School of Management, China University of Mining & Technology (Beijing), Beijing, China.
State Key Laboratory of Precision Measuring Technology and Instrument, Tianjin University, Tianjin, China.
PLoS One. 2022 Mar 24;17(3):e0264274. doi: 10.1371/journal.pone.0264274. eCollection 2022.
The Yellow River Basin (YRB) is China's substantial energy consumption base. The issue of carbon emission efficiency directly affects the ecological protection and high-quality development of the YRB. It is the key to achieving carbon peak in 2030 and carbon neutralization in 2060 ("30.60") double carbon emission reduction targets. Therefore, taking YRB as the research object, this paper first calculates the carbon emission and the decoupling state in the YRB. Secondly, the super-efficiency slacks-based measurement (SE-SBM) model is combined with the Malmquist index to analyze the temporal and spatial evolution characteristics of YRB's carbon emission efficiency from static and dynamic perspectives. Thirdly, the dynamic evolution characteristics of carbon emission efficiency are analyzed with the help of the Kernel density function. Finally, the Tobit model analyzes the influencing factors of YRB's and China's carbon emission efficiency. The results show that: (1) Among the nine provinces of YRB, the decoupling state between carbon emissions and economic growth in most provinces changes from weak decoupling to strong decoupling, and the decoupling elasticity index shows a fluctuating downward trend. (2) There are significant differences in carbon emission efficiency among provinces, but on the whole, it shows a stable growth trend. The high-value area of carbon emission efficiency is increasing, and the phenomenon of two-level differentiation is improving. The decline of the technological progress index causes the Malmquist index in Qinghai and Ningxia. On the contrary, the rise of the Malmquist index in the other seven provinces is caused by improving the technical efficiency index. (3) Industrial structure, economic development, and industrialization are the main positive factors affecting YRB's carbon emission efficiency. Urbanization level, green development level, and energy consumption level are the leading negative indicators hindering YRB's improvement of carbon emission efficiency. Therefore, targeted emission reduction suggestions should be formulated according to YRB's resource endowment and development stage characteristics.
黄河流域（YRB）是中国重要的能源消耗基地。碳排放效率问题直接影响黄河流域的生态保护和高质量发展，是实现 2030 年碳达峰、2060 年碳中和（“30.60”）双碳减排目标的关键。因此，以黄河流域为研究对象，本文首先计算了黄河流域的碳排放和脱钩状态。其次，采用超效率松弛基测量（SE-SBM）模型与 Malmquist 指数相结合，从静态和动态两个角度分析了黄河流域碳排放量效率的时空演变特征。再次，借助核密度函数分析了碳排放量效率的动态演变特征。最后，采用 Tobit 模型分析了黄河流域和中国碳排放效率的影响因素。结果表明：（1）在黄河流域的九个省份中，大部分省份的碳排放与经济增长之间的脱钩状态由弱脱钩转变为强脱钩，脱钩弹性指数呈波动下降趋势。（2）各省之间的碳排放效率存在显著差异，但总体上呈稳定增长趋势。碳排放效率的高值区在增加，两级分化现象在改善。技术进步指数的下降导致青海和宁夏的 Malmquist 指数下降，而其他七个省份的 Malmquist 指数上升则是由于技术效率指数的提高。（3）产业结构、经济发展和工业化是影响黄河流域碳排放效率的主要积极因素。城市化水平、绿色发展水平和能源消费水平是阻碍黄河流域提高碳排放效率的主要负面指标。因此，应根据黄河流域的资源禀赋和发展阶段特点，制定有针对性的减排建议。
