Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/28097
Title: Indicator based multi-criteria decision support systems for wastewater treatment plants
Authors: Renfrew, D
Vasilaki, V
Katsou, E
Keywords: decision support systems;wastewater treatment plants;multi-criteria decision-making;multi-objective optimization;technology selection;key performance indicators
Issue Date: 8-Jan-2024
Publisher: Elsevier
Citation: Renfrew, 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.
Abstract: Wastewater 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.
Description: Data availability: Data will be made available on request.
URI: https://bura.brunel.ac.uk/handle/2438/28097
DOI: https://doi.org/10.1016/j.scitotenv.2024.169903
ISSN: 0048-9697
Other Identifiers: ORCID iD: Evina Katsou https://orcid.org/0000-0002-2638-7579
169903
Appears in Collections:Dept of Civil and Environmental Engineering Research Papers
Institute of Environment, Health and Societies

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