A spatiotemporal investigation of energy-driven factors in China: A region-based structural decomposition analysis
A spatiotemporal investigation of energy-driven factors in China: A region-based structural decomposition analysis
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中国能源驱动因素时空调查：基于区域的结构分解分析
DOI：
10.1016/j.energy.2020.118249
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发表时间：
2020-09
期刊：
影响因子：
9
通讯作者：
He Rongxiao
中科院分区：
文献类型：
--
作者：
Wang Xianzhu;Huang He;Hong Jingke;Ni Danfei;He Rongxiao
为了实现中国的强制性节能减排目标，有必要在考虑区域差异的情况下研究能源增长的驱动因素。本研究建立了基于区域的结构分解分析方法，从时间角度捕捉东、中、西部驱动因素的空间异质性。结果表明，随着国民生产总值增长率的持续下降，能源增加量和增长速度都有明显的下降趋势。从历史上看，在整个调查期间，最终需求是能源使用增加的最大驱动因素，而能源强度的变化和结构变化分别被确定为2007年至2010年和2010年至2012年减少的最大贡献者。从空间上看，东部地区能源需求增长最快，其次是西部和中部地区。各驱动因素的影响均表现为局部主导。生产结构和最终需求量的变化产生了最显著的溢出效应。研究结果增强了对区域层面能源驱动因素动态演化的认识，有助于在考虑区域特殊性的基础上制定有针对性的节能政策。
To achieve China′s mandatory energy conservation and emission reduction targets, it is necessary to examine the driving factors in the energy increase with the due consideration of regional disparities. This study develops a region-based structural decomposition analysis method to capture the spatial heterogeneity of driving factors between eastern, central, and western China from a temporal perspective. The results show that there is a clear declining trend both in the amount and growth rate of energy increase linked to the continuous decrease in the rate of national GDP growth. Historically, final demand was the largest driver of increased energy use during the whole period under investigation whilst the change in energy intensity and structural change are identified as the biggest contributors to reductions from 2007 to 2010 and from 2010 to 2012, respectively. From a spatial perspective, energy demands in eastern regions have grown most, followed by the western and central regions. The impacts of all driving factors were more local-dominant. The changes in production structure and final demand volumes generated the most significant spillover effects. The findings of this study enhance the understanding of dynamic evolution in energy-driven factors at the regional level, which is beneficial to making well-directed energy conservation policies by considering regional specificity.
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