呼包鄂榆城市群低碳发展水平综合评价研究
Research on the Comprehensive Evaluation of Low Carbon De-velopment Level of Hohhot-Baotou-Ordos-Yulin Urban Ag-glomeration
丁玉贤 1王锟 1闫雪萌1
作者信息
- 1. 内蒙古科技大学土木工程学院;内蒙古自治区高校智能建造与运维工程研究中心
- 折叠
摘要
在全球大力推动"双碳"目标的大背景下,探索和推广区域低碳发展模式也成为了全球经济可持续发展的重要任务和挑战.呼包鄂榆城市群是中国北方典型的资源密集型城市群,当前发展仍存在着多产业能源利用率低、污染排放高等问题,作为我国北方重要的生态安全屏障,其低碳转型发展迫在眉睫.首先对呼包鄂榆城市群低碳发展现状进行客观分析,建立包含低碳经济、能源利用、生态环保、社会生活4个方面的低碳发展水平评价指标体系,采用主成分分析法筛选指标,构建熵权-TOPSIS模型、耦合协调度模型,定量评价呼包鄂榆城市群的低碳发展水平.综合以上研究结果,针对性地提出呼包鄂榆城市群低碳发展的优化路径.
Abstract
Against the background of vigorously promoting the"Double Carbon"goals around the world,ex-ploring and promoting regional low carbon development models has also become an important task and chal-lenge for the sustainable development of the global economy.The Hohhot-Baotou-Ordos-Yulin urban agglom-eration is a typical resource-intensive urban agglomeration in northern China.At present,there are still prob-lems of low energy utilization and high pollution emissions in multiple industries.As an important ecological se-curity barrier in northern my country,its low carbon transformation and development are imminent.First of all,the low carbon development status of the Hohhot-Baotou-Ordos-Yulin urban agglomeration is objectively ana-lyzed,and a low carbon development level evaluation indicator system is established that includes four as-pects:low carbon economy,energy utilization,ecological environmental protection,and social life.The principal component analysis method is used to screen indicators.Build an entropy weight-TOPSIS model and a cou-pled coordination degree model to quantitatively evaluate the low carbon development level of the Ho-hhot-Baotou-Ordos-Yulin urban agglomeration.Based on the above research results,this paper propose an optimized path for low carbon development of the Hohhot-Baotou-Ordos-Yulin urban agglomeration.
关键词
低碳综合评价/呼包鄂榆城市群/影响因素/耦合协调Key words
Low Carbon Comprehensive Evaluation/Hohhot-Baotou-Ordos-Yulin Urban Agglomeration/In-fluencing Factor/Coupling Coordination引用本文复制引用
出版年
2024
NETL
NSTL
万方数据