Carbon emissions from public transportation in major Chinese cities: spatiotemporal analysis, decoupling trends, and key drivers

This study utilized public transport data from 28 major Chinese cities from 2018 to 2022 and employed methods such as carbon emission measurement, standard deviation ellipse analysis, the Tapio decoupling model, and the LMDI decomposition method to ana-lyse the temporal and spatial evolution, decoupling states, and driving factors of public transport carbon emissions comprehensively. The results show that (1) total carbon emissions fluctuated markedly, and emissions dropped sharply in 2020 due to the COVID-19 pandemic, rebounded in 2021, and declined again in 2022 due to technological upgrades and policies. (2) The spatial distribution of carbon emissions follows a northeastern–southwestern pattern. The center of gravity shifted slowly southwards and slightly west-wards and was influenced by economic development and transportation policies. (3) The 28 cities were classified into four groups: Type I had high emissions but low intensity; Type II exhibited a positive decoupling trend; and Types III and IV showed weak decoupling. (4) Economic activities and line density were the main drivers of emission growth, whereas carbon emission intensity and transportation intensity increasingly inhibited emissions in recent years. On the basis of these findings, we propose differentiated low-carbon transportation policies, regional collaborative governance, and technology optimization to support urban transportation low-carbon transformation under the “dual-carbon” goal.