School of Management, China University of Mining and Technology-Beijing, Beijing, 100083, China.
Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Natural Resources, Sanhe, 065201, China.
Environ Sci Pollut Res Int. 2023 Sep;30(43):96795-96807. doi: 10.1007/s11356-023-29113-4. Epub 2023 Aug 15.
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.
作为区域协调发展的重要组成部分，黄河流域的高质量发展已成为国家战略。资源型城市进行高质量转型迫在眉睫。对黄河流域碳排放效率的分析包括考察时空演变特征和主要驱动因素。本研究利用超效率 SBM-DEA 和面板 Tobit 回归模型，并借助夜间灯光数据来完成。我们的研究结果如下：（1）碳排放持续增长。“鸡子湾”盆地是高排放城市聚集的区域。资源型城市的碳排放呈现出时间上的 W 型模式。（2）在时间上，碳排放效率呈现出 U 型曲线。从空间上看，中游地区的碳排放效率相对较低，而上游和下游地区的效率相对较高，高碳排放资源型城市的效率处于中低水平。（3）碳排放效率与能源强度、城市化率和人口密度呈显著负相关，与产业比例呈显著正相关。能源强度是最直接的驱动力。也就是说，我们可以通过降低能源强度来有效提高碳排放效率。
