{"title":"中国有色水足迹不平等的新型评估框架","authors":"Xiaoling Li , Yu Song","doi":"10.1016/j.ecolind.2025.113350","DOIUrl":null,"url":null,"abstract":"<div><div>This study establishes a novel model capable of diagnosing the inequality of China’s colored-water footprint (CWF) allocation through a multi-dimensional perspective for the years 2012, 2015, and 2017. The results indicate the following: (1) The grey water footprint (<em>WF<sub>grey</sub></em>) exceeds both the blue water footprint (<em>WF<sub>blue</sub></em>) and the green water footprint (<em>WF<sub>green</sub></em>). Provinces with higher CWF values are primarily located in the central, eastern, and southern geographical regions of China. (2) Provinces with substantial CWF outflow are primarily those with high GDP or extensive agricultural production, such as Jiangsu, Guangdong, Shandong, Henan, Zhejiang, and Sichuan. The sectors contributing most to net CWF outflows are agriculture and industry. (3) Although the Gini coefficients for CWF and socio-economic factors all remain below the warning threshold of 0.4, the Imbalance indices deviate significantly from the absolute balance line in most provinces, except for the WF<sub>green</sub>-population. Additionally, the Gini coefficient of water stress index (WSI) (0.608 ∼ 0.703) is substantially higher than that of CWF (0.000 ∼ 0.327). (4) The CWF Primacy Index for all provinces is significantly below the ideal level, indicating a polycentric spatial structure for CWF distribution across China. These findings offer valuable scientific insights for informing equitable CWF distribution strategies.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"173 ","pages":"Article 113350"},"PeriodicalIF":7.0000,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A novel assessment framework for colored-water footprint inequality in China\",\"authors\":\"Xiaoling Li , Yu Song\",\"doi\":\"10.1016/j.ecolind.2025.113350\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study establishes a novel model capable of diagnosing the inequality of China’s colored-water footprint (CWF) allocation through a multi-dimensional perspective for the years 2012, 2015, and 2017. The results indicate the following: (1) The grey water footprint (<em>WF<sub>grey</sub></em>) exceeds both the blue water footprint (<em>WF<sub>blue</sub></em>) and the green water footprint (<em>WF<sub>green</sub></em>). Provinces with higher CWF values are primarily located in the central, eastern, and southern geographical regions of China. (2) Provinces with substantial CWF outflow are primarily those with high GDP or extensive agricultural production, such as Jiangsu, Guangdong, Shandong, Henan, Zhejiang, and Sichuan. The sectors contributing most to net CWF outflows are agriculture and industry. (3) Although the Gini coefficients for CWF and socio-economic factors all remain below the warning threshold of 0.4, the Imbalance indices deviate significantly from the absolute balance line in most provinces, except for the WF<sub>green</sub>-population. Additionally, the Gini coefficient of water stress index (WSI) (0.608 ∼ 0.703) is substantially higher than that of CWF (0.000 ∼ 0.327). (4) The CWF Primacy Index for all provinces is significantly below the ideal level, indicating a polycentric spatial structure for CWF distribution across China. These findings offer valuable scientific insights for informing equitable CWF distribution strategies.</div></div>\",\"PeriodicalId\":11459,\"journal\":{\"name\":\"Ecological Indicators\",\"volume\":\"173 \",\"pages\":\"Article 113350\"},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2025-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Indicators\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1470160X2500281X\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Indicators","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1470160X2500281X","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
A novel assessment framework for colored-water footprint inequality in China
This study establishes a novel model capable of diagnosing the inequality of China’s colored-water footprint (CWF) allocation through a multi-dimensional perspective for the years 2012, 2015, and 2017. The results indicate the following: (1) The grey water footprint (WFgrey) exceeds both the blue water footprint (WFblue) and the green water footprint (WFgreen). Provinces with higher CWF values are primarily located in the central, eastern, and southern geographical regions of China. (2) Provinces with substantial CWF outflow are primarily those with high GDP or extensive agricultural production, such as Jiangsu, Guangdong, Shandong, Henan, Zhejiang, and Sichuan. The sectors contributing most to net CWF outflows are agriculture and industry. (3) Although the Gini coefficients for CWF and socio-economic factors all remain below the warning threshold of 0.4, the Imbalance indices deviate significantly from the absolute balance line in most provinces, except for the WFgreen-population. Additionally, the Gini coefficient of water stress index (WSI) (0.608 ∼ 0.703) is substantially higher than that of CWF (0.000 ∼ 0.327). (4) The CWF Primacy Index for all provinces is significantly below the ideal level, indicating a polycentric spatial structure for CWF distribution across China. These findings offer valuable scientific insights for informing equitable CWF distribution strategies.
期刊介绍:
The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published.
• All aspects of ecological and environmental indicators and indices.
• New indicators, and new approaches and methods for indicator development, testing and use.
• Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources.
• Analysis and research of resource, system- and scale-specific indicators.
• Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs.
• How research indicators can be transformed into direct application for management purposes.
• Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators.
• Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.