Sustainability Ranking of Desalination Plants Using Mamdani Fuzzy Logic Inference Systems

Rabee Rustum, Anu Mary John Kurichiyanil, Shaun Forrest, Corrado Sommariva, Adebayo J. Adeloye, Mohammad Zounemat-Kermani and Miklas Scholz
Additional contact information
Rabee Rustum: School of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University, UK, Dubai Campus, Dubai International Academic City, P.O. Box 294345 Dubai, UAE
Anu Mary John Kurichiyanil: School of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University, UK, Dubai Campus, Dubai International Academic City, P.O. Box 294345 Dubai, UAE
Shaun Forrest: Department of Geography, Carleton University, 1125 Colonel by Drive, Ottawa, ON K1S 5B6, Canada
Corrado Sommariva: ILF Consulting EngineersߞAbu Dhabi, Al Reem Island, Sky Tower, Unit 36-01, 36th Floor, P.O. Box 73250 Abu Dhabi, UAE
Adebayo J. Adeloye: School of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University, UK, Dubai Campus, Dubai International Academic City, P.O. Box 294345 Dubai, UAE
Mohammad Zounemat-Kermani: Water Engineering Department, Shahid Bahonar University of Kerman, 76169-14111 Kerman, Iran
Miklas Scholz: Division of Water Resources Engineering (TVRL), Department of Building and Environmental Technology, Faculty of Engineering, Lund University, P.O. Box 118, 22100 Lund, Sweden

Sustainability, 2020, vol. 12, issue 2, 1-22

Abstract: As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems. The fuzzy-based models were validated using data from two typical desalination plants in the UAE. The promising results obtained from the fuzzy ranking framework suggest this more in-depth sustainability analysis should be beneficial due to its flexibility and adaptability in meeting the requirements of desalination sustainability.

Keywords: artificial intelligence; decision-making in water supply; energy efficiency; ranking modelling framework; reverse osmosis; sustainability indicator list; sustainability tool; sustainable water production; unsustainable production; water pollution (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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