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The effect of fine bubble aeration intensity on membrane bioreactor sludge characteristics and fouling
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Available online at www.sciencedirect.com
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The effect of fine bubble aeration intensity on membrane bioreactor sludge characteristics and fouling L. De Temmerman a,b, T. Maere b,c, H. Temmink a,d, A. Zwijnenburg a, I. Nopens b,* a
Wetsus Centre of Excellence for Sustainable Water Technology, P.O. Box 1113, 8900 CC Leeuwarden, The Netherlands b BIOMATH, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, B-9000 Ghent, Belgium c modelEAU, Departement de genie civil et de genie des eaux, Universite Laval, 1065 Avenue de la Medecine, Quebec QC G1V 0A6, Canada d Sub-department of Environmental Technology, Wageningen University, P.O. Box 17, 6700 AA Wageningen, The Netherlands
article info
abstract
Article history:
While most membrane bioreactor (MBR) research focuses on improving membrane filtra-
Received 8 January 2015
tion through air scour, backwashing and chemical cleaning to physically counteract
Received in revised form
fouling, relatively few studies have dealt with fouling prevention, e.g. minimizing the
24 February 2015
impact of operational settings that negatively impact sludge filterability. To evaluate the
Accepted 25 February 2015
importance of those settings, the effects of bioreactor aeration intensity variations on
Available online 5 March 2015
membrane fouling have been studied in a lab-scale MBR setup while simultaneously monitoring a unique set of key sludge parameters. In particular, this paper focuses on the
Keywords:
impact of shear dynamics resulting from fine air bubbles on the activated sludge quality
MBR
and flocculation state, impacting membrane fouling. When augmenting the fine bubble
Particle size distribution
aeration intensity both the total and irreversible fouling rate increased. Major indications
Shear
for sludge filterability deterioration were found to be a shift in the particle size distribution
Floc size dynamics
(PSD) in the 3e300 mm range towards smaller sludge flocs, and increasing concentrations of
Size exclusion chromatography
submicron particles (10e1000 nm), soluble microbial products and biopolymers. When
Submicron particle concentration
lowering the aeration intensity, both the sludge characteristics and fouling either went back to background values or stabilized, respectively indicating a temporary or more permanent effect, with or without time delay. The shift in PSD to smaller flocs and fragments likely increased the total fouling through the formation of a less permeable cake layer, while high concentrations of submicron particles were likely causing increased irreversible fouling through pore blocking. The insights from the performed fouling experiments can be used to optimize system operation with respect to influent dynamics. © 2015 Elsevier Ltd. All rights reserved.
* Corresponding author. Tel.: þ32 (0)9 264 5932. E-mail address: [email protected] (I. Nopens). http://dx.doi.org/10.1016/j.watres.2015.02.057 0043-1354/© 2015 Elsevier Ltd. All rights reserved.
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1.
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Introduction
Activated sludge plants, be it membrane bioreactors (MBR) or conventional activated sludge (CAS) systems, experience considerable fluctuations in shear through dynamics in fine bubble aeration resulting from controllers reacting to loading rate dynamics. The resulting shear dynamics may influence the sludge characteristics such as floc size, floc strength and floc compactness temporarily or permanently. Changing sludge characteristics potentially affect the sludge filterability (Drews, 2010; Le-Clech et al., 2006). In this respect, understanding the effects of shear through aeration on sludge characteristics is necessary to optimize membrane operation in terms of energy efficiency (Van Kaam et al., 2006). In MBRs, aeration is typically applied near the membranes as well as in the bioreactor. Coarse bubble (>2 mm) aeration close to the membranes is applied for air scouring of the biomass in the vicinity and attached to the membrane surface. The turbulence created near the membrane delays membrane fouling. In contrast, fine bubble (<2 mm) aeration in the bioreactor is meant to maintain a sufficient dissolved oxygen (DO) concentration for nitrification and organic carbon (COD) removal. While both aeration types can induce shear stress on sludge, the impact has only been thoroughly determined for € hm et al., 2012). Most of the concoarse bubble aeration (Bo cepts related to shear are discussed in the context of wall shear stress on the membranes, e.g. Ratkovich et al. (2011) and much less with respect to stress impact on sludge flocs in the bulk. The interrelations between shear (through an impeller in this particular case), flocculation behavior and membrane fouling are illustrated in Fig. 1. The contour plots in Fig. 1 show the effect of an impellerinduced shear distribution in a reactor in a 2-dimensional XZ plane, and for two different velocity gradients Gm on floc size distribution (Prat and Ducoste, 2006). In the upper case, a low average characteristic velocity gradient (Gm ¼ 40 s1) results in larger floc sizes (here up to 64 mm) in the activated sludge tank. In the lower case, a higher average characteristic velocity gradient (Gm ¼ 90 s1) creates smaller flocs (up to 16 mm). In the latter case this is likely to result in a thicker cake layer, gel layer and pore blocking resistance compared to the former case. Flocs that are continuously exposed to low shear grow into loose and weak flocs, whereas flocs exposed to continuous high shear break up to reach the Kolmogorov scale, i.e. the smallest scale of turbulence (Nopens, 2005). Flocs intermittently exposed to low and high shear tend to form more compact flocs (Mikkelsen and Keiding, 1999). This implies that the shear dynamics largely determine the potential for floc breakage and release of small fragments and compounds such as soluble microbial products (SMP) into the bulk liquid. Hence, shear dynamics are important with respect to membrane fouling. One can monitor the breakage of sludge flocs, by measuring the particle size distribution (PSD) and concentration of SMP in the bulk liquid simultaneously, as was shown by De Temmerman et al. (2014) for a salt shock. With regards
to specific studies on airflow rates, the tendency to smaller flocs was found comparing 3 MBRs with respectively low, medium and high airflow rates (Meng et al., 2008). A study by Fan and Zhou (2007) revealed that at higher aeration rates, sludge flocs were breaking up more, resulting in higher SMP concentrations in the bulk liquid. Breakage through aeration inevitably leads to higher concentrations of very small floc fragments in the bulk liquid and SMP which can be further described as biopolymers, humic acids and the like. There is a consensus that biopolymers and, in general, SMP could increase cake- and gel layer resistance, but the exact impact, and thus the importance of SMP remains hard to quantify (Drews et al., 2008; Naessens et al., 2012; Van den Broeck et al., 2011). Similar to PSD, the importance of SMP is mostly evaluated based on quantitative comparisons (Lin et al., 2014) in which absolute numbers are compared. In reality, the variance between reactors, sludge, influents and operational settings requires a more qualitative approach, in which dynamics and relative changes of SMP concentrations are considered (De Temmerman et al., 2014). In general, shear stress can influence the balance between sludge-bound EPS and EPS in the bulk liquid (also referred to as SMP). In both short and long-term experiments in a submerged MBR in studies of Menniti et al. (2009) and Trussell et al. (2007), elevated shear led to higher protein concentrations in the bulk liquid coinciding with more membrane fouling. While polysaccharide concentrations remained mostly unaffected in these studies, other authors found that aeration-induced shear breaks up sludge flocs and enables more sludge-bound proteins and polysaccharides to be released in the bulk liquid (Braak et al., 2011; Ivanovic and Leiknes, 2008; Meng et al., 2008). Monitoring shear and its effects is complex for several reasons: shear can originate from various sources, such as pumping, mixing, recirculation (Wisniewski and Grasmick, 1998) as well as aeration, making it hard to determine the impact of each factor. Another potential obstacle when monitoring shear is that most bioreactors, even if considered homogeneously mixed, exhibit a zonal distribution of shear force impacting the local and total breakage and flocculation potential (Prat and Ducoste, 2006; Sobremisana et al., 2011). The relative volume of high turbulent zones prone to shear by mixing, recirculation and aeration and reflocculation zones with less turbulence can be important for a good filterable sludge. Given the potential important impact of fine bubble aeration fluctuations on membrane filtration performance, the shortage of data and lack of detailed analysis on the subject, this study wants to elucidate and quantify the short-term effects on both the activated sludge flocculation state and membrane fouling during a step up and step down in shear level imposed by altering fine bubble aeration intensities in a bioreactor. By monitoring both the sub- and supramicron range in a controlled experiment with real wastewater, this study aims to provide realistic insights into floc dynamics and (de)flocculation mechanisms and link those dynamics to changes in membrane fouling rates. Next to temporal effects on sludge characteristics through shear disturbances, the spatial distribution of sludge characteristics is discussed when interpreting the results.
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Fig. 1 e Conceptual illustration of the impact of shear intensity (Gm ¼ 40 or 90 s¡1) on the flocculation state of activated sludge and possible effects on membrane fouling. The contour plots of normalized average floc size predictions (respectively between 12e64 mm and 11.5e17.5 mm) are illustrative and adapted from Prat and Ducoste (2006).
2.
Materials and methods
2.1.
Lab-scale MBR setup
Two identical lab-scale submerged MBRs (Fig. 2) with a bioreactor volume of 20 L, a membrane tank of 25 L and a 5 L tank pertaining to measurements with the improved flux step method were both fed with municipal wastewater (COD: 1 307 ± 123 mg L1, NHþ 4 -N: 35 ± 9 mg L ) and monitored for COD and ammonia removal according to standard methods. The removal rates for both reactors always exceeded 95% for at least 4 months of continuous operation preceding the shear experiments. Each MBR contained 4 chlorinated polyethylene Kubota flat sheet membranes with a stack space of 6 mm between the membrane plates, and a nominal pore size of 0.4 mm. The membrane area was 0.48 m2 per MBR. The operational settings, i.e. the hydraulic retention time (HRT), sludge retention time (SRT), flow rate, flux, dissolved oxygen concentration (DO), mixed liquid suspended solids (MLSS), filtration, and relaxation time are listed in Table 1. The DO concentration in the bioreactor was controlled by means of a fine bubble disc
diffuser (Aquaflex ADD300) with almost the same diameter as the cylindrical bioreactor tank (setpoint: 2 mg L1 unless otherwise stated). Coarse bubble aeration (specific membrane aeration demand of 14 m3 m2 h1) and membrane relaxation (2 min per 18 min of filtration) were employed for fouling control.
2.2.
Description of the aeration experiments
Under normal operating conditions, the fine bubble aeration averaged 25 m3 air per hour per m3 of sludge in order to control the DO in the aeration tank at 2 mg L1 (Fig. 3, left). A default aeration situation (reference) and an elevated aeration situation (disturbance) were monitored simultaneously, each in one of both identical MBRs. The aeration disturbance was introduced as a step up from an average aeration setting of 25 m3 air per hour per m3 of sludge, to a maximum aeration setting of 50 m3 air per hour per m3 of sludge (Fig. 3, right). This was achieved by manually overruling the aeration control for a duration of 18 h resulting in a DO concentration of around 4 mg L1, followed by a step down to the average
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Fig. 2 e Layout of the lab-scale MBRs: improved flux step test reactor (left), bioreactor (middle) and membrane tank (right); 2 identical systems were used in parallel this study. The cross indicates the sample location.
Table 1 e Operational settings of the lab-scale MBRs. HRT [h] 8
SRT [d]
Flow rate [L hr1]
Net flux [L m2 h1]
DO [mg L1]
pH
MLSS [g L1]
Filtration time [s]
Relaxation time [s]
15
6.25
13
2
7.5
6
1080
120
setting to measure recovery, during which the DO concentration decreased to around 2 mg L1 (results not shown). The disturbance is meant to mimic an increased load event, e.g. first flush during a storm or a dry weather morning peak leading to concentrated inflow, etc. In full-scale wastewater treatment plants, such events commonly result in increased oxygen demand and thus elevated aeration in the bioreactor. The intensity and duration obviously differ per event.
The monitoring began 24 h prior, and continued up to 85 h after the aeration disturbance event. Hence, the effect of a shear disturbance as well as the system's recovery could be investigated and compared to the reference MBR where no disturbance was imposed. Moreover, the reference MBR also provided information regarding the natural variation in sludge composition and behavior due to other variations in the influent.
Fig. 3 e Fine bubble aeration actuation with PID-controlled DO during normal operation (setpoint ¼ 2 mg L¡1) (left). Aeration pattern for the disturbance experiments executed in the lab-scale MBRs comparing a reference aeration reactor vs. high aeration reactor (right).
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Prior to the experiment, the sludge from both MBRs was mixed and redistributed to avoid reactor-specific sludge behavior. The wastewater was buffered in a 1 m3 tank for t ¼ 24 h to t ¼ 48 h, while for t ¼ 48 h to t ¼ 96 h, the buffer tank was refilled with fresh wastewater. This allowed us to eliminate the impact of variations in wastewater quality as much as possible from all analysis except for the two final fouling rate measurements. This was, however, the best practically achievable situation.
2.3.
Activated sludge analysis
During the entire experiment, several sludge parameters as well as sludge filterability were monitored as described in Table 2.
2.3.1.
SMP analysis
Proteins and polysaccharides were analyzed from SMP according to the methods of DuBois et al. (1956) for polysaccharides and Lowry et al. (1951) for proteins. Details are described in De Temmerman et al. (2014).
2.3.2.
Particle size distribution
Sludge samples were measured for supramicron floc size (3e300 mm) utilizing optical image analysis (DIPA 2000, Donner Technologies, The Netherlands), maximum five minutes after a sample was collected. Details regarding the sample preparation can be found in De Temmerman et al. (2014). The results are further referred to as particle size distribution measurements and exhibited as number distributions. Regarding the shape of particles, the average Feret diameter was also determined based on these images. The average Feret diameter is the ratio of the object perimeter in a 2-dimensional plane, and p.
2.3.3.
Submicron particle concentration
Two considerations have to be made when measuring particles in the range, and below the range of visible light: Firstly, ensemble techniques e.g. laser diffraction and laser scattering, rely on signal decomposition to construct the PSD. € fer diffraction These techniques rely on the Mie and Fraunho theory in the range of visible light to decompose one input signal into a PSD. While sludge is naturally multimodally distributed, ensemble techniques can only construct unimodal distributions. Besides this drawback, these methods also have a relatively low resolution, produce unrealistic unimodal distributions with low confidence levels and they are not able to measure particle concentration. Nanoparticle tracking analysis, such as the Nanosight NS500 used in this work, is
able to both construct reliable PSD, and determine the particle concentration in the sample. Secondly, sample preparation is a necessary procedure for measuring submicron particles and inevitably requires a separation step of the sludge sample, such as filtration, gravitational settling or centrifugation. This separation step can influence the distribution and, to a lesser extent, the concentration of submicron particles in the bulk (Govoreanu et al., 2009). For this reason it is questionable if the particle size distribution of the prepared sample is representative for the real distribution, and therefore, in this work, results on submicron particles are only compared in terms of their concentrations. Following sample preparation as described in De Temmerman et al. (2014), submicron particle concentrations were measured in the 10e450 nm range (Nanosight NS500, Nanosight LTD, U.K.). This device's measurement principle is based on nanoparticle tracking analysis, which relates the rate of Brownian motion of particles to their size. The particles contained in the sample are visualized by virtue of the light they scatter when illuminated by a laser light. The light scattered by the particles is captured utilizing an optical digital camera, and specific software monitors the motion of each particle between subsequent frames. This rate of particle movement is associated with a sphere-equivalent hydrodynamic radius as calculated with the Stokes-Einstein equation whereby the size of submicron particles is calculated on a particle-by-particle basis. Particle tracking allows the construction of multimodal distributions based on individually tracked particles and determining particle concentrations based on counting single particles.
2.3.4.
Size exclusion chromatography
Organic matter fractions were analyzed utilizing liquid chromatography followed by an organic carbon detector (LC-OCD) (Doc-Labor, Germany) in order to distinguish between biopolymers, humic acids, low molecular weight (LMW) acids, and neutrals. Details regarding the LC-OCD instrument, analytical method, and data interpretation can be found in Huber et al. (2011).
2.3.5.
Membrane fouling rate
For each MBR, sludge was recirculated to an external 5 L vessel (HRT 1 h) containing two Kubota membrane plates with identical properties as those in the MBRs. The vessels were aerated with a coarse bubble aerator. The transmembrane pressure (TMP) (Endress & Hauser, Cerebar M PMC 41), temperature, and flux (mass balance) were monitored on-line. The irreversible fouling rate was calculated based on the improved flux step method according to Van der Marel et al. (2009), with a
Table 2 e Unit and time of analysis of activated sludge characteristics during the experiments in both reactors. t ¼ 0 represents the start of high shear. Measurement Total fouling rate Irreversible fouling rate SMP Particle size distribution Submicron particle concentration Size exclusion chromatography
Unit
Time of analysis (hour)
m1 s1 m1 s1 mg g1 TSS number % # particles ml1 ppb
24, 12, 4, 1, 6, 24, 48, 72, 96 24, 12, 4, 1, 6, 24, 48, 72, 96 5, 3.75, 0.75, 0.5, 1, 3, 4, 17, 18.65, 19.4, 23 1, 5, 20, 24 5, 3.75, 0.75, 0.18, 0.5, 1, 3, 4, 17.5, 18.65, 19.4, 23 5, 3.75, 0.75, 0.18, 0.5, 1, 3, 4, 17.5, 18.65, 19.4, 23
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step-duration set at 0.12 h for both the flux step (5e100 L m2 h1 with 5 L m2 h1 increments) and relax step (5 L m2 h1). In this improved flux step method, a non-zero value for the flux during relaxation was necessary to determine the irreversible fouling rate. The total fouling rate (increase in resistance over time) was calculated at a supercritical flux step of 50 L m2 h1. This method has distinct advantages when compared to other commonly employed flux step methods because fouling history is reduced and reversible and irreversible fouling rates can be estimated at each flux increment. After each flux step experiment, the membranes were mechanically cleaned with a high-pressure water nozzle to remove any cake- and possibly present gel layer.
3.
Results
3.1.
Membrane fouling rate
In the reference reactor, the total and irreversible fouling rates were found relatively stable and averaged 3.54 ± 0.21 108 m1 s1 (Fig. 4, top) and 3.01 ± 0.29 106 m1 s1 (Fig. 4, bottom), respectively. In contrast, the total fouling rate during shear disturbance increased with approximately 100% to a maximum value of 7.43 ± 2.01 108 m1 s1 (Fig. 4, top).
The total fouling rate subsequently decreased less than 6 h after finishing the fine bubble aeration disturbance, hereby returning to the values that were observed prior to the shear disturbance, however, still 52% higher compared to the default reactor. The irreversible fouling rate did not show an immediate change upon shear disturbance. As one would expect, this is a slower process, and the irreversible fouling rate steadily increased until the end of the experiment with approximately 35% to a maximum value of 4.15 ± 0.56 106 m1 s1 whereas it slightly decreased in the default reactor (Fig. 4, bottom). In between consecutive flux step tests, the removal of the gel layer did not result in a significant decrease of membrane resistance. The increased resistance through irreversible fouling could thus be mainly attributed to pore blocking. The recovery of the total fouling rate was not complete, which can partially be attributed to an incomplete recovery of the reversible sludge fouling propensity for the duration of the experiment, but also to the elevated irreversible fouling rates. One could envision that continuing the experiment might lead to a full recovery of the sludge fouling propensity, although it might prove difficult to distinguish it against the natural variation of the real wastewater influent composition. The use of an experimental design with a reference reactor and buffering of the influent as much as possible appears to be a necessary measure.
3.2.
SMP analysis
The observed SMP polysaccharide concentrations varied significantly in the shear reactor before, during, and after the disturbance in fine bubble aeration intensity. Natural variations occurred as indicated by the measurements in the reference reactor (Fig. 5). Upon imposing the shear disturbance, the SMP polysaccharide concentration remained fairly steady during the first 3e4 h, but started to exhibit an increase between 4 and 18 h of elevated shear up to 100% higher values compared to the reference reactor. This effect disappeared almost within 2 h after restoring the fine bubble aeration intensity. Results for SMP protein concentrations were similar (not shown).
Fig. 4 e Total fouling rate at 50 L m¡2 h¡1 (top) and irreversible fouling rate (bottom) for a reference vs. shear disturbance reactor. Vertical dashed lines indicate the start and finish of the aeration flow rate disturbance. Error bars indicate standard deviations (n ¼ 2 membranes per improved flux step test vessel).
Fig. 5 e Polysaccharide concentrations for SMP for a reference vs. shear disturbance reactor. Vertical dashed lines indicate the start and finish of the high shear event. Error bars indicate standard deviations (n ¼ 2 samples).
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3.3.
Particle size distribution
Five hours after the initiation of the disturbance, and during the increase of the total fouling rate, a significant shift in PSD was observed. Large flocs disappeared from the PSD in favor of smaller fragments (Fig. 6, top). This is in line with the deflocculation theories described in the literature: shear n et al., 2003), especially so for leads to floc rupture (Wile sludge that is not habituated to shocks. The PSD started to shift back to larger flocs within 20 h after initiation of the high shear event (2 h after ending the disturbance). Within 24 h (4 h after ending the shock), the distribution did not shift anymore and a new steady state distribution was reached, characterized by a peak at 24 mm (compared with 43 mm for the initial distribution at t ¼ 1 h), and in general, more small particles between 10 and 40 mm and less large particles between 40 and 300 mm. The PSD in the reference reactor did not change significantly during the experiment and the peak remained around 42 ± 2 mm (data not shown). Considering the particle shape quantities, more compact flocs were observed during the shear shock, reflected by a small increase in sphericity and compactness, and a large decrease of the average Feret diameter (Fig. 6, bottom).
3.4.
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Submicron particle concentration
According to Fig. 7, the submicron particle concentration in the reference reactor was around 6 106 particles per ml and remained below 8 106 particles per ml throughout the experiment, while in the shear reactor, the concentration increased rapidly to around 11 106 particles per ml (75% above reference) after 4 h of high shear. Remarkably, even before ending the high shear event, the concentrations fell back to approximately background values, indicating that these very small particles seem to take part in a reflocculation process already at high turbulence levels. Concentrations were similar for both reactors approximately 2e4 h after ending the disturbance event.
3.5.
Size exclusion chromatography
The specific characterization of SMP-related biopolymers (>10 kDa), humic acids and low molecular weight acids and neutrals (<2 kDa) is presented for the duration of the experiment (Fig. 8). Notwithstanding a lot of natural variability in the data, biopolymer and humic acids concentrations were consistently higher in the shear reactor during, and shortly after the high shear event. On the contrary, LMW acids in the shear reactor remained lower. There was no effect discernible for LMW neutrals.
4.
Discussion
Shear induced by elevated aeration intensity clearly influences the physicochemical and biological properties of MBR biomass in line with previous findings (Menniti et al., 2009). More specific, concentrations of SMP (4.1), particle size distributions (4.2), submicron particle concentrations (4.3), organic carbon fractions (4.4) were clearly affected by shear in our experiments, and this had an impact on membrane fouling (4.5).
Fig. 6 e Number-based PSD dynamics before, during and after a high shear event in the shear reactor (top). Average Feret diameter before, during and after a high shear event in the shear reactor (bottom). Error bars indicate standard deviation (n ¼ 3 separate samples).
Fig. 7 e Submicron particle concentration [10e450 nm] for a reference vs. shear reactor. Vertical dashed lines indicate the start and finish of the high shear event. Error bars indicate standard deviations (n ¼ 2 samples).
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Fig. 8 e Concentration of biopolymers, humic acids, LMW acids and LMW neutrals from LC-OCD analysis for a shear shock vs. reference reactor. Vertical dashed lines indicate the start and finish of the high shear event.
4.1.
SMP
In this study, we focused solely on SMP concentrations in the bulk liquid. While there is a clear relation between flocattached EPS and SMP, the dynamics of EPS are hard to examine because of the complicated and hard-to-standardize measurement involving a long and error-prone extraction procedure (De Temmerman et al., 2014). The SMP concentrations increased in the high aeration reactor but recovered towards the background values in the reference reactor within 4 h after ending the aeration event (Fig. 5). During and just after the shear event, SMP concentrations were significantly higher compared to the reference reactor. Shear-induced SMP-release to the bulk liquid can be attributed to floc breakage, release from bacteria and cell lysis. This outcome is in line with other short-term studies on the impact of shear imposed by e.g. recirculation (Park et al., 2005), and aeration (Meng et al., 2008; Menniti et al., 2009), where the authors found that high shear and aeration intensities led to the release of floc-bound EPS. In contrast to the submicron particle concentrations, the SMP concentrations remained high throughout the shear event indicating that the released SMP were not immediately and fully reincorporated into the flocs. It can be hypothesized that these higher SMP concentrations in the bulk liquid will attach to the membrane, resulting in more irreversible fouling.
4.2.
Particle size distribution
High aeration had an immediate impact on the supra micron particle size distribution. Within 5 h, the particle size
distribution peak decreased from approx. 43 mme18 mm (Fig. 6). These observations confirm the findings for coarse bubble aeration of Meng et al. (2008), who subjected sludge in a hollow fiber SMBR to a range of airflow rates, and also found that aeration increased sludge breakage. In this study, a 28% larger amount of flocs smaller than 50 mm were observed in the high airflow MBR (8 m3 m2 of membrane h1), compared to the low airflow MBR (1.5 m3 m2 of membrane h1). In our study, the difference was 16%, but this difference depends on the initial distribution. Although the results show a clear aeration-induced deflocculation effect, the particle size distribution measurements also indicate that this effect is, at least partially, reversible. A new steady state PSD was attained 4 h after the aeration was put back to default. This state clearly marks an improved flocculation state, even though the distribution peak at 24 mm is still very much shifted towards the smaller particle ranges. It shows that the smallest flocs aggregated in a process of orthokinetic flocculation (i.e. shear-driven) to result in a new flocculation state (basically a balance between aggregation2 and breakup). This final state was also characterized by more compactflocs given the decreased average Feret diameter, and more uniform flocs through shear, given the decreased standard deviation on this average Feret diameter. The shifted distribution with more compact flocs implies the build-up of a less porous and thus less permeable cake layer compared to the original sludge. This is reflected in the continued higher total fouling rates in the shear reactor after reducing the aeration flow (Fig. 4). The observed deflocculation - reflocculation behavior, including the hysteresis effect,
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was also further investigated by repeating the detailed shear experiments of Mikkelsen and Keiding (1999), and supports the clear shift in PSD facing turbulent shear, and a clear shift back, although not complete, when turbulent shear was lowered (results not shown).
4.3.
Submicron particle concentration
Initially, the submicron particle concentration strongly increased in response to the high aeration event (Fig. 7). This behavior has not only been hypothesized (e.g. Braak et al., 2011), but also measured: Ivanovic and Leiknes (2008) and Meng et al. (2008) compared submicron particle dynamics for different aeration rates. However, their applied measuring ensemble techniques (laser diffraction and laser scattering, respectively) are not suitable for particles in the range, and below the range, of visible light as mentioned in the Materials and Methods section. Even before the end of the aeration event, concentrations decreased to values around those of the reference reactor. This implies that, notwithstanding the higher shear, the submicron particles are either taking part in a reflocculation process, and/or attach to the membrane and cake layer causing more reversible and irreversible fouling. It is hypothesized that with the initiation of shear significant amounts of colloids and submicron particles are released, in line with the observed shift in particle size distribution towards a large number of smaller particles. This means there is an increased chance of submicron particle collisions giving rise to perikinetic (driven by Brownian motion) flocculation into bigger particles. At the same time, submicron particles likely also attach to the membrane matrix, blocking pores and giving rise to the observed irreversible fouling rate increase.
4.4.
Size exclusion chromatography
Organic carbon fractions are often analyzed in surface and drinking water, but not so much in activated sludge and wastewater. Still, they could reveal interesting information regarding those fractions that have high pore blocking potential, i.e. <0.5 mm. The measured fractions showed quite some natural variation hindering a clear analysis. Nevertheless, humic acid and biopolymer concentrations were higher throughout the high shear event (Fig. 8), and coincidentally, biopolymers have been shown to correlate well with increased membrane fouling (Kimura et al., 2014). It remains unclear whether other fractions, i.e. LMW neutrals and acids can be correlated to membrane fouling, as they do not seem to respond very much to the disturbance events. Based on current research, we do not recommend including LMW neutrals and acids in flocculation analyses in relation to shear experiments.
4.5.
Membrane fouling rates
The total fouling rate increased instantly with increasing aeration, and decreased within 6 h after fine bubble aeration but did not return back to default. This indicates a relatively rapid but incomplete recovery of sludge filterability. The results appear to confirm the hypothesis of Braak et al. (2011),
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that a shift in particle size distribution to smaller flocs reduces the cake permeability, which can only be restored through a distribution shift back towards larger particles. The incomplete recovery of total fouling combined with the incomplete recovery of PSD, suggests the importance of PSD dynamics. The irreversible fouling rate only really increases 6 h after ending high aeration, and the increase was permanent. This is mainly related to the applied measurement technique whereby irreversible fouling is accumulated over time. It is clear that increased aeration rates negatively impact irreversible fouling through shear, but an accurate quantification in short term experiments remains somewhat difficult as it manifests itself on a longer term. The increase and decrease of both supra- and submicron particles coincided very clearly with to a respectively lower or higher permeability of the cake layer on the membrane. The increasing irreversible fouling rate could be attributed mainly to pore blocking. This is thought to be a slower process, as part of the submicron particles will have an effect on cake layer resistance, but are not necessarily enhancing pore blocking as cake acts as a secondary membrane. In this way, only after a significant amount of flux steps, the effect of submicron particles on the irreversible fouling rate can be observed.
4.6. Considerations on spatial and temporal distribution effects While the impact of fine bubble aeration on sludge characteristics (Figs. 5e8) and membrane fouling is significant (Fig. 4), its impact has to be evaluated in the framework of spatial-temporally distributed shear in MBRs as illustrated in Fig. 1. Aeration is, even at steady-state DO settings, temporally and spatially distributed as a consequence of inflow dynamics and aerator design and operation (Fulton et al., 2011). First, there are different shear originators in an MBR, e.g. aeration, mixers and recirculation loops (Braak et al., 2011; Mikkelsen and Keiding, 1999; Ivanovic and Leiknes, 2008). The exact contribution of these shear originators to the overall system shear depends on the dimension of reactors, pumps, valves and the membrane design (Chan et al., 2011). Within one system, recirculation flows and membrane aeration intensity remain fairly constant, as they are mostly fixed operational values according to design protocols. These settings effectively keep the shear originating from pumps, coarse bubble aeration, mixers, jet streams, tubes and valves constant. That leaves only the fine bubble aeration as factor that strongly determines the overall shear stress variations in the system (Abbassi et al., 2000). Both the design and operation of reactors and aerators influence the spatial shear distribution, mostly by the positioning and design of bubble aerators. The spatial variation in impeller shear as presented in Fig. 1 clearly indicates that floc size distribution is also spatially distributed. Along the same lines as for impellers, aeration creates zones where the aeration intensity is high and floc breakup is promoted, while floc aggregation promoting zones can occur in those regions outside of the aerated zone. However, the latter can be greatly reduced, and even non-existent, if aeration intensities are increased. Maintaining the continuous presence of an
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effective reflocculation zone can be visualized by CFD as in Gresch et al. (2011). Next to the spatial distribution of the aerators, timedependent changes in MLSS concentrations, dynamic inflow composition but also badly designed DO controllers and illmaintained sensors all contribute to dynamics in biological aeration intensity, thereby varying the aeration pattern. As Brannock et al. (2010) emphasized, a well-mixed reactor with homogeneous fine-bubble aeration, clean and reliable sensors and good control settings is necessary to preserve homogeneity in particle size distribution throughout the aerobic reactor, and for the efficiency of nutrient removal in the aeration zone. A drawback of rigorous, homogeneous mixing could be the reduction or even absence of low turbulence zones that are necessary for reflocculation. It is hypothesized that the complete lack of reflocculation zones in the studied lab-scale set-up during high aeration maximized the deflocculation potential. While several authors have based sludge filterability on mean floc diameters (e.g. Wu and Huang, 2009), our study indicates that mean floc diameters do not reveal any conclusive relation with membrane fouling outside the scope of the specifically researched system. The influence of fine bubble aeration on activated sludge could be decreased through prevention and remediation. Prevention implies avoiding sharp stress peaks in the bioreactor through buffering the influent, by optimizing both the aeration and reactor design to preserve reflocculation zones, and e.g. by smoother aerator (actuator) control. To cope with spatial-temporal dynamics in aeration intensity, while maintaining the continuous presence of an effective reflocculation zone, it is advised to optimize the aerator tank design through CFD coupled with flocculation models (Sobremisana et al., 2011), to take the distributed flocculation parameters into account. Remediation is mainly achieved by counteracting the deflocculation increase induced by aeration dynamics, e.g. flocculant dosing, or by ad hoc operational strategies based on practice or combined CFD-flocculation model studies.
5.
Conclusions
In this study, the impact of elevated fine bubble aeration intensity on both sludge quality and sludge filterability was monitored in a lab-scale MBR setup fed with real communal wastewater. The particle size distribution of the activated sludge shifted to lower size classes during high aeration and shifted back to a new steady state after setting the aeration intensity back to default. The new steady state indicated that the reflocculation was quick but incomplete. Sludge PSDs display measurable variability over time and between reactors, so we recommend monitoring the (often subtle, but significant) distribution shifts rather than statistics such as averages as this leads to important information loss. Concentrations of bulk liquid submicron particles, SMP and organic carbon fractions shifted upon altering the aeration settings and the observed changes were
confronted with the current scientific understanding of membrane fouling and filtration. The dynamics in floc characteristics were reflected in the membrane fouling rates. During high aeration intensity, especially the total membrane fouling rate measurements increased significantly. The rate decreased again after setting the aeration back to default, but remained higher than the reference situation. The irreversible fouling rate was also negatively affected by the shear event, with a continued increase in measured fouling rates after the shock event. Sustainable solutions to prevent high shear through fine bubble aeration should be further investigated, such as influent buffering, preservation of the reflocculation potential (prevention, during design phase) and flocculant dosing (remediation).
Acknowledgments This work was performed in the TTIW cooperation framework of Wetsus, Centre of Excellence for Sustainable Water Technology (www.wetsus.nl). Wetsus is funded by the Dutch Ministry of Economic Affairs, the European Union ^ n, the Regional Development Fund, the Province of Frysla City of Leeuwarden and the EZ/Kompas programme of the Samenwerkingsverband Noord-Nederland. The authors would like to thank the participants of the research theme “Membrane Processes for Wastewater Treatment and Reuse” for the fruitful discussions and their financial support.
references
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Drews, A., Vocks, M., Bracklow, U., Iversen, V., Kraume, M., 2008. Does fouling in MBRs depend on SMP? Desalination 231, 141e149. DuBois, M., Gilles, K.A., Hamilton, J.K., Rebers, P.A., Smith, F., 1956. Colorimetric method for determination of sugars and related substances. Anal. Chem. 28, 350e356. Fan, F., Zhou, H., 2007. Interrelated effects of aeration and mixed liquor fractions on membrane fouling for submerged membrane bioreactor processes in wastewater treatment. Environ. Sci. Technol. 41, 2523e2528. rube , P.R., 2011. Fulton, B.G., Redwood, J., Tourais, M., Be Distribution of surface shear forces and bubble characteristics in full-scale gas sparged submerged hollow fiber membrane modules. Desalination 281, 128e141. Govoreanu, R., Saveyn, H., Van der Meeren, P., Nopens, I., Vanrolleghem, P.A., 2009. A methodological approach for direct quantification of the activated sludge floc size distribution by using different techniques. Water Sci. Technol. 60, 1857e1867. Gresch, M., Armbruster, M., Braun, D., Gujer, W., 2011. Effects of aeration patterns on the flow field in wastewater aeration tanks. Water Res. 45, 810e818. Huber, S.A., Balz, A., Abert, M., Pronk, W., 2011. Characterisation of aquatic humic and non-humic matter with size-exclusion chromatographyeorganic carbon detectioneorganic nitrogen detection (LC-OCD-OND). Water Res. 45, 879e885. Ivanovic, I., Leiknes, T., 2008. Impact of aeration rates on particle colloidal fraction in the biofilm membrane bioreactor (BFMBR). Desalination 231, 182e190. Kimura, K., Tanaka, K., Watanabe, Y., 2014. Microfiltration of different surface waters with/without coagulation: clear correlations between membrane fouling and hydrophilic biopolymers. Water Res. 49, 434e443. Le-Clech, P., Chen, V., Fane, T.A.G., 2006. Fouling in membrane bioreactors used in wastewater treatment. J. Memb. Sci. 284, 17e53. Lin, H., Zhang, M., Wang, F., Meng, F., Liao, B.-Q., Hong, H., Chen, J., Gao, W., 2014. A critical review of extracellular polymeric substances (EPSs) in membrane bioreactors: characteristics, roles in membrane fouling and control strategies. J. Memb. Sci. 460, 110e125. Lowry, O.H., Rosebrough, N.J., Farr, A.L., Randall, R.J., 1951. Protein measurement with the Folin phenol reagent. J. Biol. Chem. 193, 265e275. Meng, F., Yang, F., Shi, B., Zhang, H., 2008. A comprehensive study on membrane fouling in submerged membrane bioreactors operated under different aeration intensities. Sep. Purif. Technol. 59, 91e100. Menniti, A., Kang, S., Elimelech, M., Morgenroth, E., 2009. Influence of shear on the production of extracellular polymeric substances in membrane bioreactors. Water Res. 43, 4305e4315.
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Mikkelsen, H.L., Keiding, K., 1999. Equilibrium aspects of the effects of shear and solids content on aggregate deflocculation. Adv. Colloid Interface Sci. 80, 151e182. Naessens, W., Maere, T., Nopens, I., 2012. Critical review of membrane bioreactor models e part 1: biokinetic and filtration models. Bioresour. Technol. 122, 95e106. Nopens, I., 2005. Modelling the Activated Sludge Flocculation Process: a Population Balance Approach. PhD Thesis,. Ghent University, Belgium, p. 284. Park, J.S., Yeon, K.M., Lee, C.H., 2005. Hydrodynamics and microbial physiology affecting performance of a new MBR, membrane-coupled high-performance compact reactor. Desalination 172, 181e188. Prat, O.P., Ducoste, J.J., 2006. Modeling spatial distribution of floc size in turbulent processes using the quadrature method of moment and computational fluid dynamics. Chem. Eng. Sci. 61, 75e86. rube , P.R., Nopens, I., 2011. Ratkovich, N., Chan, C.C.V., Be Analysis of shear stress and energy consumption in a tubular airlift membrane system. Water Sci. Technol. 64, 189e198. Sobremisana, A.P., Ducoste, J.J., de los Reyes III, F.L., 2011. Combining CFD, floc dynamics, and biological reaction kinetics to model carbon and nitrogen removal in an activated sludge system. In: Proc. WEFTEC Conf, pp. 3272e3282. Trussell, R.S., Merlo, R.P., Hermanowicz, S.W., Jenkins, D., 2007. Influence of mixed liquor properties and aeration intensity on membrane fouling in a submerged membrane bioreactor at high mixed liquor suspended solids concentrations. Water Res. 41, 947e958. Van den Broeck, R., Krzeminski, P., Van Dierdonck, J., Gins, G., Lousada-Ferreira, M., Van Impe, J.F.M., van der Graaf, J.H.J.M., Smets, I.Y., van Lier, J.B., 2011. Activated sludge characteristics affecting sludge filterability in municipal and industrial MBRs: unraveling correlations using multi-component regression analysis. J. Memb. Sci. 378, 330e338. Van der Marel, P., Zwijnenburg, A., Kemperman, A., Wessling, M., Temmink, H., van der Meer, W., 2009. An improved flux-step method to determine the critical flux and the critical flux for irreversibility in a membrane bioreactor. J. Memb. Sci. 332, 24e29. Van Kaam, R., Anne-Archard, D., Alliet, M., Lopez, S., Albasi, C., 2006. Aeration mode, shear stress and sludge rheology in a submerged membrane bioreactor: some keys of energy saving. Desalination 199, 482e484. n, B.-M., Jin, B., Lant, P., 2003. Impacts of structural Wile characteristics on activated sludge floc stability. Water Res. 37, 3632e3645. Wisniewski, C., Grasmick, A., 1998. Floc size distribution in a membrane bioreactor and consequences for membrane fouling. Colloids Surf. A Physicochem. Eng. Asp. 138, 403e411. Wu, J., Huang, X., 2009. Effect of mixed liquor properties on fouling propensity in membrane bioreactors. J. Memb. Sci. 342, 88e96.
Available online at www.sciencedirect.com
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The effect of fine bubble aeration intensity on membrane bioreactor sludge characteristics and fouling L. De Temmerman a,b, T. Maere b,c, H. Temmink a,d, A. Zwijnenburg a, I. Nopens b,* a
Wetsus Centre of Excellence for Sustainable Water Technology, P.O. Box 1113, 8900 CC Leeuwarden, The Netherlands b BIOMATH, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, B-9000 Ghent, Belgium c modelEAU, Departement de genie civil et de genie des eaux, Universite Laval, 1065 Avenue de la Medecine, Quebec QC G1V 0A6, Canada d Sub-department of Environmental Technology, Wageningen University, P.O. Box 17, 6700 AA Wageningen, The Netherlands
article info
abstract
Article history:
While most membrane bioreactor (MBR) research focuses on improving membrane filtra-
Received 8 January 2015
tion through air scour, backwashing and chemical cleaning to physically counteract
Received in revised form
fouling, relatively few studies have dealt with fouling prevention, e.g. minimizing the
24 February 2015
impact of operational settings that negatively impact sludge filterability. To evaluate the
Accepted 25 February 2015
importance of those settings, the effects of bioreactor aeration intensity variations on
Available online 5 March 2015
membrane fouling have been studied in a lab-scale MBR setup while simultaneously monitoring a unique set of key sludge parameters. In particular, this paper focuses on the
Keywords:
impact of shear dynamics resulting from fine air bubbles on the activated sludge quality
MBR
and flocculation state, impacting membrane fouling. When augmenting the fine bubble
Particle size distribution
aeration intensity both the total and irreversible fouling rate increased. Major indications
Shear
for sludge filterability deterioration were found to be a shift in the particle size distribution
Floc size dynamics
(PSD) in the 3e300 mm range towards smaller sludge flocs, and increasing concentrations of
Size exclusion chromatography
submicron particles (10e1000 nm), soluble microbial products and biopolymers. When
Submicron particle concentration
lowering the aeration intensity, both the sludge characteristics and fouling either went back to background values or stabilized, respectively indicating a temporary or more permanent effect, with or without time delay. The shift in PSD to smaller flocs and fragments likely increased the total fouling through the formation of a less permeable cake layer, while high concentrations of submicron particles were likely causing increased irreversible fouling through pore blocking. The insights from the performed fouling experiments can be used to optimize system operation with respect to influent dynamics. © 2015 Elsevier Ltd. All rights reserved.
* Corresponding author. Tel.: þ32 (0)9 264 5932. E-mail address: [email protected] (I. Nopens). http://dx.doi.org/10.1016/j.watres.2015.02.057 0043-1354/© 2015 Elsevier Ltd. All rights reserved.
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1.
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Introduction
Activated sludge plants, be it membrane bioreactors (MBR) or conventional activated sludge (CAS) systems, experience considerable fluctuations in shear through dynamics in fine bubble aeration resulting from controllers reacting to loading rate dynamics. The resulting shear dynamics may influence the sludge characteristics such as floc size, floc strength and floc compactness temporarily or permanently. Changing sludge characteristics potentially affect the sludge filterability (Drews, 2010; Le-Clech et al., 2006). In this respect, understanding the effects of shear through aeration on sludge characteristics is necessary to optimize membrane operation in terms of energy efficiency (Van Kaam et al., 2006). In MBRs, aeration is typically applied near the membranes as well as in the bioreactor. Coarse bubble (>2 mm) aeration close to the membranes is applied for air scouring of the biomass in the vicinity and attached to the membrane surface. The turbulence created near the membrane delays membrane fouling. In contrast, fine bubble (<2 mm) aeration in the bioreactor is meant to maintain a sufficient dissolved oxygen (DO) concentration for nitrification and organic carbon (COD) removal. While both aeration types can induce shear stress on sludge, the impact has only been thoroughly determined for € hm et al., 2012). Most of the concoarse bubble aeration (Bo cepts related to shear are discussed in the context of wall shear stress on the membranes, e.g. Ratkovich et al. (2011) and much less with respect to stress impact on sludge flocs in the bulk. The interrelations between shear (through an impeller in this particular case), flocculation behavior and membrane fouling are illustrated in Fig. 1. The contour plots in Fig. 1 show the effect of an impellerinduced shear distribution in a reactor in a 2-dimensional XZ plane, and for two different velocity gradients Gm on floc size distribution (Prat and Ducoste, 2006). In the upper case, a low average characteristic velocity gradient (Gm ¼ 40 s1) results in larger floc sizes (here up to 64 mm) in the activated sludge tank. In the lower case, a higher average characteristic velocity gradient (Gm ¼ 90 s1) creates smaller flocs (up to 16 mm). In the latter case this is likely to result in a thicker cake layer, gel layer and pore blocking resistance compared to the former case. Flocs that are continuously exposed to low shear grow into loose and weak flocs, whereas flocs exposed to continuous high shear break up to reach the Kolmogorov scale, i.e. the smallest scale of turbulence (Nopens, 2005). Flocs intermittently exposed to low and high shear tend to form more compact flocs (Mikkelsen and Keiding, 1999). This implies that the shear dynamics largely determine the potential for floc breakage and release of small fragments and compounds such as soluble microbial products (SMP) into the bulk liquid. Hence, shear dynamics are important with respect to membrane fouling. One can monitor the breakage of sludge flocs, by measuring the particle size distribution (PSD) and concentration of SMP in the bulk liquid simultaneously, as was shown by De Temmerman et al. (2014) for a salt shock. With regards
to specific studies on airflow rates, the tendency to smaller flocs was found comparing 3 MBRs with respectively low, medium and high airflow rates (Meng et al., 2008). A study by Fan and Zhou (2007) revealed that at higher aeration rates, sludge flocs were breaking up more, resulting in higher SMP concentrations in the bulk liquid. Breakage through aeration inevitably leads to higher concentrations of very small floc fragments in the bulk liquid and SMP which can be further described as biopolymers, humic acids and the like. There is a consensus that biopolymers and, in general, SMP could increase cake- and gel layer resistance, but the exact impact, and thus the importance of SMP remains hard to quantify (Drews et al., 2008; Naessens et al., 2012; Van den Broeck et al., 2011). Similar to PSD, the importance of SMP is mostly evaluated based on quantitative comparisons (Lin et al., 2014) in which absolute numbers are compared. In reality, the variance between reactors, sludge, influents and operational settings requires a more qualitative approach, in which dynamics and relative changes of SMP concentrations are considered (De Temmerman et al., 2014). In general, shear stress can influence the balance between sludge-bound EPS and EPS in the bulk liquid (also referred to as SMP). In both short and long-term experiments in a submerged MBR in studies of Menniti et al. (2009) and Trussell et al. (2007), elevated shear led to higher protein concentrations in the bulk liquid coinciding with more membrane fouling. While polysaccharide concentrations remained mostly unaffected in these studies, other authors found that aeration-induced shear breaks up sludge flocs and enables more sludge-bound proteins and polysaccharides to be released in the bulk liquid (Braak et al., 2011; Ivanovic and Leiknes, 2008; Meng et al., 2008). Monitoring shear and its effects is complex for several reasons: shear can originate from various sources, such as pumping, mixing, recirculation (Wisniewski and Grasmick, 1998) as well as aeration, making it hard to determine the impact of each factor. Another potential obstacle when monitoring shear is that most bioreactors, even if considered homogeneously mixed, exhibit a zonal distribution of shear force impacting the local and total breakage and flocculation potential (Prat and Ducoste, 2006; Sobremisana et al., 2011). The relative volume of high turbulent zones prone to shear by mixing, recirculation and aeration and reflocculation zones with less turbulence can be important for a good filterable sludge. Given the potential important impact of fine bubble aeration fluctuations on membrane filtration performance, the shortage of data and lack of detailed analysis on the subject, this study wants to elucidate and quantify the short-term effects on both the activated sludge flocculation state and membrane fouling during a step up and step down in shear level imposed by altering fine bubble aeration intensities in a bioreactor. By monitoring both the sub- and supramicron range in a controlled experiment with real wastewater, this study aims to provide realistic insights into floc dynamics and (de)flocculation mechanisms and link those dynamics to changes in membrane fouling rates. Next to temporal effects on sludge characteristics through shear disturbances, the spatial distribution of sludge characteristics is discussed when interpreting the results.
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Fig. 1 e Conceptual illustration of the impact of shear intensity (Gm ¼ 40 or 90 s¡1) on the flocculation state of activated sludge and possible effects on membrane fouling. The contour plots of normalized average floc size predictions (respectively between 12e64 mm and 11.5e17.5 mm) are illustrative and adapted from Prat and Ducoste (2006).
2.
Materials and methods
2.1.
Lab-scale MBR setup
Two identical lab-scale submerged MBRs (Fig. 2) with a bioreactor volume of 20 L, a membrane tank of 25 L and a 5 L tank pertaining to measurements with the improved flux step method were both fed with municipal wastewater (COD: 1 307 ± 123 mg L1, NHþ 4 -N: 35 ± 9 mg L ) and monitored for COD and ammonia removal according to standard methods. The removal rates for both reactors always exceeded 95% for at least 4 months of continuous operation preceding the shear experiments. Each MBR contained 4 chlorinated polyethylene Kubota flat sheet membranes with a stack space of 6 mm between the membrane plates, and a nominal pore size of 0.4 mm. The membrane area was 0.48 m2 per MBR. The operational settings, i.e. the hydraulic retention time (HRT), sludge retention time (SRT), flow rate, flux, dissolved oxygen concentration (DO), mixed liquid suspended solids (MLSS), filtration, and relaxation time are listed in Table 1. The DO concentration in the bioreactor was controlled by means of a fine bubble disc
diffuser (Aquaflex ADD300) with almost the same diameter as the cylindrical bioreactor tank (setpoint: 2 mg L1 unless otherwise stated). Coarse bubble aeration (specific membrane aeration demand of 14 m3 m2 h1) and membrane relaxation (2 min per 18 min of filtration) were employed for fouling control.
2.2.
Description of the aeration experiments
Under normal operating conditions, the fine bubble aeration averaged 25 m3 air per hour per m3 of sludge in order to control the DO in the aeration tank at 2 mg L1 (Fig. 3, left). A default aeration situation (reference) and an elevated aeration situation (disturbance) were monitored simultaneously, each in one of both identical MBRs. The aeration disturbance was introduced as a step up from an average aeration setting of 25 m3 air per hour per m3 of sludge, to a maximum aeration setting of 50 m3 air per hour per m3 of sludge (Fig. 3, right). This was achieved by manually overruling the aeration control for a duration of 18 h resulting in a DO concentration of around 4 mg L1, followed by a step down to the average
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Fig. 2 e Layout of the lab-scale MBRs: improved flux step test reactor (left), bioreactor (middle) and membrane tank (right); 2 identical systems were used in parallel this study. The cross indicates the sample location.
Table 1 e Operational settings of the lab-scale MBRs. HRT [h] 8
SRT [d]
Flow rate [L hr1]
Net flux [L m2 h1]
DO [mg L1]
pH
MLSS [g L1]
Filtration time [s]
Relaxation time [s]
15
6.25
13
2
7.5
6
1080
120
setting to measure recovery, during which the DO concentration decreased to around 2 mg L1 (results not shown). The disturbance is meant to mimic an increased load event, e.g. first flush during a storm or a dry weather morning peak leading to concentrated inflow, etc. In full-scale wastewater treatment plants, such events commonly result in increased oxygen demand and thus elevated aeration in the bioreactor. The intensity and duration obviously differ per event.
The monitoring began 24 h prior, and continued up to 85 h after the aeration disturbance event. Hence, the effect of a shear disturbance as well as the system's recovery could be investigated and compared to the reference MBR where no disturbance was imposed. Moreover, the reference MBR also provided information regarding the natural variation in sludge composition and behavior due to other variations in the influent.
Fig. 3 e Fine bubble aeration actuation with PID-controlled DO during normal operation (setpoint ¼ 2 mg L¡1) (left). Aeration pattern for the disturbance experiments executed in the lab-scale MBRs comparing a reference aeration reactor vs. high aeration reactor (right).
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Prior to the experiment, the sludge from both MBRs was mixed and redistributed to avoid reactor-specific sludge behavior. The wastewater was buffered in a 1 m3 tank for t ¼ 24 h to t ¼ 48 h, while for t ¼ 48 h to t ¼ 96 h, the buffer tank was refilled with fresh wastewater. This allowed us to eliminate the impact of variations in wastewater quality as much as possible from all analysis except for the two final fouling rate measurements. This was, however, the best practically achievable situation.
2.3.
Activated sludge analysis
During the entire experiment, several sludge parameters as well as sludge filterability were monitored as described in Table 2.
2.3.1.
SMP analysis
Proteins and polysaccharides were analyzed from SMP according to the methods of DuBois et al. (1956) for polysaccharides and Lowry et al. (1951) for proteins. Details are described in De Temmerman et al. (2014).
2.3.2.
Particle size distribution
Sludge samples were measured for supramicron floc size (3e300 mm) utilizing optical image analysis (DIPA 2000, Donner Technologies, The Netherlands), maximum five minutes after a sample was collected. Details regarding the sample preparation can be found in De Temmerman et al. (2014). The results are further referred to as particle size distribution measurements and exhibited as number distributions. Regarding the shape of particles, the average Feret diameter was also determined based on these images. The average Feret diameter is the ratio of the object perimeter in a 2-dimensional plane, and p.
2.3.3.
Submicron particle concentration
Two considerations have to be made when measuring particles in the range, and below the range of visible light: Firstly, ensemble techniques e.g. laser diffraction and laser scattering, rely on signal decomposition to construct the PSD. € fer diffraction These techniques rely on the Mie and Fraunho theory in the range of visible light to decompose one input signal into a PSD. While sludge is naturally multimodally distributed, ensemble techniques can only construct unimodal distributions. Besides this drawback, these methods also have a relatively low resolution, produce unrealistic unimodal distributions with low confidence levels and they are not able to measure particle concentration. Nanoparticle tracking analysis, such as the Nanosight NS500 used in this work, is
able to both construct reliable PSD, and determine the particle concentration in the sample. Secondly, sample preparation is a necessary procedure for measuring submicron particles and inevitably requires a separation step of the sludge sample, such as filtration, gravitational settling or centrifugation. This separation step can influence the distribution and, to a lesser extent, the concentration of submicron particles in the bulk (Govoreanu et al., 2009). For this reason it is questionable if the particle size distribution of the prepared sample is representative for the real distribution, and therefore, in this work, results on submicron particles are only compared in terms of their concentrations. Following sample preparation as described in De Temmerman et al. (2014), submicron particle concentrations were measured in the 10e450 nm range (Nanosight NS500, Nanosight LTD, U.K.). This device's measurement principle is based on nanoparticle tracking analysis, which relates the rate of Brownian motion of particles to their size. The particles contained in the sample are visualized by virtue of the light they scatter when illuminated by a laser light. The light scattered by the particles is captured utilizing an optical digital camera, and specific software monitors the motion of each particle between subsequent frames. This rate of particle movement is associated with a sphere-equivalent hydrodynamic radius as calculated with the Stokes-Einstein equation whereby the size of submicron particles is calculated on a particle-by-particle basis. Particle tracking allows the construction of multimodal distributions based on individually tracked particles and determining particle concentrations based on counting single particles.
2.3.4.
Size exclusion chromatography
Organic matter fractions were analyzed utilizing liquid chromatography followed by an organic carbon detector (LC-OCD) (Doc-Labor, Germany) in order to distinguish between biopolymers, humic acids, low molecular weight (LMW) acids, and neutrals. Details regarding the LC-OCD instrument, analytical method, and data interpretation can be found in Huber et al. (2011).
2.3.5.
Membrane fouling rate
For each MBR, sludge was recirculated to an external 5 L vessel (HRT 1 h) containing two Kubota membrane plates with identical properties as those in the MBRs. The vessels were aerated with a coarse bubble aerator. The transmembrane pressure (TMP) (Endress & Hauser, Cerebar M PMC 41), temperature, and flux (mass balance) were monitored on-line. The irreversible fouling rate was calculated based on the improved flux step method according to Van der Marel et al. (2009), with a
Table 2 e Unit and time of analysis of activated sludge characteristics during the experiments in both reactors. t ¼ 0 represents the start of high shear. Measurement Total fouling rate Irreversible fouling rate SMP Particle size distribution Submicron particle concentration Size exclusion chromatography
Unit
Time of analysis (hour)
m1 s1 m1 s1 mg g1 TSS number % # particles ml1 ppb
24, 12, 4, 1, 6, 24, 48, 72, 96 24, 12, 4, 1, 6, 24, 48, 72, 96 5, 3.75, 0.75, 0.5, 1, 3, 4, 17, 18.65, 19.4, 23 1, 5, 20, 24 5, 3.75, 0.75, 0.18, 0.5, 1, 3, 4, 17.5, 18.65, 19.4, 23 5, 3.75, 0.75, 0.18, 0.5, 1, 3, 4, 17.5, 18.65, 19.4, 23
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step-duration set at 0.12 h for both the flux step (5e100 L m2 h1 with 5 L m2 h1 increments) and relax step (5 L m2 h1). In this improved flux step method, a non-zero value for the flux during relaxation was necessary to determine the irreversible fouling rate. The total fouling rate (increase in resistance over time) was calculated at a supercritical flux step of 50 L m2 h1. This method has distinct advantages when compared to other commonly employed flux step methods because fouling history is reduced and reversible and irreversible fouling rates can be estimated at each flux increment. After each flux step experiment, the membranes were mechanically cleaned with a high-pressure water nozzle to remove any cake- and possibly present gel layer.
3.
Results
3.1.
Membrane fouling rate
In the reference reactor, the total and irreversible fouling rates were found relatively stable and averaged 3.54 ± 0.21 108 m1 s1 (Fig. 4, top) and 3.01 ± 0.29 106 m1 s1 (Fig. 4, bottom), respectively. In contrast, the total fouling rate during shear disturbance increased with approximately 100% to a maximum value of 7.43 ± 2.01 108 m1 s1 (Fig. 4, top).
The total fouling rate subsequently decreased less than 6 h after finishing the fine bubble aeration disturbance, hereby returning to the values that were observed prior to the shear disturbance, however, still 52% higher compared to the default reactor. The irreversible fouling rate did not show an immediate change upon shear disturbance. As one would expect, this is a slower process, and the irreversible fouling rate steadily increased until the end of the experiment with approximately 35% to a maximum value of 4.15 ± 0.56 106 m1 s1 whereas it slightly decreased in the default reactor (Fig. 4, bottom). In between consecutive flux step tests, the removal of the gel layer did not result in a significant decrease of membrane resistance. The increased resistance through irreversible fouling could thus be mainly attributed to pore blocking. The recovery of the total fouling rate was not complete, which can partially be attributed to an incomplete recovery of the reversible sludge fouling propensity for the duration of the experiment, but also to the elevated irreversible fouling rates. One could envision that continuing the experiment might lead to a full recovery of the sludge fouling propensity, although it might prove difficult to distinguish it against the natural variation of the real wastewater influent composition. The use of an experimental design with a reference reactor and buffering of the influent as much as possible appears to be a necessary measure.
3.2.
SMP analysis
The observed SMP polysaccharide concentrations varied significantly in the shear reactor before, during, and after the disturbance in fine bubble aeration intensity. Natural variations occurred as indicated by the measurements in the reference reactor (Fig. 5). Upon imposing the shear disturbance, the SMP polysaccharide concentration remained fairly steady during the first 3e4 h, but started to exhibit an increase between 4 and 18 h of elevated shear up to 100% higher values compared to the reference reactor. This effect disappeared almost within 2 h after restoring the fine bubble aeration intensity. Results for SMP protein concentrations were similar (not shown).
Fig. 4 e Total fouling rate at 50 L m¡2 h¡1 (top) and irreversible fouling rate (bottom) for a reference vs. shear disturbance reactor. Vertical dashed lines indicate the start and finish of the aeration flow rate disturbance. Error bars indicate standard deviations (n ¼ 2 membranes per improved flux step test vessel).
Fig. 5 e Polysaccharide concentrations for SMP for a reference vs. shear disturbance reactor. Vertical dashed lines indicate the start and finish of the high shear event. Error bars indicate standard deviations (n ¼ 2 samples).
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3.3.
Particle size distribution
Five hours after the initiation of the disturbance, and during the increase of the total fouling rate, a significant shift in PSD was observed. Large flocs disappeared from the PSD in favor of smaller fragments (Fig. 6, top). This is in line with the deflocculation theories described in the literature: shear n et al., 2003), especially so for leads to floc rupture (Wile sludge that is not habituated to shocks. The PSD started to shift back to larger flocs within 20 h after initiation of the high shear event (2 h after ending the disturbance). Within 24 h (4 h after ending the shock), the distribution did not shift anymore and a new steady state distribution was reached, characterized by a peak at 24 mm (compared with 43 mm for the initial distribution at t ¼ 1 h), and in general, more small particles between 10 and 40 mm and less large particles between 40 and 300 mm. The PSD in the reference reactor did not change significantly during the experiment and the peak remained around 42 ± 2 mm (data not shown). Considering the particle shape quantities, more compact flocs were observed during the shear shock, reflected by a small increase in sphericity and compactness, and a large decrease of the average Feret diameter (Fig. 6, bottom).
3.4.
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Submicron particle concentration
According to Fig. 7, the submicron particle concentration in the reference reactor was around 6 106 particles per ml and remained below 8 106 particles per ml throughout the experiment, while in the shear reactor, the concentration increased rapidly to around 11 106 particles per ml (75% above reference) after 4 h of high shear. Remarkably, even before ending the high shear event, the concentrations fell back to approximately background values, indicating that these very small particles seem to take part in a reflocculation process already at high turbulence levels. Concentrations were similar for both reactors approximately 2e4 h after ending the disturbance event.
3.5.
Size exclusion chromatography
The specific characterization of SMP-related biopolymers (>10 kDa), humic acids and low molecular weight acids and neutrals (<2 kDa) is presented for the duration of the experiment (Fig. 8). Notwithstanding a lot of natural variability in the data, biopolymer and humic acids concentrations were consistently higher in the shear reactor during, and shortly after the high shear event. On the contrary, LMW acids in the shear reactor remained lower. There was no effect discernible for LMW neutrals.
4.
Discussion
Shear induced by elevated aeration intensity clearly influences the physicochemical and biological properties of MBR biomass in line with previous findings (Menniti et al., 2009). More specific, concentrations of SMP (4.1), particle size distributions (4.2), submicron particle concentrations (4.3), organic carbon fractions (4.4) were clearly affected by shear in our experiments, and this had an impact on membrane fouling (4.5).
Fig. 6 e Number-based PSD dynamics before, during and after a high shear event in the shear reactor (top). Average Feret diameter before, during and after a high shear event in the shear reactor (bottom). Error bars indicate standard deviation (n ¼ 3 separate samples).
Fig. 7 e Submicron particle concentration [10e450 nm] for a reference vs. shear reactor. Vertical dashed lines indicate the start and finish of the high shear event. Error bars indicate standard deviations (n ¼ 2 samples).
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Fig. 8 e Concentration of biopolymers, humic acids, LMW acids and LMW neutrals from LC-OCD analysis for a shear shock vs. reference reactor. Vertical dashed lines indicate the start and finish of the high shear event.
4.1.
SMP
In this study, we focused solely on SMP concentrations in the bulk liquid. While there is a clear relation between flocattached EPS and SMP, the dynamics of EPS are hard to examine because of the complicated and hard-to-standardize measurement involving a long and error-prone extraction procedure (De Temmerman et al., 2014). The SMP concentrations increased in the high aeration reactor but recovered towards the background values in the reference reactor within 4 h after ending the aeration event (Fig. 5). During and just after the shear event, SMP concentrations were significantly higher compared to the reference reactor. Shear-induced SMP-release to the bulk liquid can be attributed to floc breakage, release from bacteria and cell lysis. This outcome is in line with other short-term studies on the impact of shear imposed by e.g. recirculation (Park et al., 2005), and aeration (Meng et al., 2008; Menniti et al., 2009), where the authors found that high shear and aeration intensities led to the release of floc-bound EPS. In contrast to the submicron particle concentrations, the SMP concentrations remained high throughout the shear event indicating that the released SMP were not immediately and fully reincorporated into the flocs. It can be hypothesized that these higher SMP concentrations in the bulk liquid will attach to the membrane, resulting in more irreversible fouling.
4.2.
Particle size distribution
High aeration had an immediate impact on the supra micron particle size distribution. Within 5 h, the particle size
distribution peak decreased from approx. 43 mme18 mm (Fig. 6). These observations confirm the findings for coarse bubble aeration of Meng et al. (2008), who subjected sludge in a hollow fiber SMBR to a range of airflow rates, and also found that aeration increased sludge breakage. In this study, a 28% larger amount of flocs smaller than 50 mm were observed in the high airflow MBR (8 m3 m2 of membrane h1), compared to the low airflow MBR (1.5 m3 m2 of membrane h1). In our study, the difference was 16%, but this difference depends on the initial distribution. Although the results show a clear aeration-induced deflocculation effect, the particle size distribution measurements also indicate that this effect is, at least partially, reversible. A new steady state PSD was attained 4 h after the aeration was put back to default. This state clearly marks an improved flocculation state, even though the distribution peak at 24 mm is still very much shifted towards the smaller particle ranges. It shows that the smallest flocs aggregated in a process of orthokinetic flocculation (i.e. shear-driven) to result in a new flocculation state (basically a balance between aggregation2 and breakup). This final state was also characterized by more compactflocs given the decreased average Feret diameter, and more uniform flocs through shear, given the decreased standard deviation on this average Feret diameter. The shifted distribution with more compact flocs implies the build-up of a less porous and thus less permeable cake layer compared to the original sludge. This is reflected in the continued higher total fouling rates in the shear reactor after reducing the aeration flow (Fig. 4). The observed deflocculation - reflocculation behavior, including the hysteresis effect,
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was also further investigated by repeating the detailed shear experiments of Mikkelsen and Keiding (1999), and supports the clear shift in PSD facing turbulent shear, and a clear shift back, although not complete, when turbulent shear was lowered (results not shown).
4.3.
Submicron particle concentration
Initially, the submicron particle concentration strongly increased in response to the high aeration event (Fig. 7). This behavior has not only been hypothesized (e.g. Braak et al., 2011), but also measured: Ivanovic and Leiknes (2008) and Meng et al. (2008) compared submicron particle dynamics for different aeration rates. However, their applied measuring ensemble techniques (laser diffraction and laser scattering, respectively) are not suitable for particles in the range, and below the range, of visible light as mentioned in the Materials and Methods section. Even before the end of the aeration event, concentrations decreased to values around those of the reference reactor. This implies that, notwithstanding the higher shear, the submicron particles are either taking part in a reflocculation process, and/or attach to the membrane and cake layer causing more reversible and irreversible fouling. It is hypothesized that with the initiation of shear significant amounts of colloids and submicron particles are released, in line with the observed shift in particle size distribution towards a large number of smaller particles. This means there is an increased chance of submicron particle collisions giving rise to perikinetic (driven by Brownian motion) flocculation into bigger particles. At the same time, submicron particles likely also attach to the membrane matrix, blocking pores and giving rise to the observed irreversible fouling rate increase.
4.4.
Size exclusion chromatography
Organic carbon fractions are often analyzed in surface and drinking water, but not so much in activated sludge and wastewater. Still, they could reveal interesting information regarding those fractions that have high pore blocking potential, i.e. <0.5 mm. The measured fractions showed quite some natural variation hindering a clear analysis. Nevertheless, humic acid and biopolymer concentrations were higher throughout the high shear event (Fig. 8), and coincidentally, biopolymers have been shown to correlate well with increased membrane fouling (Kimura et al., 2014). It remains unclear whether other fractions, i.e. LMW neutrals and acids can be correlated to membrane fouling, as they do not seem to respond very much to the disturbance events. Based on current research, we do not recommend including LMW neutrals and acids in flocculation analyses in relation to shear experiments.
4.5.
Membrane fouling rates
The total fouling rate increased instantly with increasing aeration, and decreased within 6 h after fine bubble aeration but did not return back to default. This indicates a relatively rapid but incomplete recovery of sludge filterability. The results appear to confirm the hypothesis of Braak et al. (2011),
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that a shift in particle size distribution to smaller flocs reduces the cake permeability, which can only be restored through a distribution shift back towards larger particles. The incomplete recovery of total fouling combined with the incomplete recovery of PSD, suggests the importance of PSD dynamics. The irreversible fouling rate only really increases 6 h after ending high aeration, and the increase was permanent. This is mainly related to the applied measurement technique whereby irreversible fouling is accumulated over time. It is clear that increased aeration rates negatively impact irreversible fouling through shear, but an accurate quantification in short term experiments remains somewhat difficult as it manifests itself on a longer term. The increase and decrease of both supra- and submicron particles coincided very clearly with to a respectively lower or higher permeability of the cake layer on the membrane. The increasing irreversible fouling rate could be attributed mainly to pore blocking. This is thought to be a slower process, as part of the submicron particles will have an effect on cake layer resistance, but are not necessarily enhancing pore blocking as cake acts as a secondary membrane. In this way, only after a significant amount of flux steps, the effect of submicron particles on the irreversible fouling rate can be observed.
4.6. Considerations on spatial and temporal distribution effects While the impact of fine bubble aeration on sludge characteristics (Figs. 5e8) and membrane fouling is significant (Fig. 4), its impact has to be evaluated in the framework of spatial-temporally distributed shear in MBRs as illustrated in Fig. 1. Aeration is, even at steady-state DO settings, temporally and spatially distributed as a consequence of inflow dynamics and aerator design and operation (Fulton et al., 2011). First, there are different shear originators in an MBR, e.g. aeration, mixers and recirculation loops (Braak et al., 2011; Mikkelsen and Keiding, 1999; Ivanovic and Leiknes, 2008). The exact contribution of these shear originators to the overall system shear depends on the dimension of reactors, pumps, valves and the membrane design (Chan et al., 2011). Within one system, recirculation flows and membrane aeration intensity remain fairly constant, as they are mostly fixed operational values according to design protocols. These settings effectively keep the shear originating from pumps, coarse bubble aeration, mixers, jet streams, tubes and valves constant. That leaves only the fine bubble aeration as factor that strongly determines the overall shear stress variations in the system (Abbassi et al., 2000). Both the design and operation of reactors and aerators influence the spatial shear distribution, mostly by the positioning and design of bubble aerators. The spatial variation in impeller shear as presented in Fig. 1 clearly indicates that floc size distribution is also spatially distributed. Along the same lines as for impellers, aeration creates zones where the aeration intensity is high and floc breakup is promoted, while floc aggregation promoting zones can occur in those regions outside of the aerated zone. However, the latter can be greatly reduced, and even non-existent, if aeration intensities are increased. Maintaining the continuous presence of an
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effective reflocculation zone can be visualized by CFD as in Gresch et al. (2011). Next to the spatial distribution of the aerators, timedependent changes in MLSS concentrations, dynamic inflow composition but also badly designed DO controllers and illmaintained sensors all contribute to dynamics in biological aeration intensity, thereby varying the aeration pattern. As Brannock et al. (2010) emphasized, a well-mixed reactor with homogeneous fine-bubble aeration, clean and reliable sensors and good control settings is necessary to preserve homogeneity in particle size distribution throughout the aerobic reactor, and for the efficiency of nutrient removal in the aeration zone. A drawback of rigorous, homogeneous mixing could be the reduction or even absence of low turbulence zones that are necessary for reflocculation. It is hypothesized that the complete lack of reflocculation zones in the studied lab-scale set-up during high aeration maximized the deflocculation potential. While several authors have based sludge filterability on mean floc diameters (e.g. Wu and Huang, 2009), our study indicates that mean floc diameters do not reveal any conclusive relation with membrane fouling outside the scope of the specifically researched system. The influence of fine bubble aeration on activated sludge could be decreased through prevention and remediation. Prevention implies avoiding sharp stress peaks in the bioreactor through buffering the influent, by optimizing both the aeration and reactor design to preserve reflocculation zones, and e.g. by smoother aerator (actuator) control. To cope with spatial-temporal dynamics in aeration intensity, while maintaining the continuous presence of an effective reflocculation zone, it is advised to optimize the aerator tank design through CFD coupled with flocculation models (Sobremisana et al., 2011), to take the distributed flocculation parameters into account. Remediation is mainly achieved by counteracting the deflocculation increase induced by aeration dynamics, e.g. flocculant dosing, or by ad hoc operational strategies based on practice or combined CFD-flocculation model studies.
5.
Conclusions
In this study, the impact of elevated fine bubble aeration intensity on both sludge quality and sludge filterability was monitored in a lab-scale MBR setup fed with real communal wastewater. The particle size distribution of the activated sludge shifted to lower size classes during high aeration and shifted back to a new steady state after setting the aeration intensity back to default. The new steady state indicated that the reflocculation was quick but incomplete. Sludge PSDs display measurable variability over time and between reactors, so we recommend monitoring the (often subtle, but significant) distribution shifts rather than statistics such as averages as this leads to important information loss. Concentrations of bulk liquid submicron particles, SMP and organic carbon fractions shifted upon altering the aeration settings and the observed changes were
confronted with the current scientific understanding of membrane fouling and filtration. The dynamics in floc characteristics were reflected in the membrane fouling rates. During high aeration intensity, especially the total membrane fouling rate measurements increased significantly. The rate decreased again after setting the aeration back to default, but remained higher than the reference situation. The irreversible fouling rate was also negatively affected by the shear event, with a continued increase in measured fouling rates after the shock event. Sustainable solutions to prevent high shear through fine bubble aeration should be further investigated, such as influent buffering, preservation of the reflocculation potential (prevention, during design phase) and flocculant dosing (remediation).
Acknowledgments This work was performed in the TTIW cooperation framework of Wetsus, Centre of Excellence for Sustainable Water Technology (www.wetsus.nl). Wetsus is funded by the Dutch Ministry of Economic Affairs, the European Union ^ n, the Regional Development Fund, the Province of Frysla City of Leeuwarden and the EZ/Kompas programme of the Samenwerkingsverband Noord-Nederland. The authors would like to thank the participants of the research theme “Membrane Processes for Wastewater Treatment and Reuse” for the fruitful discussions and their financial support.
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