中国有色水足迹不平等的新型评估框架

IF 7 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Ecological Indicators Pub Date : 2025-03-15 DOI:10.1016/j.ecolind.2025.113350
Xiaoling Li , Yu Song
{"title":"中国有色水足迹不平等的新型评估框架","authors":"Xiaoling Li ,&nbsp;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 ,&nbsp;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}
引用次数: 0
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
相关文献
二甲双胍通过HDAC6和FoxO3a转录调控肌肉生长抑制素诱导肌肉萎缩
IF 8.9 1区 医学Journal of Cachexia, Sarcopenia and MusclePub Date : 2021-11-02 DOI: 10.1002/jcsm.12833
Min Ju Kang, Ji Wook Moon, Jung Ok Lee, Ji Hae Kim, Eun Jeong Jung, Su Jin Kim, Joo Yeon Oh, Sang Woo Wu, Pu Reum Lee, Sun Hwa Park, Hyeon Soo Kim
具有疾病敏感单倍型的非亲属供体脐带血移植后的1型糖尿病
IF 3.2 3区 医学Journal of Diabetes InvestigationPub Date : 2022-11-02 DOI: 10.1111/jdi.13939
Kensuke Matsumoto, Taisuke Matsuyama, Ritsu Sumiyoshi, Matsuo Takuji, Tadashi Yamamoto, Ryosuke Shirasaki, Haruko Tashiro
封面:蛋白质组学分析确定IRSp53和fastin是PRV输出和直接细胞-细胞传播的关键
IF 3.4 4区 生物学ProteomicsPub Date : 2019-12-02 DOI: 10.1002/pmic.201970201
Fei-Long Yu, Huan Miao, Jinjin Xia, Fan Jia, Huadong Wang, Fuqiang Xu, Lin Guo
来源期刊
Ecological Indicators
Ecological Indicators 环境科学-环境科学
CiteScore
11.80
自引率
8.70%
发文量
1163
审稿时长
78 days
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.
期刊最新文献
Stochastic processes dominate bacterial and fungal community assembly in ultra-high-altitude areas of southeast Tibet Inversion of heavy metal elements in characteristic agricultural areas of Shanxi Province: Application of the airborne multimodular imaging spectrometer Understanding the efficiency and uncertainty of water supply service assessment based on the Budyko framework: A case study of the Yellow River Basin, China Exploring the assessment scale for small watersheds in the Han river basin using an integrated ecosystem health index Nonlinear threshold effects of environmental drivers on vegetation cover in mountain ecosystems: From constraint mechanisms to adaptive management
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1