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<p>The Activated Sludge Model No. 1 (ASM1) is a widely adopted structured model used to simulate the dynamic behavior of aerobic biological processes in wastewater treatment systems. It provides a robust framework for the optimization of existing facilities and the design of new treatment infrastructure. In this study, a modified ASM1 model, implemented in GPS-X 8.1 software, was applied to the Beja wastewater treatment plant (WWTP) in Tunisia, which receives a mixed influent composed of domestic sewage and high-strength industrial effluent from a baker’s yeast factory. Model calibration was carried out using daily operational data, including total chemical oxygen demand (TCOD), total suspended solids (TSS), and total biochemical oxygen demand (TBOD₅). A comprehensive sensitivity analysis and automated optimization procedure were conducted to identify the most influential parameters and determine their optimal values. Key stoichiometric and kinetic parameters—including the maximum specific growth rate (µH), decay rate (b<sub>H</sub>), half-saturation constant (K<sub>SH</sub>), and biomass yield coefficient (Y<sub>H</sub>)—were calibrated, resulting in the following optimized values: Y<sub>H</sub> = 0.46 gCOD/gDCO, µ<sub>H</sub> = 7.1 d⁻<sup>1</sup>, K<sub>SH</sub> = 83.89&#xa0;mg/L, and b<sub>H</sub> = 0.34 d⁻<sup>1</sup>. The simulation results demonstrated the model’s ability to accurately reproduce plant performance under varying influent conditions. Notably, the model successfully captured the impact of industrial shock loads (COD concentrations ranging from 20 to 80&#xa0;g/L) on treatment performance. Model validation showed strong agreement between measured and simulated effluent values for TCOD and TBOD₅, with root mean square error (RMSE) values of 10% and 15%, respectively, over a one-year period. However, TSS predictions were slightly less accurate, yielding an RMSE of approximately 25%. These results confirm the reliability and practical relevance of the ASM1 model as a decision-support tool for the management of WWTPs subjected to complex and variable influents. Its successful application to the Beja plant underscores its potential to enhance treatment efficiency, anticipate performance disturbances, and support sustainable plant operation under challenging industrial discharge conditions.</p> Graphical abstract <p></p>

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Modeling and simulation of the beja wastewater treatment plant using the IWA-ASM1 model in hydromantis GPS-X

  • 期刊论文

  • 发表日期：

    2025年12月12日

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  • Boubaker Fezzani

摘要

The Activated Sludge Model No. 1 (ASM1) is a widely adopted structured model used to simulate the dynamic behavior of aerobic biological processes in wastewater treatment systems. It provides a robust framework for the optimization of existing facilities and the design of new treatment infrastructure. In this study, a modified ASM1 model, implemented in GPS-X 8.1 software, was applied to the Beja wastewater treatment plant (WWTP) in Tunisia, which receives a mixed influent composed of domestic sewage and high-strength industrial effluent from a baker’s yeast factory. Model calibration was carried out using daily operational data, including total chemical oxygen demand (TCOD), total suspended solids (TSS), and total biochemical oxygen demand (TBOD₅). A comprehensive sensitivity analysis and automated optimization procedure were conducted to identify the most influential parameters and determine their optimal values. Key stoichiometric and kinetic parameters—including the maximum specific growth rate (µH), decay rate (bH), half-saturation constant (KSH), and biomass yield coefficient (YH)—were calibrated, resulting in the following optimized values: YH = 0.46 gCOD/gDCO, µH = 7.1 d⁻1, KSH = 83.89 mg/L, and bH = 0.34 d⁻1. The simulation results demonstrated the model’s ability to accurately reproduce plant performance under varying influent conditions. Notably, the model successfully captured the impact of industrial shock loads (COD concentrations ranging from 20 to 80 g/L) on treatment performance. Model validation showed strong agreement between measured and simulated effluent values for TCOD and TBOD₅, with root mean square error (RMSE) values of 10% and 15%, respectively, over a one-year period. However, TSS predictions were slightly less accurate, yielding an RMSE of approximately 25%. These results confirm the reliability and practical relevance of the ASM1 model as a decision-support tool for the management of WWTPs subjected to complex and variable influents. Its successful application to the Beja plant underscores its potential to enhance treatment efficiency, anticipate performance disturbances, and support sustainable plant operation under challenging industrial discharge conditions.

Graphical abstract