Abstract
This study evaluates China's Carbon Neutrality Capacity (CNC) from 2011 to 2022, focusing on carbon reduction capacity and carbon removal capacity, within the framework of the Sustainable Development Goals (SDGs). Using an improved entropy-weighted TOPSIS method, CNC is assessed in alignment with key SDGs, including SDG 7, SDG 12, SDG 13, SDG 9, and SDG 15. The study analyzes regional disparities and spatiotemporal evolution of CNC using methods such as the Dagum Gini coefficient, Markov chain analysis, kernel density estimation, and spatial econometric models. The results show steady improvement in China's CNC, with faster growth in carbon removal capacity, driven by ecological restoration and carbon capture technologies. However, significant regional disparities remain, with the Northern, Eastern, and Southern Coastal Regions leading, while the Northwest and the Middle Reaches of the Yellow River lag behind. Spatial analysis reveals a concentration of high-CNC regions and limited improvement in low-CNC regions. Markov chain analysis uncovers a "lock-in effect" in low-CNC areas and a "club effect" in high-CNC areas. Spatial spillover effects show negative impacts within 100-600 km and positive impacts beyond 700 km, driven by resource competition and technology diffusion. Based on these findings, the study proposes policy recommendations, such as promoting regional equity, accelerating low-carbon innovation, and enhancing cross-regional cooperation, all aligned with the SDGs, offering practical guidance for achieving carbon neutrality in China and other developing countries.