Transition Pathways for Carbon Peaking in Mountainous Megacities: A Multi-Scenario Simulation in Chongqing, China

This research addresses several challenges, including the lack of comprehensive regional structural variables in carbon peak pathways for mountainous cities, limited policy flexibility in scenario design, and a deficiency of case studies focused on western China, by selecting Chongqing as a representative case. Utilizing the STIRPAT model, the study conducts a thorough assessment of critical regional factors such as industrial structure, energy intensity, and energy mix. To enhance the accuracy of parameter estimation, ridge regression is employed with data sourced from the China Emissions Accounting and Data System (CEADS). Seven multi-scenario combinations are developed to forecast carbon emission trajectories from 2023 to 2050. The results reveal that: (1) population size, industrial structure, and energy structure are the principal determinants of Chongqing’s carbon emissions, with population size exerting the most pronounced marginal impact; (2) under the baseline scenario, carbon emissions are projected to increase, reaching a peak of 208.009 million tons of CO₂ in 2037; conversely, the “Low Growth + Efficient Carbon Reduction” scenario, characterized by accelerated improvements in energy intensity and intensified industrial restructuring, could advance the peak to 2035 at 202.040 million tons, representing a reduction of approximately 2.9% relative to the baseline; and (3) the “Low Growth + Smart-Driven + High-Efficiency Decarbonization” pathway emerges as the most effective strategy for achieving carbon emission peaking and promoting clean production in Chongqing and comparable regions.