Modeling nutrient removal and energy consumption in an advanced activated sludge system under uncertainty

• Published in: Journal of environmental management 2022-12, Vol.323, p.116040-116040, Article 116040
• Main Authors: Szeląg, Bartosz, Kiczko, Adam, Zaborowska, Ewa, Mannina, Giorgio, Mąkinia, Jacek
• Format: Article
• Language: English
• Subjects: Activated sludge model; Nutrient removal; Sensitivity analysis; Uncertainty analysis; Wastewater treatment plant
• ISSN: 0301-4797; 1095-8630
• DOI: 10.1016/j.jenvman.2022.116040

Activated sludge models are widely used to simulate, optimize and control performance of wastewater treatment plants (WWTP). For simulation of nutrient removal and energy consumption, kinetic parameters would need to be estimated, which requires an extensive measurement campaign. In this study, a novel methodology is proposed for modeling the performance and energy consumption of a biological nutrient removal activated sludge system under sensitivity and uncertainty. The actual data from the wastewater treatment plant in Slupsk (northern Poland) were used for the analysis. Global sensitivity analysis methods accounting for interactions between kinetic parameters were compared with the local sensitivity approach. An extensive procedure for estimation of kinetic parameters allowed to reduce the computational effort in the uncertainty analysis and improve the reliability of the computational results. Due to high costs of measurement campaigns for model calibration, a modification of the Generalized Likelihood Uncertainty method was applied considering the location of measurement points. The inclusion of nutrient measurements in the aerobic compartment in the uncertainty analysis resulted in percentages of ammonium, nitrate, ortho-phosphate measurements of 81%, 90%, 78%, respectively, in the 95% confidence interval. The additional inclusion of measurements in the anaerobic compartment resulted in an increase in the percentage of ortho-phosphate measurements in the aerobic compartment by 5% in the confidence interval. The developed procedure reduces computational and measurement efforts, while maintaining a high compatibility of the observed data and model predictions. This enables to implement activated sludge models also for the facilities with a limited availability of data. •Nutrient removal and energy consumption were modeled in a real facility.•Global sensitivity analysis was compared with local sensitivity analysis.•New effective approach to uncertainty analysis was applied.•Optimal selection of sampling points and scope of measurements was determined.