Influencing factors and spatiotemporal heterogeneity of land-use carbon emissions in China's urban agglomerations.

In the context of global climate change and rapid urbanization, understanding the relationship between land use and carbon emissions is critical for sustainable development. This study investigates carbon emissions from land use and their intensity in China’s five major urban agglomerations, including Beijing-Tianjin-Hebei, Yangtze River Delta, Middle Reaches of Yangtze River, Pearl River Delta, and Chengdu-Chongqing, from 2000 to 2020. By integrating land-use and socio-economic data with geographic information systems, the Logarithmic Mean Divisia Index model, and the Kaya Identity, we analyze the spatiotemporal differentiation and evolution of carbon emissions and intensity, as well as the influencing factors behind these trends. Additionally, the Markov prediction method is employed to project land-use changes and carbon emission trends through 2025. The results indicate that the Pearl River Delta exhibited the fastest the most rapid increase in land-use carbon emissions during the study period, while simultaneously achieving the lowest land-use carbon emission intensity among all regions. Economic development and industrial structure served as the principal drivers of emission growth, whereas energy consumption intensity exerted a mitigating effect in all urban agglomerations. Despite the growing proportion of clean energy, the influence of energy structure on emission reduction remained limited, indicating a persistent dependence on fossil fuels. This study underscores the complex relationship between land use and carbon emissions in urban agglomerations, offering important insights for policy formulation. The findings emphasize the necessity of developing targeted strategies to reconcile economic growth with carbon reduction, thereby advancing sustainable land-use planning and supporting climate change mitigation and regional sustainability.