A Heterogeneity Study of Carbon Emissions Driving Factors in Beijing-Tianjin-Hebei Region, China, Based on PGTWR Model

被引:5
作者
Lou, Ting [1 ,2 ]
Ma, Jianhui [1 ,2 ,3 ]
Liu, Yu [1 ,2 ]
Yu, Lei [1 ,2 ]
Guo, Zhaopeng [1 ,2 ]
He, Yan [1 ,2 ]
机构
[1] Hebei Univ, Sch Econ, Baoding 071002, Peoples R China
[2] Hebei Univ, Res Ctr Resources Utilizat & Environm Conservat, Baoding 071002, Peoples R China
[3] Tianjin Univ, Sch Management & Econ, Tianjin 300072, Peoples R China
关键词
carbon emission; Beijing-Tianjin-Hebei region; PGTWR model; heterogeneity; driving factors; city; econometrics; GEOGRAPHICALLY-WEIGHTED REGRESSION; ENERGY-RELATED CO2; ECONOMIC-GROWTH; DECOMPOSITION; STIRPAT; IMPACT; CONSUMPTION; FORCES; LEVEL;
D O I
10.3390/ijerph19116644
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Beijing-Tianjin-Hebei region is an important economic growth pole in China and achieving carbon emission reduction in the region is of great practical significance. Studying the heterogeneity of the influencing factors of carbon emission in this region contributes to formulating targeted regional carbon emission reduction policies. Therefore, this paper adopted thirteen cities as individuals of cross-section and conducted spatial and temporal heterogeneity analysis of the influencing factors of converted carbon emissions in the region with panel data from 2013 to 2018 based on the PGTWR model. From a space-time perspective, the regression coefficient of each influencing factor in this region has obvious heterogeneity, which is mainly reflected in the time dimension. In the study period, the impact of industrial structure, the level of urbanization, energy intensity, and the level of economic growth on carbon emission showed a decline curve, while the impact of the level of opening up and the size of population was on the rise, indicating that more attention should be paid to the latter two factors for the time to come. In terms of space, the differences in the influence of industrial structure and energy intensity on carbon emission vary significantly.
引用
收藏
页数:18
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