Scenario-based Kaya identity analysis for city-level carbon dioxide emissions

Area of Science:

• Environmental Science
• Climate Change Research
• Urban Sustainability

Background:

• Global commitment to reduce carbon dioxide (CO2) emissions is increasing.
• Chinese cities are working towards 2030 peak carbon emission targets.
• Uncertainty in future CO2 emissions necessitates robust analytical methods.

Purpose of the Study:

• To analyze future CO2 emission uncertainties in Chinese cities.
• To evaluate Changning City's potential to achieve its 2030 carbon peak target.
• To explore the impact of different development scenarios on CO2 emissions.

Main Methods:

• Development of a scenario-based Kaya identity analysis methodology.
• Projection of CO2 emissions under business-as-usual, rapid economic growth, environmentalist, and slowed economic development scenarios.
• Case study analysis focused on Changning City, Hunan Province, China.

Main Results:

• Under a business-as-usual scenario, Changning's CO2 emissions are projected to increase from 3,839.1 thousand tons (2022) to 4,674.3 thousand tons (2031), missing the target.
• Rapid economic growth could lead to emissions rising to 5,447 thousand tons by 2031.
• Environmentalist and slowed economic development scenarios indicate a potential carbon peak in 2028 (3,922 and 3,980.2 thousand tons, respectively).

Conclusions:

• Changning City faces challenges in meeting its 2030 carbon peak target under current trends.
• Achieving the carbon peak target is feasible under specific scenarios emphasizing environmental protection or moderated economic growth.
• Energy-saving and emission-reduction measures are crucial to prevent emission resurgence during economic development.