A LMDI decomposition analysis of carbon dioxide emissions from the electric power sector in Northwest China

Taking advantage of the electrification strategy, Northwest China has made full use of its natural resources endowment, to develop renewable energy as the substitution of thermal power. To evaluate carbon dioxide (CO2) emissions from electric power sector, an extended Kaya identity equation and the Logarithmic mean Divisia index decomposition method are applied to Northwest China from 1998 to 2017. Six explaining factors are analyzed, including carbon intensity, energy mixes, generating efficiency, electrification, economy and population. The results show that driving forces of CO2 emissions from electricity system varied greatly among provinces. Generally, economic growth has mainly contributed to increase CO2 emission, while the improvement in the power‐generating efficiency has crucially decreased CO2 emission. In 2017, Promoting electrification directly increased CO2 emissions from electric system, but indirectly reduced CO2 emissions from the whole region by 5.10% through the estimation of a clean development mechanism method. Therefore, local governments are suggested continuing to promote electrification to guide future emission reduction, while enterprises and individuals need to make their own contributions to low‐carbon development. Recommendations for Resource Managers: Variations of carbon dioxide (CO2) emissions of all five provinces in Northwest China are analyzed. Logarithmic mean Divisia index analysis is used to study the main drivers of CO2 emission change. Improvements in the generating efficiency significantly reduced CO2 emissions. Due to electrification effects, CO2 emissions from electric power increased, but CO2 emissions from the region decreased. Economy effects were still the biggest drivers affecting CO2 emission.