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Book Details
Abstract
This international, comprehensive guide to modeling and simulation studies in activated sludge systems leads the reader through the entire modeling process – from building a mechanistic model to applying the model in practice.
Mathematical Modelling and Computer Simulation of Activated Sludge Systems will:
- Enhance the readers’ understanding of different model concepts for several (most essential) biochemical processes in the advanced activated sludge systems
- Provide extensive and up-to-date coverage of experimental methodologies of a complete model parameter estimation (longitudinal dispersion coefficient, influent wastewater fractions, kinetic and stoichiometric coefficients, settling velocity, etc.)
- Summarize and critically review the ranges of model parameters reported in literature
- Compare the existing protocols aiming at a systematic organization of the simulation study
- Outline the capabilities of the existing commercial simulators
- Present documented, successful case studies of practical model applications as a guide while planning a simulation study.
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Table of Contents
| Section Title | Page | Action | Price |
|---|---|---|---|
| Half Title | i | ||
| Title | iii | ||
| Copyright | iv | ||
| Contents | v | ||
| Chapter 1: Introduction | 1 | ||
| 1.1 HISTORY OF THE ACTIVATED SLUDGE PROCESS | 1 | ||
| 1.1.1 Initial period | 1 | ||
| 1.1.2 Biological nitrogen removal | 8 | ||
| 1.1.3 Enhanced biological phosphorus removal (EBPR) | 15 | ||
| 1.1.4 Integrated EBPR and nitrogen removal | 16 | ||
| 1.1.5 Nitrogen removal in sidestream processes | 18 | ||
| 1.1.6 Summary | 22 | ||
| 1.2 DEVELOPMENT OF THE ACTIVATED SLUDGE MODELS | 23 | ||
| 1.2.1 First period – empirical criteria | 23 | ||
| 1.2.2 Second period - steady-state relationships of microbial growth and organic substrate utilization | 25 | ||
| 1.2.3 Third period - complex dynamic models | 32 | ||
| 1.3 BASIC DEFINITIONS IN MATHEMATICAL MODELLING AND COMPUTER SIMULATION | 45 | ||
| 1.3.1 System | 46 | ||
| 1.3.2 Experimentation | 47 | ||
| 1.3.3 Model | 48 | ||
| 1.3.4 Advantages and disadvantages of mathematical modelling and computer simulation | 55 | ||
| Chapter 2: Model building | 57 | ||
| 2.1 COMPONENTS OF A COMPLETE MODEL OF AN ACTIVATED SLUDGE SYSTEM | 57 | ||
| 2.2 HYDRAULIC CONFIGURATION MODEL | 58 | ||
| 2.3 INFLUENT WASTEWATER CHARACTERIZATION MODEL | 60 | ||
| 2.4 BIOREACTOR MODEL | 70 | ||
| 2.4.1 Biokinetic model | 70 | ||
| 2.4.2 Hydrodynamic mixing model | 76 | ||
| 2.4.2.1 Types of reactors | 76 | ||
| 2.4.2.2 Longitudinal advection-dispersion model | 80 | ||
| 2.4.2.3 Combining ADE with source terms (biokinetic models) | 83 | ||
| 2.4.3 Oxygen transfer model | 86 | ||
| 2.4.3.1 Introduction | 86 | ||
| 2.4.3.2 Overall mass transfer coefficient, K⊂La | 90 | ||
| 2.4.3.3 Saturation concentration of dissolved oxygen in mixed liquor, S⊂O,sat | 95 | ||
| 2.4.4 Process temperature model | 98 | ||
| 2.4.4.1 Effects of temperature in activated sludge systems | 98 | ||
| 2.4.4.2 Historical background of temperature modelling in activated sludge reactors | 103 | ||
| 2.4.4.3 Temperature model components | 107 | ||
| 2.5 SEDIMENTATION/CLARIFICATION MODEL | 118 | ||
| 2.5.1 Solids flux theory | 120 | ||
| 2.5.2 Approaches to dynamic modelling clarifier operation | 126 | ||
| 2.5.3 Biological processes in the secondary clarifier | 131 | ||
| 2.5.3.1 Occurrence of denitrification and secondary phosphate release | 131 | ||
| 2.5.3.2 Approaches to modelling biochemical processes in secondary clarifiers | 131 | ||
| Chapter 3: Modelling specific biochemical processes occurring in activated sludge systems | 133 | ||
| 3.1 GROWTH OF MICROORGANISMS | 133 | ||
| 3.1.1 Maximum specific growth rate for heterotrophic biomass, µ⊂H,max | 136 | ||
| 3.1.2 Substrate saturation coefficient for heterotrophic biomass, K⊂S,H | 139 | ||
| 3.1.3 Yield coefficient for heterotrophic biomass, Y⊂H | 140 | ||
| 3.1.4 Correction factors for anoxic kinetics and stoichiometry | 141 | ||
| 3.2 DISAPPEARANCE (LOSS) OF BIOMASS AND CELL INTERNAL COMPONENTS | 144 | ||
| 3.3 STORAGE OF SUBSTRATES | 149 | ||
| 3.4 ADSORPTION OF SUBSTRATES | 157 | ||
| 3.5 HYDROLYSIS OF SLOWLY BIODEGRADABLE ORGANIC COMPOUNDS | 161 | ||
| 3.6 FERMENTATION (CONVERSION OF “COMPLEX ” READILY BIODEGRADABLE SUBSTRATE TO VFA) | 169 | ||
| 3.7 NITRIFICATION | 172 | ||
| 3.7.2 Modelling nitrification as a two-step conversion | 180 | ||
| 3.7.1 Modelling nitrification as a one-step conversion | 173 | ||
| 3.8 DENITRIFICATION | 184 | ||
| 3.9 ENHANCED BIOLOGICAL PHOSPHATE REMOVAL (EBPR) | 191 | ||
| 3.9.1 Mechanism of the EBPR process | 191 | ||
| 3.9.2 Carbon sources and storage products | 193 | ||
| 3.9.3 Anoxic growth of PAO | 194 | ||
| 3.9.4 Approaches to modelling the EBPR process | 197 | ||
| 3.9.5 Effect of GAO metabolism on EBPR | 203 | ||
| 3.10 BULKING SLUDGE (GROWTH OF MICROTHRIX PARVICELLA) | 206 | ||
| 3.10.1 Conceptual model for M. parvicella in activated sludge | 206 | ||
| 3.10.2 Mathematical model structure for M. parvicella in activated sludge | 208 | ||
| 3.10.3 Kinetic and stoichiometric parameters, temperature effects | 209 | ||
| 3.11 ANAEROBIC AMMONIUM OXIDATION (ANAMMOX) | 211 | ||
| 3.11.1 Mechanism of the Anammox process | 211 | ||
| 3.11.2 Approaches to modelling the ANNAMOX process | 215 | ||
| Chapter 4: Organization of a simulation study | 221 | ||
| 4.1 APPROACHES TO A SYSTEMATIC ORGANIZATION OF THE SIMULATION STUDY | 222 | ||
| 4.1.1 BIOMATH calibration protocol (Belgium) | 226 | ||
| 4.1.2 STOWA calibration protocol (Holland) | 228 | ||
| 4.1.3 WERF protocol (USA) | 231 | ||
| 4.1.4 HSG guideline (Austria, Germany, Switzerland) | 236 | ||
| 4.1.5 JS protocol (Japan) | 239 | ||
| 4.1.6 IWA Task Group protocol | 241 | ||
| 4.1.7 Summary | 244 | ||
| 4.2 DATA QUALITY CONTROL (COLLECTION, VERIFICATION AND RECONCILIATION) | 245 | ||
| 4.3 MODEL CALIBRATION/VALIDATION PROCEDURES | 253 | ||
| 4.3.1 Selection of a hydrodynamic mixing model | 254 | ||
| 4.3.1.1 Estimation of the longitudinal dispersion coefficient, E⊂L, from tracer studies | 254 | ||
| 4.3.1.2 Estimation of the longitudinal dispersion coefficient, E⊂L, from empirical formulae | 258 | ||
| 4.3.2 Influent wastewater and biomass characterization | 265 | ||
| 4.3.2.1 Integrated wastewater characterization | 265 | ||
| 4.3.2.2 Characterization of individual fractions | 269 | ||
| 4.3.3 Estimation of kinetic and stoichiometric parameters in the biokinetic models | 278 | ||
| 4.3.4 Estimation of settling parameters | 287 | ||
| 4.3.5 Estimation of the K⊂La coefficient | 289 | ||
| 4.3.5.1 Estimation of the K⊂La coefficient in the field studies | 289 | ||
| 4.3.5.2 Estimation of the K⊂La coefficient from dimensionless analysis | 293 | ||
| 4.4 GOODNESS-OF-FIT MEASURES | 294 | ||
| 4.5 UNCERTAINTY AND SENSITIVITY ANALYSIS | 297 | ||
| 4.5.1 Background | 297 | ||
| 4.5.2 Uncertainty analysis | 298 | ||
| 4.5.3 Sensitivity analysis | 300 | ||
| Chapter 5: Practical model applications | 311 | ||
| 5.1 INTRODUCTION | 311 | ||
| 5.2 OPTIMIZATION OF PROCESS PERFORMANCE | 314 | ||
| 5.3 EXPANSION AND UPGRADE OF EXISTING FACILITIES | 316 | ||
| 5.4 DESIGN OF NEW FACILITIES | 316 | ||
| 5.5 DEVELOPMENT OF NEW TREATMENT CONCEPTS | 317 | ||
| 5.6 EDUCATION (TRAINING AND TEACHING) | 320 | ||
| 5.7 CHARACTERISTICS OF THE EXISTING SIMULATOR ENVIRONMENTS | 321 | ||
| 5.7.1 ASIM (ETH/EAWAG, Switzerland) | 324 | ||
| 5.7.2 BioWin (EnviroSim, Canada) | 324 | ||
| 5.7.3 GPS-X (Hydromantis, Canada) | 325 | ||
| 5.7.4 SIMBA (IFAK, Germany) | 326 | ||
| 5.7.5 STOAT (WRc, UK) | 326 | ||
| 5.7.6 WEST (MOSTforWATER, Belgium) | 327 | ||
| References | 333 | ||
| Index | 375 |