School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China.
Int J Environ Res Public Health. 2019 Feb 14;16(4):555. doi: 10.3390/ijerph16040555.
In China, transportation accounts for a large proportion of total energy consumption and that trend is projected to increase in the future. Through the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model, OLS regressions were conducted to investigate the impacts of gross domestic product (GDP), urbanization, energy intensity and transport structure on the transport energy consumption in China's three regions. The analyses of inter-provincial panel data during the period 2006⁻2015 is compared to the analysis of the data from 1996 to 2005 to determine the change. There were two primary findings from this study. First, the changes of the influencing degree in three regions are considered. GDP is still the main driver of transport energy consumption in eastern region, while urbanization becomes the main driver in the other two regions. Second, the relationship between the elasticity and the value of each variable is detected. The elasticity of transport energy consumption with respect to GDP, transport structure, energy intensity and urbanization have separate positive and significant relationships. The primary measure is to optimize transport structure in the central region, while reducing energy intensity in the western region. Finally, we propose relevant policy recommendations for the three regions.
在中国，交通运输占总能源消耗的很大比例，而且这种趋势预计在未来还会增加。通过随机影响回归人口、富裕和技术模型（STIRPAT），进行了 OLS 回归，以研究国内生产总值（GDP）、城市化、能源强度和交通结构对中国三个地区交通能源消耗的影响。对 2006-2015 年期间的省级面板数据进行了分析，并与 1996-2005 年的数据进行了比较，以确定变化。这项研究有两个主要发现。首先，考虑了三个地区影响程度的变化。在东部地区，GDP 仍然是交通能源消耗的主要驱动因素，而在其他两个地区，城市化成为主要驱动因素。其次，检测了每个变量的弹性和值之间的关系。交通能源消耗对 GDP、交通结构、能源强度和城市化的弹性具有单独的正相关关系。主要措施是优化中部地区的交通结构，同时降低西部地区的能源强度。最后，我们为三个地区提出了相关的政策建议。
