Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/28097
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dc.contributor.authorRenfrew, D-
dc.contributor.authorVasilaki, V-
dc.contributor.authorKatsou, E-
dc.date.accessioned2024-01-25T17:30:36Z-
dc.date.available2024-01-25T17:30:36Z-
dc.date.issued2024-01-08-
dc.identifierORCID iD: Evina Katsou https://orcid.org/0000-0002-2638-7579-
dc.identifier169903-
dc.identifier.citationRenfrew, D., Vasilaki, V. and Katsou, E. (2024) 'Indicator based multi-criteria decision support systems for wastewater treatment plants', Science of The Total Environment, 915, 169903, pp. 1 - 18. doi: 10.1016/j.scitotenv.2024.169903.en_US
dc.identifier.issn0048-9697-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/28097-
dc.descriptionData availability: Data will be made available on request.en_US
dc.description.abstractWastewater treatment plant decision makers face stricter regulations regarding human health protection, environmental preservation, and emissions reduction, meaning they must improve process sustainability and circularity, whilst maintaining economic performance. This creates complex multi-objective problems when operating and selecting technologies to meet these demands, resulting in the development of many decision support systems for the water sector. European Commission publications highlight their ambition for greater levels of sustainability, circularity, and environmental and human health protection, which decision support system implementation should align with to be successful in this region. Following the review of 57 wastewater treatment plant decision support systems, the main function of multi-criteria decision-making tools are technology selection and the optimisation of process operation. A large contrast regarding their aims is found, as process optimisation tools clearly define their goals and indicators used, whilst technology selection procedures often use vague language making it difficult for decision makers to connect selected indicators and resultant outcomes. Several recommendations are made to improve decision support system usage, such as more rigorous indicator selection protocols including participatory selection approaches and expansion of indicators sets, as well as more structured investigation of results including the use of sensitivity or uncertainty analysis, and error quantification.en_US
dc.description.sponsorshipHorizon 2020 research and innovation programme DEEP PURPLE. The H2020 DEEP PURPLE project has received funding from the Bio-based Industries Joint Undertaking (JU) under the European Union's Horizon 2020 research and innovation programme under grant agreement No 837998. The JU receives support from the European Union's Horizon 2020 research and innovation programme and the Bio-based Industries Consortium.en_US
dc.format.extent1 - 18-
dc.format.mediumPrint-Electronic-
dc.languageEnglish-
dc.language.isoen_USen_US
dc.publisherElsevieren_US
dc.rightsCopyright © 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/).-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectdecision support systemsen_US
dc.subjectwastewater treatment plantsen_US
dc.subjectmulti-criteria decision-makingen_US
dc.subjectmulti-objective optimizationen_US
dc.subjecttechnology selectionen_US
dc.subjectkey performance indicatorsen_US
dc.titleIndicator based multi-criteria decision support systems for wastewater treatment plantsen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1016/j.scitotenv.2024.169903-
dc.relation.isPartOfScience of The Total Environment-
pubs.publication-statusPublished-
pubs.volume915-
dc.identifier.eissn1879-1026-
dc.rights.holderThe Authors-
Appears in Collections:Dept of Civil and Environmental Engineering Research Papers
Institute of Environment, Health and Societies

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