An integrated membrane bioreactor (MBR) model was previously proposed and tested. The model provides a comprehensive and detailed description of the nitrogen biological removal processes with respect to up-to-date literature. This paper presents a sensitivity and uncertainty analysis aimed at identifying the key factors affecting the variability of the model predictions. The Standardized Regression Coefficients (SRC) method was adopted for the sensitivity analysis. The uncertainty analysis was employed by running Monte Carlo simulations by varying only the value of the key factors affecting the model outputs. The sensitivity analysis combined with the uncertainty analysis applied here enabled to gain useful insights about the robustness of the model. By means of the SRC method 45 model factors (of 122) were selected as important. The results obtained here allowed to investigate the advantage of a detailed description of the nitrogen transformation bioprocesses (nitrification/denitrification) in terms of model accuracy and uncertainty bandwidth. The model allows to simulate the intermediate product during nitrification/denitrification, thus providing the possibility to control the nitrogen compounds that favour the formation of nitrous oxide.

Mannina, G., Cosenza, A., Viviani, G., Ekama, G.A. (2018). Sensitivity and uncertainty analysis of an integrated ASM2d MBR model for wastewater treatment. CHEMICAL ENGINEERING JOURNAL, 351, 579-588 [10.1016/j.cej.2018.06.126].

Sensitivity and uncertainty analysis of an integrated ASM2d MBR model for wastewater treatment

Mannina, Giorgio;Cosenza, Alida;Viviani, Gaspare;
2018-01-01

Abstract

An integrated membrane bioreactor (MBR) model was previously proposed and tested. The model provides a comprehensive and detailed description of the nitrogen biological removal processes with respect to up-to-date literature. This paper presents a sensitivity and uncertainty analysis aimed at identifying the key factors affecting the variability of the model predictions. The Standardized Regression Coefficients (SRC) method was adopted for the sensitivity analysis. The uncertainty analysis was employed by running Monte Carlo simulations by varying only the value of the key factors affecting the model outputs. The sensitivity analysis combined with the uncertainty analysis applied here enabled to gain useful insights about the robustness of the model. By means of the SRC method 45 model factors (of 122) were selected as important. The results obtained here allowed to investigate the advantage of a detailed description of the nitrogen transformation bioprocesses (nitrification/denitrification) in terms of model accuracy and uncertainty bandwidth. The model allows to simulate the intermediate product during nitrification/denitrification, thus providing the possibility to control the nitrogen compounds that favour the formation of nitrous oxide.
2018
Settore ICAR/03 - Ingegneria Sanitaria-Ambientale
www.elsevier.com/inca/publications/store/6/0/1/2/7/3/index.htt
Mannina, G., Cosenza, A., Viviani, G., Ekama, G.A. (2018). Sensitivity and uncertainty analysis of an integrated ASM2d MBR model for wastewater treatment. CHEMICAL ENGINEERING JOURNAL, 351, 579-588 [10.1016/j.cej.2018.06.126].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/298011
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