- Email: [email protected]
Study of (ir)reversible fouling in MBRs under various operating conditions using new on-line fouling sensor
Separation and Purification Technology 81 (2011) 208–215
Contents lists available at SciVerse ScienceDirect
Separation and Purification Technology journal homepage: www.elsevier.com/locate/seppur
Study of (ir)reversible fouling in MBRs under various operating conditions using new on-line fouling sensor Celine Huyskens a,b,⇑, Silvia Lenaerts b, Etienne Brauns a, Ludo Diels a, Heleen De Wever a a b
VITO (Flemish Institute for Technological Research), Separation and Conversion Technology, Boeretang 200, 2400 Mol, Belgium University of Antwerp, Department of Bioscience Engineering, Groenenborgerlaan 171, 2020 Antwerp, Belgium
a r t i c l e
i n f o
Article history: Received 17 May 2011 Received in revised form 20 July 2011 Accepted 20 July 2011 Available online 27 July 2011 Keywords: Membrane bioreactor Fouling measurement Sludge retention time Hydraulic retention time
a b s t r a c t In this study, a new fouling sensor was validated under different conditions of hydraulic (HRT) and sludge retention time (SRT). The MBR-VFM (membrane bioreactor-VITO Fouling Measurement) allows the simultaneous determination of the physically reversible and irreversible fouling potential of a mixed liquor during a single crossflow filtration test. In accordance with the on-line filtration behavior, the measured reversible and irreversible fouling propensities differed significantly between MBRs operated at different combinations of HRT-SRT. Moreover, a significant negative correlation was found between the on-line permeability and the reversible and irreversible fouling propensity measured by the MBRVFM. This corresponded to observations made on membrane recovery after physical or chemical cleaning actions. Higher reversible and irreversible fouling were observed at lower HRT, presumably as a consequence of increased concentrations of foulants present. The effect of SRT was much smaller and restricted to the reversible fouling component. Possible explanations for the increased fouling at prolonged SRT are the higher sludge and colloid concentration and the smaller floc size. It can be concluded that the MBRVFM is a useful tool to monitor fluctuations in a mixed liquor’s (ir)reversible fouling potential and can contribute to a deeper understanding of the occurring fouling phenomena. Ó 2011 Elsevier B.V. All rights reserved.
1. Introduction Membrane fouling remains the major challenge for further membrane bioreactor (MBR) development and application. Despite numerous studies, to date no consensus exists on the exact phenomena occurring at the membrane surface during filtration. This can be attributed to the fact that fouling in MBRs is a very complex phenomenon, influenced by many factors, all acting and interacting simultaneously, i.e. operational conditions, membrane properties and mixed liquor characteristics [1]. As a result, it is very difficult to distinguish to what extent each of these factors affects on-line filtration performance. For effective fouling control and the selection of the appropriate countermeasures, identification of the dominant fouling factor is crucial. Apart from on-line filtration performance, additional fouling monitoring tools are thus required. Abbreviations: MBR-VFM, membrane bioreactor-VITO fouling measurement; VFMirrev, irreversible fouling propensity measured by MBR-VFM (%); VFMrev, reversible fouling propensity measured by MBR-VFM (%). ⇑ Corresponding author at: VITO (Flemish Institute for Technological Research), Separation and Conversion Technology, Boeretang 200, 2400 Mol, Belgium. Tel.: +32 14 33 69 49; fax: +32 14 32 65 86. E-mail addresses: [email protected] (C. Huyskens), silvia.lenaerts @ua.ac.be (S. Lenaerts), [email protected] (E. Brauns), [email protected] (L. Diels), [email protected] (H. De Wever). 1383-5866/$ - see front matter Ó 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.seppur.2011.07.031
Some of such tools have already been reported in literature. They can roughly be divided into three groups: (1) established parameters for the Conventional Activated Sludge (CAS) process which are also used to characterize MBR operation, (2) critical flux measurements and (3) various filtration test cell measurements. The first group comprises parameters such as capillary suction time (CST) and time-to-filter (TTF). Although these methods have the advantage that they are well-known and require only simple equipment and short time, literature references regarding their usefulness for MBR operation diverge [2–5]. For the critical flux measurements, a standard protocol is lacking, making comparison of reported data difficult. Moreover, a number of recent studies have indicated that slow fouling can take place even below the critical flux, questioning its relevance for long-term MBR operation [6,7]. Therefore, modifications were made to the more traditional flux-stepping protocol developed by Le-Clech et al. [8]. Flux-down stepping was added to acquire some information regarding the reversibility of fouling [9], or intermediate physical cleaning steps were introduced to rule out membrane history effects [10]. Similar protocols were developed for constant pressure filtration [11]. These protocols were the basis for the development of the Berlin Filtration Method (BFM) [12]. This in situ filtration test cell is used to assess mixed liquor filterability by flux-stepping experiments. The first results indicate that there is a good agreement between
209
C. Huyskens et al. / Separation and Purification Technology 81 (2011) 208–215
the measured filterability and the filtration performance of MBR pilot plants. Apart from the BFM, a large number of other filtration test cells have been developed specifically for the analysis of MBR mixed liquor filterability and fouling propensity, ranging from very simplified set-ups (dead-end or stirred dead-end test cells [13–14]) to miniature MBR replicas [15–16]. Although the latter were more successful to simulate fouling mechanisms occurring in MBRs, they can only provide information on short-term cake fouling or residual fouling rates [17–18]. To overcome this limitation, Evenblij et al. [19] developed a side-stream test cell in which the behavior of a ‘fouled’ membrane can be simulated during a short-term experiment by operating at high flux. This Delft Filtration Characterization method (DFCm) proved to be a useful tool to characterize and assess the filterability of mixed liquor collected from full-scale MBRs [20]. Moreover, parallel measurements with the DFCm and the BFM on different mixed liquor samples indicated that both gave a similar evaluation of filterability for most of the samples [21]. The fouling measurement elaborated in this paper, the MBRVITO Fouling Measurement (VFM), shares some common features with both the BFM and the DFCm. On the one hand, and in accordance to the BFM, the MBR-VFM is developed as an on-line test cell which can distinguish between reversible and irreversible fouling. On the other hand, and like the DFCm, the MBR-VFM is operated in hydrodynamic conditions that lead to accelerated fouling. The MBR-VFM set-up and measurement protocol were elaborately described in [22,23]. Moreover, previous experiments have shown that the MBR-VFM is accurate, reproducible and corresponded well with the on-line filtration behavior in a lab-scale MBR under the specific circumstances of the test. Consequently, it is anticipated that the MBR-VFM poses an important advantage over simply monitoring the on-line filtration data to understand and evaluate fluctuations in a mixed liquor’s fouling propensity. Since the nature of the foulants present and, hence, the occurring reversible and irreversible fouling mechanisms are strongly dependent on the operating conditions, a more thorough validation of the MBR-VFM under a range of operating conditions was considered essential. For this purpose, lab-scale MBRs were operated under different conditions of hydraulic retention time (HRT) and sludge retention time (SRT). Numerous articles have already indicated that both have a significant effect on mixed liquor characteristics and, consequently, fouling behavior (Table 1). The primary goal of this study was to examine whether these differences in filtration performance were also reflected in the reversible and irreversible fouling propensities measured by the MBR-VFM. In
addition, the effectiveness of the MBR-VFM as a fouling monitoring tool was compared with other frequently used fouling indicators, such as critical flux, CST and TTF. Finally, complementary analyses were performed on sludge and supernatant samples in order to gain a deeper insight in the exact mechanisms leading to the occurring reversible and irreversible fouling phenomena at different SRT and HRT. 2. Experimental 2.1. Experimental set-up Lab-scale MBRs were operated under different conditions of HRT and SRT using a 22 factorial design. In total, 4 different experimental runs were executed, representing all possible combinations of a low and high level for HRT and SRT, as shown in Table 2. Low and high values of 9 and 18 h for HRT and 10 and 30 d for SRT were adopted. As only two identical lab-scale MBRs were available, the experiment was carried out in 2 test blocks. These test blocks (block1: run 1 and 2 and block 2: run 3 and 4) were chosen in such a way that the block effect was confounded with the interaction effect and all information regarding the main effects of HRT and SRT was maintained. In each block, 2 identical lab-scale submerged MBRs were operated in parallel for a period of approximately 4 months. They were fed with municipal wastewater, which was prescreened at 0.75 mm. Sodium bicarbonate was added to the influent wastewater to maintain a constant neutral pH. The reactors were seeded with return sludge from a local municipal wastewater treatment plant with a concentration of 6 g L1. An acclimatization period of two times the SRT was adopted in order to reach steady-state conditions. Each MBR had an active volume of 22.5 L and was equipped with flat sheet microfiltration membranes (Kubota). Permeate was extracted by a peristaltic pump, following an 8 min– 2 min filtration–relaxation regime. Coarse bubble aeration at an air flow rate of 18 L min1 provided oxygen for the biodegradation processes and generated a crossflow near the membrane surface. Operating conditions during each run were similar, except for HRT and SRT, as shown in Table 2. Membrane surface area was adjusted as to obtain a different HRT at a similar constant flux of 16 L m2 h1. Sludge wasting was carried out daily to maintain the desired SRT. Once a transmembrane pressure (TMP) of 0.2 bar was reached, membranes were cleaned chemically by soaking them for 2 h in 500 ppm hypochlorite. Previous tests indicated that this cleaning procedure sufficed to recover permeability for
Table 1 Effects of hydraulic retention time (HRT) and sludge retention time (SRT) on fouling and mixed liquor characteristics in municipal wastewater treatment: literature data and own results. HRT range tested
Effect of increasing HRT
Reference
1–4 h 4–10 h 9–18 h
Fouling rate ;, soluble organic matter ;, number of submicron-size particles ;, filamentous bacteria ;, sludge flocs ; Cake layer resistance ;, EPS (carbohydrates) ;, particle size ; (Ir)reversible fouling ;, DOC, SMP, SMPc ;
[24] [25] This study
SRT range tested
Effect of increasing SRT
Reference
2–10 d 3–20 d 8–40 d 10–30 d 10–33 d
Fouling rate ;, SMP and SMPc ; Fouling rate ;, SMP and EPS ; Fouling rate ;, SMPc and colloids ; Reversible fouling " (permeability =), MLSS ", floc size ; 10–20 d ? fouling rate ;, EPS and SMP ; 20–33 d ? fouling rate = Fouling rate ;, DOC ;, characteristics DOC SRT Fouling layer ; (permeability =), SMP and EPS ; Reversible fouling " (irreversible =), characteristics SMP – SRT Gel layer ;, SMP ; Sludge viscosity ", optimum filterability in SRT range 40–80 d
[26] [27] [28] This study [29]
13–50 d 23–40 d 17–102 d 10 d-NW 20 d-NW
[30] [31] [32] [33] [34]
210
C. Huyskens et al. / Separation and Purification Technology 81 (2011) 208–215
Table 2 Operating conditions and mixed liquor characteristics (average ± standard deviation) in the different runs. Only data obtained after the acclimatization period are included. + and – respectively indicate positive and negative effects of sludge retention time (SRT) and hydraulic retention time (HRT) exhibited by the t-test at p < 0.05. Parameter
Block 1
SRT (d) HRT (h) F/M ratio (gCOD gMLVSS1 d1) VFMrev (%) VFMirrev (%) CST (s) n-CST (s L g1) TTF (s) n-TTF(s L g1) Critical flux (L h1 m2) MLSS (g L1) d50 (lm) COD TTF (mg L1) SMPP (mg L1) Specific protein content (mg gMLSS1) SMPC (mg L1) Specific carbohydrate content (mg gMLSS1)
Block 2
Effect
Run 1
Run 2
Run 3
Run 4
30 18 0.3 ± 0.2 11 ± 6 3±1 24 ± 11 13 ± 6 29 ± 11 16 ± 6 21 ± 4 1.8 ± 0.3 73 ± 16 114 ± 32 31 ± 6 17 ± 4 22 ± 7 12 ± 4
10 9 0.6 ± 0.12 32 ± 18 11 ± 7 125 ± 251 69 ± 139 2199 ± 6008 1113 ± 2957 14 ± 2 1.8 ± 0.5 114 ± 73 244 ± 89 41 ± 14 24 ± 9 48 ± 19 28 ± 11
10 18 0.4 ± 0.1 15 ± 5 4±2 18 ± 6 11 ± 4 29 ± 10 18 ± 6 18 ± 3 1.7 ± 0.4 176 ± 56 134 ± 40 29 ± 5 18 ± 6 26 ± 8 16 ± 6
30 9 0.2 ± 0.1 57 ± 25 21 ± 12 272 ± 190 53 ± 36 735 ± 1745 143 ± 339 13 ± 4 5.3 ± 0.7 69 ± 9 401 ± 192 44 ± 13 7±3 73 ± 23 15 ± 6
the specific installation and the specific wastewater used, implying effective removal of organic fouling. Permeate flow, TMP and temperature were measured on-line. Data acquisition was conducted with LabView (National Instruments, US). Reactor performance was evaluated by frequent analyses on influent and effluent. The evolution of TMP with time was used to monitor fouling of the lab-scale MBR membranes. In addition, the critical flux was determined weekly by the flux-step method [8] with a step duration of 10 min and a step height of 5 L m2 h1. For each critical flux measurement a cleaned Kubota membrane was used. The highest flux at which no perceptible increase of TMP with time could be observed was denominated as the critical flux. Furthermore, MBR-VFM analyses were performed twice a week, together with analyses of mixed liquor and supernatant properties. 2.2. The MBR-VFM The MBR-VFM method comprises a small-scale crossflow filtration installation and a specific measurement protocol, described in detail elsewhere [22]. The filtration installation consists of a fouling sensor in which a single tubular membrane can be placed, and a measuring apparatus. The membrane applied in this study was an 8 mm tubular polyvinylidene difluoride (PVDF) membrane (X-Flow, The Netherlands). The application of a specific measurement protocol enables the simultaneous determination of the physically reversible and irreversible fouling propensity. The applied measurement protocol consisted of the following steps: Step 0: conditioning, 5 min, air flow rate 500 ml min1 Step 1: reversible fouling measurement Step 1A: filtration, 15 min, TMP 0.10 bar, air flow rate 200 ml min1 Step 1B: relaxation, 10 min, air flow rate 500 ml min1
SRT
HRT
+
+
+ + +
fouling so that reversible and irreversible fouling can be distinguished. After data processing, the reversible and irreversible fouling propensity are represented as a normalized reversible (VFMrev) and irreversible fouling value (VFMirrev) ranging from 0% (no fouling) to 100% (very high fouling) [23]. 2.3. Analytical methods Chemical oxygen demand (COD), concentrations of ammonium (NH 4 —N), nitrite (NO2 —N), nitrate (NO3 —N), and total nitrogen (Ntot–N) as well as total phosphorus (Ptot–P) in influent and effluent were determined with standard cuvette tests of HACH LANGE. Mixed liquor suspended solids (MLSS), mixed liquor volatile suspended solids (MLVSS) and CST were determined according to Standard Methods [35]. The TTF was measured as the time needed to filter by gravity 25 ml of a 250 ml mixed liquor sample through a paper filter (Whatman 589/1 black ribbon). The COD of the TTF filtrate was measured to quantify the amount of particles smaller than 25 lm. The normalized CST and TTF (n-CST and n-TTF) were calculated by dividing the CST and TTF values by their respective MLSS concentration. The food-to-microorganisms (F/M) ratio was calculated as the influent COD loading per amount of MLVSS. The median particle size (d50) was calculated from the volume-based particle size distribution measured by laser diffraction (Coulter LS230). For soluble microbial products (SMP) measurements, supernatant was obtained from the mixed liquor by a 15 min centrifugation at 2000g and 4 °C, followed by a 0.45 lm filtration [36]. Protein concentration (SMPP) was quantified by the Lowry method [37] using c-globulin as a standard. Carbohydrates (SMPC) were determined by the phenol-sulfuric acid method [38] using glucose as a standard. The specific protein and carbohydrate content were determined by dividing the absolute concentrations by the MLSS. 2.4. Statistical analysis
Step n (n = 2. . .10): irreversible fouling measurement Step nA: filtration, 5 min, TMP 0.10 bar, air flow rate 500 ml min1 Step nB: relaxation, 3 min, air flow rate 500 ml min1 The first filtration step is performed at low air flow rates and the following filtration steps at high air flow rates to invoke reversible and irreversible fouling, respectively. The subsequent relaxation steps at high air flow rates were optimized to remove all reversible
The data were analyzed using Statistica [39]. Statistical significance was set at the 95% confidence interval for all analyses (p < 0.05). Correlations between the fouling indicators and on-line permeability were examined by computing a Pearson product-moment correlation matrix for the whole experimental period. The Student’s t-test between groups was used to examine significant differences in mixed liquor characteristics and filterability between the 2 levels for SRT and HRT. Afterwards, analysis of variance (ANOVA) was used on the average values obtained for each
211
C. Huyskens et al. / Separation and Purification Technology 81 (2011) 208–215
3. Results and discussion Throughout the experiment, reactor performance was conform to expectations for MBR processes (Table 3). The average COD removal was approximately 90% for all runs and nitrification from ammonia to nitrate proceeded without any problem. Due to the absence of anaerobic/anoxic compartments, almost no removal of
Table 3 Influent, effluent and removal efficiencies for COD and nutrients (average ± standard deviation) in the different runs. Only data obtained after the acclimatization period are included. + and respectively indicate positive and negative effects of sludge retention time (SRT) and hydraulic retention time (HRT) exhibited by the t-test at p < 0.05. Block 1
Block 2
Run 1 1
COD influent (mg L ) COD effluent (mg L1) COD removal (%) Ntot-N influent (mg L1) Ntot–N effluent (mg L1) Ntot–N removal (%) NH 4 —N influent (mg L1) NO 3 —N effluent (mg L1) Ptot–P influent (mg L1) Ptot–P effluent (mg L1) Ptot–P removal (%)
Run 2
418 ± 86 34 ± 8 91 ± 2 72 ± 8 68 ± 10 6±8 58 ± 7
40 ± 12 90 ± 3 65 ± 9 9±9
Run 3
Effect Run 4
SRT
HRT
472 ± 150 42 ± 9 46 ± 13 90 ± 4 89 ± 4 79 ± 11 71 ± 7 73 ± 10 9 ± 13 14 ± 28 63 ± 8
65 ± 11
62 ± 10
67 ± 7
68 ± 8
12 ± 2 12 ± 2 4±5
11 ± 2 9±7
20 ± 3 19 ± 3 5±9
19 ± 3 11 ± 27
+
3.1. Validation of the MBR-VFM 3.1.1. Suitability of the MBR-VFM as fouling indicator In this study, lab-scale MBRs were operated with different values for SRT and HRT. Low and high levels for SRT and HRT were selected so as to obtain sufficient variation in mixed liquor characteristics and, hence, fouling behavior in the lab-scale MBRs. They were based on literature and former experience. It can be noted that the values for HRT were high compared to the values usually reported in literature for municipal wastewater, as shown in Table 1. However, operation at lower HRT values (i.e. 6 h) was found to be practically unfeasible for the selected wastewater, as severe fouling occurred and maximal TMP was reached within only a day’s time. It can be seen from the evolution of TMP in the lab-scale MBRs (Fig. 1) that the different values for SRT and HRT applied in the various runs were properly selected, as clear differences in filtration performance were observed between the runs. TMP remained relatively stable in runs 1 and 3, both operating at high HRT. In contrast, periods of excessive fouling and foaming were observed at low HRT, in runs 2 and 4, resulting in TMP increases up to 0.2 bar in only a few days time. To ensure continued operation of the MBRs, fluxes were temporarily reduced to 10 L m2 h1 by add-
0,15
75
0,10
50
0,05
25
0,00 30
60 90 Time (d)
0,15
75
0,10
50
0,05
25
0,00
0 0
Run 1: SRT = 30 d, HRT = 18 h 100
0,20
TMP (bar)
100 VFM(ir)rev (%)
TMP (bar)
Run 3:SRT = 10 d, HRT = 18 h 0,20
120
0 0
75
0,10
50
0,05
25 0 30
60 90 Time (d)
120
TMP (bar)
0,15
VFM(ir)rev (%)
TMP (bar)
100
0
60 90 Time (d)
120
Run 4:SRT = 30 d, HRT = 9 h
Run 2: SRT = 10 d, HRT = 9 h 0,20
0,00
30
0,20
100
0,15
75
0,10
50
0,05
25
0,00
VFM(ir)rev (%)
Parameter
total N and P was observed. Few significant differences in removal efficiencies were found between the different runs. Only the COD removal slightly increased with HRT due to the lower organic loading rate. The limited effect of SRT and HRT on biological performance might be a result of the specific characteristics of the used municipal wastewater, which mainly contained easily biodegradable substances.
VFM(ir)rev (%)
run to elucidate the exact effects. Only data obtained after the acclimatization period were used.
0 0
30
60 90 Time (d)
TMP
VFMrev
120
VFMirrev
Fig. 1. Evolution of transmembrane pressure (TMP, spades) and reversible (VFMrev, stars) and irreversible fouling propensity (VFMirrev, triangles) at different conditions of hydraulic retention time (HRT) and sludge retention time (SRT). Vertical line: end of acclimatization period; vertical downward arrow: chemical cleaning with hypochlorite; gray shaded area: operation at reduced flux.
212
C. Huyskens et al. / Separation and Purification Technology 81 (2011) 208–215
ing extra membrane surface area (so that the desired HRT was maintained). But even at this low flux operation, chemical cleanings needed to be carried out frequently. Contrarily, no clear differences in on-line filtration performance were found between SRT 10 d and SRT 30 d. From the on-line filtration data it can thus be concluded that HRT 9 h clearly resulted in more severe fouling compared to HRT 18 h, while the effect of SRT was rather limited in the tested range. In line with this, statistical analysis indicated significant differences in the measured fouling potential between the various runs. This shows that the MBR-VFM is able to discern differences in mixed liquor characteristics and filterability resulting from various operating conditions. Furthermore, these differences corresponded to what was observed on-line. Both VFMrev and VFMirrev were significantly higher at HRT 9 h (runs 2 and 4) than at HRT 18 h (runs 1 and 3) (Table 2). The effect of SRT, on the other hand, was smaller and restricted to the reversible fouling component. Moreover, elevated fouling propensity values were measured during periods of strongly increasing TMP, while values were lower during stable operation (Fig. 1). At first sight, this effect seemed more pronounced for the reversible fouling potential. It should, however, be noted that the absolute values for VFMrev and VFMirrev are merely a consequence of some chosen settings in the MBR-VFM data processing software. As a result, these absolute values are of little practical relevance. Moreover, different settings were applied for the calculation of VFMrev and VFMirrev. It is thus not possible to simply compare both. One should rather consider the evolution and relative variation of VFMrev and VFMirrev to gain some insight in the effects of SRT and HRT on the mixed liquor’s reversible and irreversible fouling potential. This relative variation was quite similar for both fouling components. Moreover, VFMrev and VFMirrev followed the same trend; they increased and decreased simultaneously. Statistical analysis confirmed that there was a significant positive correlation between VFMrev and VFMirrev (Table 4). One could argue that this implies that reversible and irreversible fouling are not properly distinguished by the MBR-VFM method. However, opposite trends for both reversible and irreversible fouling have been observed in other experiments. Therefore, it is considered more likely that reversible and irreversible fouling were properly distinguished, but that both fouling components simply occurred at the same time in this experiment. After all, depending on the operating conditions applied, a combination of various foulants is present, which in turn results in the simultaneous occurrence of different fouling phenomena. Furthermore, various studies have indicated that some foulant species, such as SMP and colloids, can contribute to reversible (cake layer, gel layer. . .) as well as irreversible fouling phenomena (pore narrowing, adsorption. . .) [30,40]. Zhang et al. [41], for example, found that SMP with molecular weight of 3–10 kDa were positively correlated with the pore blocking resistance, while the amount of SMP with a molecular weight larger than 10 kDa had a strong positive effect on cake layer resistance. Such a size distinction in SMP was not made in this experiment. However, correlations of both the reversible and irre-
versible fouling potential with the protein and carbohydrate fraction of SMP were also observed in this experiment. Both the reversible and the irreversible fouling potential showed a significant negative correlation with on-line permeability (Table 4). In line with this, the on-line filtration performance indicated that fouling was partly reversible and partly irreversible: prolonged relaxation (during reactor stand-still) resulted in a recovery of permeability, although never complete. The absolute value of the correlation coefficient was slightly higher for reversible than for irreversible fouling. A possible explanation is that irreversible fouling develops only gradually and might thus not be measured that accurately during the short-term MBR-VFM measurement. Another possibility is that, due to its long-term character, a high irreversible fouling potential has little immediate impact, and it takes a while before it is reflected in the on-line permeability values. Reversible fouling, on the other hand, develops rapidly, making it easier to measure in a short-term. Moreover, a high reversible fouling potential will quickly manifest itself in a sudden permeability decline. Another possible explanation is that, despite a high irreversible fouling potential, little irreversible fouling actually occurs in the lab-scale MBRs because the membranes are protected by a reversible cake layer acting as a secondary membrane. In the MBR-VFM, this effect is prevented by measuring the irreversible fouling under high crossflow conditions, preventing cake layer formation. It should be noted that the relationship between the MBRVFM and on-line permeability was expected, since the MBRVFM characterizes the mixed liquor in terms of reversible and irreversible fouling potential, which obviously plays a determining role in the fouling process in the lab-scale MBRs. However, as stated before, the fouling process in the MBRs is also dependent on factors other than the actual mixed liquor characteristics, such as membrane history and operating conditions. This explains the occurrence of some data points for which the correlation with VFMrev does not seem to hold true (Fig. 2). A number of these points, for example, represent measurements performed immediately after a chemical cleaning, leading to higher permeability values, regardless of the actual fouling propensity. Some other on-line permeability data were measured during reduced flux operation, but conform to expectations, this did not result in significant differences compared to the measurements at higher flux. The MBR-VFM, on the other hand, is independent of the MBR system. Because a clean membrane is used for each measurement, it only represents the actual mixed liquor characteris-
Table 4 Pearson-r correlation matrix for the fouling indicators (N = 118, p < 0.05). Correlations which are significant at the p < 0.05 are written in italics.
Perm
VFMrev
VFMirrev
n-CST
n-TTF
0.25 VFMrev
0.19 0.90 VFMirrev
0.07 0.51 0.41 n-CST
0.02 0.40 0.33 0.88 n-TTF
Fig. 2. Correlation between on-line permeability and reversible fouling propensity (VFMrev) for the different experimental runs. Open symbols: measurements performed during normal operation, full symbols: measurements performed within 3 d after chemical cleaning.
C. Huyskens et al. / Separation and Purification Technology 81 (2011) 208–215
tics and filterability, while all other influences are excluded. When applied in conjunction to permeability monitoring, the MBR-VFM can thus elucidate to what extent a declining permeability trend can be attributed to bad mixed liquor quality or poor operation or membrane conditions. As such, it contributes to a better understanding and interpretation of the fouling process and can help in the selection of suitable actions to counter reversible and/or irreversible fouling.
3.1.2. Comparison with alternative fouling indicators Several small scale lab tests exist which enable to evaluate mixed liquor filterability, such as (n-)CST and (n-)TTF. Both were measured frequently during this experiment, in parallel to the MBR-VFM measurements. Like VFMrev and VFMirrev, n-CST and n-TTF differed significantly between the runs. Values were lower for runs 1 and 3, at high HRT, which is in line with the more stable filtration conditions observed (Table 2). Furthermore, both n-CST and n-TTF were significantly correlated with each other and with VFMrev and VFMirrev (Table 4). This was conform to expectations, since of all these methods aim at characterizing mixed liquor quality. Yet, in contrast to the MBR-VFM, neither (n-)CST nor (n-)TTF correlated well with the on-line permeability. It can thus be concluded that the actual fouling behavior of a mixed liquor is better evaluated with the MBR-VFM than with standard lab tests. A possible explanation is that the conditions during the MBR-VFM measurement are more similar to the ones in the examined lab-scale MBRs and thus more representative. Accordingly, literature gives contradictory result on the usefulness of CST and TTF as fouling indicators [2,5]. The measurement of the so-called critical flux is another widely used method to determine the actual fouling propensity. In this study, a cleaned membrane, similar to the ones used during the filtration process, was used for each measurement. Significantly different critical flux values were observed for all runs, which explains the on-line fouling behavior observed in the lab-scale MBRs (Table 2). As critical fluxes were on average lower than 15 L m2 h1 for runs 2 and 4, filtration at a constant flux of 16 L m2 h1 corresponded to supra-critical filtration conditions and consequently rapid fouling. When flux was lowered to 10 L m2 h1, sub-critical filtration conditions were obtained leading to a much lower fouling rate. For runs 1 and 3 critical fluxes were usually higher than 15 L m2 h1, implying sub-critical filtration conditions. The critical flux data were not included in the Pearson correlation matrix (Table 4) as they were performed less frequently than the other fouling indicator measurements. Nevertheless, statistical analysis confirmed a significant positive correlation of critical flux with on-line permeability (r = 0.47, N = 42). Moreover, significant negative correlations with both VFMrev (r = 0.72, N = 42) and VFMirrev (r = 0.70, N = 42) were found. Critical flux is thus also useful as a fouling indicator. It can be seen from Table 2 that TTF and CST were more variable than the MBR-VFM and especially critical flux, which showed a much smaller standard deviation. A possible explanation is that some changes in mixed liquor characteristics (due to changing conditions) had a larger impact on dead-end filtration (CST and TTF) as compared to crossflow mode (MBR-VFM, critical flux). Another possibility is that CST, TTF and MBR-VFM are more sensitive to changes in mixed liquor characteristics than the critical flux measurements (with 5 L m2 h1 flux steps). As such, some changes in mixed liquor characteristic might have been large enough to impact CST, TTF and MBR-VFM, but not significant enough to lower critical flux by 5 L m2 h1. Furthermore, critical flux was also measured less frequently than the other fouling indicators (once a week versus twice a week) and might not have captured all variation in mixed liquor characteristics.
213
3.2. Effect of HRT and SRT The effects of HRT and SRT on the fouling indicators and other mixed liquor characteristics are shown in Table 2. 3.2.1. Effect of HRT Even at lower flux operation, TMP increased at a faster rate and chemical cleanings needed to be carried out more frequently at HRT 9 h (runs 2 and 4) compared to HRT 18 h (runs 1 and 3). In line with this, all fouling indicators pointed at higher fouling at lower HRT. The MBR-VFM demonstrated that this effect applied to both the reversible and the irreversible fouling component. Presumably, the increased fouling at lower HRT was caused by the higher amounts of foulants present. The higher F/M ratio at HRT 9 h compared to 18 h resulted in significantly higher concentrations of suspended solids, colloids and solutes, which is in accordance with the results described in literature (Table 1). Apart from the higher values, foulant concentrations and fouling indicator values were also much more variable in runs 2 and 4 compared to runs 1 and 3, even though steady-state was reached in terms of MLSS concentration and removal efficiencies after the acclimatization period. This clearly indicates that lower HRT operation resulted in less stable operating conditions, possibly rendering the microorganisms more susceptible to stress caused by (uncontrollable) external factors such as temperature, influent composition etc. Contrary to the observations of Chae et al. [25] and Meng et al. [42], no significant effect of HRT on the volume-based particle size distribution was found. From the results of the statistical analysis, it can thus be concluded that low HRT operation clearly resulted in increased fouling. However, when looking at the results in more detail, it can be seen that the mechanisms leading to this increased fouling differed between runs 2 and 4. Since all other operating parameters were similar, this discrepancy was assumed to be related to the different values for SRT. Our hypothesis was supported by the fact that the absolute CST and TTF were clearly higher for run 4 compared to runs 1 and 3, while the normalized CST and TTF hardly differed. In run 4, the combination of low HRT and high SRT resulted in a much higher MLSS concentration compared to the other runs, which in turn caused severe fouling. Similarly, Meng et al. [42] attributed the higher reversible fouling at shorter HRT to the increased MLSS. Some authors have suggested that high sludge concentrations lead to increased sludge viscosity, which sharply reduces the shear stress caused by membrane aeration and thus promotes fouling [43]. However, as MLSS concentrations were relatively low, viscosity was not assumed to play a crucial role in this experiment. It should be noted that these low MLSS concentrations were not a deliberate choice, since the MLSS of the sludge used as an inoculum for the MBRs was higher (6 g L1). During the course of the experiment, however, MLSS gradually decreased as a consequence of the values chosen for HRT, SRT and the characteristics of the wastewater. In contrast to run 4, MLSS was much lower in run 2 and in the same order of magnitude as for runs 1 and 3, due to the higher amounts of sludge wasted daily (low SRT). As a result, n-CST and n-TTF remained higher compared to the other runs. Factors other than MLSS must thus be responsible for the higher fouling under these conditions. Presumably, the main culprit was the higher F/ M ratio in run 2, resulting from the combination of low MLSS and high organic loading. It is well known that high F/M ratios lead to decreased biodegradation and increased production of SMP [44]. This was also observed in this experiment. Both the absolute SMP concentrations and the specific SMP content were significantly higher for run 2. In contrast, the specific protein and carbohydrate content were much lower in run 4, which clearly indicated that the elevated SMP concentrations measured in run 4 were merely a consequence of the higher amount of microorganisms present.
214
C. Huyskens et al. / Separation and Purification Technology 81 (2011) 208–215
Indeed, the F/M ratio in run 4 was similar and even slightly lower than in runs 1 and 3, representing stable operating conditions. It can be concluded from this experiment that the effect of HRT is pronounced, but also strongly dependent on the other operating conditions. Although low HRT resulted in increased fouling, regardless of the level of SRT, the mechanisms leading to this increased fouling differed. The interaction effect of SRT and HRT could not be confirmed in a statistical way, as it was confounded with the blocking effect. 3.2.2. Effect of SRT In accordance to the observations made on-line, SRT had little effect on the fouling indicator measurements in the tested range. CST, TTF, critical flux and irreversible fouling were unaffected. Although the reversible fouling component increased with increasing SRT, this effect was much smaller than the effect of HRT. The increased reversible fouling might be related to the smaller median volume-based floc size at prolonged SRT. After all, the back transport velocity of particles increases with size. The deposition of the larger flocs present at SRT 10 d can thus more easily be controlled by high shear aeration. In addition, smaller particles form a denser cake with a lower porosity and a higher specific resistance. A possible explanation for the lower floc size at prolonged SRT is the reduced sludge growth due to substrate limitation [45]. Furthermore, high SRT resulted in increased MLSS due to the smaller amounts of sludge wasted, which in turn led to decreased F/M ratios. With regard to SMP, a significant increase of the carbohydrate and colloid concentration with SRT was observed (but not for proteins). In contrast, most studies point at lower fouling at high SRT due to the lower concentrations of SMP present (higher consumption and/or lower production) (Table 2). In our experiment, it can be seen that the increase of the carbohydrate concentration with SRT only occurred at low HRT. Again, the higher MLSS under these conditions (run 4) might be responsible. Indeed, the specific carbohydrate and protein content were significantly lower at SRT 30 d compared to SRT 10 d, which is conform to literature results. As for HRT, the effects of SRT thus also depended on the other operating conditions. At HRT 18 h, no effect or even a slight decrease in fouling and SMP concentrations was observed as SRT prolonged. At HRT 9 h, on the other hand, the effect was much larger and opposite. Fouling increased with SRT due to the higher amount of foulants present (both suspended solids and SMP). The contrasting effects observed for SRT at the different levels of HRT might explain the lack of consensus on the effect of SRT in literature (Table 1). Interestingly, albeit in anaerobic conditions, Huang et al. [46] also observed that the effect of SRT was dependent on the HRT applied. Furthermore, this experiment once again indicates that fouling in MBRs is a very complex phenomenon with many influencing and interacting parameters. 4. Conclusions In this study, a new fouling measurement method, the MBRVFM, was validated under different conditions of HRT and SRT. In accordance with the on-line filtration behavior, the measured reversible and irreversible fouling propensities differed significantly for different values of SRT and HRT. This clearly indicates that the MBR-VFM is able to discern differences in mixed liquor characteristics and filterability resulting from different combinations of HRT-SRT. A significant negative correlation was found between the on-line permeability and both the reversible and irreversible fouling propensity measured by the MBR-VFM. Again, this corresponded to the observations made in the lab-scale MBRs, in which fouling was found to be partly reversible and partly irre-
versible. In addition, this correlation clearly indicates that mixed liquor quality largely determines on-line filtration performance. Nevertheless, other factors such as membrane history, were also found to determine the fouling process in the lab-scale MBRs. A comparison between the MBR-VFM and other fouling indicators indicated that the MBR-VFM was better suited to evaluate fouling than standard lab-tests such as (n-)CST and (n-)TTF and comparable to the critical flux measurement to monitor fouling behavior. Higher reversible and irreversible fouling was observed at lower HRT, presumably as a consequence of the increased concentrations of suspended solids, colloids and SMP present. The effect of SRT was much smaller and restricted to the reversible fouling component. Possible explanations for the increased fouling at prolonged SRT are the higher sludge concentration and the smaller floc size. The effect of each parameter (SRT and HRT) differed at different values of the other parameter. This demonstrates once again that fouling in MBRs is a very complex phenomenon with many influencing and interacting parameters. It can be concluded that the MBR-VFM is a useful tool to monitor fluctuations in a mixed liquor’s reversible and irreversible fouling potential and can contribute to a deeper understanding of the occurring fouling phenomena.
Acknowledgments The authors would like to thank Erwin Van Hoof, Filip Vanhoof, Guy Borgmans, Jef Verheyden, Rob Muyshondt, Louis Raats and Lynn van Tilborg for their technical assistance. Celine Huyskens is indebted to the Research Foundation-Flanders (FWO).
References [1] P. Le-Clech, V. Chen, T.A.G. Fane, Fouling in membrane bioreactors used in wastewater treatment, J. Membr. Sci. 284 (2006) 17–53. [2] Z. Wang, Z. Wu, G. Yu, J. Liu, Z. Zhou, Relationship between sludge characteristics and membrane flux determination in submerged membrane bioreactors, J. Membr. Sci. 284 (2006) 87–94. [3] H.Y. Ng, T.W. Tan, S.L. Ong, Membrane fouling of submerged membrane bioreactors: impact of mean cell residence time and the contributing factors, Environ. Sci. Technol. 40 (2006) 2706–2713. [4] E. Reid, X. Liu, S.J. Judd, Sludge characteristics and membrane fouling in fullscale submerged membrane bioreactors, Desalination 219 (2008) 240–249. [5] S. Lyko, T. Wintgens, D. Al-Halbouni, S. Baumgarten, D. Tacke, K. Drensla, A. Janot, W. Dott, J. Pinnekamp, T. Melin, Long-term monitoring of a full-scale municipal membrane bioreactor-characterisation of foulants and operational performance, J. Membr. Sci. 317 (2008) 78–87. [6] G. Guglielmi, D. Chiarana, S.J. Judd, G. Andreottola, Flux criticality and sustainability in a hollow fibre submerged membrane bioreactor for municipal wastewater treatment, J. Membr. Sci. 289 (2007) 241–248. [7] A. Pollice, A. Brookes, B. Jefferson, S. Judd, Sub-critical flux fouling in membrane bioreactors – a review of recent literature, Desalination 174 (2005) 221–230. [8] P. Le-Clech, B. Jefferson, I.S. Chang, S.J. Judd, Critical flux determination by the flux-step method in a submerged membrane bioreactor, J. Membr. Sci. 227 (2003) 181–193. [9] G. Guglielmi, D. Chiarani, D.P. Saroj, G. Andreottola, Impact of chemical cleaning and air-sparging on the critical and sustainable flux in a flat sheet membrane bioreactor for municipal wastewater treatment, Water Sci. Technol. 57 (2008) 1873–1879. [10] P. Van der Marel, A. Zwijnenburg, A. Kemperman, M. Wessling, H. Temmink, W. van der Meer, An improved flux-step method to determine the critical flux and the critical flux for irreversibility in a membrane bioreactor, J. Membr. Sci. 332 (2009) 24–29. [11] B. Espinasse, P. Bacchin, P. Aimar, Filtration method characterizing the reversibility of colloidal fouling layers at a membrane surface. Analysis through critical flux and osmotic pressure, J. Colloid Interface Sci. 320 (2005) 483–490. [12] T. de la Torre, M. Mottschall, B. Lesjean, A. Drews, A. Iheanaetu, M. Kraume, Filterability assessment using an in situ filtration test cell, Water Sci. Technol. 61 (2010) 2809–2816. [13] Y. Shen, W. Zhao, K. Xiao, X. Huang, A systematic insight into fouling propensity of soluble microbial products in membrane bioreactors based on hydrophobic interaction and size exclusion, J. Membr. Sci. 346 (2010) 187–193.
C. Huyskens et al. / Separation and Purification Technology 81 (2011) 208–215 [14] T. Jiang, M. Kennedy, V. De Schepper, S. Namnam, I. Nopens, P.A. Vanrolleghem, Characterization of soluble microbial products and their fouling impacts in membrane bioreactors, Environ. Sci. Technol. 44 (2010) 6642–6648. [15] J. Wu, X. Huang, Effect of mixed liquor properties on fouling propensity in membrane bioreactors, J. Membr. Sci. 342 (2009) 88–96. [16] S. Rosenberger, M. Kraume, Filterability of activated sludge in membrane bioreactors, Desalination 146 (2002) 373–379. [17] J.R. Pan, Y.C. Su, C. Huang, H.C. Lee, Effect of sludge characteristics on membrane fouling in membrane bioreactors, J. Membr. Sci. 349 (2010) 287– 294. [18] M. Kraume, D. Wedi, J. Schaller, V. Iversen, A. Drews, Fouling in MBR: What use are lab investigations for full-scale operation, Desalination 236 (2009) 94–103. [19] H. Evenblij, H.S. Geilvoet, S.J.H.J.M. van der Graaf, H.F. van der Roest, Filtration characterization for assessing MBR performance: three cases compared, Desalination 178 (2005) 115–124. [20] S. Geilvoet, The Delft Filtration Characterisation method – assessing membrane bioreactor activated sludge filterability, PhD. Thesis, Delft University of technology, The Netherlands, 2010. [21] T. de la Torre, V. Iversen, A. Moreau, J. Stüber, Filtration characterization methods in MBR systems: a practical comparison, Desalination Water Treat. 9 (2010) 15–21. [22] C. Huyskens, E. Brauns, E. Van Hoof, H. De Wever, A new method for the evaluation of the reversible and irreversible fouling propensity of MBR mixed liquor, J. Membr. Sci. 323 (2008) 185–192. [23] C. Huyskens, E. Brauns, E. Van Hoof, L. Diels, H. De Wever, Validation of a supervisory control system for energy savings in membrane bioreactors, Water Res. 45 (2011) 1443–1453. [24] I. Ivanovic, T. Leiknes, H. Odegaard, Influence of loading rates on production and characteristics of retentate from a biofilm membrane bioreactor (BF-MBR), Desalination 199 (2006) 490–492. [25] S.R. Chae, Y.T. Ahn, S.T. Kang, H.S. Shin, Mitigated membrane fouling in a vertical submerged membrane bioreactor (VSMBR), J. Membr. Sci. 280 (2006) 572–584. [26] R.S. Trussell, R.P. Merlo, S.W. Hermanowicz, D. Jenkins, The effect of organic loading on process performance and membrane fouling in a submerged membrane bioreactor treating municipal wastewater, Water Res. 40 (2006) 2675–2683. [27] H.Y. Ng, T.W. Tan, S.L. Ong, Membrane fouling of pre-denitrification submerged membrane bioreactors: impact of mean cell residence time and the contributing factors, Environ. Sci. Technol. 40 (2006) 2706–2713. [28] P. Grelier, S. Rosenberger, A. Tazi-Pain, Influence of sludge retention time on membrane bioreactor hydraulic performance, Desalination 192 (2006) 10–17. [29] S. Malamis, A. Andreadakis, Fractionation of proteins and carbohydrates of extracellular polymeric substances in a membrane bioreactor system, Bioresour. Technol. 100 (2009) 3350–3357. [30] T. Miyoshi, T. Tsuyuhara, R. Ogyu, K. Kimura, Y. Watanabe, Seasonal variation in membrane fouling in membrane bioreactors (MBRs) treating municipal wastewater, Water Res. 43 (2009) 5109–5118.
215
[31] D. Al-Halbouni, J. Traber, S. Lyko, T. Wintgens, T. Melin, D. Tacke, A. Janot, W. Dott, J. Hollender, Correlation of EPS content in activated sludge at different sludge retention times with membrane fouling phenomena, Water Res. 42 (2008) 1475–1488. [32] K. Kimura, T. Naruse, Y. Watanabe, Changes in characteristics of soluble microbial products in membrane bioreactors associated with different solid retention times: relation to membrane fouling, Water Res. 43 (2009) 1033– 1039. [33] K. Ouyang, J. Liu, Effect of sludge retention time on sludge characteristics and membrane fouling of membrane bioreactor, J. Environ. Sci. 21 (2009) 1329– 1335. [34] A. Pollice, G. Laera, D. Saturno, C. Giordano, Effect of sludge retention time on the performance of a membrane bioreactor treating municipal sewage, J. Membr. Sci. 317 (2007) 65–70. [35] APHA, AWWA, WEF, Standard Methods for the Examination of Water and Wastewater, 20th ed., American Public Health Association, Washington, DC, 1998. [36] L.N. Huang, H. De Wever, L. Diels, Diverse and distinct bacterial communities induced biofilm fouling in membrane bioreactors operated under different conditions, Environ. Sci. Technol. 42 (2008) 8360–8366. [37] O.H. Lowry, N.J. Rosenbrough, A.L. Farr, R.J. Randall, Protein measurement with the folin phenol reagent, J. Biol. Chem. 193 (1951) 175–265. [38] 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. [39] StatSoft, Inc., STATISTICA for Windows (Computer Program Manual), Tulsa, 2008. http://www.statsoft.com. Version 8. [40] Z. Wang, Z. Wu, X. Yin, L. Tian, Membrane fouling in submerged membrane bioreactor (MBR) under sub-critical flux operation: membrane foulant and gel layer characterization, J. Membr. Sci. 325 (2008) 238–244. [41] H.F. Zhang, Impact of soluble microbial products and extracellular polymeric substances on filtration resistance in a membrane bioreactor, Environ. Eng. Sci. 26 (2009) 1115–1122. [42] F. Meng, B. Shi, F. Yang, H. Zhang, Effect of hydraulic retention time on membrane fouling and biomass characteristics in submerged membrane bioreactors, Bioproc. Biosys. Eng. 30 (2007) 359–367. [43] S.S. Han, T.H. Bae, G.G. Jang, T.M. Tak, Influence of sludge retention time on membrane fouling and bioactivities in membrane bioreactor system, Proc. Biochem. 40 (2005) 2393–2400. [44] S.H. Yoon, Important operational parameters of membrane bioreactor-sludge disintegration (MBR-SD) system for zero excess sludge production, Water Res. 37 (2003) 1921–1931. [45] B.Q. Liao, I.G. Droppo, G.G. Leppard, S.N. Liss, Effect of solids retention time on structure and characteristics of sludge flocs in sequencing batch reactors, Water Res. 40 (2006) 2583–2591. [46] Z. Huang, S.L. Ong, H.Y. Ng, Submerged anaerobic membrane bioreactor for low-strength wastewater treatment: effect of HRT and SRT on treatment performance and membrane fouling, Water Res. 45 (2011) 705–713.
Contents lists available at SciVerse ScienceDirect
Separation and Purification Technology journal homepage: www.elsevier.com/locate/seppur
Study of (ir)reversible fouling in MBRs under various operating conditions using new on-line fouling sensor Celine Huyskens a,b,⇑, Silvia Lenaerts b, Etienne Brauns a, Ludo Diels a, Heleen De Wever a a b
VITO (Flemish Institute for Technological Research), Separation and Conversion Technology, Boeretang 200, 2400 Mol, Belgium University of Antwerp, Department of Bioscience Engineering, Groenenborgerlaan 171, 2020 Antwerp, Belgium
a r t i c l e
i n f o
Article history: Received 17 May 2011 Received in revised form 20 July 2011 Accepted 20 July 2011 Available online 27 July 2011 Keywords: Membrane bioreactor Fouling measurement Sludge retention time Hydraulic retention time
a b s t r a c t In this study, a new fouling sensor was validated under different conditions of hydraulic (HRT) and sludge retention time (SRT). The MBR-VFM (membrane bioreactor-VITO Fouling Measurement) allows the simultaneous determination of the physically reversible and irreversible fouling potential of a mixed liquor during a single crossflow filtration test. In accordance with the on-line filtration behavior, the measured reversible and irreversible fouling propensities differed significantly between MBRs operated at different combinations of HRT-SRT. Moreover, a significant negative correlation was found between the on-line permeability and the reversible and irreversible fouling propensity measured by the MBRVFM. This corresponded to observations made on membrane recovery after physical or chemical cleaning actions. Higher reversible and irreversible fouling were observed at lower HRT, presumably as a consequence of increased concentrations of foulants present. The effect of SRT was much smaller and restricted to the reversible fouling component. Possible explanations for the increased fouling at prolonged SRT are the higher sludge and colloid concentration and the smaller floc size. It can be concluded that the MBRVFM is a useful tool to monitor fluctuations in a mixed liquor’s (ir)reversible fouling potential and can contribute to a deeper understanding of the occurring fouling phenomena. Ó 2011 Elsevier B.V. All rights reserved.
1. Introduction Membrane fouling remains the major challenge for further membrane bioreactor (MBR) development and application. Despite numerous studies, to date no consensus exists on the exact phenomena occurring at the membrane surface during filtration. This can be attributed to the fact that fouling in MBRs is a very complex phenomenon, influenced by many factors, all acting and interacting simultaneously, i.e. operational conditions, membrane properties and mixed liquor characteristics [1]. As a result, it is very difficult to distinguish to what extent each of these factors affects on-line filtration performance. For effective fouling control and the selection of the appropriate countermeasures, identification of the dominant fouling factor is crucial. Apart from on-line filtration performance, additional fouling monitoring tools are thus required. Abbreviations: MBR-VFM, membrane bioreactor-VITO fouling measurement; VFMirrev, irreversible fouling propensity measured by MBR-VFM (%); VFMrev, reversible fouling propensity measured by MBR-VFM (%). ⇑ Corresponding author at: VITO (Flemish Institute for Technological Research), Separation and Conversion Technology, Boeretang 200, 2400 Mol, Belgium. Tel.: +32 14 33 69 49; fax: +32 14 32 65 86. E-mail addresses: [email protected] (C. Huyskens), silvia.lenaerts @ua.ac.be (S. Lenaerts), [email protected] (E. Brauns), [email protected] (L. Diels), [email protected] (H. De Wever). 1383-5866/$ - see front matter Ó 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.seppur.2011.07.031
Some of such tools have already been reported in literature. They can roughly be divided into three groups: (1) established parameters for the Conventional Activated Sludge (CAS) process which are also used to characterize MBR operation, (2) critical flux measurements and (3) various filtration test cell measurements. The first group comprises parameters such as capillary suction time (CST) and time-to-filter (TTF). Although these methods have the advantage that they are well-known and require only simple equipment and short time, literature references regarding their usefulness for MBR operation diverge [2–5]. For the critical flux measurements, a standard protocol is lacking, making comparison of reported data difficult. Moreover, a number of recent studies have indicated that slow fouling can take place even below the critical flux, questioning its relevance for long-term MBR operation [6,7]. Therefore, modifications were made to the more traditional flux-stepping protocol developed by Le-Clech et al. [8]. Flux-down stepping was added to acquire some information regarding the reversibility of fouling [9], or intermediate physical cleaning steps were introduced to rule out membrane history effects [10]. Similar protocols were developed for constant pressure filtration [11]. These protocols were the basis for the development of the Berlin Filtration Method (BFM) [12]. This in situ filtration test cell is used to assess mixed liquor filterability by flux-stepping experiments. The first results indicate that there is a good agreement between
209
C. Huyskens et al. / Separation and Purification Technology 81 (2011) 208–215
the measured filterability and the filtration performance of MBR pilot plants. Apart from the BFM, a large number of other filtration test cells have been developed specifically for the analysis of MBR mixed liquor filterability and fouling propensity, ranging from very simplified set-ups (dead-end or stirred dead-end test cells [13–14]) to miniature MBR replicas [15–16]. Although the latter were more successful to simulate fouling mechanisms occurring in MBRs, they can only provide information on short-term cake fouling or residual fouling rates [17–18]. To overcome this limitation, Evenblij et al. [19] developed a side-stream test cell in which the behavior of a ‘fouled’ membrane can be simulated during a short-term experiment by operating at high flux. This Delft Filtration Characterization method (DFCm) proved to be a useful tool to characterize and assess the filterability of mixed liquor collected from full-scale MBRs [20]. Moreover, parallel measurements with the DFCm and the BFM on different mixed liquor samples indicated that both gave a similar evaluation of filterability for most of the samples [21]. The fouling measurement elaborated in this paper, the MBRVITO Fouling Measurement (VFM), shares some common features with both the BFM and the DFCm. On the one hand, and in accordance to the BFM, the MBR-VFM is developed as an on-line test cell which can distinguish between reversible and irreversible fouling. On the other hand, and like the DFCm, the MBR-VFM is operated in hydrodynamic conditions that lead to accelerated fouling. The MBR-VFM set-up and measurement protocol were elaborately described in [22,23]. Moreover, previous experiments have shown that the MBR-VFM is accurate, reproducible and corresponded well with the on-line filtration behavior in a lab-scale MBR under the specific circumstances of the test. Consequently, it is anticipated that the MBR-VFM poses an important advantage over simply monitoring the on-line filtration data to understand and evaluate fluctuations in a mixed liquor’s fouling propensity. Since the nature of the foulants present and, hence, the occurring reversible and irreversible fouling mechanisms are strongly dependent on the operating conditions, a more thorough validation of the MBR-VFM under a range of operating conditions was considered essential. For this purpose, lab-scale MBRs were operated under different conditions of hydraulic retention time (HRT) and sludge retention time (SRT). Numerous articles have already indicated that both have a significant effect on mixed liquor characteristics and, consequently, fouling behavior (Table 1). The primary goal of this study was to examine whether these differences in filtration performance were also reflected in the reversible and irreversible fouling propensities measured by the MBR-VFM. In
addition, the effectiveness of the MBR-VFM as a fouling monitoring tool was compared with other frequently used fouling indicators, such as critical flux, CST and TTF. Finally, complementary analyses were performed on sludge and supernatant samples in order to gain a deeper insight in the exact mechanisms leading to the occurring reversible and irreversible fouling phenomena at different SRT and HRT. 2. Experimental 2.1. Experimental set-up Lab-scale MBRs were operated under different conditions of HRT and SRT using a 22 factorial design. In total, 4 different experimental runs were executed, representing all possible combinations of a low and high level for HRT and SRT, as shown in Table 2. Low and high values of 9 and 18 h for HRT and 10 and 30 d for SRT were adopted. As only two identical lab-scale MBRs were available, the experiment was carried out in 2 test blocks. These test blocks (block1: run 1 and 2 and block 2: run 3 and 4) were chosen in such a way that the block effect was confounded with the interaction effect and all information regarding the main effects of HRT and SRT was maintained. In each block, 2 identical lab-scale submerged MBRs were operated in parallel for a period of approximately 4 months. They were fed with municipal wastewater, which was prescreened at 0.75 mm. Sodium bicarbonate was added to the influent wastewater to maintain a constant neutral pH. The reactors were seeded with return sludge from a local municipal wastewater treatment plant with a concentration of 6 g L1. An acclimatization period of two times the SRT was adopted in order to reach steady-state conditions. Each MBR had an active volume of 22.5 L and was equipped with flat sheet microfiltration membranes (Kubota). Permeate was extracted by a peristaltic pump, following an 8 min– 2 min filtration–relaxation regime. Coarse bubble aeration at an air flow rate of 18 L min1 provided oxygen for the biodegradation processes and generated a crossflow near the membrane surface. Operating conditions during each run were similar, except for HRT and SRT, as shown in Table 2. Membrane surface area was adjusted as to obtain a different HRT at a similar constant flux of 16 L m2 h1. Sludge wasting was carried out daily to maintain the desired SRT. Once a transmembrane pressure (TMP) of 0.2 bar was reached, membranes were cleaned chemically by soaking them for 2 h in 500 ppm hypochlorite. Previous tests indicated that this cleaning procedure sufficed to recover permeability for
Table 1 Effects of hydraulic retention time (HRT) and sludge retention time (SRT) on fouling and mixed liquor characteristics in municipal wastewater treatment: literature data and own results. HRT range tested
Effect of increasing HRT
Reference
1–4 h 4–10 h 9–18 h
Fouling rate ;, soluble organic matter ;, number of submicron-size particles ;, filamentous bacteria ;, sludge flocs ; Cake layer resistance ;, EPS (carbohydrates) ;, particle size ; (Ir)reversible fouling ;, DOC, SMP, SMPc ;
[24] [25] This study
SRT range tested
Effect of increasing SRT
Reference
2–10 d 3–20 d 8–40 d 10–30 d 10–33 d
Fouling rate ;, SMP and SMPc ; Fouling rate ;, SMP and EPS ; Fouling rate ;, SMPc and colloids ; Reversible fouling " (permeability =), MLSS ", floc size ; 10–20 d ? fouling rate ;, EPS and SMP ; 20–33 d ? fouling rate = Fouling rate ;, DOC ;, characteristics DOC SRT Fouling layer ; (permeability =), SMP and EPS ; Reversible fouling " (irreversible =), characteristics SMP – SRT Gel layer ;, SMP ; Sludge viscosity ", optimum filterability in SRT range 40–80 d
[26] [27] [28] This study [29]
13–50 d 23–40 d 17–102 d 10 d-NW 20 d-NW
[30] [31] [32] [33] [34]
210
C. Huyskens et al. / Separation and Purification Technology 81 (2011) 208–215
Table 2 Operating conditions and mixed liquor characteristics (average ± standard deviation) in the different runs. Only data obtained after the acclimatization period are included. + and – respectively indicate positive and negative effects of sludge retention time (SRT) and hydraulic retention time (HRT) exhibited by the t-test at p < 0.05. Parameter
Block 1
SRT (d) HRT (h) F/M ratio (gCOD gMLVSS1 d1) VFMrev (%) VFMirrev (%) CST (s) n-CST (s L g1) TTF (s) n-TTF(s L g1) Critical flux (L h1 m2) MLSS (g L1) d50 (lm) COD TTF (mg L1) SMPP (mg L1) Specific protein content (mg gMLSS1) SMPC (mg L1) Specific carbohydrate content (mg gMLSS1)
Block 2
Effect
Run 1
Run 2
Run 3
Run 4
30 18 0.3 ± 0.2 11 ± 6 3±1 24 ± 11 13 ± 6 29 ± 11 16 ± 6 21 ± 4 1.8 ± 0.3 73 ± 16 114 ± 32 31 ± 6 17 ± 4 22 ± 7 12 ± 4
10 9 0.6 ± 0.12 32 ± 18 11 ± 7 125 ± 251 69 ± 139 2199 ± 6008 1113 ± 2957 14 ± 2 1.8 ± 0.5 114 ± 73 244 ± 89 41 ± 14 24 ± 9 48 ± 19 28 ± 11
10 18 0.4 ± 0.1 15 ± 5 4±2 18 ± 6 11 ± 4 29 ± 10 18 ± 6 18 ± 3 1.7 ± 0.4 176 ± 56 134 ± 40 29 ± 5 18 ± 6 26 ± 8 16 ± 6
30 9 0.2 ± 0.1 57 ± 25 21 ± 12 272 ± 190 53 ± 36 735 ± 1745 143 ± 339 13 ± 4 5.3 ± 0.7 69 ± 9 401 ± 192 44 ± 13 7±3 73 ± 23 15 ± 6
the specific installation and the specific wastewater used, implying effective removal of organic fouling. Permeate flow, TMP and temperature were measured on-line. Data acquisition was conducted with LabView (National Instruments, US). Reactor performance was evaluated by frequent analyses on influent and effluent. The evolution of TMP with time was used to monitor fouling of the lab-scale MBR membranes. In addition, the critical flux was determined weekly by the flux-step method [8] with a step duration of 10 min and a step height of 5 L m2 h1. For each critical flux measurement a cleaned Kubota membrane was used. The highest flux at which no perceptible increase of TMP with time could be observed was denominated as the critical flux. Furthermore, MBR-VFM analyses were performed twice a week, together with analyses of mixed liquor and supernatant properties. 2.2. The MBR-VFM The MBR-VFM method comprises a small-scale crossflow filtration installation and a specific measurement protocol, described in detail elsewhere [22]. The filtration installation consists of a fouling sensor in which a single tubular membrane can be placed, and a measuring apparatus. The membrane applied in this study was an 8 mm tubular polyvinylidene difluoride (PVDF) membrane (X-Flow, The Netherlands). The application of a specific measurement protocol enables the simultaneous determination of the physically reversible and irreversible fouling propensity. The applied measurement protocol consisted of the following steps: Step 0: conditioning, 5 min, air flow rate 500 ml min1 Step 1: reversible fouling measurement Step 1A: filtration, 15 min, TMP 0.10 bar, air flow rate 200 ml min1 Step 1B: relaxation, 10 min, air flow rate 500 ml min1
SRT
HRT
+
+
+ + +
fouling so that reversible and irreversible fouling can be distinguished. After data processing, the reversible and irreversible fouling propensity are represented as a normalized reversible (VFMrev) and irreversible fouling value (VFMirrev) ranging from 0% (no fouling) to 100% (very high fouling) [23]. 2.3. Analytical methods Chemical oxygen demand (COD), concentrations of ammonium (NH 4 —N), nitrite (NO2 —N), nitrate (NO3 —N), and total nitrogen (Ntot–N) as well as total phosphorus (Ptot–P) in influent and effluent were determined with standard cuvette tests of HACH LANGE. Mixed liquor suspended solids (MLSS), mixed liquor volatile suspended solids (MLVSS) and CST were determined according to Standard Methods [35]. The TTF was measured as the time needed to filter by gravity 25 ml of a 250 ml mixed liquor sample through a paper filter (Whatman 589/1 black ribbon). The COD of the TTF filtrate was measured to quantify the amount of particles smaller than 25 lm. The normalized CST and TTF (n-CST and n-TTF) were calculated by dividing the CST and TTF values by their respective MLSS concentration. The food-to-microorganisms (F/M) ratio was calculated as the influent COD loading per amount of MLVSS. The median particle size (d50) was calculated from the volume-based particle size distribution measured by laser diffraction (Coulter LS230). For soluble microbial products (SMP) measurements, supernatant was obtained from the mixed liquor by a 15 min centrifugation at 2000g and 4 °C, followed by a 0.45 lm filtration [36]. Protein concentration (SMPP) was quantified by the Lowry method [37] using c-globulin as a standard. Carbohydrates (SMPC) were determined by the phenol-sulfuric acid method [38] using glucose as a standard. The specific protein and carbohydrate content were determined by dividing the absolute concentrations by the MLSS. 2.4. Statistical analysis
Step n (n = 2. . .10): irreversible fouling measurement Step nA: filtration, 5 min, TMP 0.10 bar, air flow rate 500 ml min1 Step nB: relaxation, 3 min, air flow rate 500 ml min1 The first filtration step is performed at low air flow rates and the following filtration steps at high air flow rates to invoke reversible and irreversible fouling, respectively. The subsequent relaxation steps at high air flow rates were optimized to remove all reversible
The data were analyzed using Statistica [39]. Statistical significance was set at the 95% confidence interval for all analyses (p < 0.05). Correlations between the fouling indicators and on-line permeability were examined by computing a Pearson product-moment correlation matrix for the whole experimental period. The Student’s t-test between groups was used to examine significant differences in mixed liquor characteristics and filterability between the 2 levels for SRT and HRT. Afterwards, analysis of variance (ANOVA) was used on the average values obtained for each
211
C. Huyskens et al. / Separation and Purification Technology 81 (2011) 208–215
3. Results and discussion Throughout the experiment, reactor performance was conform to expectations for MBR processes (Table 3). The average COD removal was approximately 90% for all runs and nitrification from ammonia to nitrate proceeded without any problem. Due to the absence of anaerobic/anoxic compartments, almost no removal of
Table 3 Influent, effluent and removal efficiencies for COD and nutrients (average ± standard deviation) in the different runs. Only data obtained after the acclimatization period are included. + and respectively indicate positive and negative effects of sludge retention time (SRT) and hydraulic retention time (HRT) exhibited by the t-test at p < 0.05. Block 1
Block 2
Run 1 1
COD influent (mg L ) COD effluent (mg L1) COD removal (%) Ntot-N influent (mg L1) Ntot–N effluent (mg L1) Ntot–N removal (%) NH 4 —N influent (mg L1) NO 3 —N effluent (mg L1) Ptot–P influent (mg L1) Ptot–P effluent (mg L1) Ptot–P removal (%)
Run 2
418 ± 86 34 ± 8 91 ± 2 72 ± 8 68 ± 10 6±8 58 ± 7
40 ± 12 90 ± 3 65 ± 9 9±9
Run 3
Effect Run 4
SRT
HRT
472 ± 150 42 ± 9 46 ± 13 90 ± 4 89 ± 4 79 ± 11 71 ± 7 73 ± 10 9 ± 13 14 ± 28 63 ± 8
65 ± 11
62 ± 10
67 ± 7
68 ± 8
12 ± 2 12 ± 2 4±5
11 ± 2 9±7
20 ± 3 19 ± 3 5±9
19 ± 3 11 ± 27
+
3.1. Validation of the MBR-VFM 3.1.1. Suitability of the MBR-VFM as fouling indicator In this study, lab-scale MBRs were operated with different values for SRT and HRT. Low and high levels for SRT and HRT were selected so as to obtain sufficient variation in mixed liquor characteristics and, hence, fouling behavior in the lab-scale MBRs. They were based on literature and former experience. It can be noted that the values for HRT were high compared to the values usually reported in literature for municipal wastewater, as shown in Table 1. However, operation at lower HRT values (i.e. 6 h) was found to be practically unfeasible for the selected wastewater, as severe fouling occurred and maximal TMP was reached within only a day’s time. It can be seen from the evolution of TMP in the lab-scale MBRs (Fig. 1) that the different values for SRT and HRT applied in the various runs were properly selected, as clear differences in filtration performance were observed between the runs. TMP remained relatively stable in runs 1 and 3, both operating at high HRT. In contrast, periods of excessive fouling and foaming were observed at low HRT, in runs 2 and 4, resulting in TMP increases up to 0.2 bar in only a few days time. To ensure continued operation of the MBRs, fluxes were temporarily reduced to 10 L m2 h1 by add-
0,15
75
0,10
50
0,05
25
0,00 30
60 90 Time (d)
0,15
75
0,10
50
0,05
25
0,00
0 0
Run 1: SRT = 30 d, HRT = 18 h 100
0,20
TMP (bar)
100 VFM(ir)rev (%)
TMP (bar)
Run 3:SRT = 10 d, HRT = 18 h 0,20
120
0 0
75
0,10
50
0,05
25 0 30
60 90 Time (d)
120
TMP (bar)
0,15
VFM(ir)rev (%)
TMP (bar)
100
0
60 90 Time (d)
120
Run 4:SRT = 30 d, HRT = 9 h
Run 2: SRT = 10 d, HRT = 9 h 0,20
0,00
30
0,20
100
0,15
75
0,10
50
0,05
25
0,00
VFM(ir)rev (%)
Parameter
total N and P was observed. Few significant differences in removal efficiencies were found between the different runs. Only the COD removal slightly increased with HRT due to the lower organic loading rate. The limited effect of SRT and HRT on biological performance might be a result of the specific characteristics of the used municipal wastewater, which mainly contained easily biodegradable substances.
VFM(ir)rev (%)
run to elucidate the exact effects. Only data obtained after the acclimatization period were used.
0 0
30
60 90 Time (d)
TMP
VFMrev
120
VFMirrev
Fig. 1. Evolution of transmembrane pressure (TMP, spades) and reversible (VFMrev, stars) and irreversible fouling propensity (VFMirrev, triangles) at different conditions of hydraulic retention time (HRT) and sludge retention time (SRT). Vertical line: end of acclimatization period; vertical downward arrow: chemical cleaning with hypochlorite; gray shaded area: operation at reduced flux.
212
C. Huyskens et al. / Separation and Purification Technology 81 (2011) 208–215
ing extra membrane surface area (so that the desired HRT was maintained). But even at this low flux operation, chemical cleanings needed to be carried out frequently. Contrarily, no clear differences in on-line filtration performance were found between SRT 10 d and SRT 30 d. From the on-line filtration data it can thus be concluded that HRT 9 h clearly resulted in more severe fouling compared to HRT 18 h, while the effect of SRT was rather limited in the tested range. In line with this, statistical analysis indicated significant differences in the measured fouling potential between the various runs. This shows that the MBR-VFM is able to discern differences in mixed liquor characteristics and filterability resulting from various operating conditions. Furthermore, these differences corresponded to what was observed on-line. Both VFMrev and VFMirrev were significantly higher at HRT 9 h (runs 2 and 4) than at HRT 18 h (runs 1 and 3) (Table 2). The effect of SRT, on the other hand, was smaller and restricted to the reversible fouling component. Moreover, elevated fouling propensity values were measured during periods of strongly increasing TMP, while values were lower during stable operation (Fig. 1). At first sight, this effect seemed more pronounced for the reversible fouling potential. It should, however, be noted that the absolute values for VFMrev and VFMirrev are merely a consequence of some chosen settings in the MBR-VFM data processing software. As a result, these absolute values are of little practical relevance. Moreover, different settings were applied for the calculation of VFMrev and VFMirrev. It is thus not possible to simply compare both. One should rather consider the evolution and relative variation of VFMrev and VFMirrev to gain some insight in the effects of SRT and HRT on the mixed liquor’s reversible and irreversible fouling potential. This relative variation was quite similar for both fouling components. Moreover, VFMrev and VFMirrev followed the same trend; they increased and decreased simultaneously. Statistical analysis confirmed that there was a significant positive correlation between VFMrev and VFMirrev (Table 4). One could argue that this implies that reversible and irreversible fouling are not properly distinguished by the MBR-VFM method. However, opposite trends for both reversible and irreversible fouling have been observed in other experiments. Therefore, it is considered more likely that reversible and irreversible fouling were properly distinguished, but that both fouling components simply occurred at the same time in this experiment. After all, depending on the operating conditions applied, a combination of various foulants is present, which in turn results in the simultaneous occurrence of different fouling phenomena. Furthermore, various studies have indicated that some foulant species, such as SMP and colloids, can contribute to reversible (cake layer, gel layer. . .) as well as irreversible fouling phenomena (pore narrowing, adsorption. . .) [30,40]. Zhang et al. [41], for example, found that SMP with molecular weight of 3–10 kDa were positively correlated with the pore blocking resistance, while the amount of SMP with a molecular weight larger than 10 kDa had a strong positive effect on cake layer resistance. Such a size distinction in SMP was not made in this experiment. However, correlations of both the reversible and irre-
versible fouling potential with the protein and carbohydrate fraction of SMP were also observed in this experiment. Both the reversible and the irreversible fouling potential showed a significant negative correlation with on-line permeability (Table 4). In line with this, the on-line filtration performance indicated that fouling was partly reversible and partly irreversible: prolonged relaxation (during reactor stand-still) resulted in a recovery of permeability, although never complete. The absolute value of the correlation coefficient was slightly higher for reversible than for irreversible fouling. A possible explanation is that irreversible fouling develops only gradually and might thus not be measured that accurately during the short-term MBR-VFM measurement. Another possibility is that, due to its long-term character, a high irreversible fouling potential has little immediate impact, and it takes a while before it is reflected in the on-line permeability values. Reversible fouling, on the other hand, develops rapidly, making it easier to measure in a short-term. Moreover, a high reversible fouling potential will quickly manifest itself in a sudden permeability decline. Another possible explanation is that, despite a high irreversible fouling potential, little irreversible fouling actually occurs in the lab-scale MBRs because the membranes are protected by a reversible cake layer acting as a secondary membrane. In the MBR-VFM, this effect is prevented by measuring the irreversible fouling under high crossflow conditions, preventing cake layer formation. It should be noted that the relationship between the MBRVFM and on-line permeability was expected, since the MBRVFM characterizes the mixed liquor in terms of reversible and irreversible fouling potential, which obviously plays a determining role in the fouling process in the lab-scale MBRs. However, as stated before, the fouling process in the MBRs is also dependent on factors other than the actual mixed liquor characteristics, such as membrane history and operating conditions. This explains the occurrence of some data points for which the correlation with VFMrev does not seem to hold true (Fig. 2). A number of these points, for example, represent measurements performed immediately after a chemical cleaning, leading to higher permeability values, regardless of the actual fouling propensity. Some other on-line permeability data were measured during reduced flux operation, but conform to expectations, this did not result in significant differences compared to the measurements at higher flux. The MBR-VFM, on the other hand, is independent of the MBR system. Because a clean membrane is used for each measurement, it only represents the actual mixed liquor characteris-
Table 4 Pearson-r correlation matrix for the fouling indicators (N = 118, p < 0.05). Correlations which are significant at the p < 0.05 are written in italics.
Perm
VFMrev
VFMirrev
n-CST
n-TTF
0.25 VFMrev
0.19 0.90 VFMirrev
0.07 0.51 0.41 n-CST
0.02 0.40 0.33 0.88 n-TTF
Fig. 2. Correlation between on-line permeability and reversible fouling propensity (VFMrev) for the different experimental runs. Open symbols: measurements performed during normal operation, full symbols: measurements performed within 3 d after chemical cleaning.
C. Huyskens et al. / Separation and Purification Technology 81 (2011) 208–215
tics and filterability, while all other influences are excluded. When applied in conjunction to permeability monitoring, the MBR-VFM can thus elucidate to what extent a declining permeability trend can be attributed to bad mixed liquor quality or poor operation or membrane conditions. As such, it contributes to a better understanding and interpretation of the fouling process and can help in the selection of suitable actions to counter reversible and/or irreversible fouling.
3.1.2. Comparison with alternative fouling indicators Several small scale lab tests exist which enable to evaluate mixed liquor filterability, such as (n-)CST and (n-)TTF. Both were measured frequently during this experiment, in parallel to the MBR-VFM measurements. Like VFMrev and VFMirrev, n-CST and n-TTF differed significantly between the runs. Values were lower for runs 1 and 3, at high HRT, which is in line with the more stable filtration conditions observed (Table 2). Furthermore, both n-CST and n-TTF were significantly correlated with each other and with VFMrev and VFMirrev (Table 4). This was conform to expectations, since of all these methods aim at characterizing mixed liquor quality. Yet, in contrast to the MBR-VFM, neither (n-)CST nor (n-)TTF correlated well with the on-line permeability. It can thus be concluded that the actual fouling behavior of a mixed liquor is better evaluated with the MBR-VFM than with standard lab tests. A possible explanation is that the conditions during the MBR-VFM measurement are more similar to the ones in the examined lab-scale MBRs and thus more representative. Accordingly, literature gives contradictory result on the usefulness of CST and TTF as fouling indicators [2,5]. The measurement of the so-called critical flux is another widely used method to determine the actual fouling propensity. In this study, a cleaned membrane, similar to the ones used during the filtration process, was used for each measurement. Significantly different critical flux values were observed for all runs, which explains the on-line fouling behavior observed in the lab-scale MBRs (Table 2). As critical fluxes were on average lower than 15 L m2 h1 for runs 2 and 4, filtration at a constant flux of 16 L m2 h1 corresponded to supra-critical filtration conditions and consequently rapid fouling. When flux was lowered to 10 L m2 h1, sub-critical filtration conditions were obtained leading to a much lower fouling rate. For runs 1 and 3 critical fluxes were usually higher than 15 L m2 h1, implying sub-critical filtration conditions. The critical flux data were not included in the Pearson correlation matrix (Table 4) as they were performed less frequently than the other fouling indicator measurements. Nevertheless, statistical analysis confirmed a significant positive correlation of critical flux with on-line permeability (r = 0.47, N = 42). Moreover, significant negative correlations with both VFMrev (r = 0.72, N = 42) and VFMirrev (r = 0.70, N = 42) were found. Critical flux is thus also useful as a fouling indicator. It can be seen from Table 2 that TTF and CST were more variable than the MBR-VFM and especially critical flux, which showed a much smaller standard deviation. A possible explanation is that some changes in mixed liquor characteristics (due to changing conditions) had a larger impact on dead-end filtration (CST and TTF) as compared to crossflow mode (MBR-VFM, critical flux). Another possibility is that CST, TTF and MBR-VFM are more sensitive to changes in mixed liquor characteristics than the critical flux measurements (with 5 L m2 h1 flux steps). As such, some changes in mixed liquor characteristic might have been large enough to impact CST, TTF and MBR-VFM, but not significant enough to lower critical flux by 5 L m2 h1. Furthermore, critical flux was also measured less frequently than the other fouling indicators (once a week versus twice a week) and might not have captured all variation in mixed liquor characteristics.
213
3.2. Effect of HRT and SRT The effects of HRT and SRT on the fouling indicators and other mixed liquor characteristics are shown in Table 2. 3.2.1. Effect of HRT Even at lower flux operation, TMP increased at a faster rate and chemical cleanings needed to be carried out more frequently at HRT 9 h (runs 2 and 4) compared to HRT 18 h (runs 1 and 3). In line with this, all fouling indicators pointed at higher fouling at lower HRT. The MBR-VFM demonstrated that this effect applied to both the reversible and the irreversible fouling component. Presumably, the increased fouling at lower HRT was caused by the higher amounts of foulants present. The higher F/M ratio at HRT 9 h compared to 18 h resulted in significantly higher concentrations of suspended solids, colloids and solutes, which is in accordance with the results described in literature (Table 1). Apart from the higher values, foulant concentrations and fouling indicator values were also much more variable in runs 2 and 4 compared to runs 1 and 3, even though steady-state was reached in terms of MLSS concentration and removal efficiencies after the acclimatization period. This clearly indicates that lower HRT operation resulted in less stable operating conditions, possibly rendering the microorganisms more susceptible to stress caused by (uncontrollable) external factors such as temperature, influent composition etc. Contrary to the observations of Chae et al. [25] and Meng et al. [42], no significant effect of HRT on the volume-based particle size distribution was found. From the results of the statistical analysis, it can thus be concluded that low HRT operation clearly resulted in increased fouling. However, when looking at the results in more detail, it can be seen that the mechanisms leading to this increased fouling differed between runs 2 and 4. Since all other operating parameters were similar, this discrepancy was assumed to be related to the different values for SRT. Our hypothesis was supported by the fact that the absolute CST and TTF were clearly higher for run 4 compared to runs 1 and 3, while the normalized CST and TTF hardly differed. In run 4, the combination of low HRT and high SRT resulted in a much higher MLSS concentration compared to the other runs, which in turn caused severe fouling. Similarly, Meng et al. [42] attributed the higher reversible fouling at shorter HRT to the increased MLSS. Some authors have suggested that high sludge concentrations lead to increased sludge viscosity, which sharply reduces the shear stress caused by membrane aeration and thus promotes fouling [43]. However, as MLSS concentrations were relatively low, viscosity was not assumed to play a crucial role in this experiment. It should be noted that these low MLSS concentrations were not a deliberate choice, since the MLSS of the sludge used as an inoculum for the MBRs was higher (6 g L1). During the course of the experiment, however, MLSS gradually decreased as a consequence of the values chosen for HRT, SRT and the characteristics of the wastewater. In contrast to run 4, MLSS was much lower in run 2 and in the same order of magnitude as for runs 1 and 3, due to the higher amounts of sludge wasted daily (low SRT). As a result, n-CST and n-TTF remained higher compared to the other runs. Factors other than MLSS must thus be responsible for the higher fouling under these conditions. Presumably, the main culprit was the higher F/ M ratio in run 2, resulting from the combination of low MLSS and high organic loading. It is well known that high F/M ratios lead to decreased biodegradation and increased production of SMP [44]. This was also observed in this experiment. Both the absolute SMP concentrations and the specific SMP content were significantly higher for run 2. In contrast, the specific protein and carbohydrate content were much lower in run 4, which clearly indicated that the elevated SMP concentrations measured in run 4 were merely a consequence of the higher amount of microorganisms present.
214
C. Huyskens et al. / Separation and Purification Technology 81 (2011) 208–215
Indeed, the F/M ratio in run 4 was similar and even slightly lower than in runs 1 and 3, representing stable operating conditions. It can be concluded from this experiment that the effect of HRT is pronounced, but also strongly dependent on the other operating conditions. Although low HRT resulted in increased fouling, regardless of the level of SRT, the mechanisms leading to this increased fouling differed. The interaction effect of SRT and HRT could not be confirmed in a statistical way, as it was confounded with the blocking effect. 3.2.2. Effect of SRT In accordance to the observations made on-line, SRT had little effect on the fouling indicator measurements in the tested range. CST, TTF, critical flux and irreversible fouling were unaffected. Although the reversible fouling component increased with increasing SRT, this effect was much smaller than the effect of HRT. The increased reversible fouling might be related to the smaller median volume-based floc size at prolonged SRT. After all, the back transport velocity of particles increases with size. The deposition of the larger flocs present at SRT 10 d can thus more easily be controlled by high shear aeration. In addition, smaller particles form a denser cake with a lower porosity and a higher specific resistance. A possible explanation for the lower floc size at prolonged SRT is the reduced sludge growth due to substrate limitation [45]. Furthermore, high SRT resulted in increased MLSS due to the smaller amounts of sludge wasted, which in turn led to decreased F/M ratios. With regard to SMP, a significant increase of the carbohydrate and colloid concentration with SRT was observed (but not for proteins). In contrast, most studies point at lower fouling at high SRT due to the lower concentrations of SMP present (higher consumption and/or lower production) (Table 2). In our experiment, it can be seen that the increase of the carbohydrate concentration with SRT only occurred at low HRT. Again, the higher MLSS under these conditions (run 4) might be responsible. Indeed, the specific carbohydrate and protein content were significantly lower at SRT 30 d compared to SRT 10 d, which is conform to literature results. As for HRT, the effects of SRT thus also depended on the other operating conditions. At HRT 18 h, no effect or even a slight decrease in fouling and SMP concentrations was observed as SRT prolonged. At HRT 9 h, on the other hand, the effect was much larger and opposite. Fouling increased with SRT due to the higher amount of foulants present (both suspended solids and SMP). The contrasting effects observed for SRT at the different levels of HRT might explain the lack of consensus on the effect of SRT in literature (Table 1). Interestingly, albeit in anaerobic conditions, Huang et al. [46] also observed that the effect of SRT was dependent on the HRT applied. Furthermore, this experiment once again indicates that fouling in MBRs is a very complex phenomenon with many influencing and interacting parameters. 4. Conclusions In this study, a new fouling measurement method, the MBRVFM, was validated under different conditions of HRT and SRT. In accordance with the on-line filtration behavior, the measured reversible and irreversible fouling propensities differed significantly for different values of SRT and HRT. This clearly indicates that the MBR-VFM is able to discern differences in mixed liquor characteristics and filterability resulting from different combinations of HRT-SRT. A significant negative correlation was found between the on-line permeability and both the reversible and irreversible fouling propensity measured by the MBR-VFM. Again, this corresponded to the observations made in the lab-scale MBRs, in which fouling was found to be partly reversible and partly irre-
versible. In addition, this correlation clearly indicates that mixed liquor quality largely determines on-line filtration performance. Nevertheless, other factors such as membrane history, were also found to determine the fouling process in the lab-scale MBRs. A comparison between the MBR-VFM and other fouling indicators indicated that the MBR-VFM was better suited to evaluate fouling than standard lab-tests such as (n-)CST and (n-)TTF and comparable to the critical flux measurement to monitor fouling behavior. Higher reversible and irreversible fouling was observed at lower HRT, presumably as a consequence of the increased concentrations of suspended solids, colloids and SMP present. The effect of SRT was much smaller and restricted to the reversible fouling component. Possible explanations for the increased fouling at prolonged SRT are the higher sludge concentration and the smaller floc size. The effect of each parameter (SRT and HRT) differed at different values of the other parameter. This demonstrates once again that fouling in MBRs is a very complex phenomenon with many influencing and interacting parameters. It can be concluded that the MBR-VFM is a useful tool to monitor fluctuations in a mixed liquor’s reversible and irreversible fouling potential and can contribute to a deeper understanding of the occurring fouling phenomena.
Acknowledgments The authors would like to thank Erwin Van Hoof, Filip Vanhoof, Guy Borgmans, Jef Verheyden, Rob Muyshondt, Louis Raats and Lynn van Tilborg for their technical assistance. Celine Huyskens is indebted to the Research Foundation-Flanders (FWO).
References [1] P. Le-Clech, V. Chen, T.A.G. Fane, Fouling in membrane bioreactors used in wastewater treatment, J. Membr. Sci. 284 (2006) 17–53. [2] Z. Wang, Z. Wu, G. Yu, J. Liu, Z. Zhou, Relationship between sludge characteristics and membrane flux determination in submerged membrane bioreactors, J. Membr. Sci. 284 (2006) 87–94. [3] H.Y. Ng, T.W. Tan, S.L. Ong, Membrane fouling of submerged membrane bioreactors: impact of mean cell residence time and the contributing factors, Environ. Sci. Technol. 40 (2006) 2706–2713. [4] E. Reid, X. Liu, S.J. Judd, Sludge characteristics and membrane fouling in fullscale submerged membrane bioreactors, Desalination 219 (2008) 240–249. [5] S. Lyko, T. Wintgens, D. Al-Halbouni, S. Baumgarten, D. Tacke, K. Drensla, A. Janot, W. Dott, J. Pinnekamp, T. Melin, Long-term monitoring of a full-scale municipal membrane bioreactor-characterisation of foulants and operational performance, J. Membr. Sci. 317 (2008) 78–87. [6] G. Guglielmi, D. Chiarana, S.J. Judd, G. Andreottola, Flux criticality and sustainability in a hollow fibre submerged membrane bioreactor for municipal wastewater treatment, J. Membr. Sci. 289 (2007) 241–248. [7] A. Pollice, A. Brookes, B. Jefferson, S. Judd, Sub-critical flux fouling in membrane bioreactors – a review of recent literature, Desalination 174 (2005) 221–230. [8] P. Le-Clech, B. Jefferson, I.S. Chang, S.J. Judd, Critical flux determination by the flux-step method in a submerged membrane bioreactor, J. Membr. Sci. 227 (2003) 181–193. [9] G. Guglielmi, D. Chiarani, D.P. Saroj, G. Andreottola, Impact of chemical cleaning and air-sparging on the critical and sustainable flux in a flat sheet membrane bioreactor for municipal wastewater treatment, Water Sci. Technol. 57 (2008) 1873–1879. [10] P. Van der Marel, A. Zwijnenburg, A. Kemperman, M. Wessling, H. Temmink, W. van der Meer, An improved flux-step method to determine the critical flux and the critical flux for irreversibility in a membrane bioreactor, J. Membr. Sci. 332 (2009) 24–29. [11] B. Espinasse, P. Bacchin, P. Aimar, Filtration method characterizing the reversibility of colloidal fouling layers at a membrane surface. Analysis through critical flux and osmotic pressure, J. Colloid Interface Sci. 320 (2005) 483–490. [12] T. de la Torre, M. Mottschall, B. Lesjean, A. Drews, A. Iheanaetu, M. Kraume, Filterability assessment using an in situ filtration test cell, Water Sci. Technol. 61 (2010) 2809–2816. [13] Y. Shen, W. Zhao, K. Xiao, X. Huang, A systematic insight into fouling propensity of soluble microbial products in membrane bioreactors based on hydrophobic interaction and size exclusion, J. Membr. Sci. 346 (2010) 187–193.
C. Huyskens et al. / Separation and Purification Technology 81 (2011) 208–215 [14] T. Jiang, M. Kennedy, V. De Schepper, S. Namnam, I. Nopens, P.A. Vanrolleghem, Characterization of soluble microbial products and their fouling impacts in membrane bioreactors, Environ. Sci. Technol. 44 (2010) 6642–6648. [15] J. Wu, X. Huang, Effect of mixed liquor properties on fouling propensity in membrane bioreactors, J. Membr. Sci. 342 (2009) 88–96. [16] S. Rosenberger, M. Kraume, Filterability of activated sludge in membrane bioreactors, Desalination 146 (2002) 373–379. [17] J.R. Pan, Y.C. Su, C. Huang, H.C. Lee, Effect of sludge characteristics on membrane fouling in membrane bioreactors, J. Membr. Sci. 349 (2010) 287– 294. [18] M. Kraume, D. Wedi, J. Schaller, V. Iversen, A. Drews, Fouling in MBR: What use are lab investigations for full-scale operation, Desalination 236 (2009) 94–103. [19] H. Evenblij, H.S. Geilvoet, S.J.H.J.M. van der Graaf, H.F. van der Roest, Filtration characterization for assessing MBR performance: three cases compared, Desalination 178 (2005) 115–124. [20] S. Geilvoet, The Delft Filtration Characterisation method – assessing membrane bioreactor activated sludge filterability, PhD. Thesis, Delft University of technology, The Netherlands, 2010. [21] T. de la Torre, V. Iversen, A. Moreau, J. Stüber, Filtration characterization methods in MBR systems: a practical comparison, Desalination Water Treat. 9 (2010) 15–21. [22] C. Huyskens, E. Brauns, E. Van Hoof, H. De Wever, A new method for the evaluation of the reversible and irreversible fouling propensity of MBR mixed liquor, J. Membr. Sci. 323 (2008) 185–192. [23] C. Huyskens, E. Brauns, E. Van Hoof, L. Diels, H. De Wever, Validation of a supervisory control system for energy savings in membrane bioreactors, Water Res. 45 (2011) 1443–1453. [24] I. Ivanovic, T. Leiknes, H. Odegaard, Influence of loading rates on production and characteristics of retentate from a biofilm membrane bioreactor (BF-MBR), Desalination 199 (2006) 490–492. [25] S.R. Chae, Y.T. Ahn, S.T. Kang, H.S. Shin, Mitigated membrane fouling in a vertical submerged membrane bioreactor (VSMBR), J. Membr. Sci. 280 (2006) 572–584. [26] R.S. Trussell, R.P. Merlo, S.W. Hermanowicz, D. Jenkins, The effect of organic loading on process performance and membrane fouling in a submerged membrane bioreactor treating municipal wastewater, Water Res. 40 (2006) 2675–2683. [27] H.Y. Ng, T.W. Tan, S.L. Ong, Membrane fouling of pre-denitrification submerged membrane bioreactors: impact of mean cell residence time and the contributing factors, Environ. Sci. Technol. 40 (2006) 2706–2713. [28] P. Grelier, S. Rosenberger, A. Tazi-Pain, Influence of sludge retention time on membrane bioreactor hydraulic performance, Desalination 192 (2006) 10–17. [29] S. Malamis, A. Andreadakis, Fractionation of proteins and carbohydrates of extracellular polymeric substances in a membrane bioreactor system, Bioresour. Technol. 100 (2009) 3350–3357. [30] T. Miyoshi, T. Tsuyuhara, R. Ogyu, K. Kimura, Y. Watanabe, Seasonal variation in membrane fouling in membrane bioreactors (MBRs) treating municipal wastewater, Water Res. 43 (2009) 5109–5118.
215
[31] D. Al-Halbouni, J. Traber, S. Lyko, T. Wintgens, T. Melin, D. Tacke, A. Janot, W. Dott, J. Hollender, Correlation of EPS content in activated sludge at different sludge retention times with membrane fouling phenomena, Water Res. 42 (2008) 1475–1488. [32] K. Kimura, T. Naruse, Y. Watanabe, Changes in characteristics of soluble microbial products in membrane bioreactors associated with different solid retention times: relation to membrane fouling, Water Res. 43 (2009) 1033– 1039. [33] K. Ouyang, J. Liu, Effect of sludge retention time on sludge characteristics and membrane fouling of membrane bioreactor, J. Environ. Sci. 21 (2009) 1329– 1335. [34] A. Pollice, G. Laera, D. Saturno, C. Giordano, Effect of sludge retention time on the performance of a membrane bioreactor treating municipal sewage, J. Membr. Sci. 317 (2007) 65–70. [35] APHA, AWWA, WEF, Standard Methods for the Examination of Water and Wastewater, 20th ed., American Public Health Association, Washington, DC, 1998. [36] L.N. Huang, H. De Wever, L. Diels, Diverse and distinct bacterial communities induced biofilm fouling in membrane bioreactors operated under different conditions, Environ. Sci. Technol. 42 (2008) 8360–8366. [37] O.H. Lowry, N.J. Rosenbrough, A.L. Farr, R.J. Randall, Protein measurement with the folin phenol reagent, J. Biol. Chem. 193 (1951) 175–265. [38] 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. [39] StatSoft, Inc., STATISTICA for Windows (Computer Program Manual), Tulsa, 2008. http://www.statsoft.com. Version 8. [40] Z. Wang, Z. Wu, X. Yin, L. Tian, Membrane fouling in submerged membrane bioreactor (MBR) under sub-critical flux operation: membrane foulant and gel layer characterization, J. Membr. Sci. 325 (2008) 238–244. [41] H.F. Zhang, Impact of soluble microbial products and extracellular polymeric substances on filtration resistance in a membrane bioreactor, Environ. Eng. Sci. 26 (2009) 1115–1122. [42] F. Meng, B. Shi, F. Yang, H. Zhang, Effect of hydraulic retention time on membrane fouling and biomass characteristics in submerged membrane bioreactors, Bioproc. Biosys. Eng. 30 (2007) 359–367. [43] S.S. Han, T.H. Bae, G.G. Jang, T.M. Tak, Influence of sludge retention time on membrane fouling and bioactivities in membrane bioreactor system, Proc. Biochem. 40 (2005) 2393–2400. [44] S.H. Yoon, Important operational parameters of membrane bioreactor-sludge disintegration (MBR-SD) system for zero excess sludge production, Water Res. 37 (2003) 1921–1931. [45] B.Q. Liao, I.G. Droppo, G.G. Leppard, S.N. Liss, Effect of solids retention time on structure and characteristics of sludge flocs in sequencing batch reactors, Water Res. 40 (2006) 2583–2591. [46] Z. Huang, S.L. Ong, H.Y. Ng, Submerged anaerobic membrane bioreactor for low-strength wastewater treatment: effect of HRT and SRT on treatment performance and membrane fouling, Water Res. 45 (2011) 705–713.