Wiley Wastewater Quality Monitoring and Treatment_10 pptx

JWBK117-2.3 JWBK117-Quevauviller October 10, 2006 20:18 Char Count= 0 158 Monitoring in Rural Areas this means that the system is not as fully automated as some might hope and that regular visits to the stations by employees should be foreseen. Also, a too complex ‘black-box’ concept of the system leads to a significant loss of data. The processing of the sensor signal to data should be transparent showing what can be done by using PC-based modulesforthecontrolofthe station.Aweb-basedcommunication enables remote control of the stations and the integration of the data into databases. This concept also allows for a full remote control of the station by authorised persons and a limited accessibility for data consultation by users through the web. A better spatial representation can be obtained by embedding the monitoring and the modelling in a GIS system (Vivoni and Richards, 2005). 2.3.4 CONCLUSIONS AND PERSPECTIVES Monitoring in rural areas needs a different approach than in urban areas. The pollu- tion in rural areas cannot be measured at certain points along the water body, but can only be estimated by making evaluations of the water quality together with infor- mation on what and how many polluting substances are applied in the area. Models, describing all processes on those substances before entering the water, can provide a means to evaluate the magnitude of pollution coming from diffuse pollution and to evaluate scenarios for diffuse pollution reduction. Specific data are needed to calibrate and build those models. Therefore, the traditional cycle in water management should be inversed. Instead of starting from the data set to select an appropriate tool and hence use this tool for management, one should first define the problem, select a tool that can support this problem and then design an appropriate monitoring program to feed the tool. In that way, money is spent to generate primarily the information that is indeed needed. A closer cooperation between monitoring and modelling efforts will make sure that models for diffuse pollution can be used with sufficient reliability. Automated monitoring can help to catch the high variability or short rain-driven events. Such tools can only provide reliable data provided that the monitoring system is transparent and follows quality control procedures with regard to maintenance and calibration. While a high level of automation may support such procedures, it still requires considerable manpower that should be foreseen in any monitoring budget. REFERENCES Arnold, J.G., Williams, J.R., Srinivasan, R. and King, K.W. (1996) SWAT Manual. USDA, Agri- cultural Research Service and Blackland Research Center, Texas. Barthelemy, P.A. and Vidal, C. (1999) A dynamic European agricultural and agri-foodstuff sec- tor. In: Agriculture, Environment, Rural Development, Facts and Figures – A Challenge for Agriculture. European Commission Report, Belgium. Beck, M.B. (1987) Water Resour. Res., 23(8), 1393. JWBK117-2.3 JWBK117-Quevauviller October 10, 2006 20:18 Char Count= 0 References 159 Bervoets, L., Schneiders, A. and Verheyen, R.F. (1989) Onderzoek naar de verspreiding en de typologie van ecologisch waardevolle waterlopen in het Vlaams gewest. Deel 1 - Het Dender- bekken, Universitaire Instelling Antwerpen. In Dutch. Boschma, M., Joaris, A. and Vidal, C. (1999) Concentrations of livestock production. In: Agri- culture, Environment, Rural Development, Facts and Figures – A Challenge for Agriculture. European Commission Report, Belgium. Brown, L.C. and Barnwell T.O. (1987) The Enhanced Stream Water Quality Models QUAL2E and QUAL2E-UNCAS: Documentation and User Model. EPA/600/3-87/007, USA. Janssen, P.H.M., Heuberger, P.S.C. and Sanders,S. (1992) ManualUncsam 1.1, aSoftware Package for Sensitivity and Uncertainty Analysis. Bilthoven, The Netherlands. Krysanova, V. and Haberlandt, U. (2001) Ecol. Modelling, 150, 255–275. McKay, M.D. (1988) Sensitivity and uncertainty analysis using a statistical sample of input values. In: Uncertainty Analysis, Y. Ronen, ed. CRC Press, Inc., Boca Raton, FL, pp. 145–186. Montarella, L. (1999) Soil at the interface between agriculture and environment. In: Agriculture, Environment, Rural Development, Facts and Figures – A Challenge for Agriculture. European Commission Report, Belgium. Pau Val, M. and Vidal, C. (1999) Nitrogen in agriculture. In: Agriculture, Environment, Rural Development, Facts and Figures – A Challenge for Agriculture. European Commission Report, Belgium. Poirot, M. (1999) Crop trends and environmental impacts. In: Agriculture, Environment, Rural Development, Facts and Figures – A Challenge for Agriculture. European Commission Report, Belgium. Sevruk, B. (1986) Proceedings of the ETH, IAHS International Workshop on the Correction of Precipitation Measurements, 1–3 April 1985. ETH Z¨urich, Z¨uricher Geographische Schriften, Z¨urich, p. 23. Smets, S. (1999) Modelling of nutrient losses in the Dender catchment using SWAT. Masters dissertation. Katholieke Universiteit Leuven –Vrije Universiteit, Brussels, Belgium. Vandenberghe, V., van Griensven, A. and Bauwens, W. (2005) Water Sci.Technol., 51(3-4), 347– 354. Vandenberghe, V., Goethals, P., van Griensven, A., Meirlaen, J., De Pauw, N., Vanrolleghem, P.A. and Bauwens, W. (2004) Environ. Monitor Assess., 108, 85–98. van Griensven, A. and Bauwens, W. (2001) Water Sci. Technol., 43(7), 321–328. van Griensven, A. and Bauwens, W. (2003) Water Resour. Res., 39(10), 1348. van Griensven, A., Vandenberghe, V. and Bauwens, W. (2002) Proceedings of the International IWA Conference on Automation in Water Quality Monitoring, 21–22, May 2002. Vienna, Austria. Vivoni, E.R. and Richards, K.T. (2005) J. Hydroinform., 7(4), 235–250. JWBK117-3.1 JWBK117-Quevauviller October 10, 2006 20:25 Char Count= 0 3.1 Elements of Modelling and Control of Urban Wastewater Treatment Systems Olivier Potier and Marie-No¨elle Pons 3.1.1 Introduction 3.1.2 Short Description of the Biological Process by Activated Sludge 3.1.3 Process Parameters 3.1.3.1 Biokinetics 3.1.3.2 Oxygen Transfer 3.1.3.3 Hydrodynamics 3.1.3.4 Wastewater Variability 3.1.3.5 Mass Balance 3.1.4 Sensors 3.1.4.1 In-line Sensors 3.1.4.2 On-line Sensors 3.1.5 Introduction to the Control Methods of a Wastewater Treatment Plant by Activated Sludge 3.1.6 Conclusion and Perspectives Acknowledgement References Wastewater Quality Monitoring and Treatment Edited by P. Quevauviller, O. Thomas and A. van der Beken C  2006 John Wiley & Sons, Ltd. ISBN: 0-471-49929-3 JWBK117-3.1 JWBK117-Quevauviller October 10, 2006 20:25 Char Count= 0 162 Elements of Modelling andControlof Urban Wastewater Treatment Systems 3.1.1 INTRODUCTION A wastewater treatment plant (WWTP) is an intricate system made of unit operations based on physical, biological and physico-chemical principles. Its aim is principally the removal of organic, nitrogen and phosphorus pollution. The basic processes are complex and the various arrangements of the unit operations which can be proposed lead to many possible configurations of WWTPs. It is difficult to describe in detail all of the processes here and only the basics of biological treatment by activated sludge will be examined. It is the most widespread for WWTPs of medium and large size. The interested reader will find more details in Henze et al. (Henze et al., 2000). We focus our attention on the most important parameters for optimization and process control of pollution removal in large plants, where spatial distribution of substrate and nutrient in the reacting system plays a large role. In smaller plants, time scheduling can replace spatial gradients as in sequencing batch reactors for example. Whatever the case and in spite of the perturbations in terms of flow, composition and concentration experienced at the inletof any WWTP, specificationson the discharged water should be kept within strict limits to avoid taxes and penalties. Different tools for monitoring and process control are also presented. 3.1.2 SHORT DESCRIPTION OF THE BIOLOGICAL PROCESS BY ACTIVATED SLUDGE The biological step (often called secondary treatment) is an essential part of the WWTP. At the inlet of the plant, the water is usually pretreated to remove gross debris (grit removal) and can be further treated in a primary settler, which will elim- inate a large part (usually 40–50 %) of the particulate pollution. In doing so, part of the biodegradable pollution is indeed removed, which might not always be a good idea: denitrification, one of the steps involved in nitrogen pollution removal, requires a certain balance between carbon and nitrogen and an external carbon source is often added in that step. This could be avoided (or at least limited) by direct injection into the biological reactor of unsettled wastewater. The principle of activated sludge is the intensification in a reactor of the principle of self-purification, which is naturally oc- curring in the environment, in presence of a much higher bacterial concentration than in rivers or lakes. The task of the secondary clarifier (Figure 3.1.1) is to separate the biological reactor by activated sludge return sludge purified water clarifier Figure 3.1.1 Schematic representation of an activated sludge system JWBK117-3.1 JWBK117-Quevauviller October 10, 2006 20:25 Char Count= 0 Process Parameters 163 aerobic zone anoxic zone Post-denitrification aerobic zone anoxic zone Pre-denitrification C Figure 3.1.2 Schemes of different activated sludge reactors with anoxic zone flocculated bacteria (sludge flocs) from the treated water. The sludge is returned to the inlet of the reactor and the purified water is polished in a tertiary stage (post- treatment of phosphorus, filtration, disinfection, etc.) and/or discharged. In the presence of oxygen, carbon and a small amount of nitrogen (from ammonia and hydrolysed organic nitrogen) are metabolizedby heterotrophic biomass and most of the nitrogen by autotrophic bacteria. The latter produced nitrates can be reduced by heterotrophs under anoxic conditions. As indicated previously, organic matter is needed for this reaction and therefore an addition of carbon (such as methanol) is often necessary. In the case of a pre-denitrification system, mixed liquor from the outlet of the reactor is recycled to the anoxic zone. Some of the most classical schemes are presented in Figure 3.1.2. In order to ensure the best process efficiency, different parameters must be known and controlled: the main reactions of pollution removal and their kinetics; the spatial distribution of the substrates with respect to the micro-organisms and therefore the reactor hydrodynamics; the aeration capacity and therefore the oxygen transfer; and the variability of thewastewater,in terms ofcomposition,concentrationand flowrate. 3.1.3 PROCESS PARAMETERS 3.1.3.1 Biokinetics Many differentcompoundsand micro-organismsarefoundin a biologicalwastewater system. In addition, the ecosystem is never at steady state. Therefore, an exact and complete kinetic model is out of reach. For many years the scientific community has tried to provide models of reasonable complexity, able to describe the main steps of activated sludge behaviour. The basic model is ASM1 (Activated Sludge Model n ◦ 1), devoted to carbon and nitrogen removal (Henze et al., 1987). Improved versions have been proposed, such as ASM2, which takes into account phosphorus removal, and ASM3 (IWA, 2000). ASM1 is a good compromise between the description of the complex reality of biological reactions and the simplicity of a model. The identification of any model parameter should be possible theoretically (structural identifiability) and experimen- tally through experiments which can be run in the laboratory as well as on full-scale systems. JWBK117-3.1 JWBK117-Quevauviller October 10, 2006 20:25 Char Count= 0 164 Elements of Modelling andControlof Urban Wastewater Treatment Systems S s S o X s X p S NH S I X I X B,H X B,A X ND S ND S NO r 3 r 4 r 3 r 3 r 6 r 8 r 5 r 5 r 5 r 4 r 4 r 2 r 2 r 2 r 7 r 1 r 1 r 1 S I : Soluble inert organic matter S s : readily biodegradable substrate X s : Slowly biodegradable substrate X I : Particulate inert organic matter X B,H : Active heterotrophic biomass X B,A : Active autotrophic biomass X p : Particulate products arising from biomass decay S o : Oxygen S NO : Nitrate and nitrite nitrogen S NH : NH 4 + and NH 3 nitrogen S ND : Soluble biodegradable organic nitrogen X ND : Particulate biodegradable organic nitrogen Figure 3.1.3 Schematic representation of the ASM1 kinetic pathways As ASM1 is more particularly used, it will be described in some detail. In ASM1 (Figure 3.1.3), wastewater compounds are divided into different categories: inert (i.e. nonbiodegradable) versus biodegradable matter, particulate versus soluble. Partic- ulate biodegradable matter should be hydrolysed to become readily biodegradable. The biomass is divided into two parts: heterotrophic and autotrophic. Note that toxic events could trigger strong inhibition of bacteria. Inhibition terms can be added to the basic ASM1 model for specific purpose (industrial wastewater mainly). Autotrophs are deemed to be more sensitive to toxics than heterotrophs. 3.1.3.2 Oxygen Transfer Influence of oxygen on pollution removal Bacteria use oxygen for their respiration. In the ASM1 model, the oxygen concen- tration is considered to be a substrate: r For the aerobic growth of heterotrophs, where readily biodegradable substrate is consumed: ρ 1 = μ H  S S K S + S S  S O K O,H + S O  X B,H where ρ 1 is the aerobic growth rate of heterotrophs, S S the biodegradable soluble substrate concentration, S O the oxygen concentration, X B,H the concentration of heterotrophs, K S the heterotrophic half-saturation coefficient for S S , K O,H the het- erotrophic half-saturation/inhibition coefficient for oxygen and μ H the maximum growth rate of heterotrophs. JWBK117-3.1 JWBK117-Quevauviller October 10, 2006 20:25 Char Count= 0 Process Parameters 165 r For the aerobic growth of autotrophs, where NH 4 + and NH 3 nitrogen are trans- formed into nitrates: ρ 3 = μ A  S NH K NH + S NH  S O K O,A + S O  X B,A where ρ 3 is the aerobic growth rate of autotrophs, S NH the ammonium concen- tration, X B,A the concentration of autotrophs, K NH the autotrophic half-saturation coefficient for S NH , K O,A the autotrophic half-saturation coefficient for oxygen and μ A the maximum growth rate of heterotrophs. For the anoxic growth of heterotrophs, a very low concentration of oxygen is required to avoid any inhibition: ρ 2 = μ H  S S K S + S S  K O,H K O,H + S O  S NO K NO + S NO  η g X B,H where ρ 2 is the anoxic growth rate of heterotrophs, S NO the nitrate concentration, K NO the heterotrophic half-saturation coefficient for S NO and η g the anoxic growth rate correction factor for heterotrophs. Thus, the oxygen concentration has a great importance: it should be low in the anoxic stages and nonlimiting in the aerated zones. However, excessive oxygen supply should be penalized in terms of cost. Oxygen is provided by gas diffusers or surface aerators. Oxygen transfer model Generally, the gas–liquid transfer is modelled by means of the double film theory (Roustan et al., 2003), according to which the gas–liquid interface is located between a gas film and a liquid film. For the oxygen–water system, the transfer resistance is found in the liquid film, due to the low solubility of oxygen in water. The oxygen flux is a function of the difference between the oxygen concentration at saturation (S ∗ O ) and the dissolved oxygen concentration in the reactor ( S O ) and of the global coefficient of oxygen transfer (k L a  ). Experimental values of k L a  are generally between 2 h −1 and 10 h −1 . If it is assumed that the reactor can be modelled as a Continuous Perfectly Mixed Reactor (CPMR) (Figure 3.1.4), with a uniform oxygen concentration, the oxygen mass balance is written as: QS OI + k L a  (S ∗ O − S O )V = QS O +r O V + V dS O dt with S OI the oxygen concentration at the inlet, r O the oxygen consumption rate, V the reactor volume and Q the liquid flow rate. The coefficient transfer is measured directly in the presence of sludge (k L a  ), or in clean water without sludge (k L a)(H´eduit and Racault, 1983a,b; ASCE, 1992; JWBK117-3.1 JWBK117-Quevauviller October 10, 2006 20:25 Char Count= 0 166 Elements of Modelling andControlof Urban Wastewater Treatment Systems air water inlet water outlet QS OI QS O S O Figure 3.1.4 An aerated Continuous Perfectly Mixed Reactor Roustan et al., 2003). In this case, the so-called ‘alpha’ factor (α) must be taken into account (Boumansour and Vasel, 1996): k L a  = αk L a Example of oxygen profile in a WWTP bioreactor To illustrate the open loop behaviour of a biological reactor, with no aeration adjust- ment as a function of the oxygen demand, the oxygen profile was measured during 1 day in a 3300 m 3 channel reactor with a large aspect ratio. The reactor is 100 m long and 8 m wide and aerated by means of fine bubble diffusers located on its floor. The dissolved oxygen concentration was regularly measured in six locations along the reactor with a portable probe (WTW, Weilheim, Germany) (Figure 3.1.5). The 1.8 0.8 0.6 0.4 0.2 0 0 5 10 15 20 25 30 1.6 1.4 1.2 1 time/h dissolved oxygen/mg L − 1 O 2 (near inlet) O 2 (1/8 of the length) O 2 (1/3 of the length) O 2 (1/2 of the length) O 2 (2/3 of the length) O 2 (near outlet) Figure 3.1.5 Variations of the dissolved oxygen concentration in different locations of an acti- vated sludge channel reactor during 1 day JWBK117-3.1 JWBK117-Quevauviller October 10, 2006 20:25 Char Count= 0 Process Parameters 167 air flow rate was constant and equally distributed along the reactor, which was con- tinuously fed by urban presettled wastewater. The dissolved oxygen concentration changes with the oxygen consumption, and therefore with biodegradable pollution concentration, which depends on time and space in the reactor. In Figure 3.1.5, it can be seen that dissolved oxygen concentration is higher during the night, when pollution is lower. The concentration increases along the reactor as the oxygen consumption decreases due to a decrease in the biodegradable substrate availability. During the day, dissolved oxygen concentration remains very low, even near the reactor outlet, which indicates complete pollution removal is not achieved. Under such conditions oxygen limitation occurs. Better aeration with a larger air flow rate could alleviate such a limitation without increasing the reactor volume. 3.1.3.3 Hydrodynamics In brief, two types of reactor shape are found: a compact, ‘parallelepipedic’ or ‘cylindrical’ design, often fitted with surface turbines for aeration; and an elongated design suitable for gas diffusion devices. Elongated reactors are often folded or built as ‘race tracks’, which avoids recirculation pumps (Figure 3.1.6). In this case they are generally called ‘oxidation ditches’ when the aerators are horizontal and ‘carousels’ when they are vertical. Many variations have been proposed by various manufacturers, such as sets of several concentric channels as in the Orbal TM sys- tem and OCO TM process, inclusion of anaerobic and anoxic zones equipped with mechanical mixing devices, or combination of spatial gradients along the tanks with alternating mode of operation, such as in the Biodenipho TM or Biodenitro TM process. Capacity, land availability, flow circulation, process type (carbon and/or nutrient removal) are some of the criteria for selection. Hydrodynamics haveagreat importance in a process, because linked withkinetics, they affect pollution removal efficiency and the bacteria species selectivity. Usually the reactor behaviour is compared with one of two ideal types: the Continuous Perfectly Mixed Reactor (or CPMR) and the Plug Flow Reactor. The CPMR is characterized by a uniform concentration of each component in all the volume of the reactor. This type of reactor can be found in small WWTPs, where the length is similar to the width. aerobic and anoxic zone Figure 3.1.6 A ‘race track’ reactor JWBK117-3.1 JWBK117-Quevauviller October 10, 2006 20:25 Char Count= 0 168 Elements of Modelling andControlof Urban Wastewater Treatment Systems 123 J Q Q Figure 3.1.7 J CPMRs in series The Plug Flow Reactor model is very different. It is composed of a succession of parallel volumes infinitiely small, perpendicular to the flow, with no transfer between them. These volumes move forward from the inlet to the outlet, at a velocity linearly related to the flow. There is a progressive change in concentrations. However, if the ideal Plug Flow Reactor model could be used for tubular or fixed-bed reactors in the chemical industry, it rarely represents in a satisfactory manner an aerated tank in a WWTP. Models based on CPMRs in series (Figure 3.1.7) offerthebestsimplealternative to model full-scale plants and generally give a good agreement with experimental data. Theoretically, the number of reactors in series (J) can vary between 1 and infinity. In practice, J is determined by tracing experiments and takes values between 3 and 20. Although a series of J CPMRs is a discrete hydrodynamic model, it can model a continuous liquid system like a channel reactor. Hydrodynamic characterization A relatively simple method for the characterization of hydrodynamics is the Resi- dence Time Distribution (RTD) method. Each molecule has is own residence time (r t ) in the reactor, which depends on the reactor hydrodynamics (Figure 3.1.8). The goal of the RTD method is to measure the different residence times based on statis- tics. A pulse of nonreactive tracer is injected at the inlet of the reactor. Different chemical substances are used, such as lithium chloride (detection by atomic ab- sorption), rhodamine (detection by fluorescence sensor) and radioactive elements. The tracer is dissolved in the mixed liquor in the reactor and behaves as the liquid phase. At the reactor outlet, the tracer concentration is measured to calculate the RTD (Villermaux, 1993; Levenspiel, 1999). Inlet signal Outlet signal Figure 3.1.8 Inert tracing of a reactor [...]... computer speed and the possible parallelization of some calculations, the simulation time remains very long and it is still difficult to introduce mass transfer and kinetics in this type of simulation 3.1.3.4 Wastewater Variability Different types of variability Wastewater characteristics change with time, not only in terms of flow rate, but also in terms of composition and concentration Wastewater variability... (BioView, Delta Light & Optics, Denmark) and infrared technology (Steyer et al., 2002) offer also new prospects for in-situ wastewater quality monitoring based on spectroscopy (Pons et al., 2004) 3.1.4.2 On-line Sensors On-line sensors have been proposed for nitrate, ammonia, phosphate, short-term biological oxygen demand (BOD) (to evaluate the oxygen demand and control the aeration rate), toxicity... Jeppsson, U and Pons, M.N (2004) Control Engin Pract., 12, 299–304 Langergraber, G., Fleischmann, N and Hofst¨ dter, F (2003) Water Sci Technol., 47 (2), 63–71 a Levenspiel, O (1999) Chemical Reaction Engineering, 3rd Edn John Wiley & Sons, Inc., New York Olsson, G., Nielsen, M.K., Yuan, Z, Lynggaard A and Steyer, J.P (2005) Instrumentation, control and automation in wastewater systems Scientific and Technical... 853–861 Gernaey, K and Jørgensen, S.B (2004) Control Engin Pract., 12, 357–373 H´ duit, A and Racault, Y (1983a) Water Res., 17, 97–103 e H´ duit, A and Racault, Y (1983b) Water Res., 17, 289–297 e Henze, M., Grady, C., Gujer, W., Marais, G and Matsuo, T (1987) Activated sludge model no.1 IAWPRC Task Group Report IWA, London Henze, M., Harrem¨ es, P., La Cour Jansen, J and Arvin, E (2000) Wastewater Treatment... Arvin, E (2000) Wastewater Treatment Bioo logical and Chemical Processes, 3rd Ed Springer, Berlin IWA (2000) Task group on mathematical modelling for design and operation of biological wastewater treatment, Activated sludge models ASM1, ASM2, ASM2D and ASM3 Scientific and Technical Report no 9 IWA, London Jeppsson, U., Alex, J., Pons, M.N., Spanjers, H and Vanrolleghem, P.A (2002) Water Sci Technol.,... treatment efficiency and they are necessary to monitor, control and optimize the processes (Vanrolleghem and Lee, 2003; Degr´ mont, 2005) There are three types of sensors: e in-line sensors situated directly in the process; on-line sensors, based on automated sampling and conditioning of the sample; and off-line devices, in plant laboratories, which require human operators In any case in-line and on-line sensors... bacterial respiration) (Vanrolleghem et al., 1994) and sludge volume index (to detect settling problems such as filamentous bulking) (Vanderhasselt et al., 1999) JWBK117-3.1 174 JWBK117-Quevauviller October 10, 2006 20:25 Char Count= 0 Elements of Modelling and Control of Urban Wastewater Treatment Systems 3.1.5 INTRODUCTION TO THE CONTROL METHODS OF A WASTEWATER TREATMENT PLANT BY ACTIVATED SLUDGE The... the level of implementation of instrumentation, control and automation systems varies depending on the country (Jeppsson et al., 2002; Olsson et al., 2005) WWTPs are very complex to control because of the composition and the time variability of the biomass and the wastewater As shown previously, their models need many parameters, are nonstationary and strongly nonlinear Many control strategies, presenting... sufficient detail the behaviour of WWTPs and that can be used to ‘benchmark’ control strategies (Jeppsson and Pons, 2004) could help the modernization of plants from the control point of view ACKNOWLEDGEMENT The authors wish to thank Degr´ mont and particularly Eric Garcin, Fran¸ oise e c Petitpain-Perrin, Jean-Pierre Hazard and Didier Perrin REFERENCES ASCE (1992) Standard Measurement of Oxygen Transfer... incoming wastewater was bypassed and directly discharged to the river, which explained the limitation at 6500 m3 /h RTDs were determined in the channel reactors previously described under different flow conditions and they show that the tanks can be modelled by CPMRs in series The hydrodynamic behaviour is modified by the flow rate and the number of CPMRs (Figure 3.1.12), J , changes with the space-time τ , and . Sludge 3.1.6 Conclusion and Perspectives Acknowledgement References Wastewater Quality Monitoring and Treatment Edited by P. Quevauviller, O. Thomas and A. van der Beken C  2006 John Wiley & Sons,. L.C. and Barnwell T.O. (1987) The Enhanced Stream Water Quality Models QUAL2E and QUAL2E-UNCAS: Documentation and User Model. EPA/600/3-87/007, USA. Janssen, P.H.M., Heuberger, P.S.C. and Sanders,S JWBK117-Quevauviller October 10, 2006 20:25 Char Count= 0 162 Elements of Modelling andControlof Urban Wastewater Treatment Systems 3.1.1 INTRODUCTION A wastewater treatment plant (WWTP) is an