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Drivers of the decoupling indicator between the economic growth and energy-related CO2 in China: A revisit from the perspectives of decomposition and spatiotemporal heterogeneity
- Dong, Feng, Li, Jingyun, Wang, Yue, Zhang, Xiaoyun, Zhang, Shengnan, Zhang, Shuaiqing
- The Science of the total environment 2019 v.685 pp. 631-658
- business enterprises, carbon, carbon dioxide, coal, emissions, energy, industrialization, issues and policy, China
- As China becomes the world's largest country for carbon emissions, it becomes one of China's major tasks to seek a path of coordinated development between the environment and the economy. Decoupling analysis is a significant method for analysing the relationship between economic growth and carbon emissions. This paper studies the changes and causes of decoupling index at two levels. At the national level, this paper decomposes the decoupling of carbon emissions from GDP into three parts. Then, the Laspeyers method is adopted to decompose the contribution of each part. At the regional level, this paper decomposes the decoupling index into eight influencing factors, and employs Geographically Temporally Weighted Regression (GTWR) to investigate the spatial and temporal heterogeneity of the influencing factors in each region. The following conclusions are generated: (1) At the national level, decoupling of carbon emissions from GDP consists of weak decoupling and expansive coupling. (2) At the national level, the decoupling effect of carbon emissions from fossil energy is an important negative driver for index changes of carbon emissions decoupled from GDP. The decoupling effect of total energy consumption from GDP is an important positive driver for index changes of carbon emissions decoupled from GDP. However, the decoupling effect of fossil energy from total energy consumption is a minimal positive driver. (3) At the regional level, decoupling of carbon emissions from GDP consists of weak decoupling, expansive coupling, and expansive negative decoupling in most years. (4) At the regional level, each influencing factor shows spatial and temporal heterogeneity based on GTWR. In terms of policy implications, central and western regions should increase the degree of openness to the outside world and strengthen the rectification of high-pollution and high-emission enterprises. Meanwhile, it's important to accelerate the industrialisation process and reduce excessive dependence on fossil fuels such as coal.