Danzhu Liu, Jinqiang Liang, Jibin Zhou, Shuliang Xu, Mao Ye, Zhongmin Liu
{"title":"中国资源流动的区域差异:基于MRIO和机器学习聚类的多维分析","authors":"Danzhu Liu, Jinqiang Liang, Jibin Zhou, Shuliang Xu, Mao Ye, Zhongmin Liu","doi":"10.1021/acssuschemeng.4c09911","DOIUrl":null,"url":null,"abstract":"In the context of globalization and trade liberalization, the harmonious development of the economy, energy, and ecology has become a critical global issue. The inter-regional flows of energy, water resources, and carbon emissions play an increasingly influential role in economic growth. However, there are significant differences in resource endowment and consumption among different regions of China. To bridge these regional gaps and enable a quantitative understanding of multidimensional resource interactions, this study presents a resources embodied flow framework based on input-output model, quantitatively characterizing resources flows across 30 regions of China from six dimensions: monetary trade, fossil energy and renewable energy, blue water and green water, as well as carbon emissions. Furthermore, it carries out artificial intelligence algorithms to conduct a comprehensive clustering and analysis of resource utilization and environmental disparities across various regions in China, enabling a quantitative assessment of each region’s resources sustainability index. The findings identify three distinct regional clusters: the average resources sustainable development evaluation index (<i>SDI</i>) of the northern and western resource-intensive areas (Cluster 1) is −0.68, indicating that the resources are mainly in the output state; The average <i>SDI</i> of the central and eastern production-oriented regions (Cluster 2) is about 0.10, showing a relatively balanced utilization of resources and preferable regional sustainability; The average <i>SDI</i> of the developed region driven by economy and consumption (Cluster 3) is as high as 1.31, presenting serious net import of resources and environmental pressure. This article emphasizes the significant differences in regional resource sustainability and reveals the importance of analyzing energy and ecological resources from a trade perspective to achieve more balanced regional development.","PeriodicalId":25,"journal":{"name":"ACS Sustainable Chemistry & Engineering","volume":"47 1","pages":""},"PeriodicalIF":7.3000,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Regional Differences Reflected in Resource Flow in China: Multidimensional Analysis Integrating MRIO and Machine Learning Clustering\",\"authors\":\"Danzhu Liu, Jinqiang Liang, Jibin Zhou, Shuliang Xu, Mao Ye, Zhongmin Liu\",\"doi\":\"10.1021/acssuschemeng.4c09911\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the context of globalization and trade liberalization, the harmonious development of the economy, energy, and ecology has become a critical global issue. The inter-regional flows of energy, water resources, and carbon emissions play an increasingly influential role in economic growth. However, there are significant differences in resource endowment and consumption among different regions of China. To bridge these regional gaps and enable a quantitative understanding of multidimensional resource interactions, this study presents a resources embodied flow framework based on input-output model, quantitatively characterizing resources flows across 30 regions of China from six dimensions: monetary trade, fossil energy and renewable energy, blue water and green water, as well as carbon emissions. Furthermore, it carries out artificial intelligence algorithms to conduct a comprehensive clustering and analysis of resource utilization and environmental disparities across various regions in China, enabling a quantitative assessment of each region’s resources sustainability index. The findings identify three distinct regional clusters: the average resources sustainable development evaluation index (<i>SDI</i>) of the northern and western resource-intensive areas (Cluster 1) is −0.68, indicating that the resources are mainly in the output state; The average <i>SDI</i> of the central and eastern production-oriented regions (Cluster 2) is about 0.10, showing a relatively balanced utilization of resources and preferable regional sustainability; The average <i>SDI</i> of the developed region driven by economy and consumption (Cluster 3) is as high as 1.31, presenting serious net import of resources and environmental pressure. This article emphasizes the significant differences in regional resource sustainability and reveals the importance of analyzing energy and ecological resources from a trade perspective to achieve more balanced regional development.\",\"PeriodicalId\":25,\"journal\":{\"name\":\"ACS Sustainable Chemistry & Engineering\",\"volume\":\"47 1\",\"pages\":\"\"},\"PeriodicalIF\":7.3000,\"publicationDate\":\"2025-06-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Sustainable Chemistry & Engineering\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1021/acssuschemeng.4c09911\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Sustainable Chemistry & Engineering","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1021/acssuschemeng.4c09911","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Regional Differences Reflected in Resource Flow in China: Multidimensional Analysis Integrating MRIO and Machine Learning Clustering
In the context of globalization and trade liberalization, the harmonious development of the economy, energy, and ecology has become a critical global issue. The inter-regional flows of energy, water resources, and carbon emissions play an increasingly influential role in economic growth. However, there are significant differences in resource endowment and consumption among different regions of China. To bridge these regional gaps and enable a quantitative understanding of multidimensional resource interactions, this study presents a resources embodied flow framework based on input-output model, quantitatively characterizing resources flows across 30 regions of China from six dimensions: monetary trade, fossil energy and renewable energy, blue water and green water, as well as carbon emissions. Furthermore, it carries out artificial intelligence algorithms to conduct a comprehensive clustering and analysis of resource utilization and environmental disparities across various regions in China, enabling a quantitative assessment of each region’s resources sustainability index. The findings identify three distinct regional clusters: the average resources sustainable development evaluation index (SDI) of the northern and western resource-intensive areas (Cluster 1) is −0.68, indicating that the resources are mainly in the output state; The average SDI of the central and eastern production-oriented regions (Cluster 2) is about 0.10, showing a relatively balanced utilization of resources and preferable regional sustainability; The average SDI of the developed region driven by economy and consumption (Cluster 3) is as high as 1.31, presenting serious net import of resources and environmental pressure. This article emphasizes the significant differences in regional resource sustainability and reveals the importance of analyzing energy and ecological resources from a trade perspective to achieve more balanced regional development.
期刊介绍:
ACS Sustainable Chemistry & Engineering is a prestigious weekly peer-reviewed scientific journal published by the American Chemical Society. Dedicated to advancing the principles of green chemistry and green engineering, it covers a wide array of research topics including green chemistry, green engineering, biomass, alternative energy, and life cycle assessment.
The journal welcomes submissions in various formats, including Letters, Articles, Features, and Perspectives (Reviews), that address the challenges of sustainability in the chemical enterprise and contribute to the advancement of sustainable practices. Join us in shaping the future of sustainable chemistry and engineering.