Evolution-based CO2 emission baseline scenarios of Chinese cities in 2025

Abstract City-level CO2 emission scenarios are important for cities’ policies of emission reduction. However, current studies do not reveal the macro patterns of the evolution of cities. This work uses the evolution-based city emission scenario (ECES) model, which tracks the city evolution patterns by probability methods based on multiple cities’ emissions of different periods, to reveal the underlying evolution rules of cities’ CO2 emissions. By the K-means clustering method, five clusters of cities are divided, and the evolution patterns of the city clusters are analyzed. Based on the maximum evolution probability, we discover the city evolution chains that reflect the common pattern of city development. We also propose two indicators for the estimation of emission intensity in 2025 in the natural evolution scenario. Policy implications are then discussed, including optimizing the low-carbon development pathway of cities, cooperate with similar cities.