Unraveling the decoupling mechanisms and nonlinear drivers of carbon emissions in Chinese cities

Decoupling carbon emissions from economic development is crucial for sustainable development and achieving carbon peaking and neutrality goals. However, previous studies primarily assume linear relationships between influencing factors and carbon emissions, with limited attention to nonlinear effects at the urban scale. This study investigates the spatiotemporal evolution of carbon emissions across 232 Chinese cities from 2000 to 2022. Using the Tapio decoupling model, we analyze the relationship between carbon emissions and economic growth, as well as their spatiotemporal variations. Additionally, an XGBoost-SHAP model is applied to uncover nonlinear drivers of carbon emissions. The results show that, over the past 23 years, total and per capita carbon emissions have increased, while carbon emission intensity has declined. Northern cities, particularly in the Hohhot-Baotou-Ordos-Yulin (HBOY) urban agglomeration and Northeast China, exhibit higher emissions and intensity compared to southern cities. From 2000 to 2022, over 94 % of cities achieved decoupling between economic growth and carbon emissions, though most were classified as weak decoupling. The proportion of cities achieving strong decoupling increased from 20 % to 40 % over three phases. Expansive negative decoupling and expansive coupling cities are concentrated in the HBOY region and Northeast China. Key determinants of carbon emissions include GDP, population size, industrial structure, and energy intensity. GDP and energy intensity have near-linear positive effects, while industrial structure, green patents, and environmental regulations show inverted U-shaped relationships. Conversely, population size, environmental protection expenditures, environmental rights trading exhibits a U-shaped trend This study highlights the nonlinear effects of various factors on emissions and offers insights for emission reduction strategies in diverse regions.