Clarifying the intrinsic mechanism of county carbon emission intensity (CEI) is essential for guiding the realization of a low-carbon economy as well as for the strategic goals of carbon peaking and carbon neutrality. However, at present, scholars mostly focus on provincial and city scales, with the identification of influencing factors and spatial effect mechanisms of CEI rarely included in the analysis framework. Herein, with the help of three spatial weight matrices, the spatial autocorrelation, the "F + S" influence factor identification method, and the spatial panel econometric model were used to analyze the evolutionary paths and influencing factors of CEI for 209 counties in the Yangtze River Delta (YRD) from 2007 to 2020. The results show that (1) the CEI of the YRD decreased from 1.998t/104 RMB to 0.858t/104 RMB. Furthermore, the spatial pattern was low in the southeast and high in the northwest, with high-value areas concentrated in municipal districts and resource-based counties. (2) Moran's I spatial autocorrelation index indicated significant spatial clustering of county CEI. (3) Financial science and technology expenditure, industrial structure, share of urban built-up land, and the urban-rural income gap affected the change in CEI and its spatial effect, whereas total imports and exports had a significant negative effect on local CEI. Therefore, to achieve China's "double carbon" goal, it is necessary to consider the five development concepts as the core, strengthen inter-county exchanges and collaboration, as well as promote collaborative management of the ecological environment.
Keywords: Carbon emission intensity; Spatial autocorrelation; Spatial panel econometric model; Yangtze River Delta counties.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.