Polycentric Spatial Structure and Reduction in Carbon Emission Intensity: Pathways and Heterogeneity Across China’s 21 Major Urban Agglomerations
Changyi Liang, Jing Li, Peng Gao, Yuedong GengThis paper mainly investigates the causal relationship between the spatial structure of urban agglomerations and carbon emission intensity, and clarifies the underlying mechanisms. We employ the rank-size rule to characterize the polycentric indices of 21 Chinese urban agglomerations from 2006 to 2022, representing their spatial structures, with carbon emission intensity measured as the ratio of total carbon emissions to GDP. Using a two-way fixed-effects model and employing topographic relief as an instrumental variable, our paper examines the impact of urban agglomeration spatial structures on carbon emission intensity and further investigates the underlying transmission mechanisms and heterogeneity effects. The findings reveal that polycentric spatial development in urban agglomerations leads to statistically significant reductions in carbon emission intensity. The robustness and endogeneity tests support the benchmark regression results. Mechanism tests reveal that polycentric spatial structures of urban agglomeration reduce carbon emission intensity by promoting technological progress, guiding industrial relocation, and alleviating traffic congestion. However, they also increase carbon emission intensity by reducing public transportation and promoting urban sprawl, indicating negative environmental externalities. Overall, the positive environmental externalities of polycentric structures outweigh the negative ones. Considering the considerable differences in internal integration across urban agglomerations in China, we perform a heterogeneity analysis. Heterogeneity analysis shows that internal integration moderates the effect of polycentric spatial structure on carbon emission intensity, with greater integration weakening the emission-reduction effect.