Carbon peak prediction for differentiated cities from a low-carbon perspective: Key factors, scenario analysis, and low-carbon pathways

• 21 cities (prefectures) in Sichuan Province were divided into 4 categories. • Considering the factors of government intervention, four scenarios are set. • The bottom-up carbon emission scenario analysis framework was established. • Explore low-carbon development path from the perspective of urban differentiation. Cities constitute a critical component of the “dual carbon” strategy, highlighting the importance of examining the carbon emission trends within various city categories to formulate a low-carbon development path. In this paper, 21 cities (prefectures) in Sichuan province were divided into 4 categories (service-based cities, resource-based cities, industry-based cities, and other cities) through K-means clustering, and the differences in driving factors of carbon emissions in different types of cities were explored. At the same time, baseline scenarios, technological innovation scenarios, controlled development scenarios, and mandatory emission reduction scenarios were set up to dynamically simulate the evolution path of urban carbon emissions in the next 30 years from the bottom-up. The results show that: (1) Input scale is the main driving factor for carbon emission growth in Sichuan province, while input carbon intensity is the leading factor for carbon emission reduction. Environmental input and population scale have opposite effects on carbon emission of different urban types. (2) Resource-based cities face challenges in completing the phased goal of “carbon peaking” under both baseline scenarios and controlled development scenarios. These cities have gradually become the predominant city type of emission source in Sichuan province, surpassing service-based cities. (3) Except for the normal scenario, Sichuan province can achieve the target of “carbon peaking” in other scenarios, and is expected to achieve the target of 90 % greenhouse gas reduction by 2050. (4) Among the 81 development paths derived from the urban scenario combinations, the path labeled M−B−C−M exhibits the lowest economic-ecological comprehensive impact coefficient. The bottom-up carbon emission scenario analysis framework established in this paper offers a novel perspective for the study of “carbon peaking” and can provide theoretical support for policymakers in devising regional low-carbon development strategies.