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Minimizing membrane bioreactor environmental footprint by multiple objective optimization

Mannina, Giorgio ; Ni, Bing Jie ; Ferreira Rebouças, Taise ; Cosenza, Alida and Olsson, Gustaf LU (2020) In Bioresource Technology 302.
Abstract

This paper presents a modelling study aimed at minimizing the environmental foot print of a membrane bioreactor (MBR) for wastewater treatment. Specifically, an integrated model for MBR was employed in view of the management optimization of an MBR biological nutrient removal (BNR) pilot plant in terms of operational costs and direct greenhouse gases emissions. The influence of the operational parameters (OPs) on performance indicators (PIs) was investigated by adopting the Extended-FAST sensitivity analysis method. Further, a multi-objective analysis was performed by applying the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The results show-up that the sludge retention time is the OP mostly affecting all... (More)

This paper presents a modelling study aimed at minimizing the environmental foot print of a membrane bioreactor (MBR) for wastewater treatment. Specifically, an integrated model for MBR was employed in view of the management optimization of an MBR biological nutrient removal (BNR) pilot plant in terms of operational costs and direct greenhouse gases emissions. The influence of the operational parameters (OPs) on performance indicators (PIs) was investigated by adopting the Extended-FAST sensitivity analysis method. Further, a multi-objective analysis was performed by applying the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The results show-up that the sludge retention time is the OP mostly affecting all the investigated PIs. By applying the set of optimal OPs, there was a reduction of 48% and 10% of the operational costs and direct emissions, respectively.

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author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Greenhouse gases, Mathematical modelling optimization, Membrane fouling, Multi-objective analysis, Wastewater treatment plant
in
Bioresource Technology
volume
302
article number
122824
publisher
Elsevier
external identifiers
  • scopus:85078319426
  • pmid:32000132
ISSN
0960-8524
DOI
10.1016/j.biortech.2020.122824
language
English
LU publication?
yes
id
16d55042-e371-4adb-af07-c4caebb13c4f
date added to LUP
2020-02-04 11:21:47
date last changed
2024-10-02 20:04:34
@article{16d55042-e371-4adb-af07-c4caebb13c4f,
  abstract     = {{<p>This paper presents a modelling study aimed at minimizing the environmental foot print of a membrane bioreactor (MBR) for wastewater treatment. Specifically, an integrated model for MBR was employed in view of the management optimization of an MBR biological nutrient removal (BNR) pilot plant in terms of operational costs and direct greenhouse gases emissions. The influence of the operational parameters (OPs) on performance indicators (PIs) was investigated by adopting the Extended-FAST sensitivity analysis method. Further, a multi-objective analysis was performed by applying the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The results show-up that the sludge retention time is the OP mostly affecting all the investigated PIs. By applying the set of optimal OPs, there was a reduction of 48% and 10% of the operational costs and direct emissions, respectively.</p>}},
  author       = {{Mannina, Giorgio and Ni, Bing Jie and Ferreira Rebouças, Taise and Cosenza, Alida and Olsson, Gustaf}},
  issn         = {{0960-8524}},
  keywords     = {{Greenhouse gases; Mathematical modelling optimization; Membrane fouling; Multi-objective analysis; Wastewater treatment plant}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{Bioresource Technology}},
  title        = {{Minimizing membrane bioreactor environmental footprint by multiple objective optimization}},
  url          = {{http://dx.doi.org/10.1016/j.biortech.2020.122824}},
  doi          = {{10.1016/j.biortech.2020.122824}},
  volume       = {{302}},
  year         = {{2020}},
}