Supply chain-wide sectoral water use characteristics based on multi-perspective measurements. (20th September 2020)

• Record Type: Journal Article
• Authors: Gao, Zhihao; Li, Yashuai; Qu, Shen; Xu, Ming
• Is Part Of: Journal of cleaner production. Volume 268(2020)
• Publication Date: 2020-09-20
• Subjects: Input-output analysis -- Water use -- Income-based method -- Betweenness-based method -- Cluster analysis; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2020.122345
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: To identify the water-use characteristics of sectors, previous studies primarily focused on measuring water use from the production side and the consumption side. In addition to sectors causing pressure on water resources as producers and drivers, there are also other important water-using sectors as primary suppliers and intermediate good suppliers. Income-based and betweenness-based methods are introduced here to measure the water use from these viewpoints. Using China as a case study, the results reveal critical differences between different perspectives, and sectors with novel water use characteristics have been identified. The K-means clustering method is used to cluster 139 sectors into five categories with distinctive features, of which the intermediate production drivers (category 2) are the critical virtual water transmission sectors which are rarely focused on before. New water-saving strategies can be revealed from the income perspective and the betweenness perspective, such as levying an income tax or improving the use efficiency of upstream input. The novelty of this study lies in the application of an unsupervised statistical learning technique to synthesize the different roles played by economic sectors for water-saving. Highlights: The water use of 139 sectors in 2012 China is measured from four perspectives. The income-based and betweenness-based methods reveal critical but often neglected sectors. The 139 sectors are clustered into five categories with distinctive characteristics. Targeted sector-specific water-saving suggestions are offered.