Applying the improved EBM and spatial statistical models to examining carbon emission performance: Evidence from Yellow River Basin urban agglomerations.

This article focuses on measuring and analyzing carbon emission performance (CEP) in the Yellow River Basin urban agglomerations in China using an improved epsilon-based measure (EBM) model that accounts for undesirable outputs. The study finds that overall CEP in the basin is relatively high but unevenly distributed, with eastern urban agglomerations exhibiting higher CEP than central and western ones, and significant spatial clustering patterns identified through spatial autocorrelation analysis. Key factors positively influencing CEP include economic development level (PGGDP), technological progress (TP), industrialization level (IND), and human capital (HC), while population density (PD) and energy structure (ES) have inhibitory effects; industrial agglomeration (IA) shows a nonlinear "U"-shaped relationship with CEP. Additionally, foreign direct investment (FDI), IND, and HC demonstrate significant spatial spillover effects on neighboring cities' CEP, highlighting the importance of regional cooperation and tailored policy measures for low-carbon development in the basin.