黄河流域能源综合效率的时空演变与驱动因素

doi:10.18402/resci.2020.01.15

摘要/Abstract

摘要：

黄河流域是中国重要的能源基地,黄河流域能源综合效率问题直接影响黄河流域生态保护和高质量发展。本文基于超效率SBM模型测度1997—2017年黄河流域9省区的能源综合效率值,选取核密度估计方法等分析能源综合效率的时空演变特征,借助地理探测器分析能源综合效率的驱动因素。结果表明：①从时序变化来看,1997—2017年,黄河流域能源综合效率总体呈“高—低—高”的U型变化特征,其中1997—2003年总体呈降低趋势,2004—2010年迅速增长后于2009年下降,2011—2017年持续下降后于2015年上升。②从空间差异来看,黄河流域西部省份能源综合效率相对较低,中部省份能源综合效率受多重因素影响而上下波动,东部的山东省能源综合效率优势显著。总体来看,黄河流域地区能源综合效率由非均衡逐渐向均衡转变。③能源综合效率驱动因子解释力从大到小依次为财政分权、城镇化水平、人力资本水平、对外开放程度,黄河流域省份地方财政支出的扩大、城镇化进程的加快、人才结构的升级、对外开放程度的提高,共同驱动能源综合效率提高。应充分发挥黄河流域地区比较优势,在各项政策指导下加强流域内协作,推动黄河流域生态保护和高质量发展。

关键词: 能源综合效率, 环境要素, 社会要素, 超效率SBM模型, 地理探测器, 黄河流域

Abstract:

The Yellow River Basin is an important energy base in China. The comprehensive energy efficiency of the Yellow River basin directly affects the ecological protection and high-quality development of the region. Using the super efficiency slack based measure (SBM) model to measure the comprehensive energy efficiency of nine provinces (autonomous regions) in the Yellow River Basin from 1997 to 2017, the nuclear density estimation method was selected to analyze the temporal and spatial change characteristics of comprehensive energy efficiency, and the driving factors of comprehensive energy efficiency were analyzed with the help of the geographical detector. The results show that: (1) From 1997 to 2017, the comprehensive energy efficiency of the Yellow River Basin showed a U-shaped trend of high-low-high. The comprehensive energy efficiency of the Yellow River Basin decreased from 1997 to 2003, decreased in 2009 after rapid growth from 2004 to 2010, and increased in 2015 after continuous decline from 2011 to 2017. (2) Spatially, the comprehensive energy efficiency of the western provinces of the Yellow River Basin is relatively low, and the comprehensive energy efficiency of the central provinces is greatly affected by multiple factors, while the comprehensive energy efficiency of the eastern province Shandong is significantly higher. The comprehensive energy efficiencies of the eastern, central, and western provinces and the upper, middle, and lower reaches of the Yellow River Basin have all changed from spatially unbalanced to balanced. (3) With regard to the driving factors, the explanation power of factors is in the order of financial decentralization, urbanization level, human capital level, and the degree of opening to the outside world. Expansion of local financial expenditure, acceleration of urbanization, upgrading of talent structure, and improvement of opening-up in the Yellow River Basin jointly drive the improvement of comprehensive energy efficiency. Give full play to the comparative advantages of the Yellow River Basin, and strengthen collaboration within the basin under various policies for promoting the ecological protection and high-quality development of the Yellow River Basin.

Key words: comprehensive energy efficiency, environmental element, social element, Super-SBM model, geographical detector, Yellow River Basin

关伟, 许淑婷, 郭岫垚. 黄河流域能源综合效率的时空演变与驱动因素[J]. 资源科学, 2020, 42(1): 150-158.

GUAN Wei, XU Shuting, GUO Xiuyao. Spatiotemporal change and driving factors of comprehensive energy efficiency in the Yellow River Basin[J]. Resources Science, 2020, 42(1): 150-158.

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类型	一级	二级	三级
投入	资源要素	能源消费	地区能源消费总量
	资本要素	资本存量	张军算法下的资本存量
	劳动力要素	就业人口	年末就业人口数
	技术要素	技术贸易	技术市场成交额
产出	期望产出	经济效益	以1997年为基期的不变价人均GDP值
	期望产出	社会效益	人均公共财政支出
	非期望产出	环境污染	工业二氧化硫排放量、PM_2.5、工业废水排放总量、工业烟（粉）尘排放量、工业固体废物产生量
	非期望产出	环境影响	二氧化碳排放量

省份	1997年	2007年	2017年
山东	1.050	0.931	1.022
河南	0.842	0.695	1.063
山西	1.101	0.827	1.078
陕西	0.596	0.633	1.034
内蒙古	1.018	0.742	1.050
宁夏	1.019	0.694	1.019
甘肃	1.012	0.584	1.117
四川	1.011	0.688	1.043
青海	1.008	0.621	1.009

	X₁	X₂	X₃	X₄
X₁	0.202
X₂	0.393	0.178
X₃	0.289	0.238	0.120
X₄	0.266	0.288	0.285	0.043