Department of Economics and Management, North China Electric Power University, Baoding, Hebei, China.
Department of Economics and Management, North China Electric Power University, Baoding, Hebei, China.
Sci Total Environ. 2019 Dec 1;694:133724. doi: 10.1016/j.scitotenv.2019.133724. Epub 2019 Aug 1.
As the maximal carbon dioxide (CO) contributor in world, China is embracing severe stress from emission reduction. It is increasingly important to study the factors affecting China's CO emissions. Many researches had extensively researched the driving forces of CO emissions of China. However, majority of the researches adopt a conventional linear method based on time-series or cross-section data for researching the CO emissions as well as nearly neglect nonlinear relationships. To surmount the limitations of extant investigations, this research adopts a data-driven nonparametric additive regression approach to examine primary influencing factors of China's CO emissions. The results manifest that the nonlinear influence of economy on CO emissions is same as the Environmental Kuznets Curve hypothesis. The household consumption level embodies the inverted "U-type" pattern. The industrialization also embodies the overturned "U-type" relationship. Aggregate retail sales of consumer goods present a positive "U-type" effect upon CO emissions. Similarly, the urbanization signifies a positive "U-type" nexus upon CO emissions. Energy intensity indicates a positive "U-type" nexus. The paper ought to exert more attention to the dynamic effects of the driving forces above in order to abate the CO emissions of China. This study will also propose corresponding policies and recommendations according to the dynamic effects.
作为世界上最大的二氧化碳（CO）排放国，中国正面临减排的巨大压力。研究影响中国 CO 排放的因素变得越来越重要。许多研究已经广泛研究了中国 CO 排放的驱动因素。然而，大多数研究采用基于时间序列或横截面数据的常规线性方法来研究 CO 排放，几乎忽略了非线性关系。为了克服现有研究的局限性，本研究采用数据驱动的非参数加法回归方法来检验中国 CO 排放的主要影响因素。研究结果表明，经济对 CO 排放的非线性影响与环境库兹涅茨曲线假说相同。家庭消费水平表现出倒“U 型”模式。工业化也体现了翻转的“U 型”关系。社会消费品零售总额对 CO 排放呈正“U 型”效应。同样，城市化对 CO 排放也具有正“U 型”关系。能源强度显示出正“U 型”关系。本文应更加关注上述驱动力的动态效应，以减少中国的 CO 排放。根据动态效应，本文还将提出相应的政策和建议。
