基于动态概率加权法的中国 12 个城市群协调差异驱动的可持续性评价

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society Pub Date : 2024-10-17 DOI:10.1016/j.scs.2024.105904

{"title":"基于动态概率加权法的中国 12 个城市群协调差异驱动的可持续性评价","authors":"","doi":"10.1016/j.scs.2024.105904","DOIUrl":null,"url":null,"abstract":"<div><div>The sustainable development of urban agglomerations represents a significant driving force in national and global development. This study establishes an indicator system comprising factors associated with the economy, society, and environment, in accordance with the Triple Bottom Line, to assess the sustainability of 12 urban agglomerations in China. A novel framework is proposed, including a dynamic probability weighting method based on sufficient stochastic simulations and a coordination-difference-driven aggregation approach that considers the coordination degree and differences between evaluated objects. The evaluation revealed significant regional disparities in urban agglomeration sustainability from 2012 to 2021. The eastern region's Yangtze River Delta, Pearl River Delta, Beijing–Tianjin–Hebei region, and Shandong Peninsula exhibit above-average sustainability performance. Conversely, the western region's Guangzhong, Guangxi Beibu Gulf, Chengyu, and Ningxia Yellow River regions exhibit below-average performance. Moreover, the growth rate of sustainability values for the 12 urban agglomerations followed a downward trajectory. Furthermore, the environmental dimension is the primary driver of sustainable development in urban agglomerations, while the economic dimension represents the main obstacle. These findings offer policymakers a scientific and practical framework to guide sustainability-related decisions.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":null,"pages":null},"PeriodicalIF":10.5000,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation of the coordination-difference-driven sustainability of 12 urban agglomerations in China based on the dynamic probability weighting method\",\"authors\":\"\",\"doi\":\"10.1016/j.scs.2024.105904\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The sustainable development of urban agglomerations represents a significant driving force in national and global development. This study establishes an indicator system comprising factors associated with the economy, society, and environment, in accordance with the Triple Bottom Line, to assess the sustainability of 12 urban agglomerations in China. A novel framework is proposed, including a dynamic probability weighting method based on sufficient stochastic simulations and a coordination-difference-driven aggregation approach that considers the coordination degree and differences between evaluated objects. The evaluation revealed significant regional disparities in urban agglomeration sustainability from 2012 to 2021. The eastern region's Yangtze River Delta, Pearl River Delta, Beijing–Tianjin–Hebei region, and Shandong Peninsula exhibit above-average sustainability performance. Conversely, the western region's Guangzhong, Guangxi Beibu Gulf, Chengyu, and Ningxia Yellow River regions exhibit below-average performance. Moreover, the growth rate of sustainability values for the 12 urban agglomerations followed a downward trajectory. Furthermore, the environmental dimension is the primary driver of sustainable development in urban agglomerations, while the economic dimension represents the main obstacle. These findings offer policymakers a scientific and practical framework to guide sustainability-related decisions.</div></div>\",\"PeriodicalId\":48659,\"journal\":{\"name\":\"Sustainable Cities and Society\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":10.5000,\"publicationDate\":\"2024-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sustainable Cities and Society\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2210670724007285\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CONSTRUCTION & BUILDING TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Cities and Society","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210670724007285","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}

引用次数: 0

摘要

城市群的可持续发展是国家和全球发展的重要推动力。本研究根据 "三重底线 "理论，建立了一个由经济、社会和环境相关因素组成的指标体系，以评估中国 12 个城市群的可持续发展状况。提出了一个新颖的框架，包括基于充分随机模拟的动态概率加权方法，以及考虑评价对象之间协调程度和差异的协调-差异驱动的汇总方法。评估结果表明，从 2012 年到 2021 年，城市群可持续性存在明显的区域差异。东部地区的长江三角洲、珠江三角洲、京津冀地区和山东半岛的可持续性表现高于平均水平。相反，西部地区的广东、广西北部湾、成渝和宁夏黄河流域的可持续性表现低于平均水平。此外，12 个城市群的可持续性值增长率呈下降趋势。此外，环境维度是城市群可持续发展的主要驱动力，而经济维度则是主要障碍。这些发现为政策制定者提供了一个科学实用的框架，以指导与可持续性相关的决策。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Evaluation of the coordination-difference-driven sustainability of 12 urban agglomerations in China based on the dynamic probability weighting method

The sustainable development of urban agglomerations represents a significant driving force in national and global development. This study establishes an indicator system comprising factors associated with the economy, society, and environment, in accordance with the Triple Bottom Line, to assess the sustainability of 12 urban agglomerations in China. A novel framework is proposed, including a dynamic probability weighting method based on sufficient stochastic simulations and a coordination-difference-driven aggregation approach that considers the coordination degree and differences between evaluated objects. The evaluation revealed significant regional disparities in urban agglomeration sustainability from 2012 to 2021. The eastern region's Yangtze River Delta, Pearl River Delta, Beijing–Tianjin–Hebei region, and Shandong Peninsula exhibit above-average sustainability performance. Conversely, the western region's Guangzhong, Guangxi Beibu Gulf, Chengyu, and Ningxia Yellow River regions exhibit below-average performance. Moreover, the growth rate of sustainability values for the 12 urban agglomerations followed a downward trajectory. Furthermore, the environmental dimension is the primary driver of sustainable development in urban agglomerations, while the economic dimension represents the main obstacle. These findings offer policymakers a scientific and practical framework to guide sustainability-related decisions.

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

来源期刊

Sustainable Cities and Society Social Sciences-Geography, Planning and Development

CiteScore

22.00

自引率

13.70%

发文量

810

审稿时长

27 days

期刊介绍： Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including: 1. Smart cities and resilient environments; 2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management; 3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management); 4. Energy efficient, low/zero carbon, and green buildings/communities; 5. Climate change mitigation and adaptation in urban environments; 6. Green infrastructure and BMPs; 7. Environmental Footprint accounting and management; 8. Urban agriculture and forestry; 9. ICT, smart grid and intelligent infrastructure; 10. Urban design/planning, regulations, legislation, certification, economics, and policy; 11. Social aspects, impacts and resiliency of cities; 12. Behavior monitoring, analysis and change within urban communities; 13. Health monitoring and improvement; 14. Nexus issues related to sustainable cities and societies; 15. Smart city governance; 16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society; 17. Big data, machine learning, and artificial intelligence applications and case studies; 18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems. 19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management; 20. Waste reduction and recycling; 21. Wastewater collection, treatment and recycling; 22. Smart, clean and healthy transportation systems and infrastructure;