Indicator based multi-criteria decision support systems for wastewater treatment plants
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...
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Veröffentlicht in: | The Science of the total environment 2024-03, Vol.915, p.169903-169903, Article 169903 |
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Sprache: | eng |
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Zusammenfassung: | 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.
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•DSS indicators are not selected in line with water sector sustainability targets.•Process optimisation DSSs state much clearer aims than technology selection DSSs.•Inconsistent categorisation of environmental, social, and technical KPIs•Fuzzy-AHP and -TOPSIS are commonly employed to reduce human error.•Few examples of real-world WWTP process control optimisation due to reliance on BSM. |
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ISSN: | 0048-9697 1879-1026 |
DOI: | 10.1016/j.scitotenv.2024.169903 |