Carbon peaking pathways for topographic-constrained megacities: multi-scenario simulations and regional comparisons based on Chongqing

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🔬研究者:The extended STIRPAT model with ridge regression and multi-scenario design is a methodological contribution for carbon emission projection studies.

🏢実務担当者:Scenario planning insights for local governments and industries in topographically constrained regions to design emission reduction strategies.

🏛政策担当者:Evidence that early action on energy-intensive industries and regional energy coordination can accelerate carbon peaking in similar cities.

This research uses Chongqing, China, as a representative case study to address the challenges inherent in investigating carbon peak pathways within topographically constrained inland Chinese cities. These challenges include the lack of regional structural variables, limited flexibility in scenario design, and a scarcity of case studies focusing on western China. Employing an extended STIRPAT model, the study systematically assesses the influence of critical regional factors—such as industrial structure, energy intensity, and energy mix—on carbon emissions. To improve the accuracy of parameter estimation and mitigate multicollinearity among variables, ridge regression was applied using data from China’s Carbon Emissions Accounting Database (CEADs). Seven multi-scenario combinations were developed to project carbon emission trajectories from 2023 to 2050, followed by a comparative analysis with analogous studies conducted in Yunnan Province. The principal findings are as follows: (1) Population size, industrial structure, and energy mix constitute the primary determinants of carbon emissions in Chongqing; (2) Under the baseline scenario, carbon emissions are projected to peak in 2037, whereas adopting a “low-growth plus high-efficiency decarbonization” pathway could effectively advance the peak to 2035; (3) Relative to Yunnan—a similarly topographically constrained region in Southwest China—Chongqing exhibits more pronounced “valley industry” lock-in effects. Accordingly, mitigation strategies for Chongqing should emphasize accelerating the transformation of energy-intensive industries and enhancing regional energy coordination. This study illustrates how variations in industrial foundations lead to divergent carbon peak trajectories under comparable topographical constraints, thereby offering tailored policy insights for analogous regions.

• semanticscholar https://doi.org/10.1038/s41598-026-44711-1first seen 2026-07-24 07:03:42