Decarbonizing cities through energy transition: A composite framework for assessing spatial disparity and convergence pathway of energy-related carbon emissions from industrial sector in Chinese western urban agglomerations

Abstract

Assessing spatial disparity of industrial energy-related carbon emissions (ERCE) in urban agglomeration (UA) is crucial for urban decarbonization. The spatial variations and convergence pathways of industrial ERCE in China’s western UAs are revealed by K-means cluster algorithm, double-weighted Theil index and convergence models. Firstly, ERCE exhibited an upward trend and spatial imbalance characteristics. Cluster Ⅰ, characterized by low emissions and high energy efficiency, had the highest number of cities at 18 with the proportion of 36.73%. The high-emission clusters Ⅲ and V included 9 cities with the proportion of 18.37%. Secondly, regional differences in ERCE gradually widened. The differences between UAs were greater than those within them, constituting the main source of overall differences. Finally, ERCE gap gradually increased without significant α convergence. It showed significant absolute and conditional β convergence. The former showed a long convergence period and the latter converged faster but relies on optimization of industrial development level, energy intensity and energy structure. The inconsistent city quantities across different UAs and unexplored key factors including green innovation make it difficult to conduct β convergence for individual UAs. The findings provide scientific basis for strengthening inter-city energy cooperation and establish collaborative industrial reduction mechanisms in Chinese western UAs.