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, Miklas Scholz

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)
80 Downloads (Pure)


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.
Original languageEnglish
Article number631
Issue number2
Publication statusPublished - 15 Jan 2020


  • 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

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Management, Monitoring, Policy and Law


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