Simulated Wastewater Treatment Plant Research Articles

Application of standardized methods to evaluate the environmental safety of polyvinyl alcohol disposed of down the drain.

The purpose of this research was to use polyvinyl alcohol (PVOH) 18-88 as a case study to evaluate the environmental fate, ecotoxicity, and overall safety profile of water-soluble, nonmodified PVOH polymers used in detergent films. An OECD 303A Wastewater Treatment Plant Simulation Study was conducted with dissolved organic carbon as the analytical endpoint to evaluate the removal of PVOH 18-88 during wastewater treatment. During the plateau phase, high levels of removal due to biodegradation were observed (average 97.4 ± 7.1, range: 88%-116%). The OECD 303A study quantitatively verified that surface water is the dominant receiving compartment for PVOH 18-88 post wastewater treatment. Acute algae, invertebrate, and fish embryo (fish embryo acute toxicity test [FET]) ecotoxicity studies quanitified the 50% lethal/effect concentration (L/EC50) for PVOH 18-88. Due to the potential for the chorion to impact PVOH 18-88 bioavailability, both chorionated and dechorionated FET tests were conducted. L/EC50 > 1000 mg/L for FET (chorionated and dechorionated), invertebrate, and algae were observed. The Sustainable Futures (US) and REACH (EU) frameworks were used to evaluate environmental risk. For the US assessment, the Exposure and Fate Assessment Screening Tool was used to predict the single day lowest flow over a 10-year period (1Q10) surface water concentration and the seven consecutive days of lowest flow over a 10-year period (7Q10) surface water concentration and compared with acute and chronic concentrations of concern. For the EUassessment, the European Union System for the Evaluation of Substances was used to predict local and regional exposure concentrations and compared to the predicted no effect concentration. For both regulatory assessments, the exposure concentrations were >2 orders of magnitude below the effect concentrations. Integr Environ Assess Manag 2024;20:1693-1705. © 2024 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Hydraulic simulation of an urban river affected by treated effluent based on signal processing theory and physically based models

Study regionThe Tonghui River–a treated effluent-affected urban river located in Beijing, China. Study focusInspired by the signal processing theory, this study presented a simulation scheme for the treated effluent-affected river based on hydrologic monitoring, pattern recognization, pattern extraction, and hydrologic/hydraulic modelling. It aimed to precisely depict the river flow patterns when detailed wastewater treatment plant effluent data was absent and to fill in the gap of the application of signal-based hydrological time series processing methods in physically based hydraulic simulation. New hydrological insights for the regionDiurnal and semidiurnal patterns caused by the wastewater treatment plant (WWTP) effluent were recognized from the water level series using the continuous wavelet transform. Due to their small amplitudes, they were masked during flood events but dominated the flow regime in dry seasons. Based on the discrete wavelet decomposition and Fourier series fitting, these periodical patterns were extracted and fitted. With a preliminarily calibrated hydraulic model and a linear signal amplifier, a simulated WWTP effluent was retrieved. Dry seasons simulation utilizing the simulated effluent obtained significantly better performance than using the average effluent data from the aspects of conventional evaluation metrics, cross-wavelet transform, and wavelet coherence.

Enhancing the Performance of a Simulated WWTP: Comparative Analysis of Control Strategies for the BSM2 Model

This study aimed to improve the performance of a wastewater treatment plant (WWTP) simulated with Benchmark Model No. 2 (BSM2). To achieve this objective, three control strategies were implemented and tested. The first control strategy aimed to maintain the concentration of nitrate and nitrite nitrogen (SNO) by controlling the external carbon flowrate (strategy A1), and the second control strategy aimed to maintain the ammonia and ammonium nitrogen (SNH) at a desired level with the use of a cascade controller (strategy A2). The third strategy was applied to control the total suspended solids (TSS) (strategy A3). Combinations of these strategies were considered (B1, B2, and B3 strategies), as well as the use of all three together (strategy C1). The control strategies presented in this paper were compared to the default control strategy of BSM2 to validate and identify the one that provided the best performance. The results revealed that the B1 strategy was the most environmentally friendly, while C1 obtained the highest overall performance. Several Monte Carlo simulations were performed for the validated control strategies, to identify the optimal setpoint values. For the C1 strategy, a second method of optimization regarding polynomial interpolation was considered. The applied optimization methods provided the optimal reference values for the PI (proportional integral) controllers.

The ASM2d model with two-step nitrification can better simulate biological nutrient removal systems enriched with complete ammonia oxidizing bacteria (comammox Nitrospira)

The discovery of comammox Nitrospira, a complete ammonia-oxidizing microorganism belonging to the genus Nitrospira, has brought new insights into the nitrification process in wastewater treatment plants (WWTPs). The applicability of Activated Sludge Model No. 2 d with one-step nitrification (ASM2d-OSN) or two-step nitrification (ASM2d-TSN) for the simulation of the biological nutrient removal (BNR) processes of a full-scale WWTP in the presence of comammox Nitrospira was studied. Microbial analysis and kinetic parameter measurements showed comammox Nitrospira was enriched in the BNR system operated under low dissolved oxygen (DO) and long sludge retention time (SRT). The relative abundance of Nitrospira under the conditions of stage I (DO = 0.5 mg/L, SRT = 60 d) was about twice of that under stage II conditions (DO = 4.0 mg/L, SRT = 26 d), and the copy number of the comammox amoA gene for stage I was 33 times higher than that for stage II. Compared to the ASM2d-OSN model, the ASM2d-TSN model simulated the performance of the WWTP under stage I conditions better, and the Theil inequality coefficient values of all the tested water quality parameters were lower than using ASM2d-OSN. These results indicate that an ASM2d model with two-step nitrification is a better choice for the simulation of WWTPs with the presence of comammox.

Zero‐dimensional modelling and bacterial characterization of an aerobic granular sludge reactor

AbstractBackgroundAerobic granular sludge (AGS) has emerged as a novel wastewater treatment technology and as a suppressing alternative to conventional activated sludge. The development of mathematical models of the AGS process, which can be used for wastewater treatment plant (WWTP) design and optimization, is therefore necessary to support successful implementation of AGS technology. This study aims to develop a zero‐dimensional (0D) AGS model that can be used in engineering practice for the above‐mentioned purposes.ResultsA laboratory AGS sequencing batch reactor (SBR), removing soluble organic substrate, nitrogen and phosphorus, was fed with artificial wastewater and modelled using a 0D approach. Model development was supported by bacterial characterization using 16S rRNA gene amplicon high‐throughput sequencing. The mathematical model was based on the activated sludge model no. 2d (ASM2d) and extended with both two‐step nitrification as implemented in the wastewater treatment plant simulator Sumo19 (Dynamita SARL) and ammonia nitrogen adsorption and desorption according to the Langmuir model. The variations of ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, orthophosphate phosphorus and dissolved oxygen concentrations during one cycle of the SBR were successfully reproduced by the model (all Pearson's r values ≥0.93 and all r2 ≥ 0.86).ConclusionsThe 0D modelling approach was proven to be applicable to AGS. It is possible that the 0D approach can fill the gap that has developed between engineering and research in the biofilm modelling community. The 0D modelling approach therefore merits further exploration using reactors fed with real wastewater, as well as on pilot and full‐scale WWTPs. © 2022 Society of Chemical Industry (SCI).

Combined Biological and Photocatalytic Degradation of Dibutyl Phthalate in a Simulated Wastewater Treatment Plant

The removal of organic pollutant in wastewater has become a major priority in water treatment. In this study, organic pollutant dibutyl phthalate (DBP) has been biologically and photocatalytically degraded in wastewater using modified transition metal dichalcogenides. The as-synthesized nanoparticles were characterized using various characterization techniques, which includes XRD, Raman, FT-IR, SEM, TEM, UV-Vis, XPS, PL, EIS, and photocurrent responses. The nanoparticles synthesized by slightly modified hydrothermal method depicted a hexagonal phase, as evidenced by XRD and Raman analyses. The biological degradation of 69% dibutyl phthalate was achieved. Moreover, the total organic carbon removal efficiency of 70% was further achieved. Incorporating biological and photocatalytic systems significantly improved dibutyl phthalate removal in secondary effluent by three folds when compared to the unilateral operating setup. The optimized parameters such as pH = 7, 5 ppm and DBP concentration with the addition of 10 mg catalysts loading were employed for the photocatalytic degradation of dibutyl phthalate in water. Pristine WS2 exhibited photocatalytic efficiencies of 46% after 60 min illumination. The use of dual system 3% Ce/Gd-WS2 exhibited the highest photodegradation of 85%, with a chemical oxygen demand of 80% and total organic carbon of 77%. The enhanced activity by the composite is attested to the formation of heterojunction exhibiting excellent charge separation and low rate of recombination. The 3% Ce/Gd-WS2 can be used up to seven times and still achieve a degradation of 56%.

Incentive Schemes Increase Risky Behavior in a Safety-Critical Working Task: An Experimental Comparison in a Simulated High-Reliability Organization

As financial incentive schemes have the tendency to increase risky behavior, we analyzed their effect on rule-related behavior in a safety-critical task. We compared risky behavior (in terms of the amount of rule violations) between three payment condition: continuous, up-front, and bonus pay. Fifty-nine participants were trained as production personnel to conduct a start-up procedure of a simulated wastewater treatment plant, representing a high reliability organization. During the 5-h experimental study, risky behavior could have been applied 48 times while building a simulated production year. The results show that the conditions with an incentive scheme (up-front and bonus pay) led to significantly more rule violations than the condition with continuous payment without an incentive scheme. Our study highlights the general increased risk effect of incentive schemes and provides a starting point for industries to assess their implicit and explicit incentive schemes.

Simultaneous bacterial inactivation and microcontaminant removal by solar photo-Fenton mediated by Fe3+-NTA in WWTP secondary effluents

Simultaneous microorganism inactivation and organic microcontaminant removal in municipal wastewater treatment plant (WWTP) secondary effluents by the solar photo-Fenton process mediated by Fe3+-NTA is studied in depth. To achieve this objective, different key aspects were addressed: (i) the effect of initial Fe3+-NTA concentration at 1:1 molar ratio (0.10-0.30 mM) and H2O2 concentration (1.47-5.88 mM), (ii) the effect of initial microorganism load (103 and 106 CFU/mL) and (iii) the impact of the disinfection target on treatment cost. The first stage of this work was carried out in simulated WWTP effluent spiked with 100 µg/L of imidacloprid (IMD) as model microcontaminant and inoculated with Escherichia coli (E. coli) K-12 as reference strain, in a pilot scale raceway pond reactor with 5-cm of liquid-depth. Secondly, the most cost-effective conditions were validated in actual WWTP effluent. The kinetic analysis revealed that increasing Fe3+-NTA concentration over 0.20 mM does not significantly reduce treatment time due to the limited effect caused on the volumetric rate photon absorption. Treatment cost is determined by the disinfection process, since IMD removal was always faster than E. coli inactivation. The most cost-effective strategy to achieve 10 CFU/100 mL of E. coli (Regulation EU 2020/741) was 0.20/4.41 mM Fe3+-NTA/H2O2, with a cost of 0.32 €/m3. A less restrictive disinfection target, 100 CFU/100 mL, allowed reducing reactant concentration and cost, 0.10/1.47 mM Fe3+-NTA/H2O2 and 0.15 €/m3, respectively. In both cases, no regrowth at 24 h and more than 90% of IMD removal were observed.

Greenhouse Gas Emission Assessment of Simulated Wastewater Biorefinery

A wastewater treatment plant (WWTP) can be considered a system where dirty water enters and fresh water (by means of treatment processes) and other co-products such as sludge and biogas exit. Inside the system, typically, the following steps occur: preliminary treatment, primary treatment, secondary treatment, tertiary treatment, disinfection, and solids handling. The system transforms biomass into several energy and non-energy products, which fall into the definition of a biorefinery. This research compares three simulated WWTP in terms of their environmental greenhouse gas (GHG) emission release to the atmosphere: a generic one (without co-product valorization), one that converts co-products into fertilizer, heat, and electricity, and a third one that converts co-products into heat, electricity, fertilizer, and bioplastic. Heat and electricity are used to provide its energy needs. The chosen impact category is GHG, and the aim is to project the best scenario to the European context in terms of GHG avoidance (savings). The scope is the upstream electricity and natural gas production, the in-use emissions, and the avoided emissions by substituting equivalent fossil-based products. The functional unit is 1 L of sewage (“dirty water”). The GHG savings are evaluated by comparing a generic WWTP scenario, without co-product valorization, with alternative scenarios of co-product valorization. Conventional LCA assuming all the emissions occurs at instant zero is compared to a more realistic environment where for each year, the average of the variable emission pulses occurs. Variable emissions pulses are taken from variable inflows data publicly available from European COST actions (COST Action 682 “Integrated Wastewater Management” as well as within the first IAWQ (later IWA) Task Group on respirometry-based control of the activated sludge process), within the later COST Action 624 on “Optimal Management of Wastewater Systems”). The GHG uncertainty is estimated based on the inputs benchmark data from the WWTP literature and by having different available global warming potential dynamic models. The conventional LCA versus dynamic LCA approach is discussed especially because a WWTP is by nature a dynamic system, having variable inputs along time and therefore variable output GHG emission pulses. It is concluded that heat needs are fully covered by biogas production in the anaerobic digester and combustion, covering its own energy needs and with a potential for heat district supply. Only 30–40% of electricity needs are covered by combined heat and power. Bioplastics and/or fertilizer yields potentially represent less than 3% of current European needs, which suggests the need to reduce their consumption levels. In comparison to generic WWTP, GHG savings are 20%, considering the uncertainty in the benchmark input assumptions. The former is much higher than the uncertainty in the dynamic global warming potential model selection, which means that the model selection is not important in this case study.

Model-Based Solution for Upgrading Nitrogen Removal for a Full-Scale Municipal Wastewater Treatment Plant with CASS Process

Aiming at providing cost-effective approach for upgrading the existing municipal wastewater treatment plants in the cold region of China to meet more stringent discharge standards of nitrogen removal, a full-scale sewage treatment plant with the CASS process was selected through focusing on biological process, key equipment and hydrodynamics in bioreactors by the activated sludge model 1 (ASM1) and computational fluid dynamics (CFD) model. Influent COD fractions and the key characteristic parameters (YH and bH) of the activated sludge were determined through the respirometry at temperatures of 10 °C and 20 °C, respectively. The layout of submerged agitator installation in the bioreactor of the CASS process was optimized through CFD simulation. The calculation of the average relative deviation (less than 20%) between simulated data and the operation data, demonstrated that the ASM1 model could be reasonably used in the wastewater treatment plant simulation. The upgrade solution based on modelling of ASM1 and CFD was successfully applied in practice, which not only made the effluent COD, NH4+-N and TN concentrations meet with the discharge standard of Grade I-A, but also reduced the energy consumption by 25% and 16.67% in summer and winter, respectively. After upgrading, microbial diversity increased in both summer and winter, with an especially significant increase of the relative abundance of denitrifying bacteria.

KMS platform: A complete tool for modeling chemical and biochemical reactors

Computer-based activities to study chemical kinetic principles have been widely used in engineering education for the last 60 years. These academic tools must be user-friendly for teachers and students and easy to adapt to practical cases. The Chemical and Environmental Engineering Group (GIQA) at University Rey Juan Carlos (URJC) has developed a Kinetic, Modeling and Simulation (KMS) platform for chemical and biochemical processes. The KMS platform provides different simulation applications programmed in Matlab® with a friendly interface design environment for users. In this work, we will focus on the Kinetics in Conventional Activated Sludge (KCAS) application, as part of the KMS platform. The design of kinetic models and the dynamic simulation of wastewater treatment plants are typically implemented by a variety of dedicated software, mostly developed for research and development purposes at universities, institutes or consulting companies. These programming tools have inherent weaknesses as simulators in virtual laboratories for academics, needing steep learning curves and lacking flexibility to evaluate complex problems, particularly in bachelor degrees programs that are not completely devoted to the mathematical modeling of processes. The simplicity and versatility of KCAS simulator make it very useful for students as starting educational tool to define kinetic models and to make the dynamic simulation of a conventional activated sludge reactor followed by a secondary decanter using different inlet streams or operation conditions. The students interact with the program through a friendly Graphical User Interface (GUI), and the results can be easily exported to a conventional spreadsheet in EXCEL© format files. With KCAS, the students can formulate kinetic models (potential models, diffusional models, Monod equations, etc.) to simulate the evolution from simple reaction systems, to complex biochemical models such as ASM (Activated Sludge Models) from the International Water Association (IWA). The KCAS simulator allows the students to enhance the understanding of complex interactions among the physical, chemical, and biological processes, reinforcing the acquisition of competences and learning skills in Environmental Engineering. The KCAS application was implemented as laboratory demonstration practice in subjects of different Engineering Degrees at URJC.

Fe3+-NTA as iron source for solar photo-Fenton at neutral pH in raceway pond reactors

This work presents, for the first time, a kinetic study of the solar photo-Fenton process at neutral pH mediated by the Fe3+-NTA complex (molar ratio 1: 1) applied to remove contaminants of emerging concern (CECs). To this end, wastewater treatment plant (WWTP) secondary effluents were treated in a raceway pond reactor (RPR) at pilot plant scale with 0.1 mM Fe3+-NTA and 0.88 mM H2O2 under average solar UVA irradiance of 35 W/m2. Sulfamethoxazole and imidacloprid, at 50 μg/L of initial concentration each, were selected as model CECs. Up to 40% of the sum of both model CECs was removed from simulated WWTP effluent by the Fe3+-NTA Fenton-like process, and >80% was removed by solar photo-Fenton. The effect of liquid depth in the reactor was evaluated, showing an increase of the treatment capacity from 12 mg CEC/m2·h to 18 mg CEC/m2·h when liquid depth increased from 5 to 15 cm. Afterwards, these results were validated with real WWTP effluents and compared with the results obtained with the Fe3+-EDDS complex under the same operating conditions. The same CEC removal rates were obtained with Fe3+-NTA and Fe3+-EDDS at 5 cm of liquid depth (kinetic constants of 0.110 min−1 and 0.046 min−1 for sulfamethoxazole and imidacloprid, respectively). Conversely, at 15 cm of liquid depth, the degradation rates were lower with Fe3+-NTA (kinetic constants of 0.034 min−1 for sulfamethoxazole and 0.017 min−1 for imidacloprid), whereas with Fe3+-EDDS the values were 0.076 min−1 and 0.047 min−1 for sulfamethoxazole and imidacloprid, respectively. Regarding process cost estimation, the use of NTA as iron chelate for solar photo-Fenton at neutral pH at pilot plant scale resulted very cost-effective (0.13–0.14 €/m3) in comparison with the use of EDDS (0.46–0.48 €/m3) at the two liquid depths tested.

Knowledge based recursive non-linear partial least squares (RNPLS)

Soft sensors driven by data are very common in industrial plants to perform indirect measurements of difficult to measure critical variables by using other variables that are relatively easier to obtain. The use of soft sensors implies some challenges, such as the colinearity of the predictor variables, the time-varying and possible non-linear nature of the industrial process. To deal with the first challenge, the partial least square (PLS) regression has been employed in many applications to model the linear relations between process variables, with noisy and highly correlated data. However, the PLS model needs to deal with the other two issues: the non-linear and time-varying characteristics of the processes. In this work, a new knowledge-based methodology for a recursive non-linear PLS algorithm (RNPLS) is systematized to deal with these issues. Here, the non-linear PLS algorithm is set up by carrying out the PLS regression over the augmented input matrix, which includes knowledge based non-linear transformations of some of the variables. This transformation depends on the system’s nature, and takes into account the available knowledge about the process, which is provided by expert knowledge or emulated using software tools. Then, the recursive exponential weighted PLS is used to modify and adapt the model according to the process changes. This RNPLS algorithm has been tested using two case studies according to the available knowledge, a real industrial evaporation station of the sugar industry, where the expert knowledge about the process permits the formulation of the relationships, and a simulated wastewater treatment plant, where the necessary knowledge about the process is obtained by a software tool. The results show that the methodology involving knowledge regarding the process is able to adjust the process changes, providing highly accurate predictions.

Dynamic Influent Generator for Alternative Wastewater Management with Urine Source Separation

AbstractThe simulation of wastewater treatment plants allows obtaining predictive results when one needs to understand, evaluate, optimize, or design a plant. However, one of the bottlenecks of sim...

Data-Driven Mode Identification and Unsupervised Fault Detection for Nonlinear Multimode Processes

In modern plants, industrial processes typically operate under different states to meet the different requirements of high-quality products. Many monitoring models for industrial processes were constructed based on the prior knowledge (the mechanism's model or the process data characteristics) to monitor such processes (called multimode processes). However, obtaining this prior knowledge is difficult in practice. Efficiently monitoring nonlinear multimode processes without any prior knowledge is an open problem that demands further exploration. Since data from different modes follow different distributions while data from the same mode are considered to be sampled from the same distribution, the modes of multimode processes can be uncovered based on the characteristics of the process data. This article proposes using a Dirichlet process Gaussian mixed model to classify the modes of multimode processes based on historical data, and then, determine the mode types of the monitored data. A nonlinear monitoring strategy based on the t-distributed stochastic neighbor embedding is then proposed to achieve nonlinear dimensionality reduction and visualize the data. Finally, a monitoring index that is integrated with support vector data description is constructed for comprehensive monitoring. The proposed nonlinear multimode framework completely realizes data-driven mode identification and unsupervised fault detection without knowing any prior knowledge. The effectiveness and feasibility of the proposed model are demonstrated using data from a simulated wastewater treatment plant.

Modelling performance of oxidation ditch in wastewater treatment plant by STOAT software

This paper adopted the IAWQ# 1 model based on ASM in STOAT software to model the treating performance of oxidation ditch. STOAT software is a free modeling package for numerical modeling and simulation of wastewater treatment plants (WWTP). The dynamic model evaluates the effects of influent water qualities (TN, TP and COD) and water flow rate on the pollutant removal efficiency. The model was able to predict the changing trend in terms of TN, TP and COD concentrations. The effluent TN and TP concentrations did not greatly affected by the change of influent TN and TP concentrations. The removal efficiency of TN was clearly stronger than that of TP. However, the COD removal performance of oxidation ditch was outstanding. Meanwhile, the water flow rate was of importance for the COD biodegradation efficiency. The increase of water flow rate was likely to decrease COD removal efficiency. The flow rate varied between 1000 and 10000 m3/h, and the effluent COD concentration varied from 118.98 to 501.49 mg/L. Overall, STOAT software is a useful and reliable tool for the prediction and optimization of oxidation ditch process.

Modified Newton-Raphson Method to Minimize Calculation Time for Wastewater Treatment Plant Simulation

Modified Newton-Raphson Method to Minimize Calculation Time for Wastewater Treatment Plant Simulation

The bomb crater effect under the influence of audit feedback: Now you see me, now you don’t

Safety-related rule violations in High Reliability Organizations have the potential to cause accidents, with severe consequences for people, organizations or even society. To prevent such accidents, safety audits are conducted to monitor and ensure high safety standards. In the area of finance, over the last decade, studies have investigated a counterproductive effect of tax audits, termed the bomb crater effect. This describes an increased tendency to evade taxes after a conducted audit. As underlying dynamic the loss repair is contrasted with the misperception of chance. Transferring these investigations to the field of process industries, we also investigated the bomb crater effect (and its promoting latent variables) after safety-related audits. Using WaTrSim, a simulated waste water treatment plant, we analyzed the data of 231 participants – trained as control room operators – regarding the impact of framed production outcomes and the effect of positive or negative audit feedback with financial punishments as a consequence of rule violations. We found strong evidence, that negative audit feedback and loss framing influence an operatoŕs tendency to violate safety rules after an audit.

An adaptive observer design approach for a class of discrete-time nonlinear systems

Abstract We consider the problem of joint estimation of states and some constant parameters for a class of nonlinear discrete-time systems. This class contains systems that could be transformed into a quasi-LPV (linear parameter varying) polytopic model in the Takagi-Sugeno (T-S) form. Such systems could have unmeasured premise variables, a case usually overlooked in the observer design literature. We assert that, for such systems in discrete-time, the current literature lacks design strategies for joint state and parameter estimation. To this end, we adapt the existing literature on continuous-time linear systems for joint state and time-varying parameter estimation. We first develop the discrete-time version of this result for linear systems. A Lyapunov approach is used to illustrate stability, and bounds for the estimation error are obtained via the bounded real lemma. We use this result to achieve our objective for a design procedure for a class of nonlinear systems with constant parameters. This results in less conservative conditions and a simplified design procedure. A basic waste water treatment plant simulation example is discussed to illustrate the design procedure.

Full-scale wastewater treatment plant simulation for real-time optimization

Abstract A dynamic simulation model has been developed and validated for the 1.4 million p.e. capacity Budapest Central Wastewater Treatment Plant to support intensification, process development and risk assessment. By the integration of both the biological and physico-chemical processes the technological design of separated units becomes possible as well as the exploration of the connections within the system. The calibration of the model parameters for an operating treatment plant is the key requirement for the proper application of dynamic simulation tool to optimize operational and maintenance conditions and specify the potential development areas. We have done a one-year period of validation which included sensitivity analysis and the simulation of time intervals in the same way as in the calibration process. At the same time we investigated the suitability of the simulation system for real-time operation optimization. As conclusion we ascertained that due to the computational power necessity of a properly detailed model, it is not applicable for real-time operation optimization, nevertheless it is suitable for the detection of the system reactions for long-term changes of the influent load. This means that a properly functioning model is applicable for indicating the development directions.