Chen Wenhui, Lei Yalin
School of Humanities and Economic Management, China University of Geosciences, Room 505 of Administrative Building, 29# Xueyuan Rd, Haidian District, Beijing, 100083, People's Republic of China.
Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resources, Beijing, 100083, China.
Environ Sci Pollut Res Int. 2017 Feb;24(6):5757-5772. doi: 10.1007/s11356-016-8300-y. Epub 2017 Jan 3.
Identifying the impact path on factors of CO emissions is crucial for the government to take effective measures to reduce carbon emissions. The most existing research focuses on the total influence of factors on CO emissions without differentiating between the direct and indirect influence. Moreover, scholars have addressed the relationships among energy consumption, economic growth, and CO emissions rather than estimating all the causal relationships simultaneously. To fill this research gaps and explore overall driving factors' influence mechanism on CO emissions, this paper utilizes a path analysis model with latent variables (PA-LV) to estimate the direct and indirect effect of factors on China's energy-related carbon emissions and to investigate the causal relationships among variables. Three key findings emanate from the analysis: (1) The change in the economic growth pattern inhibits the growth rate of CO emissions by reducing the energy intensity; (2) adjustment of industrial structure contributes to energy conservation and CO emission reduction by raising the proportion of the tertiary industry; and (3) the growth of CO emissions impacts energy consumption and energy intensity negatively, which results in a negative impact indirectly on itself. To further control CO emissions, the Chinese government should (1) adjust the industrial structure and actively develop its tertiary industry to improve energy efficiency and develop low-carbon economy, (2) optimize population shifts to avoid excessive population growth and reduce energy consumption, and (3) promote urbanization steadily to avoid high energy consumption and low energy efficiency.
识别一氧化碳排放因素的影响路径对于政府采取有效措施减少碳排放至关重要。现有的大多数研究都集中在因素对一氧化碳排放的总体影响上，而没有区分直接影响和间接影响。此外，学者们关注的是能源消耗、经济增长和一氧化碳排放之间的关系，而不是同时估计所有的因果关系。为了填补这一研究空白并探索总体驱动因素对一氧化碳排放的影响机制，本文采用了带有潜在变量的路径分析模型（PA-LV）来估计因素对中国能源相关碳排放的直接和间接影响，并研究变量之间的因果关系。分析得出三个关键发现：（1）经济增长模式的变化通过降低能源强度抑制了一氧化碳排放的增长率；（2）产业结构调整通过提高第三产业比重有助于节能和减少碳排放；（3）一氧化碳排放的增长对能源消耗和能源强度产生负面影响，进而间接对其自身产生负面影响。为了进一步控制一氧化碳排放，中国政府应（1）调整产业结构，积极发展第三产业，以提高能源效率并发展低碳经济；（2）优化人口转移，避免人口过度增长并减少能源消耗；（3）稳步推进城市化，避免高能耗和低能效。
