Work

Decomposition and decoupling of carbon footprint pressure from economic growth under energy system transition in China’s urban agglomerations: Insights from prefecture-level cities (2000–2023)

Year: 2025
Type: article
Abstract: The accelerating imbalance between surging carbon emissions and vegetation carbon sink exacerbates climate vulnerabilities, threatening the achievement of Sustainable Development Goal 13 (Climate Action). As the world’s largest carbon emitter, China’s urban agglomerations significantly contribute to its total emissions. Assessing carbon footprint pressure (CFP) and the environmental influence brought by economic activities is critical to China’s carbon reduction policies. By integrating land-based emissions (from cropland, water, and barren land) and activity-based emissions with vegetation carbon sequestration, this study systematically evaluates the CFP dynamics of five major Chinese urban agglomerations from 2000 to 2023. Our research reveals three key findings: (1) Through Logarithmic Mean Divisia Index (LMDI) decomposition, rapid economic growth is the primary driver of surging CFP, with urban agglomerations along the Yangtze River Economic Belt experiencing disproportionately higher impacts. (2) The decomposition further demonstrates that energy consumption and carbon emission intensities have mitigated CFP growth during 2000–2020 and 2021–2023, respectively. (3) Tapio decoupling shows a predominant coexistence of strong and weak decoupling states between CFP and GDP. While Beijing-Tianjin-Hebei faced persistent decoupling challenges, the Middle Reaches of Yangtze River Urban Agglomeration exhibited fluctuating patterns with localized declines. These findings provide a theoretical foundation for optimizing low-carbon strategies and advancing sustainable urban planning in China, through dual approaches of emission reduction (via energy efficiency improvements and industrial restructuring) and enhanced carbon sinks (targeted vegetation restoration and ecological conservation).
Authors: Yushan Liu, Zhuang Shao, Jing Zhao
Language: English
Open Access status: gold
Estimated APC paid: $3,170
OpenAlex ID: W4413428535
FWCI:
Cites: 74
Cited by:
Related to: 10