Driving forces and clustering analysis of provincial-level CO2 emissions from the power sector in China from 2005 to 2015

Understanding the drivers of provincial-level CO2 emissions from the power sector is critical for realizing power sector decarbonization and achieving national carbon reduction targets. In this study, the CO2 emissions from electricity generation in 30 provinces of China during the period of 2005-2015 are systematically inventoried. The Logarithmic Mean Divisia Index (LMDI) model is used to analyze the driving forces of changes in CO2 emissions of the power sector. In addition, to analyze the impact of the Chinese 11th and 12th Five-Year Plan on carbon emissions, this study divides the studied period into two sub-periods, 2005-2010 and 2010-2015. Finally, based on their CO2 emission characteristics, we divide 30 provinces into 5 clusters using the K-means clustering to further investigate the carbon reduction measures. The results show that for national CO2 emissions of the power sector, the economic activity effect played a key role in raising CO2 emissions in 2005-2015, while the industrial electricity intensity effect and the energy efficiency effect contributed the most to CO2 reduction during the periods of 2005-2010 and 2010-2015, respectively. During the period of 2010-2015, Inner Mongolia, Jiangsu, Shandong, and Xinjiang contributed the most to reducing CO2 emissions. In addition, for most provinces, the industrial electricity intensity effect was the main driver for reducing CO2 emissions of the power sector. Meanwhile, the electricity structure effect played an increasingly decisive role in declining emissions in provinces where renewable energy is blooming, such as in Yunnan and Sichuan; while for the industrial structure optimized provinces like Hebei and Jiangsu, the industry structure effect played a primary role. By investigating the driving forces of changes in CO2 emissions from the power sector, this study aims to provide insights for provincial decarbonization pathways of the power sector. (C) 2019 Elsevier Ltd. All rights reserved.