CO₂ emissions in China's power industry by using the LMDI method

Area of Science:

• Environmental Science
• Energy Economics
• Climate Change Policy

Background:

• China's power sector faces pressure to meet carbon peak and neutrality targets, contributing over 40% of national CO2 emissions.
• The industry is transitioning from thermal energy to non-fossil sources, but the actual CO2 reduction impact remains unclear.
• Lifecycle CO2 emissions, including those from non-fossil power generation, require comprehensive analysis.

Purpose of the Study:

• To analyze the lifecycle carbon dioxide (CO2) emissions of China's power industry from 2009 to 2018.
• To identify key factors influencing CO2 emission trends within the power sector.
• To compare the CO2 emission impacts of different energy investment strategies.

Main Methods:

• Logarithmic Mean Divisia Index (LMDI) method to decompose factors affecting CO2 emissions.
• Modified Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model for validation.
• Lifecycle assessment of CO2 emissions across various power generation types.

Main Results:

• China's power industry CO2 emissions increased from 276.5 million tons of CO2 equivalent (Mtce) in 2009 to 436.44 Mtce in 2018.
• Investment intensity, structure, and emission intensity reduced CO2 emissions (-28.88%, -11.89%, -3.16%).
• Investment efficiency, economic development, and population size increased CO2 emissions (29.76%, 24.68%, 1.07%).

Conclusions:

• Hydropower investment yields the lowest CO2 emissions, followed by wind, nuclear, and photovoltaic, with thermal power being the highest.
• Improved investment decision-making is crucial for effective CO2 reduction in the power sector.
• Prioritizing hydropower and other non-fossil energy investments is essential for achieving China's climate goals.