A Study on the Drivers of Carbon Emissions in China’s Power Industry Based on an Improved PDA Method

Abstract

The power industry is a major source of carbon emissions in China. In order to better explore the driving factors of carbon emissions in China’s power industry and assist the Chinese government in formulating emission reduction strategies for the power industry, this study applies the improved production-theoretical decomposition analysis (PDA) method to analyze the carbon emission drivers of China’s power industry. This study investigates the impact of energy intensity, per capita GDP, population density, power generation structure, and environmental climate on carbon emissions in China’s power industry in 30 provinces from 2005 to 2020. It was found that the carbon emission ratios of the power sector in all provinces and cities are basically greater than 1, which indicates that carbon emissions in most of the power sectors in the country are still increasing as of 2020. Overall, the effects of potential thermal fuel carbon emission efficiency, potential thermal energy consumption efficiency, the carbon emission efficiency of thermal power generation, economic scale, population density, and annual rainfall change are mostly greater than 1 and will promote the growth of carbon emissions in the power sector. Moreover, the effects of thermal power generation energy efficiency technology, thermal power generation emission reduction technology, power generation structure, and power generation per unit GDP are mostly less than 1 and will inhibit the growth of carbon emissions in the power sector. However, each of these drivers does not have the same degree of influence and impact effect for each province and city. Based on the research results, some policy recommendations are proposed.

Keywords

• carbon emission
• distance function
• DEA method
• LMDI
• production-theoretical decomposition