Carbon emission governance and public health efficiency in transitional China: Regional differences and spatial aggregation

Background: With the coordinated advancement of China’s “dual carbon” goals and the Healthy China strategy, the harmonious development of carbon emission governance and public health service efficiency has emerged as a central issue in China’s sustainable transition. Methods: This study takes 31 provincial-level administrative units in China over the period 2012–2023 as the unit of analysis, and constructs a systematic analytical framework encompassing “measurement–coupling–inequality decomposition–determinant identification.” Specifically, the entropy weight method is employed to assess the composite level of carbon emission governance; the DEA-SBM model is applied to evaluate public health service efficiency; the coupling coordination degree model is used to quantify the coordinated development level of the two systems; the Dagum Gini coefficient decomposition is then utilized to identify the sources of regional disparities; the Global Moran’s Index is adopted to track the evolution of spatial agglomeration; and a two-way fixed effects Tobit model is constructed to identify associated factors. Results: The national coupling coordination degree (CCD) exhibited an overall trajectory of initial fluctuation followed by a sustained upward trend. During 2012–2017, the CCD of most provinces remained within the range of 0.44–0.63, rising broadly to the 0.54–0.72 interval after 2018. Inter-regional inequality consistently constituted the dominant source of total disparity throughout the study period. After 2018, the coordination gap between eastern and western regions continued to widen, while intra-regional disparities among western provinces simultaneously intensified, with both trends jointly driving an increasingly pronounced pattern of regional divergence. The Global Moran’s Index rose from 0.227 to 0.497, indicating a continuous strengthening of spatial agglomeration. The associated factors exhibited significant regional heterogeneity: R&D investment intensity demonstrated a significant positive association with CCD in central and western regions; urban population density exerted a significant inhibitory effect on coordination degree in western provinces; and the direction of the association between economic development level and CCD was opposite in eastern and central regions. Conclusions: Institutional time lags, factor endowment disparities, and spatial polarization mechanisms constitute the core structural barriers constraining the coordinated development of the two systems. There is an urgent need to establish a differentiated, region-specific, and phase-based policy intervention framework to promote balanced and coordinated regional development.