Activated Sludge Model No. 1 Model Research Articles

Dynamic simulation and optimization of activated sludge unit using the ASM3 model to maximize removal efficiency of slowly biodegradable substrates

Slowly biodegradable substrates (Xs) form an important part of the total chemical oxygen demand (COD) of municipal and industrial wastewaters entering the activated sludge (AS) unit. Using an effective configuration of activated sludge and optimization of operating parameters are two methods to improve removal efficiency of Xs. The main objective of this work is dynamic simulation of AS with different configurations to investigate the effect of these two methods on removal efficiency of Xs. First, a procedure is developed to simulate AS using the activated sludge model No.3 (ASM3). Then, seven configurations of AS with three different aeration tanks including continuous stirred-tank reactor (CSTR), plug flow reactor (PFR) and sequencing batch reactors (SBR) are simulated in Mathematica under identical operating conditions and total volume. The results indicate that configuration with two series AS and CSTR as aeration tank (AS-CSTR5) presents the best performance for Xs removal. Moreover, this configuration presents superior performance for denitrification and nitrification. Then, operating parameters of AS-CSTR5 are optimized using the Taguchi method and Minitab to maximize the removal efficiency of Xs. To simplify simulation of AS, usually biochemical reactions in clarifier of AS are ignored. The results of this work, however, indicate that this can lead to predict inaccurate results for some parameters such as removal efficiency of XS. The results of this work can be used to construct new AS units and improve the overall performance of available units.

Performance evaluation of an oily industrial wastewater treatment system using the application of activated sludge model No. 3

AbstractThe purpose of the present study was to adapt the activated sludge model No. 3 (ASM3) to the characteristics of oily industrial wastewater, determining the utmost significant and appropriate kinetic as well as stoichiometric parameters. An oily industrial wastewater treatment system was simulated to assess ASM3 validation and perform sensitivity analysis using the STOAT program. The obtained results revealed that the ASM3 model, which was calibrated after adding the Arrhenius equation into consideration, provided strong correlations with the analytical results of chemical oxygen demand (COD), total suspended solids (TSS), mixed liquor volatile suspended solids (MLVSS) and total suspended solids in the return activated sludge flow (TSS in RAS) concentrations. The values of modelled effluent COD and TSS are very close to those corresponding real values of the treated wastewater by a difference of between 0.5% and 1.5%. Thus, this model becomes successful in representing oily industrial wastewater treatment as a new trend added to the traditional modelling of sewage treatment.

Investigation, biokinetic calculation, and modelling of a real combined industrial wastewater biological treatment process by activated sludge models

Background: Treatment of combined industrial wastewater from industrial parks is one of the most complex and difficult wastewater treatment processes. Also, the accuracy of biological models for the prediction of the performance of these processes has not been sufficiently evaluated. Therefore, in this study, the International Association on Water Quality (IAWQ(-Activated Sludge Model No. 1 (ASM1) was implemented for the Jey industrial park in Isfahan province, Iran. Methods: The Jey IPWWTP process is a combination of anaerobic and aerobic biological processes. To evaluate the overall performance of IPWWTP, organic compounds, suspended solids, nutrients, attached biomass, and some operating parameters were measured during 6 months. Then, the biokinetic coefficients of aerobic processes were determined using Monod equations. Finally, the aerobic processes were modeled using ASM1 implemented in STOAT software. Results: The values of the biokinetic coefficients K, Y, Ks, Kd, and µmax were calculated as 2.7d- , 0.34 mg VSS/mg COD, 133.36 mg/L COD, 0.03d- , and 0.93d- , respectively. Based on the default coefficients and conditions of the ASM model, the difference between the experiments and model prediction was about 2 to 98%. After calibrating the ASM model, the difference between the experiments and prediction in all parameters was reduced to less than 10%. Conclusion: Investigations showed that the default coefficients and operation conditions of the ASM1 model do not have good predictability for complex industrial wastewaters and the outputs show a low accuracy compared to the experiments. After calibrating the kinetic coefficients and operating conditions, the model performance is acceptable and the predictions show a good agreement with the experiments.

Establishment of nitrous oxide (N2O) dynamics model based on ASM3 model during biological nitrogen removal via nitrification

ABSTRACT Nitrous oxide (N2O), as one of the six greenhouse gases, is mainly produced in the biological nitrogen removal process of wastewater treatment plants (WWTPs). Establishing the N2O kinetic model can provide insight into the N2O generation mechanism and regulate its production. This work uses Activated Sludge Model NO.3 (ASM3) as the basic framework, combines organic storage with endogenous respiration theory, and couples ammonia-oxidizing bacteria (AOB) denitrification pathway and the NH2OH/NOH model to establish a kinetic model. Meanwhile, the Sequencing Batch Reactor (SBR) process with artificial simulated urban domestic sewage was used as the carrier; MATLAB and EXCEL software were used as tools to establish a model calculation programme. The simulated values obtained by substituting the operating conditions of the SBR process into the model and the measured values of the SBR process were analysed. The correlation coefficient (R 2) between the experimental values and simulated values obtained for the 5 components of COD, ammonia, nitrite, nitrate and total N2O is 0.952, 0.996, 0.902, 0.991 and 0.956, respectively, which indicates that the N2O kinetic model has great consistency, this further shows that the established model modelling mechanism is clear and accurate, and provides a new method for the N2O dynamic model.

A Methodology for Global Sensitivity Analysis of Activated Sludge Models: Case Study with Activated Sludge Model No. 3 (ASM3).

The main objective of this study was to demonstrate a computational approach of global sensitivity analysis (GSA) integrated with functional principal component analysis (fPCA) for activated sludge models through aggregation of time-dependent model response patterns into time-independent coefficients of functional principal components (PCs). This proposed approach addresses the main issue of time-varying character of GSA indices when calculated solely on the time-dependent model outputs. The GSA-fPCA methodology was implemented using the rigorous model Activated Sludge Model No. 3 (ASM3) as case study. The approach transforms the time-dependent model outputs into functional PCs prior to calculation of GSA indices to remove the time-varying character of the calculated GSA indices. This work focused on the evaluation of the following key computational factors that may significantly influence the performance of the GSA-fPCA methodology: (a) model parameter sampling range, (b) model simulation period, (c) basis functions system, and (d) state of the system being modeled-batch or continuous activated sludge process. Results show that first few functional PCs capture up to 100% of the curve patterns in the time-dependent model outputs. The sensitivity indices calculated from the PC scores via Morris' GSA technique elucidated parameter sensitivity patterns inherent to the complex mathematical structure of ASM3. PRACTITIONER POINTS: Functional principal components-mediated GSA technique to remove time-varying character of sensitivity indices derived from time-dependent dynamical models. Technique amenable to improving efficiency of capturing response patterns into few functional principal components through various basis functions. Identifying priority parameters for ASM3 model calibration requires specification of target model outputs to which parameter sensitivities are calculated. GSA-fPCA offers a comprehensive numerical approach to manipulating models depending on the intended applications: simple fast-responding models to complex models.

Steady-state modeling of the biodegradation performance of a multistage moving bed biofilm reactor (MBBR) used for on-site greywater treatment

In this study, the Activated Sludge Model No. 3 (ASM3) was applied for the simulation of the removal of organics and nitrogen in a multistage moving bed biofilm reactor (MBBR) used for biological greywater treatment. The data related to the characterization of the greywater were collected over a period of 5months to be investigated in the model. The reactor showed a high performance for the removal of chemical oxygen demand (COD), dissolved organic carbon (DOC), biological oxygen demand (BOD5), ammonia (NH4-N), and total nitrogen (TN) with a removal efficiency of 93%, 80.7%, 99%, 89%, and 77%, respectively. The results of modeling showed a good correlation between simulated and experimental concentrations of COD issued from different reactors of the MBBR system. The adaptability of the ASM3 model to fit other parameters such as TN, NH4-N, total suspended solids (TSS), and the dissolved oxygen (DO) was also investigated for two selected reactors: reactor (R1) and the reactor (R5). The simulation results showed an acceptable correlation regarding the evolution of the investigated parameters in R1 and R5 and in the effluent except for total nitrogen TN. The adjustment of the stoichiometric parameters led to a satisfactory simulation of TN concentrations.

Modeling and simulation of a biological process for treating different COD:N ratio wastewater using an extended ASM1 model

The aim of this study was to establish a mathematical model for simulating a biological nutrient removal (BNR) process for treating wastewater with different COD:N ratios. Through phylogenetic analysis, the microbial communities in a cyclic activated sludge system (CASS) reactor under different COD:N ratios were quantitatively characterised, while the necessity of incorporating the microbial interaction mechanism in the extended ASM1 (E-ASM1) was validated. Since the newly introduced parameters affected the original kinetics in the activated sludge model No. 1 (ASM1), the poorly defined parameters were altered based on the batch experimental data taken from a lab-scale CASS and the results of a root-mean-square sensitivity analysis. The simulation results indicated that effluent COD and biopolymer concentrations decreased with an increase in influent COD:N ratio, while the trend was opposite for nitrification. Compared to the ASM1-SMP-EPS model, the extended ASM1 (E-ASM1) proved to be a preferable reference for the simulations of the CASS performance in substrate degradation and biopolymers formation mechanism, strongly suggesting that the interactive relationship among different bacteria and the biopolymer dynamics should be simultaneously included in this model.

Estimation of Yield, Growth Rate, Decay Rate, and Half-Saturation Coefficients of ASM1 Model Parameters

In this paper, determination of parameter values for yield, growth rate, decay rate, and half-saturation coefficients of Activated Sludge Model No. 1 (ASM1) has been carried out. The activated sludge samples are collected from the sewage treatment plant used for the evaluation of ASM1 model parameters. The stoichiometric and kinetic parameters of autotrophic and heterotrophic biomass are determined using respiration rates in a respirometer operated at the temperature of 23 °C. These parameters are important when estimating oxygen demands, autotrophic, and heterotrophic biomass concentrations during the design and operation of activated sludge process. It should be noted that the parameters of ASM1 model are obtained from individual respirometric experiments. Results indicate that the parameter values determined in this study are in agreement within the range of values proposed in the literature at 20 °C and are useful for system analysis (modeling, optimization, and control) in activated sludge process. The estimated values of Y A, Y H, b A, b H, µ mA, µ mH, K S, and K NH are 0.22 mg cell COD formed (mg N oxidized)−1, 0.677 mg cell COD formed (mg COD oxidized)−1, 0.102 day−1, 0.196 day−1, 0.74 day−1, 3.836 day−1, 20.1893 mg COD/l and 1.016 mg NH3–N/l, respectively.

Simulating a cyclic activated sludge system by employing a modified ASM3 model for wastewater treatment.

To interpret the biological nutrient removal in a cyclic activated sludge system (CAS), a modified model was developed by combining the process of simultaneous storage and growth, and the kinetics of soluble microbial product (S SMP) and extracellular polymeric substance (X EPS) with activated sludge model no. 3 (ASM3). These most sensitive parameters were initially selected whilst parameters with low sensitivity were given values from literature. The selected parameters were then calibrated on an oxygen uptake rate test and a batch CAS reactor on an operational cycle. The calibrated model was validated using a combination of the measurements from a batch CAS reactor operated for 1month and the average deviation method. The simulations demonstrated that the modified model was capable of predicting higher effluent concentrations compared to outputs of the ASM3 model. Additionally, it was also shown that the average deviation of effluent S COD, S NH, S SMP and X EPS simulated with the modified model was all less than 1mgL-1. In summary, the model could effectively describe biological processes in a CAS reactor and provide a wonderful tool for operation.

Modelling energy costs for different operational strategies of a large water resource recovery facility.

The main objective of this paper is to demonstrate the importance of applying dynamic modelling and real energy prices on a full scale water resource recovery facility (WRRF) for the evaluation of control strategies in terms of energy costs with aeration. The Activated Sludge Model No. 1 (ASM1) was coupled with real energy pricing and a power consumption model and applied as a dynamic simulation case study. The model calibration is based on the STOWA protocol. The case study investigates the importance of providing real energy pricing comparing (i) real energy pricing, (ii) weighted arithmetic mean energy pricing and (iii) arithmetic mean energy pricing. The operational strategies evaluated were (i) old versus new air diffusers, (ii) different DO set-points and (iii) implementation of a carbon removal controller based on nitrate sensor readings. The application in a full scale WRRF of the ASM1 model coupled with real energy costs was successful. Dynamic modelling with real energy pricing instead of constant energy pricing enables the wastewater utility to optimize energy consumption according to the real energy price structure. Specific energy cost allows the identification of time periods with potential for linking WRRF with the electric grid to optimize the treatment costs, satisfying operational goals.

Comparison and Database Development of Four Recent ASM3 Model Extensions

AbstractIn the last decade, many Activated Sludge Model No. 3 (ASM3) extensions were proposed to adopt new concepts such as simultaneous storage and growth of heterotrophic organisms and two-step nitrification-denitrification processes. From these ASM3 model extensions, four are included in this study: ASM3 with two-step nitrification-denitrification, ASM3 for simultaneous autotrophic and heterotrophic storage-growth, ASM3 extension for two-step nitrification-denitrification, and ASM3 for simultaneous storage-growth and nitrification-denitrification. The four models are analyzed and compared to the original ASM3 model with respect to the modeling concepts adopted, the process kinetic rates modified, and the kinetic parameters and stoichiometric coefficients introduced. A new schematic representation of the modeling concepts concerning the organisms’ activities is introduced. A database of all parameters and coefficients of the four considered model extensions is developed using a unified notation system t...

Simulation and calibration of a full-scale sequencing batch reactor for wastewater treatment

The aim of this study is to apply the main mathematical models used in activated sludge reactors, the Activated Sludge Model No. 1 (ASM1) and its variations (ASM2d and ASM3), to predict the behavior of a full-scale sequencing batch reactor (SBR) used for the treatment of domestic wastewater employing the software ASIM®. Two cycles were studied, the step-feed cycle and conventional filling. Samples were taken from the raw influent, from the reactor and from the treated wastewater, and these data were used to calibrate the models. The ASM1 model was the best model to represent the cycle with only an input, while model ASM3 was the best for simulating the scaled filling cycle. This work presents calibrated parameters for the two kinds of filling. The results of these simulations indicate that the calibration process succeeded and can be used as a model for future studies.

Simulation and Optimization of Compound A<sup>2</sup>/O Treatment Process Based on Model ASM3

Introduction is given to the content of activated sludge model No.3 (ASM3). The simulation program which based on the integration of ASM3 and Anaerobic Digestion Model was used to simulate A2/O with AquaMats Process. The predicted results of effluent COD, NH3-N and NO3-N accorded with the actuality. The removal efficiency of TP was quite low when sludge return rate was 100%. Based on this condition, the improved scheme which adjusts sludge reflux ratio to 60% was put forward and simulated. Process was optimized depending on the simulation results and the removal efficiencies of COD, NH3-N and TP reached to 83.1%, 98.75 and 24.01%. It is verified that ASM3 can be used as the platform of activated sludge process design.

Simulation of the performance of aerobic granular sludge SBR using modified ASM3 model

The activated sludge model No. 3 (ASM3) was modified to describe the biological reactions in aerobic granular sludge SBR. The simultaneous storage and growth, nitrification and denitrification were all accounted for in modified model. The sensitivities of effluent COD, NH4+–N, and TN toward the stoichiometric and kinetic coefficients were analyzed. A standard set of parameters obtained from a combination of literature data was chosen for the model. The experimental results for the time profile of COD, NH4+–N, and TN in a typical cycle were used to verify the ASM3 model. The verification results show the model established is applicable for simulating the performance of an aerobic granule-based SBR. A comparison of the measured and predicted values of substrate removal for both the modified ASM3 and the original ASM3 was also performed. The verification and comparison results show the modified ASM3 model describes the aerobic granule-based SBR better and more mechanistically.

Modeling of partial nitrification and denitrification in an SBR for leachate treatment without carbon addition

A process of partial nitrification and denitrification in a sequencing batch reactor (SBR) treating leachate was simulated by applying a modified version of activated sludge model no. 3 (ASM3), named ASM3_2step. This model modifies the ASM3 model by separating nitrification and denitrification into two steps with nitrite as an intermediate substrate. Three periods, including long term period, steady state and cycle evolution, were used for calibration. Three main processes were observed, including biomass production, nitrification (focusing on nitrite accumulation) and denitrification. The kinetic and stoichiometric parameters (\( \mu_{{{\text{A\_NH}}}} \), \( Y_{{{\text{A\_NH}}}} \), \( Y_{{{\text{A}}\_{\text{NO}}_{2} }} \), \( Y_{{{\text{H}}\_{\text{O}}_{2} }} \), bA, \( K_{{{\text{A\_NH}}}} \)), were determined from biokinetic and respirometry tests. Some of the default values of kinetic and stoichiometric parameters available in the ASM3 model and in the literature were kept constant, while some others were adjusted step by step until observed state variables fit with experimental data. The maximum specific growth rate of nitrite oxidizing bacteria (0.108 day−1) (simulated by the model) and that of ammonium oxidizing bacteria (0.61 day−1) (from biokinetic tests) are the parameters which have the highest influence on the nitrite accumulation, even more than oxygen supply intensity or Kla value. Other important parameters were \( K_{{{\text{AO\_NH}}}} \) and \( K_{{{\text{AO}}\_{\text{NO}}_{2} }} \), calibrated at the values of 1.37 and 1.59 mg O2/L, respectively. The modified model and values of the kinetic and stoichiometric parameters obtained from the modeling process will be used for optimization of the partial nitrification in the next study.

A systematic model calibration methodology based on multiple errors minimization method for the optimal parameter estimation of ASM1

A one-step model calibration methodology of the activated sludge model no. 1 (ASM1) of a full-scale wastewater treatment plant (WWTP) is proposed. First, the key parameters among all parameters of the ASM1 model are selected by sensitivity analysis based on the effluent quality index. Second, multiple response surface methodology (MRSM) is conducted to find the optimal parameter values of the ASM1 model. Lastly, an MRSM analysis is conducted in order to determine the optimal parameter values. This study was conducted in order to develop a new systematic model calibration methodology that can greatly help the modeler to find the optimal solution by selecting the key parameters and optimizing the parameters. In two case studies of simple activated sludge process and a full-scale plant, the experimental results indicated that the calibrated models can improve the prediction quality of the ASM model and the efficiency of the modeling.

Studies of Computational Model Simulation for Nitrogen Removal Based on ASM1

Activated sludge process is generally applied on biological wastewater treatment. The Activated sludge Model No.1 (ASM1) is a mathematical description of biochemical processes in the reactor for nitrogen and chemical oxygen demand removal. ASM1 model was used to simulate the concentrations of components in leaving water with single-stage completely mixed CSTR (continuously stirred tank reactor) assumed. According to the concentrations of components in entering water of published data, curve simulation results of SNH and SNo show that the nitrogen removal process follows the nitrification-denitrification principle. And the steady-state results of 10 kinds of selected components indicate the simulation of the components concentration of leaving water is relatively accurate,and the nitrogen removal effect is obvious. The simulation system can provide effective technical support for wastewater treatment of actual plant.

Modelling microbial population dynamics in nitritation processes

In the wastewater treatment industry nitrite is no longer viewed as a toxic and undesirable intermediate in the biological oxidation chain transforming ammonium into nitrate. On the contrary, it is receiving growing attention as the pivotal component in a variety of new processes for biological nutrient removal. These new practises aim at saving energy and resources through the nitritation shortcut as an alternative to full nitrification. In order to understand the biological and engineering implications of nitritation, models have to be adapted to these new process conditions and related changes in microbial community. For this reason a previous modification of the ASM3 model [Iacopozzi, I., Innocenti, V., Marsili-Libelli, S., Giusti, E. 2007. A modified Activated Sludge Model No. 3 (ASM3) with two-step nitrification-denitrification. Environmental Modelling & Software 22: 847–861] was adapted to these particular process conditions, that the conventional models fail to reproduce satisfactorily. As with many new nitrogen removal processes, the nitritating condition does not occur spontaneously on a major scale, but it must be induced and maintained through computer control. The data used to calibrate this modified model were obtained from a long-horizon experiment in which a pilot-scale Sequencing Batch Reactor (SBR) fed with landfill leachate was kept in nitritating conditions. In this paper we set out to investigate the following points: (a) demonstrate that our previous two-step nitrification model could be adapted to describe the nitritating condition; (b) provide a thorough sensitivity/identifiability assessment of this new model, since no general sensitivity study on two-step nitrification models is available as yet; (c) try to relate the observed changes in parameter values to the possible modifications in microbial inventory during the shift from nitrification to nitritation, even if the available data were very scarce. On the first count, the model was modified by fully separating the nitrite and nitrate denitrification routes (a partial decoupling was already attempted in the previous model) and using the mixed substrate assumption. In this way, correct anoxic respiration rates and substrate consumption were obtained even when the oxidation was limited to nitrite alone. The second aspect was investigated by carrying out a complete sensitivity study considering several output combinations and ranking the model parameters according to their identifiability, showing that the most sensitive parameters are those related to the microbial characteristics. For the third aspect, several calibration “windows” were selected, in which nitrite and nitrate measurements were available, and the identifiable parameters were calibrated with each data set. From the examination of the parametric variations in the calibration windows it can be concluded that the nitritating conditions represent a critical process condition forcing drastic changes in the microbial inventory, which may be partly reflected by parametric changes.

Linearization of the full activated sludge model No 1 for interaction analysis

This paper deals with the linearization of the full activated sludge model No 1 (ASM1) in the scope of interaction analysis. For consistency, the linearization procedure is developed and validated within the BSM1 simulation benchmark framework. It is based on reaction rate approximation by linear combinations of states. The linear rate models are identified and incorporated in the mass balance equations, yielding a linear locally equivalent to the ASM1 model. Linear models for anoxic and aerated compartments are proposed. It is observed that the presented models track very closely the nonlinear ASM1 responses to various influent data. The key feature of this linearization strategy is that the gotten linear version of the ASM1 model is linear time invariant (LTI) and that it conserves the states biological interpretation and the original ASM1 dimension. It allows, therefore, application of interaction analysis methods and makes it possible to determine motivated control configurations for the ASM1 model.

A thermodynamic analysis of the activated sludge process: Application to soybean wastewater treatment in a sequencing batch reactor

AbstractA bioenergetic methodology was integrated with a modified activated sludge model No.1 (ASM1) to analyze the activated sludge process, with the treatment of soybean‐processing wastewater as an example. With the bioenergetic methodology established by McCarty and coworkers, the microbial yield was predicted and the overall stoichiometrics for biological reactions involving the key chemical and biological species in activated sludge were established. These obtained parameters were related to the ASM1 model, which was modified after coupling the biological reactions in activated sludge with electron balances. This approach was able to approximately describe the treatment of soybean wastewater by activated sludge in a sequencing batch reactor in terms of substrate utilization, biomass growth, and the elector acceptor consumption. Such an attempt provides useful information for accurate modeling of the complex activated sludge process. © 2009 American Institute of Chemical Engineers AIChE J, 2009