The History of Membranes in Water Treatment Processes
The utilization of membranes to separate liquids with diﬀerent concentra-tions was reported for the first time in 1748 by Nollet, a French physicist. He was the first to report the process in which semi-permeable membranes are implemented to disassociate liquids with diﬀerent concentrations of contam-inants until osmotic equilibrium is reached (Atasi et al, 2006).
The use of membranes started to be seen as a new technology in the second part of XIX century and was especially influenced by Fick’s law of diﬀusion, Van’t Hoﬀ’s osmotic pressure equation and Graham’s work in gas separation (Judd and Judd, 2011).
During this period, some experiments demonstrated that when energy (in the form of pressure or a vacuum) was applied to the liquid solution with contaminants, the liquid could still move though the membrane but left contaminants behind and discharged clean water. This simple and powerful idea is the nest of MBR processes where water is forced to pass through a filter with narrow pore sizes capable of removing even tiny particles such as salts, viruses, pesticides and most organic compounds (Atasi et al, 2006). The first documented “ultrafiltration” (UF) experiment was carried out by Schimidt in 1856, where he used bovine heart membranes (the pore dimension being 1 −50 nm) to separate soluble Acacia. This concept has been the core of many studies that resulted in a first synthetic UF membrane prepared by Bechhold in 1907, which he named “ultrafilter”.
Inspired by this new technology, Zsigmondy at the University of Goettin-gen started to think about commercially producing a membrane, and thus did this with Bachmman between 1918 and 1922. They developed a method to produce porous collodion membrane in an industrial scale. Sartorius Werke GmbH was the first membrane supplier established in Goettingen in 1925 (Judd and Judd, 2011).
One of the first applications with membranes was in the treatment of drinking water, followed by wastewater treatment (Atasi et al, 2006). This combination of a physical separation and the biological treatment has proven successful in the field of wastewater treatment, resulting in a process with a higher concentration of activated sludge retained in the reactor, higher sludge retention time (SRT) and lower F/M ratio (Acharya et al, 2006; Lu et al, 2001).
Throughout the years many combinations of membrane types and appli-cations have been designed, with each membrane property diﬀering accord-ing to the process. This will be seen in more details in Section 220.127.116.11 where the pore size refers to the membrane properties, for example: the Ultrafiltra-tion removes viruses and is useful for large molecule recovery making water recycling in industry more economic; the Microfiltration removes protozoan parasites and decreases turbidity and it is the core of membrane bioreactor treatment plants for eﬄuents; the Nanofiltration is applied to surface water removes, color and large ions, gives a higher flux than reverse osmosis, adds value or recovers value from wastes; and the Reverse Osmoses is used for portable use and industrial reuse removal of small ions (Howell, 2004). A summary can be seen in Figure 1.1.
Definitions and Descriptions
The term ‘membrane bioreactor’ (MBR) has been applied to all water and wastewater treatment processes integrating a perm−selective membrane with a biological process. In Figure 1.2 the generic submerged membrane bioreac-tor (sMBR) processes scheme is represented .
Figure 1.2: Generic application of submerged MBR representation (figure edited from Pimentel et al (2015a)).
Normally, an MBR is integrated with micro or ultrafiltration membrane technology (with pore sizes ranging from 0.05 to 0.4 µm), resulting in complete physical retention of bacterial flocks, as aforementioned, and virtually all suspended solids within the bioreactor.
The Membrane Classification
Membrane materials are selected based on the kind of process and appli-cation. The most important characteristics in the membrane selection are the membrane pore size, the applied pressure, the Molecular Weight Cutoﬀ (MWCO) and some material characteristics such as hydrophobicity, process temperature and pH, which helps in this selection. Nowadays, membranes can be constituted by three main types of materials: (i) polymeric, the most implemented in industrial MBR processes; (ii) ceramic, with the largest range of utilization and (iii) metallic, which is not used for MBR processes.
The desired eﬄuent quality and removal mechanisms of pollutants may be chosen by selecting the class of membrane. An useful table (Table 1.1) has been proposed by Atasi et al (2006) and summarize these properties. To remove impurities by size exclusion, Microfiltration (MF) and Ultrafiltration (UF) are normally used. If the process requires a removal by diﬀusion and charges (electrostatic) exclusion as well as size exclusion, the most used are the Nanofiltration (NF) and Reverse osmosis (RO) filters.
Followed by the material properties, pore size and MWCO, the geometric shape of the membrane has a great impact in the filtration eﬃciency and in the choice for its application. The following items proposed by Judd and Judd (2011) may be used as a guide for selecting the most reasonable filter for a desired application.
1. pleated filter cartridge (FC) – extremely poor turbulence promotion, no possibility of backwash and applicable in dead-end membrane filtration and used in processes with low total suspended solid concentration;
2. plate-and-frame/flat sheet (FS) – fair turbulence promotion, no possibility of backwash and applicable in electrodialysis, ultrafiltration and reverse osmosis;
3. spiral-wound (SW) – poor turbulence promotion, no possibility of back-wash and applicable in reverse osmosis/nanofiltration and ultrafiltration and reverse;
4. (multi)tubular (MT) – extremely good turbulence promotion, no pos-sibility of backwash and applicable in cross-flow membrane filtration/ ultrafiltration and nanofiltration, and used in process with high total suspended solid concentrations;
5. capillary tube (CT) – fair turbulence promotion, possibility of backwash and applicable in ultrafiltration;
6. hollow fiber (HF) – extremely poor to fair turbulence promotion, pos-sibility of backwash and applicable in microfiltration/ultrafiltration and reverse osmosis;
Membrane Process Configurations
Judd and Judd (2011) stress that the process configuration needs to be de-signed considering the application, the type and the classification of the membrane. The membrane should be configured so as to have a:
• high membrane area to module-bulk-volume ratio,
• high degree of turbulence for mass transfer promotion on the feed side,
• low energy expenditure per unit of product water volume,
• low cost per unit membrane area,
• design that facilitates cleaning,
• design that permits modularization.
There are two main membrane process configurations: the submerged membrane and side-stream membrane (Figure 1.3).
• The submerged membrane bioreactor (sMBR) is composed by a filter submerged inside a tank (the bioreactor). This tank is equipped with air blowers in the bottom part which have the property to air shear the membrane surface preventing it from depositing solid particles, named fouling (this will be explained in more detail in Section 1.4). This con-figuration is increasingly used for domestic wastewater treatment, and there is a growing need to provide valuable modeling tools for sMBR design and operation (Naessens et al, 2012a). In its simplest form, a submerged membrane bioreactor system can combine the functions of an activated sludge aeration system, secondary clarifiers, and tertiary filtrations in a single tank (Atasi et al, 2006). The submerged membrane units features rather low trans-membrane pressure (TMP), requiring less energy consumption and is more cost eﬀective (Wintgens et al, 2003). The aeration provides the main operating cost component, as it is required for both mixing and oxygen transfer. On the other hand, the lower flow under which the submerged system operates implies a higher membrane area and thus a higher associated initial capital cost (Gander et al, 2000). Normally, hollow-fiber and flat-sheet membranes are used in this con-figuration.
Table of contents :
1 MBR Fundamentals
1.1 The History of Membranes inWater Treatment Processes
1.1.1 Definitions and Descriptions
18.104.22.168 The Membrane Classification
1.1.2 Membrane Process Configurations
1.2 MBR Market
1.3 Conventional Activated Sludge vs. sMBR
1.3.1 sMBR Advantages
1.3.2 sMBR Drawbacks
1.4 Fouling Formation
1.4.1 Backwash, Relaxation and Chemical Cleaning
2 Modeling sMBR
2.1 MathematicalModeling of Biological Systems
2.2 MathematicalModel Types
2.2.1 Black-box Models
2.2.2 White-box Models
2.2.3 Gray-box Models
2.3 Motivation for Modeling sMBRs
2.4 sMBR Model Types
2.4.1 sMBR Biological Modeling
2.4.2 sMBR Physical Modeling
2.4.3 sMBR Integrated Modeling
2.5 Proposed Simple Integrated sMBR Model
3 Analysis, Parameter Identification & Simulation
3.2 Full Model Analysis
3.2.1 Fast and Slow Dynamics
22.214.171.124 Singular Perturbations
126.96.36.199 Three-time-scale Singular Perturbation
3.2.2 Asymptotic Analysis
3.2.3 Study of the Linearized Dynamics – Short-term
188.8.131.52 SL2H applied to sMBR Model
184.108.40.206 Lie Brackets Applied to sMBR Model
3.3 Biological Aspect Simulations and Analysis
3.3.1 Global Stability Study
3.4 Physical Aspect Simulation and Analysis
3.5 Model Simulation and Parameter Identification
4 Model Validation with Experimental Data 96
4.1 Recir culating Aquaculture System Fitted with sMBR Pilot Plant Design
4.1.1 Process Description
4.1.2 Experimental Setup
4.1.3 Data Logging and Instrumentation
4.1.4 Recirculating Aquaculture System and sMBR
4.1.5 Critical Flux
4.1.6 Air Cross-Flow Study
4.1.7 Model Identification and Cross-validation
220.127.116.11 Ultra-fast Dynamic Identification
18.104.22.168 Fast Dynamic Identification
22.214.171.124 Slow Dynamic Identification
4.2 Wastewater Treatment Pilot Plant1
4.2.1 Pilot Plant Description
4.2.2 Recorded Data
4.2.3 TMP Long-term Exponential-like Behavior
4.2.4 Permeate and TMP Amplitude
4.2.6 Temperature Influence
4.2.7 Air-blowers Temperature
4.2.8 Model Identification and Cross-validation
126.96.36.199 Short-term Identification
188.8.131.52 Long-term Identification
4.3 Analysis of the Identified Parameters
5 Control Strategies for sMBRs
5.1 NMPC to a WWTP fitted with an sMBR
5.1.1 NMPC-sMBR Process Control
5.1.2 Simulation Results
5.2 Partial state-feedback linearizing control based on a quadratic control-Lyapunov function
5.2.1 Formula for Feedback
184.108.40.206 Control-Lyapunov Function
220.127.116.11 Partial state-feedback linearization
5.2.2 Stabilizing Sludge Cake Mass
6 Conclusions & Directions for Further Research