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The treatment of wastewater is highly challenging due to large fluctuations in flowrates, pollutants, and variable influent water compositions. A sequencing batch reactor (SBR) and modified SBR cycle-step-feed process (SSBR) configuration are studied in this work to effectively treat municipal wastewater while simultaneously removing nitrogen and phosphorus. To control the amount of dissolved oxygen in an SBR, three axiomatic control strategies (proportional integral (PI), fractional proportional integral (FPI), and fuzzy logic controllers) are presented. Relevant control algorithms have been designed using plant data with the models of SBR and SSBR based on ASM2d framework. On comparison, FPI showed a significant reduction in nutrient levels and added an improvement in effluent quality. The overall effluent quality is improved by 0.86% in FPI in comparison with PI controller. The SSBR, which was improved by precisely optimizing nutrient supply and aeration, establishes a delicate equilibrium. This refined method reduces oxygen requirements while reliably sustaining important biological functions. Focusing solely on the FPI controller's performance in terms of total air volume consumption, the step-feed SBR mechanism achieves an excellent 11.04% reduction in consumption.

Wastewater treatment plants (WWTPs) are high-energy-consuming units. Reasonable operation strategies can enable WWTPs to meet discharge standards while reducing the operating cost. In this study, the activated sludge model 2d (ASM2d), Pareto analysis of variance (ANOVA), and response surface methodology (RSM) were jointly used to simulate and optimize the operation of a lab-scale anaerobic-anoxic-oxic (AAO) reactor. The optimization objective was to determine the optimal design and operational parameters (DOPs) that could enhance both pollutant removal and energy saving. The DOPs that had significant influence on the optimization objective, such as sludge retention time (SRT), dissolved oxygen (DO), and the ratio of biodegradable chemical oxygen demand to total nitrogen (BCOD/TN), were identified by Pareto ANOVA. The optimal DOPs with SRT of 15 days, DO concentration of 0.5 mg/L, and BCOD/TN of 5.21 were determined by RSM. Under the optimal conditions, the removal efficiencies of NH4+-N, total nitrogen (TN), and total phosphorus (TP) were 96.2%, 76.8%, and 92.8%, respectively, and the annual operating cost was $26.4. Furthermore, this combination of DOPs was validated using a pilot-scale AAO system. The TN and TP removal efficiencies were improved by 11.0% and 5.0%, respectively, and the annual operating cost could be reduced by 15.0%. Overall, this study confirmed that the method integrating ASM2d with Pareto ANOVA and RSM was effective in optimizing wastewater treatment processes.

The operation of a wastewater treatment plant (WWTP) is a typical complex control problem, with nonlinear dynamics and coupling effects among the variables, which renders the implementation of real-time optimal control an enormous challenge. In this study, a Q-learning algorithm with activated sludge model No. 2d-guided (ASM2d-guided) reward setting (an integrated ASM2d-QL algorithm) is proposed, and the widely applied anaerobic-anoxic-oxic (AAO) system is chosen as the research paradigm. The integrated ASM2d-QL algorithms equipped with a self-learning mechanism are derived for optimizing the control strategies (hydraulic retention time (HRT) and internal recycling ratio (IRR)) of the AAO system. To optimize the control strategies of the AAO system under varying influent loads, Q matrixes were built for both HRTs and IRR optimization through the pair of based on the integrated ASM2d-QL algorithm. 8 days of actual influent qualities of a certain municipal AAO wastewater treatment plant in June were arbitrarily chosen as the influent concentrations for model verification. Good agreement between the values of the model simulations and experimental results indicated that this proposed integrated ASM2d-QL algorithm performed properly and successfully realized intelligent modeling and stable optimal control strategies under fluctuating influent loads during wastewater treatment.

Oxic-settling-anaerobic (OSA) process has been introduced into the treatment line of wastewater in order to upgrade activated sludge processes and to reduce the production of excess sludge. The aim of the present study was to simulate the performance of an OSA pilot plant by implementing the Activated Sludge Model No.2d (ASM2d) into a mathematical modelling software (BioWin). The stepwise calibration, performed both by off-line experiments and software dynamic calibration, was carried out in a heuristic way, adjusting the parameters values that showed a major influence to the effluent and internal concentrations. All the reduction factors introduced into ASM2d to simulate the processes occurring in anoxic and anaerobic conditions were lowered in order to reproduce the concentrations of interest. In addition, the values of parameters of the PAOs (polyphosphate accumulating organisms)-related process (namely qPHA and YPO4) were found lower than those usually adopted. In general, theoretical results were in good agreement with the experimental data obtained from plant’s operation, showing an accurate predictive capacity of the model. Good performance was achieved considering the phosphorus removal related process, while some failures were detected in COD and ammonia simulations.

A comprehensive model for nitrous oxide (N2O) emissions in an anaerobic/oxygen-limited aerobic (A/OLA) process is proposed here. This paper includes the following main innovations: (i) adding the phosphorus-accumulating organism (XPAO) denitrification pathway to the contribution of N2O emissions; (ii) considering the biological removal of organic matter and phosphorus and predicting the effect of influent phosphorus concentration on N2O emissions via an increase in the influent phosphorus concentration; and (iii) determining the effect of XPAO on N2O production in a simultaneous nitrification, denitrification and phosphorus removal (SNDPR) system by sensitivity analysis. The results suggested that the simulated data matched the measured data well. The predominant pathways of N2O emissions in the process of A/OLA were the ammonium-oxidizing bacterium (XAOB) denitrification pathway and the heterotrophic bacterium (XH) denitrification pathway, while the incomplete hydroxylamine (NH2OH) oxidation pathway and the XPAO denitrification pathway contributed less to N2O emissions. The metabolic activity of XPAO had a significant effect on N2O emissions, and increasing the influent phosphorus concentration was beneficial for reducing the release of N2O. This study is expected to provide a meaningful reference for reducing N2O emissions in wastewater treatment engineering.

Detailed knowledge on the composition of the influent going into the wastewater treatment system is essential for the development of a reliable computer model. In the context of WWTPs (wastewater treatment plants), the wastewater characteristics are not only important for activated sludge system modelling, but also have an impact on the appropriate control of single unit operations. The aim of this study was to evaluate the concepts of COD (chemical oxygen demand) fractionation measurement in municipal wastewater with a respirometric method in control, and modelling the biological treatment processes at WWTP using the modified Activated Sludge Model no. 2d (ASM2d) developed by Drewnowski and Makinia. The batch OUR (oxygen uptake rate) test results and COD measurements obtained at BNR plant (96,000 m3/d) in Gdansk (Poland), were compared and evaluated with the main BNR (biological nutrient removal) WWTP (144,000 m3/d) located in Malaga (Spain). Respirometric tests and COD fractionation provided the experimental database for the comparison of the wastewater characteristics and model predictions at both large WWTPs. Some parameters, such as the heterotrophic growth yield (YH) coefficient, required calibration/validation of the range (YH = 0.64 and 0.74 gCOD/gCOD for Gdańsk and Malaga WWTP, respectively) to fit the modified ASM2d. The crucial issue when dealing with the newly developed model and proposed wastewater characterization for both study plants were extremely low and high values of the XS/XI ratio, which can be used to control full-scale WWTP and balance the solid retention time (SRT) in activated sludge systems.

This paper examines the effect of different model assumptions when describing biological nutrient removal (BNR) by the activated sludge models (ASM) 1, 2d & 3. The performance of a nitrogen removal (WWTP1) and a combined nitrogen and phosphorus removal (WWTP2) benchmark wastewater treatment plant was compared for a series of model assumptions. Three different model approaches describing BNR are considered. In the reference case, the original model implementations are used to simulate WWTP1 (ASM1 & 3) and WWTP2 (ASM2d). The second set of models includes a reactive settler, which extends the description of the non-reactive TSS sedimentation and transport in the reference case with the full set of ASM processes. Finally, the third set of models is based on including electron acceptor dependency of biomass decay rates for ASM1 (WWTP1) and ASM2d (WWTP2). The results show that incorporation of a reactive settler: (1) increases the hydrolysis of particulates; (2) increases the overall plant's denitrification efficiency by reducing the SNOx concentration at the bottom of the clarifier; (3) increases the oxidation of COD compounds; (4) increases XOHO and XANO decay; and, finally, (5) increases the growth of XPAO and formation of XPHA,Stor for ASM2d, which has a major impact on the whole P removal system. Introduction of electron acceptor dependent decay leads to a substantial increase of the concentration of XANO, XOHO and XPAO in the bottom of the clarifier. The paper ends with a critical discussion of the influence of the different model assumptions, and emphasizes the need for a model user to understand the significant differences in simulation results that are obtained when applying different combinations of ‘standard’ models.

An environment-friendly decentralized wastewater treatment process that is comprised of activated sludge process (ASP) and wetland vegetation, named as vegetation-activated sludge process (V-ASP), was developed for decentralized wastewater treatment. The long-term experimental results evidenced that the vegetation sequencing batch reactor (V-SBR) process had consistently stable higher removal efficiencies of organic substances and nutrients from domestic wastewater compared with traditional sequencing batch reactor (SBR). The vegetation allocated into V-SBR system could not only remove nutrients through its vegetation transpiration ratio but also provide great surface area for microorganism activity enhancement. This high vegetation transpiration ratio enhanced nutrients removal effectiveness from wastewater mainly by flux enhancement, oxygen and substrate transportation acceleration, and vegetation respiration stimulation. A mathematical model based on ASM2d was successfully established by involving the specific function of vegetation to simulate system performance. The simulation results on the influence of operational parameters on V-ASP treatment effectiveness demonstrated that V-SBR had a high resistance to seasonal temperature fluctuations and influent loading shocking.

Hydrolysis is an important process in biological wastewater treatment and is known to be the rate-limiting step in organic carbon removal from municipal or industrial wastewater. The influence of the readily biodegradable chemical oxygen demand fraction in biological wastewater treatment systems has been extensively investigated, but little is known about the effects of slowly biodegradable substrate (XS) on denitrification and enhanced biological phosphorus removal. The biodegradation of XS is initiated by hydrolysis, which is an integral part of activated sludge models, such as the Activated Sludge Model no. 2d (ASM2d). This process is slower than heterotrophic growth and thus becomes the rate-limiting step for the biodegradation of organic compounds. The aim of this study was to evaluate different concepts of modeling the hydrolysis process using the original and modified version of ASM2d. Batch test results obtained at a large biological nutrient removal (BNR) plant in Gdansk (Poland) provided an experimental database for comparison of the two model predictions. Both models were compared in terms of their predictions for the most important process rates in BNR activated sludge systems. In comparison with the orginal ASM2d, the modified model had no or only minor effect on the predicted nitrate utilization rate, phosphate release rate and anoxic/aerobic phosphate uptake rate, but better predicted the oxygen uptake rate. The average ARDs (average relative deviations) were 19.0 and 29.3% (original ASM2d) vs. 13.4 and 20.4% (modified ASM2d), respectively, for the settled wastewater without pretreatment and after coagulation–flocculation.

The Activated Sludge Model No. 2d (ASM2d) presents a model for biological phosphorus removal with simultaneous nitrification-denitrification in activated sludge systems. ASM2d is based on ASM2 and is expanded to include the denitrifying activity of the phosphorus accumulating organisms (PAOs). This extension of ASM2 allows for improved modeling of the processes, especially with respect to the dynamics of nitrate and phosphate.