Fouling Issues in Membrane Bioreactors (MBRs) for Wastewater Treatment: Major Mechanisms, Prevention and Control Strategies
Abstract
:1. Introduction
2. Major Mechanisms
2.1. The Driving Force
2.2. Factors Opposing the Driving Force
2.2.1. Concentration Polarization (CP)
- (a)
- the concentration of rejected solute near the membrane surface,
- (b)
- the precipitation of sparingly soluble macromolecular polymeric and inorganic (gel layer formation and scaling, respectively) at the membrane surface and
- (c)
- the accumulation of retained solids on the membrane (cake layer formation).
2.2.2. Fouling
- -
- inorganic fouling which refers to the deposit of inorganic material like salts, clay and metal oxides,
- -
- organic fouling which includes all kind of deposit of organic material like grease, oil, surfactants, proteins, polysaccharides, humic substances and other organic biopolymers and
- -
- biofouling which designates the formation of biofilms by compounds and microorganisms attached and growing at the membrane surface [3].
2.2.3. Clogging
- The solids agglomeration rate in the channels relates to the rate at which water is drained from the sludge. This in turn is dependent on both the flux and the residence time of the sludge in the membrane channels, since the extent of dewatering increases at longer residence times.
- The residence time in the membrane channel itself is directly related to membrane aeration, with respect to both the distribution of the air bubbles throughout the channels and the overall aeration rate.
- Agglomeration must also depend both on the concentration and the characteristics of the particles, since particles which, for whatever reason, more readily adhere to the membrane and/or each other can be expected to agglomerate faster. These may be presumed to be partly related to feedwater physicochemical parameters, since these are known to impact on sludge quality and the physical nature of the inert solids specifically.
2.3. Membrane Fouling in Membrane Bioreactors (MBRs)
2.3.1. Fouling Mechanisms in MBRs
2.3.1.1. Stage 1: Conditioning Fouling
2.3.1.2. Stage 2: Slow/Steady Fouling
2.3.1.3. Stage 3: TMP Jump
- (i)
- Inhomogeneous fouling (area loss) model: This model was proposed to explain the observed TMP profiles in nominally sub-critical filtration of upflow anaerobic sludge [111]. The TMP jump appeared to coincide with a measured loss of local permeability at different positions along the membrane, due to slow fouling by EPS. It was argued that the flux redistribution (to maintain the constant average flux) resulted in regions of sub-critical flux and consequently in rapid fouling and TMP rise.
- (ii)
- Inhomogeneous fouling (pore loss) model: Similar TMP transients have been observed for the crossflow MF of a model biopolymer (alginate) [112]. These trends revealed the TMP transient to occur with relatively simple feeds. The data obtained have been explained by a model that involves flux redistribution among open pores. Local pore velocities eventually exceed the critical flux of alginate aggregates that rapidly block the pores. This idea was also the base of the model proposed by Ognier et al. [113]. While the “area loss” model considers macroscopic redistribution of flux, the “pore loss” model focuses on microscopic scale. In MBR systems, it is expected that both mechanisms occur simultaneously.
- (iii)
- Critical suction pressure model: The two-stage pattern of a gradual TMP rise followed by a more rapid increase has been observed from studies conducted based on dead-end filtration of a fine colloid by an immersed HF. At a critical suction pressure it is suggested coagulation or collapse occurs at the base of the cake, based on membrane autopsy evaluations supplemented with modeling [114]. A very thin dense layer close to the membrane surface, as observed in the study, would account for the rapid increase in resistance leading to the TMP jump. Although this work was based on dead-end rather than crossflow operation, the mechanism could apply to any membrane system where fouling continues until the critical suction pressure is reached, where-upon the depositing compound(s) coalesce or collapse to produce a more impermeable fouling layer.
- (iv)
- Percolation theory: According to percolation theory, the porosity of the fouling layer gradually decreases due to the continuous filtration and material deposition within the deposit layer. At a critical condition, the fouling cake loses connectivity and resistance, resulting in a rapid increase in TMP. This model has been proposed for MBRs [115], but indicates a very rapid change (within minutes), which is not always observed in practice. However, the combination of percolation theory with the inhomogeneous fouling (area loss) model could satisfy the more typically gradual inclines observed for TMP transients. Similarly, fractal theory was successfully applied to describe cake microstructure and properties and to explain the cake compression observed during MBR operation.
- (v)
- Inhomogeneous fiber bundle model: Another manifestation of the TMP transient has been observed for a model fiber bundle where the flow from individual fibers was monitored [116]. The bundle was operated under suction at constant permeate flow, giving constant average flux and the flow was initially evenly distributed among the fibers. However, over the time the flows became less evenly distributed so that the standard deviation of the fluxes of individual fibers started to increase from the initial range of 0.1–0.15 up to 0.4. Consequently, the TMP rose to maintain the average flux across the fiber bundle, mirroring the increase in the standard deviation of the fluxes. At some point, both TMP and standard deviation rose rapidly. This is believed to be due to flow maldistribution within the bundle leading to local pore and flow channel occlusion. It was possible to obtain steadier TMP and standard deviation profiles when the flow regime around the fibers was more rigorously controlled by applying higher liquid and/or airflows.
2.3.2. Biomass Foulants
- Practically, based on permeability recovery,
- Mechanistically, based on fouling mechanism, and
- By material type, based on chemical or physical nature or on origin.
Practical | Mechanism | Foulant material type |
---|---|---|
Reversible/temporary:
Irreversible/permanent:
Irrecoverable */absolute:
| Pore blocking/filtration models (
Figure 3):
| Size:
Surface charge/chemistry:
Chemical type:
Origin:
|
2.3.2.1. Extracellular Polymeric Substances (EPS)
2.3.2.2. Selection and Evaluation of EPS Extraction Methods
2.3.2.3. EPS Quantification and Characterization
2.3.2.4. Soluble Microbial Products (SMP)
2.3.2.5. Organic Fouling by EPS
3. Prevention and Control Strategies
- 1.
- Applying appropriate pretreatment to the feedwater,
- 2.
- Employing appropriate physical or chemical cleaning protocols,
- 3.
- Reducing the flux,
- 4.
- Increasing the aeration,
- 5.
- Chemically or biochemically modifying the mixed liquor and
- 6.
- Membrane surface modification.
3.1. Feed Pretreatment
3.1.1. Screening
3.1.2. Other Feed Pretreatment Methods
3.2. Physical and Chemical Cleaning Protocols
Definition (with Preferred Term) | Fouling Rate (mbar/min) | Time Interval | Cleaning Method Applied |
---|---|---|---|
Cake, reversible or removable fouling | 0.1–1 | 10 min | Physical cleaning (e.g., relaxation, backflush) |
Residual fouling | 0.01–0.1 | 1–2 weeks | Maintenance cleaning (e.g., chemically enhanced backflush) |
Irreversible fouling | 0.001–0.01 | 6–12 months | Chemical cleaning |
Permanent, long-term or irrecoverable fouling | 0.0001–0.001 | Several years | Cannot be removed |
3.2.1. Physical Cleaning
3.2.2. Chemical Cleaning
- Maintenance cleaning at moderate chemical concentrations on a twice weekly to monthly basis, designed to remove residual fouling and
- Intensive (or recovery) chemical cleaning (once or twice a year), used to remove the so-called irreversible fouling.
3.2.3. Feedback Control Systems
3.2.4. Chemical/Biochemical Mixed Liquor Modification
3.2.4.1. Coagulant Addition
3.2.4.2. Adsorbent Agents
3.2.4.3. Proprietary and Other Reagents
3.2.4.4. Quorum Sensing (QS)
3.2.5. Application of Ultrasound, Electric Field and Ozone
3.3. Optimal Operation of MBR Process
3.3.1. Flux Reduction
- Sustainable permeability operation: In this instance, the conditions are chosen so as to maintain stable operation (little or negligible increase in TMP at constant flux) over an extended period of time (i.e., several weeks or months) with only moderate remedial measures (namely relaxation), if any. Most immersed FS and all sidestream systems have traditionally operated under these conditions, with sMBRs operating continuously (i.e., without relaxation) between chemical cleans.
- Intermittent operation: In this mode of operation, the operational flux is above that which can be sustained by the filtration cycle operating conditions and, as a result, intermittent remedial measures are employed. These comprise relaxation supplemented with backflushing and usually some kind of maintenance chemical cleaning procedure. All immersed HF systems operate in this manner.
3.3.2. Aeration Increase
3.4. Membrane Surface Modification
3.4.1. Physical Coating/Adsorption on the Membrane Surface
3.4.1.1. Coating via Filtration
3.4.1.2. Coating via Adsorption
3.4.1.3. Coating via Casting
3.4.2. Development of Low-Fouling Polymer Membranes via Photoinitiated Grafting
3.4.3. Miscellaneous Grafting Methods on the Membrane Surface
3.4.4. Patterned Membranes
3.4.5. Plasma Treatment of Polymer Membranes
3.4.6. Chemical Reactions on the Membrane Surface for Fouling Reduction
3.4.7. Surface Modification with Nanoparticles
3.4.7.1. Membrane Modification with Deposited Nanoparticles
3.4.7.2. Phase Inversion Method
4. Conclusions
- New aeration systems
- New cleaning/fouling mitigation methods
- Emerging technologies (forward osmosis MBRs)Finally, the basic question “What should be the focus of research moving forward?”
- Will further research in the mechanisms of fouling shed some light in the efficient operation of MBRs?
- Or should research move to more macroscopic approaches such as mathematical modelling based on empirical relationships?
Table of Symbols
AA | acrylic acid | |
AAG | 2-acrylamidoglycolic acid | |
AAm | acrylamide | |
ACH | aluminium chlorohydrate | |
AFM | atomic force spectroscopy | |
AMPS | 2-acrylamido-methylpropane sulfonic acid | |
anMBR | anaerobic membrane bioreactor | |
aniMBR | anaerobic immersed membrane bioreactor | |
AS | activated sludge | |
ASP | activated sludge process | |
BAC | biologically activated carbon | |
bEPS | bound extracellular polymeric substances | |
BFM | Berlin filtration method | |
BSA | bovine serum albumin | |
CA | concentration of component A | mol·m−3 |
CA | cellulose acetate | |
CASP | conventional activated sludge plant | |
CER | cation exchange resin | |
CFV | cross flow velocity | m·s−1 |
Cg | gel layer concentration | g·cm−3 |
CIA | cleaning in air | |
Cim1 | concentration of component i inside membrane wall on feed side | mol·m−3 |
Cim2 | concentration of component i inside membrane wall on permeate side | mol·m−3 |
CIP | cleaning in place | |
CLSM | confocal laser scanning microscopy | |
COD | chemical oxygen demand | mg·L−1 |
Cp | permeate concentration | g·cm−3 |
CP | concentration polarization | |
Cr | retentate concentration | g·cm−3 |
CS | chitosan | |
CST | capillary suction time | s |
D | inside diameter of the pipe | ft |
Di | diffusivity of component i | m2·s−1 |
DFCm | Delft filtration characterization method | |
DO | dissolved oxygen | |
DOC | dissolved organic carbon | |
DTAB | dodecyltrimethyl ammonium bromide | |
DW | dry weight | g |
EDA | ethylene diamine | |
EDTA | ethylenediaminetetraacetic acid | |
EEM | excitation-emission matrix | |
eEPS | extracted extracellular polymeric substances | |
EGSB | expanded granular sludge bed | |
EPS | extracellular polymeric substances | |
EPSc | carbohydrate fraction of EPS | |
EPSp | protein fraction of EPS | |
ESEM | environmental scanning electron microscopy | |
F/M | food to microorganisms | |
FISH | fluorescence in situ hybridization | |
FOG | fats, oil and grease | |
FS | flat sheet | |
FTIR | Fourier transform infrared spectroscopy | |
GAMA | d-gluconamidoethyl methacrylate | |
gDMAEM | quaternized 2 (dimethylamino) ethyl methacrylate | |
GFC | gel filtration chromatography | |
h | height of the channel | m |
HA | humic acid | |
HEMA | 2-hydroxyethyl methacrylate | |
HF | hollow fiber | |
HFRB | hair and fiber reinforced biomass | |
HPSEC | high-pressure size exclusion chromatography | |
iMBR | immersed membrane bioreactor | |
IR | infrared spectroscopy | |
J | membrane flux | m3·m−2·h−1 |
Ji | flux of component i | mol·m−2·s−1 |
K | membrane permeability | L·h−1·bar−1·m−2 |
k | mass transfer coefficient | m3·m−2·s−1 |
L | length of the flow channel | m |
MBR | membrane bioreactor | |
MC | methylcellulose | |
MF | microfiltration | |
MLSS | mixed liquor suspended solids | |
MPDSAH | [(methacryloylamino)propyl]-dimethyl (3-sulfopropyl) ammonium hydroxide | |
MW | molecular weight | |
NF | nanofiltration | |
NMR | nuclear magnetic resonance | |
NOM | natural organic matter | |
NVC | N-vinyl-caprolactam | |
NVF | N-vinyl-formamide | |
NVP | N-vinyl-2-pyrrolidone | |
OC | organic carbon | |
PA | polyamide | |
PAC | powdered activated carbon | |
PAN | polyacrylonitrile | |
PCR-DGGE | polymerase chain reaction denaturing gradient gel electrophoresis | |
PDA | 2,4-phenylenediamine | |
PE | polyethylene | |
PEGDA | poly(ethylene glycol) diacrylate | |
PEGMA | poly(ethylene glycol) methacrylate | |
PEI | polyethylenimine | |
PEO | polyethylene oxide | |
PI | polyimide | |
PP | polypropylene | |
PS | polysulfone | |
PSS | poly(sodium 4-styrene sulfonated) | |
PVA | polyvinyl alcohol | |
PVP | polyvinylpyrrolidone | |
PVS | polyvinyl sulfate-potassium salt | |
QS | quorum sensing | |
RAS | return activated sludge | |
Rcol | resistance attributed to colloidal matter | m−1 |
Re | Reynolds number | |
Rm | resistance to flow through the membrane | psi·s·cm2·cm−3 |
Rg | resistance to flow through the gel | psi·s·cm2·cm−3 |
RI | refractive index | |
RO | reverse osmosis | |
Rsol | resistance attributed to soluble matter | m−1 |
SBR | sequencing batch reactor | |
SDS | sodium dodecyl sulfate | |
sEPS | soluble EPS | |
SLS | static light scattering | |
sMBR | submerged membrane bioreactor | |
SMP | soluble microbial product | |
SMPc | carbohydrate fraction of soluble microbial product | |
SMPp | protein fraction of soluble microbial product | |
SPMA | 3-sulfopropyl methacrylate | |
SRF | specific resistance to filtration | |
SRT | sludge retention time | d |
SS | suspended solids | |
SUVA | spectrophotometer using ultraviolet | |
tcrit | critical time | s |
TFC | thin film composite | |
TIPS | thermally induced phase separation | |
tm | thickness of the membrane | m |
TMC | trimesoyl chloride | |
TMP | transmembrane pressure | bar |
TOC | total organic carbon | |
u | fluid velocity | ft·s−1 |
ub | linear velocity through the channel | m·s−1 |
UF | ultrafiltration | |
UMFI | unified membrane fouling index | |
UV | ultraviolet | |
VFM | VITO fouling measurement | |
VSS | volatile suspended solids | |
WS2 | tungsten disulfide | |
XPS | X-ray photoelectron spectroscopy | |
ΔP or ΔPm | pressure difference | bar |
η | viscosity | Pa·s |
μ | fluid viscosity | lb·ft−1·s−1 |
ν | fluid kinematic viscosity | ft2·s−1 |
ρ | fluid density | lb·ft−3 |
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Gkotsis, P.K.; Banti, D.C.; Peleka, E.N.; Zouboulis, A.I.; Samaras, P.E. Fouling Issues in Membrane Bioreactors (MBRs) for Wastewater Treatment: Major Mechanisms, Prevention and Control Strategies. Processes 2014, 2, 795-866. https://doi.org/10.3390/pr2040795
Gkotsis PK, Banti DC, Peleka EN, Zouboulis AI, Samaras PE. Fouling Issues in Membrane Bioreactors (MBRs) for Wastewater Treatment: Major Mechanisms, Prevention and Control Strategies. Processes. 2014; 2(4):795-866. https://doi.org/10.3390/pr2040795
Chicago/Turabian StyleGkotsis, Petros K., Dimitra Ch. Banti, Efrosini N. Peleka, Anastasios I. Zouboulis, and Petros E. Samaras. 2014. "Fouling Issues in Membrane Bioreactors (MBRs) for Wastewater Treatment: Major Mechanisms, Prevention and Control Strategies" Processes 2, no. 4: 795-866. https://doi.org/10.3390/pr2040795
APA StyleGkotsis, P. K., Banti, D. C., Peleka, E. N., Zouboulis, A. I., & Samaras, P. E. (2014). Fouling Issues in Membrane Bioreactors (MBRs) for Wastewater Treatment: Major Mechanisms, Prevention and Control Strategies. Processes, 2(4), 795-866. https://doi.org/10.3390/pr2040795