Spatiotemporal evolution and driving factors of carbon emission efficiency of resource-based cities in the Yellow River Basin of China

被引:0
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作者
Mei Song
Yujin Gao
Liyan Zhang
Furong Dong
Xinxin Zhao
Jin Wu
机构
[1] China University of Mining and Technology-Beijing,School of Management
[2] Ministry of Natural Resources,Key Laboratory of Carrying Capacity Assessment for Resource and Environment
[3] Bank of China,undefined
[4] Chongqing Branch,undefined
关键词
Resource-based city; Carbon emission efficiency; Super-efficiency SBM-DEA model; Panel Tobit regression model; Yellow River Basin;
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中图分类号
学科分类号
摘要
As an important part of regional coordinated development, the high-quality development of the Yellow River Basin has become a national strategy. It is imminent for resource-based cities to perform a high-quality transformation. The analysis of carbon emission efficiency in the Yellow River Basin includes the examination of spatiotemporal evolution characteristics and the main driving factors. This is done by utilizing the super-efficiency SBM-DEA and panel Tobit regression models, with the assistance of night light data. Our findings are as follows: (1) Carbon emissions continue to grow. The “Jiziwan” basin is an area where plenty of high-emitting cities agglomerate. The carbon emission of resource-based cities presents a W-shaped pattern in time. (2) In time, the carbon emission efficiency follows a U-shaped curve. Spatially, the carbon emission efficiency in the middle reaches is comparatively low, whereas it is relatively high in both the upper and lower reaches. And that in high carbon-emitting resource-based cities are in the low to medium range. (3) Carbon emission efficiency has a significant negative relationship with energy intensity, urbanization rate, and population density and a significant positive relationship with industrial proportion. Energy intensity is the most direct driving force. That is to say, we can increase carbon emission efficiency effectively by reducing energy intensity.
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页码:96795 / 96807
页数:12
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