• Journal of Environmental Impact Assessment
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• v.8 no.2
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• pp.83-93
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• 1999

ASPEN PLUS, a steady-state simulator, was used in this study for predicting emissions of VOCs and tracing the fate of all compounds in biodegradation processes. Mathematical models for the processes such as volatilization, reaction and clarification were adopted from literatures. Unlike most previous simulations that various pollutants were considered as a single component, COD or BOD, four components of water, biomass, VOCs and COD were included in this simulation. Sensitivity analysis of several physical parameters on the performance of the WWTP was conducted. Model predictions of VOCs emissions agreed well with the plant data. The simulator could provide design conditions for a future WWTP as well as monitoring/control regimes to an existing WWTP.

• Journal of Korean Society on Water Environment
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• v.20 no.2
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• pp.132-144
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• 2004

The purpose of this study was to evaluate alternatives for stable operation of WWTP(Wastewater Treatment Plant) with a higher rate of inflows and a higher concentration of pollutants during wet weather to minimize the pollution loads being discharged into receiving waters. 3Q(Q: dry weather flow) of a base flow is normally intercepted and flows into WWTP as it was current practice. It is revealed by simulation that the bypassing alternative of 1Q through secondary treatment and 2Q into the stream after primary treatment was as good as it is expected. The bypass pollution loads were in the range of 23.9 ~ 38.5 % of the total loads flowing into the WWTP indicating that the bypassed flows need an extra treatment such as stormwater detention reservoir, high-rate coagulation with sedimentation, and step-feed. The high-rate coagulation with sedimentation was the most effective with respect to removal of the pollution loads.

• Membrane and Water Treatment
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• v.9 no.3
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• pp.155-162
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• 2018

Process modeling with activated sludge models (ASMs) is useful for the design and operational improvement of biological nutrient removal (BNR) processes. Effective utilization of ASMs requires the influent fraction analysis (IFA) of the wastewater treatment plant (WWTP). However, this is difficult due to the time and cost involved in the design and operation steps, thereby declining the simulation reliability. Harmony Search (HS) algorithm was utilized herein to determine the relationships between composite variables and state variables of the model IWA ASM1. Influent fraction analysis was used in estimating fractions of the state variables of the WWTP influent and its application to 9 wastewater treatment processes in South Korea. The results of influent $S_s$ and $Xs+X_{BH}$, which are the most sensitive variables for design of activated sludge process, are estimated within the error ranges of 8.9-14.2% and 3.8-6.4%, respectively. Utilizing the chemical oxygen demand (COD) fraction analysis for influent wastewater, it was possible to predict the concentrations of treated organic matter and nitrogen in 9 full scale BNR processes with high accuracy. In addition, the results of daily influent fraction analysis (D-IFA) method were superior to those of the constant influent fraction analysis (C-IFA) method.

• Coupled systems mechanics
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• v.5 no.1
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• pp.21-39
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• 2016

Wastewater process models are the essential tools for understanding relevant aspects of wastewater treatment system. Wastewater process modeling provides more options for upgrades and better understanding of new plant design, as well as improvements of operational controls. The software packages (BioWin, GPS-X, Aqua designer, etc) solve a series of simulated equations simultaneously in order to propose several solutions for a specific facility. Research and implementation of wastewater process modeling in combination with computational fluid dynamics enable testing for improvements of flow characteristics for WWTP and at the same time exam biological, physical, and chemical characteristics of the flow. Application of WWTP models requires broad knowledge of the process and expertise in modeling. Therefore, an efficient and good modeling practice requires both experience and set of proper guidelines as a background.

• Journal of Wetlands Research
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• v.24 no.4
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• pp.345-353
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• 2022

A wastewater treatment plant (WWTP) is a major gateway for the engineered nano-particles (ENPs) entering the water bodies. However existing studies have reported that many WWTPs exceed the No Observed Effective Concentration (NOEC) for ENPs in the effluent and thus they need to be designed or operated to more effectively control ENPs. Understanding and predicting ENPs behaviors in the unit and \the whole process of a WWTP should be the key first step to develop strategies for controlling ENPs using a WWTP. This study aims to provide a modeling tool for predicting behaviors and removal efficiencies of ENPs in a WWTP associated with process characteristics and major operating conditions. In the developed model, four unit processes for water treatment (primary clarifier, bioreactor, secondary clarifier, and tertiary treatment unit) were considered. Additionally the model simulates the sludge treatment system as a single process that integrates multiple unit processes including thickeners, digesters, and dewatering units. The simulated ENP was nano-sized TiO₂, (nano-TiO₂) assuming that its behavior in a WWTP is dominated by the attachment with suspendid solids (SS), while dissolution and transformation are insignificant. The attachment mechanism of nano-TiO₂ to SS was incorporated into the model equations using the apparent solid-liquid partition coefficient (Kd) under the equilibrium assumption between solid and liquid phase, and a steady state condition of nano-TiO₂ was assumed. Furthermore, an MS Excel-based user interface was developed to provide user-friendly environment for the nano-TiO₂ removal efficiency calculations. Using the developed model, a preliminary simulation was conducted to examine how the solid retention time (SRT), a major operating variable affects the removal efficiency of nano-TiO₂ particles in a WWTP.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.4
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• pp.13-22
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• 2007

The uncertainty in water quality model predictions is inevitably high due to natural stochasticity, model uncertainty, and parameter uncertainty. An integrated modeling system under uncertainty was described and demonstrated for use in watershed management and receiving-water quality prediction. A watershed model (HSPF), a receiving water quality model (WASP), and a wetland model (NPS-WET) were incorporated into an integrated modeling system (modified-BASINS) and applied to the Hwaseong Reservoir watershed. Reservoir water quality was predicted using the calibrated integrated modeling system, and the deterministic integrated modeling output was useful for estimating mean water quality given future watershed conditions and assessing the spatial distribution of pollutant loads. A Monte Carlo simulation was used to investigate the effect of various uncertainties on output prediction. Without pollution control measures in the watershed, the concentrations of total nitrogen (T-N) and total phosphorous (T-P) in the Hwaseong Reservoir, considering uncertainty, would be less than about 4.8 and 0.26 mg 4.8 and 0.26 mg $L^{-1}$, respectively, with 95% confidence. The effects of two watershed management practices, a wastewater treatment plant (WWTP) and a constructed wetland (WETLAND), were evaluated. The combined scenario (WWTP + WETLAND) was the most effective at improving reservoir water quality, bringing concentrations of T-N and T-P in the Hwaseong Reservoir to less than 3.54 and 0.15 mg ${L^{-1}$, 26.7 and 42.9% improvements, respectively, with 95% confidence. Overall, the Monte Carlo simulation in the integrated modeling system was practical for estimating uncertainty and reliable in water quality prediction. The approach described here may allow decisions to be made based on probability and level of risk, and its application is recommended.

• Korean Chemical Engineering Research
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• v.48 no.5
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• pp.589-597
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• 2010

Strengthening the regulation standard of biological nutrient in wastewater treatment plant(WWTP), the necessity of repair of WWTP which is operated in conventional activated sludge process to advanced nutrient removal treatment is increased. However, in full-scale wastewater treatment system, it is not easy to fine the optimized operational condition of the advanced nutrient removal treatment through experiment due to the complex response of various influent conditions and operational conditions. Therefore, in this study, an upgrading design of conventional activated sludge process to advanced nutrient removal process using the modeling and simulation method based on activated sludge model(ASMs) is executed. And a design optimization of advanced treatment process using the response surface method(RSM) is carried out for statistical and systematic approach. In addition, for the operational optimization of full-scale WWTP, a correct analysis about kinetic variables of wastewater treatment is necessary. In this study, through partial least square(PLS) analysis which is one of the multivariable statistical analysis methods, a correlation between the kinetic variables of wastewater treatment system is comprehended, and the most effective variables to the advanced treatment operation result is deducted. Through this study, the methodology for upgrading design and operational optimization of advanced treatment process is provided, and an efficient repair of WWTP to advanced treatment can be expected reducing the design time and costs.

• Journal of Korean Society of Water and Wastewater
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• v.28 no.6
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• pp.735-745
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• 2014

This paper presents PKES(PuKyung -Excel based Simulator) for WWTPs(wastewater treatment plants) by using MS Excel and VBA(Visual Basic for Application). PKES is a user-friendly simulator for the design and optimization of the whole plant including biological and physico-chemical processes for the wastewater and sludge treatment. PKES calculates the performance under steady or dynamic state and allows changing the mathematical model by the user. Mathematical model implemented in PKES is a improved integration model based on ASM2d and ADM1 for simulation of AS(activated sludge) and AD(anaerobic digestion). Gaseous components of $N_2$, $N_2O$, $CO_2$ and $CH_4$ are added for estimation of GHGs(greenhouse gases) emission. The simulation results for comparison between PKES and Aquasim(EAWAG) showed about the same effluent concentrations. As a result of verification using by measured data of BOD, TSS, TN and TP for 2 years of operation, calculated effluent concentrations were similar to measured effluent concentrations. The values of average RMSE(root mean square error) were 1.9, 0.8, 1.6 and 0.2 mg/L for BOD, TSS, TN and TP, respectively. Total GHGs emission of WWTP calculated by PKES was 138.5 ton-$CO_2$/day and GHGs emissions of $N_2O$, $CO_2$ and $CH_4$ were calculated at 21.7, 28.9 and 87.9 ton-$CO_2$/day, respectively. GHGs emission of activated sludge was 32.5 % and that of anaerobic digestion was 67.5 %.

• Journal of Korean Society on Water Environment
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• v.26 no.1
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• pp.96-103
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• 2010

In this work, the presence of nitrification biochemical oxygen demand (NBOD) frequently occurred in the sewer outflow in winter season was analysed by the COD fraction methods using the respirometry and process simulations with real operation data measurements and analysis. The activated sludge models applied in this process simulation were based on the ASM No.2d temp. models, published by International Association on Water Quality (IAWQ). The ASM No.2d model is an extension of the ASM No.2 model and takes into account of carbon removal, nitrification, denitrification and phosphorus removal. The denitrifying capacity of phosphorus accumulating organisms has been implemented in the ASM No.2d model because experimental evidence shows that some of the phosphorus accumulating organisms can denitrify. It was shown that the concentrations of autotrophs (X_AUT) in the secondary clarifier and the $NH_4-N$ of T-N increased in the presence of NBOD measurements. Because of the low temperature (average $8^{\circ}C$) and possible operational troubles, the outcoming autotrophs exhausted oxygen in the process of nitrifying $NH_4-N$.