Activated Sludge Model No. 1 Research Articles

Wastewater treatment plant design and modeling for the city of Erzurum

Currently large amounts of wastewater are produced by domestic and industrial activities. Discharge of wastewater to the receiving environment without treatment causes significant health and environmental problems. Modeling and optimization of Wastewater Treatment Plants (WWTP) developed to treat domestic wastewater play key roles in determining unit components, design parameters and operation conditions. Several models were proposed to predict the treatment performance in WWTP. The Activated Sludge Model No. 1 (ASM1) is one of the commonly-used standard models developed to better understand removal of carbonaceous and nitrogenous materials. In this study, a WWTP is proposed for domestic wastewater using grit chamber, circular primary and secondary clarifiers, completely-mixed aeration tank, sludge thickener, sludge dewatering and anaerobic digestion processes together. The WWTP was modeled with ASM1 noting the topographic and meteorological features of the city. The treatment performances with wastewater temperatures of 10°C and 20°C were investigated for this plant, operating at high elevation. Removal efficiencies at 20°C were 95.7%, 92.2%, 97.9% and 99.2% for MLSS, COD, BOD and NH4, while effluent concentrations were 14.83, 48.51, 6.55 and 0.3 mg L-1, respectively. At 10°C, removal efficiencies were 88.9%, 88%, 93.2%, and 26.9%, while effluent concentrations were 38, 75, 21.83 and 26.13 mg L-1, respectively. A clear reduction was observed in nitrogenous material removal at low temperatures. Additionally, keeping dissolved oxygen concentration in the aeration tank at 1.5 mg L-1 with PID control increased nitrification efficiency by 30%. The findings reveal the importance of modeling studies during planning of WWTP.

A linear reduced-order model for the activated sludge process for the integration into a mixed-integer linear energy system optimisation model

Conventional wastewater treatment plants consume significant amounts of electricity. The constant aeration of the wastewater in order to foster the growth of microorganisms or the pumping of wastewater are two examples for energy-intensive processes within a plant. Case studies have shown that switching off blowers and inlet pumps for a certain period of time is possible without a loss in water quality. This yields a potential for wastewater treatment plants to provide demand response (DR) to the power system and thereby increase overall system flexibility. So far, the DR potential has only been quantified for individual plants, while the effects of large-scale DR provision by the wastewater treatment sector for the power system have not yet been studied. One reason for this is the lack of optimisation models which include both the wastewater treatment process and the power system operation in sufficient detail. Our model tackles this gap in the literature by providing a reduced-order linear biochemical model for the activated sludge process within a WWTP that can be incorporated into an operational energy system model. The results show that the effluent concentrations are predicted well by the linear reduced-order model in comparison to the results of the Standard Activated-Sludge model No. 1 (ASM1). Potential model applications are the variation of the airflow rate within a certain range and the variation of liquid influent flow rate to the system, which is a result of electricity load shedding of the inlet pumps and the blowers connected to the activated sludge tank.

Modelling greenhouse gas emissions from biological wastewater treatment by GPS-X: The full-scale case study of Corleone (Italy)

Greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs) can affect climate change and must be measured and reduced. Mathematical modelling is an attractive solution to get a tool for GHG mitigation. However, although many efforts have been made to create reliable tools that can simulate “sustainable” full-scale WWTP operation, these studies are not considered complete enough to include GHG emissions and energy consumption of biological processes under long-term dynamic conditions. In this study, activated sludge model no. 1 (ASM1) was modified to model nitrous oxide (N2O) emissions with a plant-wide modelling approach. The model is novel compared to the state of the art since it includes three steps denitrification, all N2O production pathways and its stripping in an ASM1. The model has been calibrated and validated through long-term water quality and short-term N2O emissions data collected from Corleone (Italy) WWTP. Different dissolved oxygen (DO) concentrations and return sludge (RAS) ratios were tested with dynamic simulations to optimise the full-scale WWTP. The scenarios have been compared synergistically with effluent quality, direct GHG emissions, and energy footprint by the water-energy‑carbon coupling index (WECCI). This modelling study is novel as it fully covers long-term calibration/validation of the model with N2O measurements and tests the dynamic optimisation. Decision-makers and operators can use this new model to optimise GHG emissions and treatment costs.

Bioprocess Modelling, Intensification, and Control


 
 
 Chemical bio-process intensification, driven by the need for sustainability and cost-effectiveness, has gained significant attention. This study explores dynamic intensification (DI), a strategy to enhance efficiency by modifying system dynamics, operation, and control. Two key approaches are investigated: intensification by design, involving deliberate changes to physical and chemical aspects, and intensification by control, optimizing process parameters and feedback loops.
 The research focuses on the Optimal Periodic Control (OPC) method, dating back to the 1960s but now revisited with modern technology. To investigate the feasibility and effectiveness of dynamic intensification, a comprehensive methodology encompassing modeling, optimization, linearization, dynamic intensification, and control was designed. This methodology ensures systematic and standardized testing of DI in various bioprocesses within the industry.
 Through rigorous case studies, such as Activated Sludge Model No. 1 (ASM1) and an antibiotic perfusion bioreactor, the study demonstrates the practical benefits of dynamic intensification, including enhanced process efficiency and control. Applying model predictive control (MPC) further improves process efficiency, and the intensified systems are thoroughly compared to their respective base cases.
 The insights gained from this research contribute to advancements in bioprocessing technologies across industries, paving the way for sustainable and efficient engineering practices. Engineers can leverage this knowledge and the developed methodology to optimize chemical bioprocesses through innovative intensification strategies, ultimately promoting more eco-friendly and economical bio-processes. The study's comprehensive methodology offers valuable insights and understanding for bioprocess engineers seeking to enhance system efficiency and contribute to a greener future.
 
 

The Design and Performance Prediction Model of an Integrated Scheme of a Membrane Bioreactor and Anaerobic Digester for the Treatment of Domestic Wastewater and Biowaste

An innovative and integrated scheme that encompasses two well-established waste treatment technologies, the aerobic biological degradation of organic matter bioprocess via membranes and anaerobic digestion, was demonstrated as a zero-waste approach that may effectively treat wastewater and biowaste in an integrated and symbiotic manner. Aiming to create a tool for the design, monitoring, and control of the scheme, prediction models were developed, validated, and implemented for the process simulation of the integrated scheme. The minimization of selected objective functions led to the estimation of the models’ parameters. The activated sludge model no. 1 (ASM1) was adopted for the simulation of the aerobic membrane bioreactor. The kinetic parameters were calibrated using volatile suspended solids and total nitrogen as the objective functions permitting the model to simulate the bioprocess satisfactorily (Nash–Sutcliffe efficiency > 0.86) and to calculate the concentration of the active biomass. The predominance of heterotrophic bacteria (4300 to 9770 mg COD/L) over autotrophic biomass (508 to 1422 mg COD/L) was showcased. For the anaerobic process unit, a simplified anaerobic digestion model 1 ADM1-R4 was used, and the first-order hydrolysis constants (kch 0.41 d−1, kpr 0.25 d−1, kli 0.09 d−1) and microbial decay rate (kdec 0.02 d−1) were evaluated, enabling an accurate prediction of biogas production rates. A full-scale implementation of the integrated scheme was conducted for a decentralized waste treatment plant in a small community. Preliminary design calculations were performed in order to estimate the values related to certain process and technical parameters. The performance of this full-scale plant was simulated by the developed model, presenting clear benefits for practical applications in waste treatment plants.

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.

A model of reactive settling of activated sludge: Comparison with experimental data

A non-negligible part of the biological reactions in the activated sludge process for treatment of wastewater takes place in secondary settling tanks (SST) that follow biological reactors. It is therefore of interest to develop models of so-called reactive settling that describe the spatial variability of reaction rates caused by the variation of local concentration of biomass due to hindered settling and compression. A reactive-settling model of an SST is described by a system of nonlinear partial differential equations and a numerical scheme is introduced for the simulation of hindered settling of flocculated particles, compression at high concentrations, dispersion of the flocculated particles in the suspension, dispersion of the dissolved substrates in the fluid, and the mixing that occurs near the feed inlet. The model is fitted to experiments from a pilot plant where the SST has a varying cross-sectional area. For the reactions, the Activated Sludge Model No. 1 (ASM1) is used with temperature-adjusted standard coefficients. The constitutive functions for hindered settling and compression are calibrated to a series of conventional batch settling experiments after the initial induction period of turbulence and reflocculation has been transformed away. The overall conclusion is thus that a careful treatment of batch-settling data to calibrate the sedimentation-compression model is sufficient to ensure good predictability of the reactive sedimentation process in a pilot SST, while the optional inclusion of hydrodynamic dispersion (modelled with two parameters) or a term modelling the mixing of the suspension near the feed inlet at most marginally improve predictability.

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.

A moving-boundary model of reactive settling in wastewater treatment. Part 2: Numerical scheme

A numerical scheme is proposed for the simulation of reactive settling in sequencing batch reactors (SBRs) in wastewater treatment plants. Reactive settling is the process of sedimentation of flocculated particles (biomass; activated sludge) consisting of several material components that react with substrates dissolved in the fluid. An SBR is operated in cycles of consecutive fill, react, settle, draw, and idle stages, which means that the volume in the tank varies and the surface moves with time. The process is modelled by a system of spatially one-dimensional, nonlinear, strongly degenerate parabolic convection-diffusion-reaction equations. This system is coupled via conditions of mass conservation to transport equations on a half line whose origin is located at a moving boundary and that models the effluent pipe. A finite-difference scheme is proved to satisfy an invariant-region property (in particular, it is positivity preserving) if executed in a simple splitting way. Simulations are presented with a modified variant of the established activated sludge model no. 1 (ASM1).

A generalized whole-cell model for wastewater-fed microbial fuel cells

A comprehensive mathematical modeling of wastewater-fed microbial fuel cells (MFC) demands an in-depth process understanding of the main electrical and bioelectrochemical interactions at both electrodes. In this study, a novel holistic simulation approach using a low-parameterized model was applied to predict pollutant transport, conversion, and electrical processes of mixed-culture single-chamber MFCs. The proposed whole-cell model couples the combined bioelectrochemical-electrical model with the well-established Activated Sludge Model No.1 (ASM1) and specific equations from ASM2. The cathodic gas–liquid mass transfer of oxygen and free ammonia nitrogen was described in terms of a diffusion film model, while the diminishing diffusivity due to salt deposits was considered via a fouling decline kinetic model. The predictive capacity of the model was validated using experimental data of three continuous-flow single-chamber MFCs operated with municipal wastewater for 150 days. Electrochemical parameters were estimated in real-time by pulse-width modulated connection of the external electrical load resistance. Following a sensitivity analysis, the most relevant model parameters were optimized through the Monte-Carlo Markov-Chain method using the adaptive Metropolis algorithm. All other parameters were adopted from benchmark simulation studies. The simulated relative contributions of aerobic carbon oxidation, denitrification, electrogenesis, and methanogenesis to the total COD removal rate were 21–22%, 44–45%, 21–25%, and 9–14%. Overall, the presented whole-cell model is able to successfully predict the evolution of electricity generation, methane production, and effluent concentrations (soluble COD and total ammonia nitrogen) under different hydraulic conditions and organic loading rates.

Modelling of micropollutant fate in hybrid growthsystems: model concepts, Peterson matrix, and application to a lab-scale pilot plant.

Modelling the fate of micropollutants in different wastewater treatment processes is of present concern. Moreover, during the last few years, there has been an increasing interest in the development of hybrid reactors whichcontainbothsuspended biomass and biofilm. Here, a new model developed which tries to determine the fate of micropollutants in hybrid reactors such as moving bed biofilm reactor (MBBR) and called the ASM-biofilm-MPs model considered the main mechanisms leading to the micropollutant removal (sorption/desorption, biodegradation, cometabolism) in hybrid reactors. This dynamic model describes the fate of micropollutants in a hybrid reactor using first-order kinetics for biotransformation and sorption/desorption equations. Also, it considered the reactions for carbon oxidation, nitrification, and denitrification in attached and suspended biomass under aerobic conditions. The mathematical model consists of three connected models for the simulation of micropollutants, suspended biomass, and biofilm. Biochemical conversions are evaluated according to the Activated Sludge Model No. 1 (ASM1) for both attached and suspended biomass. The model is applied for a laboratory MBBR, which fed with synthetic wastewater containing 4-nonylphenol (4-NP) asmicropollutant, and accurately describes the experimental concentrations of COD, attached and suspended biomass, nitrogen, and 4-NP micropollutant obtained during 180days working at different loadings. The differences between simulations and experiments in all operational periods for sCOD, NH4-N, NO3-N, and attached and suspended biomass concentrations were less than 15%, 10%, 10%, 5% and 5%, respectively. Finally, the contribution of adsorption and biodegradation mechanisms in the fate of 4-NP was calculated, when 4-NP concentration is set to 1µg/L (biodegradation = 86.5%, sorption = 5%) and 50µg/L (biodegradation = 55.9%, sorption = 34.7%).

Fractional order-based hierarchical controller design and evaluation with Bürger-Diehl settler model in a total nitrogen removal wastewater treatment process.

The primary objective of this study was to establish two-level structured control techniques based on the globally known benchmark simulation model no. 1 (BSM1) and the Bürger-Diehl settler model in order to improve effluent quality. The latter was based on the activated sludge model no. 1 (ASM1), while the classic Takacs model was superseded by the more recent Bürger-Diehl settler model with enhanced predictive potential. A two-level hierarchical control structure was considered to maintain the dissolved oxygen concentration basing on the ammonia levels and also a nitrate controller was considered to improve nitrogen removal efficiency. Fractional order PI controllers were considered at the secondary level and advanced control techniques, namely, MPC and fuzzy, were implemented at the primary level. Two advance control schemes, being, FPI-MPC and FPI-fuzzy were designed in the present work. The controllers were designed based on the plant model which was identified using prediction-error minimization method. It was observed that the implemented control strategies in consideration with the plant modifications showed a profound impact in improving the plant performance in terms of the effluent quality. FPI-fuzzy resulted in noticeable 60% and 53% reduction in total nitrogen violations for dry and storm climatic conditions, respectively.

Modeling granule-based completely autotrophic nitrogen removal over the nitrite (CANON) process in an SBR

AbstractBased on the simplified activated sludge model No. 1 (ASM1), a 1D biofilm model containing autotrophic and heterotrophic microorganisms was developed to describe the microbial population dynamics and reactor dynamics of completely autotrophic nitrogen removal over the nitrite in sequencing batch reactor (CANON SBR). After sensitivity analysis and calibration for parameters, the simulation results of NH4+-N concentration and NO2−-N concentration were consistent with the measured results, while the simulated NO3−-N concentration was slightly lower than the measured. The simulation results showed that the soluble microbial products had an extremely low concentration. The aerobic ammonia oxidation bacteria and anaerobic ammonia oxidation bacteria were the dominant microbial populations of the CANON system, while nitrite oxidization bacteria and heterotrophic bacteria were eliminated completely. The optimal ratio of air aeration load to influent NH4+-N load was about 0.18 L air/mgN. The operating condition of the reactor was optimized according to the simulation results, and the total nitrogen removal rate and the total nitrogen removal efficiency increased from 0.312 ± 0.015 to 0.485 ± 0.013 kg N/m3/d and from 71.2 ± 4.3 to 85.7 ± 1.4%, respectively.

Kinetic characterization of a low-dissolved‑oxygen oxic-anoxic process treating low COD/N tropical wastewater revealed selection of nitrifiers with high substrate affinity

The design of wastewater treatment plants in the tropics is largely based on default parameters from the studies in temperate climates. This may lead to suboptimal design, such as the intensive aeration required for biological nitrogen removal. To reduce the aeration energy, a low-dissolved‑oxygen oxic-anoxic (low-DO OA) process was developed for treating low chemical oxygen demand-to‑nitrogen (COD/N) tropical wastewater. This study calibrated the growth kinetic parameters of microbes in a conventional anoxic-oxic (AO) and a low-DO OA sequencing batch reactors (SBRs) based on a modified version of Activated Sludge Model No. 1 (ASM1). We selected three parameters to be calibrated, namely the maximum growth rate of heterotrophs (μH), maximum growth rate of nitrifiers (μA) and nitrifiers' affinity towards ammoniacal nitrogen (NH4+−N) (KNH). The low-DO OA SBR selected for microbes with a low μH (2.2 d−1), μA (1.49 d−1) and KNH (0.035 mgNH4+−NL−1), which supported the observed proliferation of K-strategist Nitrospira at low-DO condition (0.4 ± 0.2 mg O2 L−1). The calibrated parameters for the AO SBR (1.7 ± 0.2 mg O2 L−1) were significantly higher (μH=9.3 d−1, μA=4.49 d−1, KNH=6.3 mgNH4+−NL−1) than the low-DO OA SBR. The calibrated ASM1 adequately simulated the low-DO OA SBR performance under different sludge retention times. The findings demonstrated a kinetic insight into the unique K-strategist nitrifiers in a low-DO OA process. Moreover, this study reinforced the importance of using parameters for tropical wastewater rather than relying on default values from studies in temperate climates.

Sensitivity analysis and principal component analysis for the determination of the most influential kinetic parameters in activated sludge modeling

This study presents the results of a simulation work performed using activated sludge model no. 3 (ASM3) extended with biological phosphorus removal processes to determine the most influential kinetic parameters in the model prior to a comprehensive calibration and simulation work. Sensitivity analysis was performed for a total of 44 kinetic parameters separately and the results were compared with the base scenario in which all parameters are set to their defaults. Besides, principal component analysis was employed to extract patterns of the most influential parameters. The values of parameters were changed between 70% and 130% of their defaults and effluent concentrations as well as removal efficiencies for performance parameters were obtained to calculate normalized sensitivities of the model outputs with respect to each kinetic parameter. Results showed that, out of 44 kinetic parameters, 10 of them can be used for calibration purposes and the effects of the rest are negligible.

Two-Dimensional Steady-State Analysis of Selected Wastewater State Variables Using ASM3

Performance of activated sludge wastewater treatment plants are mainly dependent on bacterial growth, which is limited by many factors. These factors include availability of suitable substrate, limiting nutrients, environmental conditions, and energy. In activated sludge model no. 3 (ASM3), constituents in wastewater are divided into two main categories: carbonaceous compounds and nitrogenous compounds, which are further subdivided depending on their solubility and biodegradability. These compounds are not mutually independent; hence, the fate of one compound in the biological processes is affected by one or more of the other compounds. In this study, a steady-state analysis was conducted to investigate the effect of initial readily biodegradable substrate, oxygen, ammonia nitrogen, nitrite plus nitrate, and heterotrophic organisms’ concentrations on the effluent concentrations of readily biodegradable COD and nitrogen compounds. The studied ranges of the selected wastewater state variables were identified based on literature surveys including previous studies concerning domestic, industrial, and synthetic wastewaters. The results proved that the effluent readily biodegradable substrate and ammonia nitrogen concentrations are reduced as the initial dissolved oxygen and nitrite plus nitrate concentrations are increased. Moreover, better nitrification-denitrification process is achieved at lower initial readily biodegradable concentration leading to lower nitrite plus nitrate concentrations.

A coupled hydrodynamic‐biokinetic simulation of three‐phase flow in an oxidation ditch using CFD

AbstractCoupling the hydrodynamic and biokinetic models, was done on a lab‐scale oxidation ditch as the bioreactor of the activated sludge process and validated against the available experimental data. The simulation was carried out in three‐phase, three‐dimensional conditions with k‐є and Eulerian–Eulerian methods. A simplified activated sludge model No.1 (ASM1) has been added to transport terms to account for the biokinetic model. Rotatory speed for surface aerator was initially increased and its corresponding effects on solid volume fraction, dissolved oxygen, and velocity profile and values were observed. A 150 rpm increase in the rotational velocity resulted in 36% higher average liquid phase velocity for the one‐aerator arrangement, which was 3% more than that of the two‐aerator oxidation ditch. The 150% increase in the solid volume fraction led to a 10% reduction in the maximum liquid phase velocity. The effect of aerators number has been considered explicitly on baffle performance and liquid phase velocity profile. Finally, a new design for the aerator has been offered that provides an ordered flow field and optimal conditions for the performance of the baffle and oxidation process.

On the Use of Mathematical Models for Wastewater Treatment: A Review and Analysis of Activated Sludge Models ASM1 and ASM3

Mathematical models describing the dynamics of key biochemical processes in conventional activated sludge processes are commonly used to design and operate wastewater treatment plants. Since the introduction of the first activated sludge model, namely Activated Sludge Model No. 1 (ASM1), in 1987 by the International Water Association, ASM models received considerable attention and several extensions were suggested. In this study, we briefly review the literature on two important activated sludge models, ASM1 and ASM3. Our literature review indicates that despite the presence of many articles on ASM there is no study on the parameter sensitivity of these differential equation models. In the second part of the study, these two models are simulated in MATLAB with different initial values and parameter combinations to develop further insight into the model structures. In the third part of the study, experiments with ASM1 and ASM3 models are conducted in MATLAB and a basic sensitivity analysis is applied for the parameters of the two models.

An efficient hydrodynamic-biokinetic model for the optimization of operational strategy applied in a full-scale oxidation ditch by CFD integrated with ASM2

Oxidation ditches (ODs) are often used for wastewater treatment. However, limitations of ODs like high energy expenditure and increased sludge sedimentation hinder its wide application. In this study, the computational fluid dynamics (CFD) model integrated with Activated Sludge Model No. 2 (ASM2) was proposed and applied in a full-scale OD. The integrated model provided heterogeneous information on the characteristics of hydrodynamics and biokinetics of OD, especially with respect to the simulation of total phosphorus removal by CFD-ASM2 integration model for the first time. The simulated values of flow velocities, suspended solids (SS), dissolved oxygen, chemical oxygen demand, total nitrogen, ammonium nitrogen, and total phosphorus concentrations were well validated with the measured results, with the standard deviation errors of less than 5.56%, 0.28%, 0.74%, 7.39%, 3.17%, 5.27%, and 7.40%, respectively. Based on the integrated model, four different operational strategies were simulated. The proposed operational strategy of operating 7 surface aerators and 10 submerged impellers not only met the standard discharge requirements (GB 18918–2002) but also consumed less energy by 22.3%, compared with the original strategy of operating 9 surface aerators and 13 submerged impellers. Meanwhile, this proposed operational strategy also reduced the SS concentrations in the second and fourth channels, which was beneficial to elimination of sludge sedimentation. Moreover, the proposed operational strategy was successfully applied and validated in full-scale OD. The foregoing results collectively suggest that the CFD-AMS2 integration model is numerically capable to optimize the operational strategy of ODs.