{"title":"利用更新的全球盐度数据集和地理空间多标准分析绘制内陆全球太阳能脱盐需求图","authors":"O. Sanan, G. Pertuz, A. Winter, J. Bessette","doi":"10.1016/j.desal.2025.119355","DOIUrl":null,"url":null,"abstract":"<div><div>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 poorly quantified 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 – exceeding 1.1 million georeferenced points – and analyzed it alongside several key localized metrics including water stress, population density, solar irradiance, water cost, and electricity prices. By benchmarking five different statistical and machine learning approaches side-by-side, 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 1-degree spatial 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, novel geospatial multicriteria computational methods, and new insights into global solar desalination potential via a high-fidelity map.</div></div>","PeriodicalId":299,"journal":{"name":"Desalination","volume":"617 ","pages":"Article 119355"},"PeriodicalIF":9.8000,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mapping inland global solar desalination demand using an updated global salinity dataset and geospatial multicriteria analysis\",\"authors\":\"O. Sanan, G. Pertuz, A. Winter, J. Bessette\",\"doi\":\"10.1016/j.desal.2025.119355\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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 poorly quantified 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 – exceeding 1.1 million georeferenced points – and analyzed it alongside several key localized metrics including water stress, population density, solar irradiance, water cost, and electricity prices. By benchmarking five different statistical and machine learning approaches side-by-side, 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 1-degree spatial 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, novel geospatial multicriteria computational methods, and new insights into global solar desalination potential via a high-fidelity map.</div></div>\",\"PeriodicalId\":299,\"journal\":{\"name\":\"Desalination\",\"volume\":\"617 \",\"pages\":\"Article 119355\"},\"PeriodicalIF\":9.8000,\"publicationDate\":\"2025-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Desalination\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0011916425008318\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Desalination","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0011916425008318","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
Mapping inland global solar desalination demand using an updated global salinity dataset and geospatial multicriteria analysis
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 poorly quantified 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 – exceeding 1.1 million georeferenced points – and analyzed it alongside several key localized metrics including water stress, population density, solar irradiance, water cost, and electricity prices. By benchmarking five different statistical and machine learning approaches side-by-side, 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 1-degree spatial 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, novel geospatial multicriteria computational methods, and new insights into global solar desalination potential via a high-fidelity map.
期刊介绍:
Desalination is a scholarly journal that focuses on the field of desalination materials, processes, and associated technologies. It encompasses a wide range of disciplines and aims to publish exceptional papers in this area.
The journal invites submissions that explicitly revolve around water desalting and its applications to various sources such as seawater, groundwater, and wastewater. It particularly encourages research on diverse desalination methods including thermal, membrane, sorption, and hybrid processes.
By providing a platform for innovative studies, Desalination aims to advance the understanding and development of desalination technologies, promoting sustainable solutions for water scarcity challenges.