respectively. After dye addition, the bio-cake was incubated for 30 min at room temperature in the dark and then washed with phosphate-buffered saline (PBS) solution. The stained bio-cake was immediately observed by
means of a CLSM (Radiance 2000, Bio-Rad, UK) which consisted of a microscope (Nikon, Japan) and krypton–argon mixed gas laser source. Signals were recorded in the green channel and the red channel. For the observation (magnification ×600), an oil lens with 40 × 1.3NA (numerical aperture) lens was used. A series of CLSM images of optical sections with a step size of 1 m were simultaneously taken for each specimen. The spatial resolutions of CLSM are 395 nm in the xy plane and 500 nm in the z direction. To check interferences from background fluorescence of the membrane, the fresh PVDF membrane followed the same procedure of staining as the used membrane with bio-cakes. But any fluorescence was not detected, indicating no background interference from the PVDF membrane. Two CLSM images based on cell and polysaccharide respectively were merged together by means of the IMARIS Program (v4.1.3, Bitplane AG, Zurich, Switzerland) [10] and then the merged images were used for calculation of the porosity of bio-cake with a software, Image Structure Analyzer-2 (ISA-2), developed by Beyenal et al. [11]. The relative standard deviations in determining the bio-cake porosity are in the range of 2.0–2.9%, indicating fairly good reproducibility for this analysis. Fig. 5a and b represents the merged CLSM images for the bio-cakes developed on the membrane module corresponding to the local points [F1 , P3] and [F13 , P3], respectively in Fig. 6a. 2.5. Analytical methods Mixed liquor suspended solids (MLSS) were measured according to the analytical methods described in the standard methods [12]. DO concentration and pH of a mixed liquor were measured with a multi-meter (Orion 1230, USA). COD was determined by the spectrophotometric method (DR 4000, HACH, USA). Particle size distributions were analyzed with a particle size analyzer, based on a laser scattering method (Mastersizer/E, Malvern, UK)
Table 2 Fluorescence probes used in bio-cake staining and their spectral characteristics. Probes
Label
Excitation (nm)
Emission (nm)
Specificity (target)
Channel
SYTO9 Concanavalin A
– TRITCa
488 568
515/30 600/50
Nucleic acids (Bacterial cell) ␣-Mannose, ␣-glucose (Polysaccharide)
Green Red
a
TRITC, tetramethylrhodamine isothiocyanate.
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Fig. 5. Merged CLSM images (Green; cells, Red; polysaccharides); (a) [F1 , P3] and (b) [F13 , P3] represent the local points in Fig. 6a from which two bio-cake specimens were taken respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)
Fig. 6. Vertical and horizontal distribution of (a) bio-cake porosity and (b) TMP.
which allows the measurement of particle size in the range of 0.1–600 m. The extraction of bound EPS from suspended microbial flocs was carried out through a heating method [13]. Proteins and polysaccharides were analyzed by spectrophotometric methods: protein concentration was determined according to the modified Lowry method with the Lowry reagent (P 5656, Sigma). A calibration curve was prepared with a solution of bovine serum albumin. For the quantitative analysis of polysaccharides, the phenol-sulfuric acid method was used with glucose as a standard [14]. 3. Results and discussion 3.1. Local distribution of permeate flux and TMP In a submerged MBR, the spatial distribution of bio-cake porosity and flux in the membrane module is vital in identifying local membrane biofouling which is directly related to efficient membrane-cleaning, energy consumption, and membrane life span. In operating the submerged MBR, however, we usually measure only the average flux or the highest TMP, neglecting their local distributions in the same membrane module. The TMP dis-
tribution of a submerged hollow fiber has been predicted via a model equation, but has not yet been determined experimentally [15,16]. The local flux distribution throughout the hollow fiber membrane module was measured with a new experimental method developed in this study, as described in Section 2. Using Eq. (2) we calculated local TMPs by measuring local permeate fluxes for D.I. water (Table 3). During the operation of a MBR system, however, bio-cakes continuously develop on the membrane surface and thus bio-cake resistances change along with the operation time. In this case, although we can measure local permeate fluxes for mixed liquor in an activated sludge reactor we cannot use any more Eq. (2) because the intrinsic membrane resistance (Rm ) should be replaced by resistances originated from not only the membrane itself (Rm ) but also the architecture of bio-cakes formed which we do not know. Therefore it is impossible to obtain the spatial distribution and temporal change of local TMPs on the membrane surface when the real feed, e.g., the mixed liquor is filtered. Consequently, the distribution of local TMPs shown in Fig. 3 does not represent those developed with the bio-cakes because the absolute values of local TMPs measured with D.I. water in Table 3 should be different from those measured with mixed liquor.
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Table 3 Local distributions of permeate volume, permeate flux, and TMP. C5
C4
C3
vations, comparisons between the local porosity and local TMP are made in the following section. C2
C1
V (mL)
Fiber 1 Fiber 2 Fiber 3
14.0 13.3 12.5
14.8 13.9 13.0
15.5 14.6 13.7
16.3 15.3 14.3
17.1 16.1 15.2
J (L/m2 h)
Fiber 1 Fiber 2 Fiber 3
93.3 88.7 83.3
98.7 92.7 86.7
103.3 97.3 91.3
108.7 102.0 95.3
114.0 107.3 101.3
PT (kPa)
Fiber 1 Fiber 2 Fiber 3
16.8 16.0 15.0
17.8 16.7 15.6
18.6 17.5 16.5
19.6 18.4 17.2
20.5 19.3 18.3
The bold values represents the nearest or the farthest position from the suction pump.
However, the suction pressure inside of hollow fiber lumens would be dropped along with the fiber length and the local TMPs are largely dependent on their relative positions to a suction pump in a submerged MBR. For example, TMP at C1 is certainly greater than that at C5 because C1 is closer to the suction pump than C5 for each fiber in Fig. 1. Accordingly the relative sizes of local TMPs were assumed to be consistent for both measurements with D.I. water and mixed liquor, respectively. Based on this assumption, we tried to compare the relative TMPs with the relative porosities of bio-cakes to identify the correlation between them which will be discussed in Section 3.3. Table 3 shows the permeate volume, permeate flux, TMP for various combinations of compartments (C1–C5) and fibers (F1–F3) depicted in Fig. 1. For the fixed filtration time of 1 h, the largest volume of water was permeated in F1 and C1 which were located at the nearest point to the suction pump, whereas the least volume of water was permeated in F3 and C5 which were located at the farthest point to the pump. The permeate volumes were gradually increased as the membrane fibers approached the suction pump, from F3 to F1 or from C5 to C1. The local permeate flux (Ji ) was calculated by use of Eq. (1) and the local permeate volume (Vi ). Just like the permeate volume, the local permeate flux changed from 83.3 to the maximum of 114.0 L/m2 h depending on the distance of a fiber fraction from the suction pump. It suggests a heterogeneous flow rate exists through the same membrane module. The distribution of local TMP (PTi ) was also calculated with Eq. (2) and the local permeate flux (Ji ). As expected, the local TMP also ranged from the minimum value of 15.0 kPa at the farthest point [F3, C5] to the maximum of 20.5 kPa at the nearest point [F1, C1] from the suction pump. This result coincides well with the report by Lee et al. [15] and Shao and Huang [16], where they predicted theoretically the greatest local TMP at the potted end [C1] of a hollow fiber and the lowest local TMP at the sealed end [C5]. 3.2. Local distribution of bio-cake porosity In the operation of MBR depicted in Fig. 3, when the TMP reached 30 kPa, the hollow fiber membrane module was taken out from the MBR to analyze the local porosities of bio-cakes formed on the membrane surface. Fig. 6a shows the vertical and horizontal distributions of bio-cake porosities formed on the surface of a hollow fiber membrane module. The bio-cake porosity was dependent on the position of bio-cake over the module. On the vertical level, e.g., for the same fiber, the bio-cake porosity near the potted end [P1] was lower than that near the sealed end [P4] for all fibers tested. In addition, on the horizontal level the bio-cake porosities from a fiber near the suction part [F1 ] were always lower than those from a fiber on the right parts (F9 and F13 ). To elucidate these obser-
3.3. Correlation between the local TMP distribution and the bio-cake porosity The distribution of local TMP along the vertical and horizontal position of hollow fibers was determined with a method described in Section 3.1 and shown in Fig. 6b. TMP was gradually increased as the location over the module approached horizontally or vertically nearer to the suction pump. As a result, the bio-cake formed on the nearest point to the suction pump (F1 , P1 in Fig. 6a) would be compressed most easily by the highest TMP, and thus its porosity should be lower than that of any other point over the module. In contrast, the bio-cake formed on the farthest point to the suction pump (F13 , P4 in Fig. 6a) would be compressed the least by the lowest TMP, and thus its porosity should be higher than that of any other point over the module. It was concluded that there is good correlation between local bio-cake porosity and local TMP over the membrane in a submerged MBR. These findings led us to a further study on the optimum position of an aerator inside the bioreactor to mitigate the membrane biofouling and thus to reduce energy consumption. 3.4. Optimum position of an aerator in a submerged MBR to reduce membrane biofouling We found that heterogeneous porosities of the bio-cake are generated over the same membrane module during the operation of a submerged MBR owing to the heterogeneous TMP development, depending on how far the zone on the module is located from the suction pump, the smallest porosity being at the nearest zone to the suction pump whereas the highest porosity is at the farthest zone from the suction pump. In other words, the extent of biofouling on the membrane module which is exposed to the identical mixed liquor of activated sludge could differ from place to place. This suggests that we should change the aeration strategy to mitigate the biofouling by aeration more efficiently. An additional filtration experiment was therefore carried out to confirm the best position of an aerator to achieve the least membrane biofouling. Fig. 7a shows a schematic diagram of an MBR with different locations of aerators. The bioreactor was divided into four compartments by means of baffles to minimize the effect of shear force generated by the aeration from the other compartments. The mixed liquor was, however, freely moved throughout the bioreactor so that all four membrane modules could be exposed to the same environment of activated sludge (MLSS = 4800 mg/L). Four hollow fiber membrane modules (ZeeWeed 500c, PVDF, Zenon) of the same size (fiber length = 20 cm; membrane area = 60 cm2 ) were dipped into each compartment. The aeration was done using a plate type aerator at the air supply of 1 L/min on the bottom of all four compartments (the plate type aerator was not depicted in Fig. 7a). And then, the same strength of aeration (air supply of 1 L/min) using a bubble stone was supplemented to three compartments (for M2–M4) where each bubble stone located at different position. For Membrane 1 (M1), no bubble stone was supplied. For M2, the bubble stone was located near the sealed end which is farthest to the suction pump. For M3, it was located in the middle of the part, whereas for M4 it was located near the potted end which is nearest from the suction pump. Filtration under the same constant flux (30 L/m2 h) was conducted simultaneously through four membrane modules and the variations in TMP for four submerged modules were also simultaneously monitored and plotted in Fig. 7b. To reach the same TMP of 30 kPa, it took about 8 h for M1. It showed the smallest membrane operation time than those of other membrane modules since the aeration was not supple-
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4. Conclusions In this study, the local bio-cake porosity was determined experimentally and correlated with the local TMPs measured by a newly developed experimental method. This exercise made it possible to suggest the optimum position of an aerator in MBR to obtain higher membrane-cleaning efficiency. The following conclusions can be drawn: (1) During the operation of submerged MBR under the constant flux, the distribution of local TMPs is developed depending on local positions on the membrane due to the pressure drop along the lumen of hollow fibers. (2) The distribution of local TMPs coincided well with the distribution of the bio-cake porosities. The bio-cake formed on the membrane near the suction pump would be more easily compressed by higher TMP, and thus its porosity should be lower than those at other locations. (3) The positioning of an aerator should be near to the part of the membrane module where a bio-cake with smaller porosity develops in order to increase membrane-cleaning efficiency through the aeration. Acknowledgements This work was supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the government (MOST) (No. R0A-2007-000-20073-0). The authors thank the National Instrumentation Center for Environment Management (NICEM) for the use of the confocal laser scanning microscope system. References
Fig. 7. Effect of the location of aerator on membrane filterability.
mented for M1. However, when the additional aeration (1 L/min) was added to the other three membranes using the bubble stones, the membrane operation time was elongated depending on the aerator position. It took about 14 and 20 h for M2 and M3, whereas it was elongated to about 27 h for M4. This demonstrated that the nearer the aerator to the suction pump, the more efficient the alleviation of membrane biofouling in a submerged MBR. It is because the nearer the bio-cakes to suction pump, the smaller the biocake porosities and thus the greater membrane biofouling. The results in Fig. 7b coincided well with the heterogeneous distribution of bio-cake porosities over the membrane module which was determined experimentally and described in the previous section. In real MBR plants, uniform aeration is usually applied throughout the entire membrane module. From a practical point of view, however, the results from this study suggest that in the design and operation of a submerged MBR the aeration should focus as much as possible on the part of the module where a bio-cake with smaller porosity develops in order to increase membrane-cleaning efficiency through the aeration.
[1] M.A. Yun, K.M. Yeon, J.S. Park, C.H. Lee, J. Chun, D.J. Lim, Characterization of biofilm structure and its effect on membrane permeability in MBR for dye wastewater treatment, Water Res. 40 (1) (2006) 45–52. [2] Y.L. Jin, W.N. Lee, C.H. Lee, I.S. Chang, X. Huang, T. Swaminathan, Effect of DO concentration on biofilm structure and membrane filterability in submerged membrane bioreactor, Water Res. 40 (15) (2006) 2829–2836. [3] S.H. Hong, W.N. Lee, H.S. Oh, K.M. Yeon, B.K. Hwang, C.H. Lee, I.S. Chang, S. Lee, The effects of intermittent aeration on the characteristics of bio-cake layers in a membrane bioreactor, Environ. Sci. Technol. 41 (17) (2007) 6270–6276. [4] I.S. Chang, P.L. Clech, B. Jefferson, S. Judd, Membrane fouling in membrane bioreactors for wastewater treatment, J. Environ. Eng. 128 (11) (2002) 1018–1029. [5] T. Ueda, K. Hata, Y. Kikuoka, O. Seino, Effects of aeration on suction pressure in an submerged membrane bioreactor, Water Res. 31 (3) (1997) 489–494. [6] S.H. Yoon, H.S. Kim, I.T. Yeom, Optimization model of submerged hollow fiber membrane modules, J. Membr. Sci. 234 (1–2) (2004) 147–156. [7] W.N. Lee, I.S. Chang, B.K. Hwang, P.K. Park, C.H. Lee, X. Huang, Changes in biofilm architecture with addition of membrane fouling reducer in a membrane bioreactor, Process Biochem. 42 (4) (2007) 655–661. [8] B.K. Hwang, W.N. Lee, P.K. Park, C.H. Lee, I.S. Chang, Effect of membrane fouling reducer on cake structure and membrane permeability in membrane bioreactor, J. Membr. Sci. 288 (2007) 149–156. [9] M. Mulder, Basic Principles of Membrane Technology, Kluer Academic Publishers, Nethelands, 1991, pp. 230–231. [10] C. Staudt, H. Horn, D.C. Hempel, T.R. Neu, Volumetric measurements of bacterial cells and extracellular polymeric substance glycoconjugates in biofilm, Biotechnol. Bioeng. 88 (5) (2004) 585–592. [11] H. Beyenal, C. Donovan, Z. Lewandowski, G. Harkin, Three-dimensional biofilm structure quantification, J. Microbiol. Methods 59 (2004) 395–413. [12] APHA, AWWA, WEF, Standard Methods for the Examination of Water and Wastewater, 22nd ed., American Public Health Association, Washington, DC, 2005. [13] I.S. Chang, C.H. Lee, Membrane filtration characteristics in membrane coupled activated sludge system—the effect of physiological states of activated sludge on membrane fouling, Desalination 120 (3) (1998) 221–233. [14] M. Dubois, K.A. Gilles, J.K. Hamilton, P.A. Rebers, F. Smith, Colorimetric method for determination of sugars and related substances, Anal. Chem. 28 (1956) 350–356. [15] H.M. Lee, C.H. Lee, K.Y. Chung, S.H. Lee, Prediction model for transmembrane pressure in a submerged hollow-fiber microfiltration membrane, Sep. Sci. Technol. 39 (8) (2004) 1833–1856. [16] P. Shao, R.Y.M. Huang, An analytical approach to the gas pressure drop in hollow fiber membranes, J. Membr. Sci. 271 (1/2) (2006) 69–76.