Mapping inland global solar desalination demand using an updated global salinity dataset and geospatial multicriteria analysis
Year: 2025
Type: article
Abstract: The global demand for inland, solar-powered water desalination technology is rapidly evolving, driven by increasing water scarcity, climate change, and population growth. However, this demand, especially in Low- and middle-income countries, remains unknown due to the lack of comprehensive global data and analysis of these regions. This study aggregates and interprets data using diverse computational methods to create a high-resolution global map identifying locations of high potential for inland, solar-powered water desalination. To the authors' knowledge, we compiled one of the most extensive inland water salinity datasets to date and analyzed it alongside several key localized metrics including water stress, population density, solar irradiance, water cost, and electricity prices. Using five different statistical and machine learning approaches, we developed a holistic feasibility score for solar desalination, identifying high-potential areas in regions including Africa, the Middle East, South and Southeast Asia, Central America, Mexico, and southern Europe at high resolution. Our binning methodology revealed that approximately 22% of global land area shows high feasibility scores, with peak values concentrated in the Middle East, Western Africa and Northern Africa regions. The Top 6 regions displayed a mean desalination feasibility score (using binning method) of 77.7%, which was approximately 50% higher than the feasibility score of 51.8% for the Rest of the World. This research provides an updated pointwise global groundwater salinity dataset, geospatial multicriteria computational methods, and new insights into global solar desalination potential via a high-fidelity map.
Source: Desalination
Authors: O. Sanan, G. Pertuz, A. Winter, J. Bessette
Institution: Massachusetts Institute of Technology
Language: English
Field: Energy
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,580
OpenAlex ID: W7082987913