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| “双碳”目标下中国三大城市群减污降碳协同治理区域差异及关键路径识别 | |
| 引用本文： | 狄乾斌,陈小龙,侯智文.“双碳”目标下中国三大城市群减污降碳协同治理区域差异及关键路径识别[J].资源科学,2022,44(6):1155-1167. |
| 作者姓名： | 狄乾斌 陈小龙 侯智文 |
| 作者单位： | 1.辽宁师范大学地理科学学院,大连116029 2.辽宁师范大学海洋经济与可持续发展研究中心,大连 116029 |
| 基金项目： | 国家自然科学基金项目(42076222) |
| 摘 要： | 城市群是中国区域经济与绿色发展的主要承载形式,其战略地位与日俱增,在实现碳中和、碳达峰目标下研究城市群减污降碳协同治理,是探索区域可持续发展的重要内容。基于减污降碳协同治理演化机理,借助2010—2019年三大城市群的面板数据,采用相关系数矩阵法、复合系统协同度模型测度城市群减污降碳协同治理协同度;结合基尼系数、变异系数、泰尔指数、引力模型等方法分析城市群减污降碳协同治理区域差异及空间联系强度;并对减污降碳协同治理关键路径进行识别。结果表明：①三大城市群减污降碳协同治理有序度呈显著增长趋势;而减污降碳协同治理协同度水平较低,系统处于不稳定、不协调的状态。②京津冀减污降碳协同治理度内部差异逐步减小,长三角内部差异基本保持稳定,珠三角内部差异波动较大。③京津冀和珠三角减污降碳协同治理协同度的网络密度和网络结构的复杂程度高于长三角,空间联系强度等级较高。为此,三大城市群减污降碳协同治理可以从政策、技术、能力建设等方面,通过做好顶层设计、转型升级、合作拓展等路径予以推进。 |
| 关 键 词： | “双碳”目标 城市群 减污降碳 协同治理 空间联系 路径识别 复合系统协同度模型 |
| 收稿时间： | 2021-12-01 |
| 修稿时间： | 2022-03-25 |
Regional differences and key pathway identification of the coordinated governance of pollution control and carbon emission reduction in the three major urban agglomerations of China under the “Double-Carbon” targets |
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| DI Qianbin,CHEN Xiaolong,HOU Zhiwen.Regional differences and key pathway identification of the coordinated governance of pollution control and carbon emission reduction in the three major urban agglomerations of China under the “Double-Carbon” targets[J].Resources Science,2022,44(6):1155-1167. | |
| Authors: | DI Qianbin CHEN Xiaolong HOU Zhiwen |
| Institution: | 1. School of Geography, Liaoning Normal University, Dalian 116029, China 2. Marine Economies and Sustainable Development Research Center, Liaoning Normal University, Dalian 116029, China |
| Abstract: | Urban agglomerations are the main carrier of regional economic and green development in China, and their strategic position is rapidly increasing. Under the targets of carbon neutralization and carbon peaking, research on coordinated governance of urban agglomeration pollution control and carbon emission reduction is an important content of exploring regional sustainable development. Based on the mechanism of change of coordinated governance of pollution control and carbon emission reduction, this study used the panel data of the three major urban agglomerations of China from 2010 to 2019 to measure the coordination degree of coordinated governance of pollution control and carbon emission reduction in these regions with correlation coefficient matrix method and composite system coordination degree model. Using Gini coefficient, coefficient of variation, Theil index and its decomposition method, and gravity model, this study analyzed the regional differences and spatial connection intensity of the coordinated governance of pollution control and carbon emission reduction and identified the critical pathways of pollution control and carbon emission reduction coordinated governance. The results show that: (1) The orderliness degree of coordinated governance in the three major urban agglomerations showed a significant growth trend; However, the coordination degree is low, and the system is in an unstable and uncoordinated state. (2) The differences in the coordination degree of coordinated governance of pollution control and carbon emission reduction in the Beijing-Tianjin-Hebei region gradually decreased, while the differences in the Yangtze River Delta remained stable, and the internal differences in the Pearl River Delta fluctuate greatly. (3) The network density and network structure complexity in the Beijing-Tianjin-Hebei region and the Pearl River Delta are higher than those in the Yangtze River Delta, and the spatial connection intensity is higher. The cities are interconnected and influenced by each other. The coordinated governance of pollution control and carbon emission reduction in the three major urban agglomerations can be promoted from the aspects of policy, technology, capacity building, top-level design, transformation and upgrading, and cooperation and expansion. |
| Keywords: | Dual-Carbon targets urban agglomerations pollution control and carbon emission reduction coordinated governance spatial connection critical pathway identification coordination degree model of composite system |
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