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

Gaspare Viviani, Giorgio Mannina, Alida Cosenza, Giorgio Mannina, George A. Ekama

Risultato della ricerca: Article

5 Citazioni (Scopus)

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.
Lingua originaleEnglish
pagine (da-a)579-588
Numero di pagine10
RivistaChemical Engineering Journal
Volume351
Stato di pubblicazionePublished - 2018

Fingerprint

Uncertainty analysis
uncertainty analysis
Bioreactors
Wastewater treatment
bioreactor
Sensitivity analysis
sensitivity analysis
membrane
Membranes
Nitrification
Denitrification
nitrification
denitrification
Nitrogen
Nitrogen Compounds
Nitrogen compounds
wastewater treatment
nitrogen compound
nitrogen
Nitrous Oxide

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Environmental Chemistry
  • Chemical Engineering(all)
  • Industrial and Manufacturing Engineering

Cita questo

@article{d1a78ddd84374815861867ef908789c9,
title = "Sensitivity and uncertainty analysis of an integrated ASM2d MBR model for wastewater treatment",
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.",
keywords = "ASM, Chemical Engineering (all), Chemistry (all), Environmental Chemistry, Industrial and Manufacturing Engineering, Membrane fouling, Membrane modelling, Model uncertainty",
author = "Gaspare Viviani and Giorgio Mannina and Alida Cosenza and Giorgio Mannina and Ekama, {George A.}",
year = "2018",
language = "English",
volume = "351",
pages = "579--588",
journal = "Chemical Engineering Journal",
issn = "1385-8947",
publisher = "Elsevier",

}

TY - JOUR

T1 - Sensitivity and uncertainty analysis of an integrated ASM2d MBR model for wastewater treatment

AU - Viviani, Gaspare

AU - Mannina, Giorgio

AU - Cosenza, Alida

AU - Mannina, Giorgio

AU - Ekama, George A.

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

KW - ASM

KW - Chemical Engineering (all)

KW - Chemistry (all)

KW - Environmental Chemistry

KW - Industrial and Manufacturing Engineering

KW - Membrane fouling

KW - Membrane modelling

KW - Model uncertainty

UR - http://hdl.handle.net/10447/298011

UR - http://www.elsevier.com/inca/publications/store/6/0/1/2/7/3/index.htt

M3 - Article

VL - 351

SP - 579

EP - 588

JO - Chemical Engineering Journal

JF - Chemical Engineering Journal

SN - 1385-8947

ER -