Abstract
The International Energy Agency (IEA) pointed out that thermal electricity generation was the largest contributor to the CO2 emissions in 2018, particularly in China. Inequality and spatial decomposition analyses have been extensively applied to monitor CO2 emissions and climate change. However, there have been no studies focusing on the inequality of CO2 emissions or aggregate carbon intensity (ACI) in the electricity sector. Furthermore, inequality analysis and spatial analysis have not been combined to analyze the ACI in the electricity sector. This study adopts the Theil index to analyze the intraregional and interregional inequality of provincial ACI in China’s thermal electricity sector. In addition, the nested spatial decomposition approach is proposed to isolate the factors behind variation in the ACI at the regional and provincial levels. The ACI of most provincial thermal electricity generation grids declined substantially during 2000-2016. By 2016, half of the provinces had achieved the 2020 ACI reduction target of 865 gCO2/kWh ahead of schedule. Decomposition based on the Theil index demonstrated that intraregional inequality was the major factor causing the overall inequality of ACI, especially within the North and South regions. The spatial decomposition indicates that energy intensity is the most significant factor behind the decrease in ACI followed by energy structure. The emission coefficient exerted limited impact across all the six regions. Besides, Northwest rose in the rankings of based on the energy intensity, energy structure, and ACI during 2000-2016, whereas North and Northeast saw the opposite pattern. Policy implications based on empirical research are provided to further govern the ACI and curb CO2 emissions.
Wang, Y.; Yan, Q; Li, Z; s Baležentis, T; Zhang, Y; Gang, L; Streimikiene, D. 2020. Aggregate carbon intensity of China’s thermal electricity generation: The inequality analysis and nested spatial decomposition. Journal of Cleaner Production. Vol. 247, 119139, ISSN 0959-6526, https://doi.org/10.1016/j.jclepro.2019.119139; [Geographical Abstracts; Engineering Village - GEOBASE; Fluid Abstracts; FLUIDEX; Scopus; INSPEC; Science Citation Index Expanded].