The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation

被引:13
|
作者
Zheng, Ruijing [1 ]
Cheng, Yu [1 ]
Liu, Haimeng [2 ]
Chen, Wei [1 ]
Chen, Xiaodong [3 ]
Wang, Yaping [1 ]
机构
[1] Shandong Normal Univ, Coll Geog & Environm, Jinan 250358, Peoples R China
[2] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
[3] Sichuan Anticultural Univ, Coll Management, Chengdu 611130, Peoples R China
关键词
carbon emission efficiency; super-SBM model; spatiotemporal pattern; technological innovation; panel data models; urban agglomerations; SLACKS-BASED MEASURE; UNIT-ROOT TESTS; PANEL-DATA; INDUSTRIAL-STRUCTURE; ENERGY-CONSUMPTION; CHINA; URBANIZATION; PERFORMANCE; INTENSITY; SECTOR;
D O I
10.3390/ijerph19159111
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Urban agglomerations have become the core areas for carbon reduction in China since they account for around 75% of its total emissions. Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and the Pearl River Delta (PRD), which are its most important poles of regional development and technological innovation, are key to achieving China's carbon peak emissions target. Based on the panel data of these three major urban agglomerations from 2003 to 2017, this study estimated the carbon emission efficiency (CEE) by the super-efficiency slacks-based measure (super-SBM) model and analyzed its spatiotemporal distribution pattern. The Dagum Gini coefficient was used to evaluate the difference in CEE between the three major agglomerations, while panel data models were established to analyze the impact of technological innovation on the three agglomerations. The overall CEE showed an upward trend during the study period, with significant spatial and temporal variations. Additionally, the main source of urban agglomeration difference in CEE evolved from inter-regional net differences to intensity of transvariation. While technological innovations are expected to significantly improve CEE, their effect varies among urban agglomerations. These results provide policymakers with insights on the collaborative planning of urban agglomerations and the low-carbon economy.
引用
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页数:22
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