Dynamic simulation for wastewater treatment plants management: Case of Souk-Ahras region, north-eastern Algeria

Abstract

Treatment performances of two wastewater treatment plants (WWTPs), located in North-Eastern Algeria (Souk-Ahras and Sedrata) were tested using ASM1 model.The model, to be considered as a decision tool for the appropriate management of activated sludge systems, served for the prediction of both WWTP behaviours under different operating conditions. In Sedrata WWTP the first management scenarios is based on an increase of inflow rate, taking into account a new transfer volume from a nearby zone. In a second scenerio, the ultimate flow of 40 000 m 3 ·d -1 is estimated. Regarding Souk-Ahras WWTP, three scenarios were tested. The first tested the impact of an increase of the extraction flow rate and yielded a reduction by 37% of sludge production. The second dealt with the management of the mass budget of substrata and biomass. Finally, the third application was devoted to the estimation of the plant ultimate capacity, estimated to be 60 000 m 3 ·d -1.

Steady-State and Dynamic Simulation for Wastewater Treatment Plant Management: Case Study of Maghnia City, North-West Algeria

“…Furthermore, the NH4-N effluent failed to meet the international discharge standard (<20 mg/L), with a deviation of 93.33% in NH4-N effluent concentrations exceeding the specified limit. These outcomes are consistent with similar findings in two separate studies conducted on sewage treatment plants in northeastern Algeria [58] and the United Arab Emirates [13]. In both cases, the dynamic simulation results exhibited relatively low congruence with the observed TSS and NH4-N values.…”

“…All kinetic and stoichiometric parameters related to the nitrification process (Mass N/mass COD in biomass (i XB ), Nitrate for denitrifying heterotrophs (K NO ), ammonification rate (Ka), and correction factor for anoxic hydrolysis ( directed towards fine-tuning COD adjustments. For TSS, the influent average was introduced through the calibration of two stoichiometric coefficients: the VSS/TSS ratio was fixed at 0.80 g VSS/ g TSS, consistent with the findings of [58], and XCOD/VSS was adjusted to 1.3 g COD/g VSS, differing from the default value of 1.48. The model effectively mirrored the observed TSS data in Figure 6, with an RMSE of 17% calculated.…”

Improving the operational performance of a wastewater treatment plant using GPS-X simulation program: A case study in northern Taiwan

“…For the GPS-X simulation, the Guishan WWTP model was calibrated by using measured effluent data (BOD, COD, SS, NH3-N, and TN) from 2021. Disparities between measured data and simulated data are related to the fractionation of organic matter, stoichiometric parameters [10], and kinetic parameters [11]. Model input data for influent water quality and influent volume are based on the measured influent water quality and influent volume at Guishan WWTP in 2021.…”

Evaluating Long-Term Treatment Performance and Cost of Nutrient Removal at Water Resource Recovery Facilities under Stochastic Influent Characteristics Using Artificial Neural Networks as Surrogates for Plantwide Modeling

“…Various computer programs (e.g., GPS-X and BioWin) have been developed that allow for simulation of WRRF treatment alternatives. − In practice, these simulators help identify alternative processes that best align with point source nutrient reduction goals and determine the most cost-effective approaches to nutrient reduction. − These types of simulations also allow for scenario-based experimentation without disturbing a real WRRF’s operation. However, integration of a point source model with other nonpoint source models for system-based solutions to watershed optimization studies are challenging, as process modeling software are typically proprietary and do not natively integrate with external programs.…”