Increasing urbanization in China has caused severe haze pollution in Chinese cities in recent years. This study investigates the impact of urban spatial development mode on haze pollution from the leapfrog spatial dimension. We constructed a dataset containing LandScan population dynamic statistical data, PM2.5 surface concentration data, and urban economic statistical data and adopted ordinary least squares (OLS) and instrumental variable methods. The findings indicate that the polycentric spatial structure within the city increases the PM2.5 levels, indicating that the urban monocentric spatial development mode is conducive to alleviating haze pollution. The use of the core explanatory variables, lagged by one and two periods, and of the number of Qing Dynasty walls as the instrumental variable confirm the robustness of the benchmark results. The heterogeneity analysis demonstrates that, in cities with underdeveloped public rail transit, the monocentric spatial development mode has a more obvious effect on reducing haze pollution. The results of the influence mechanism test show that the urban polycentric spatial development mode aggravates urban haze pollution, mainly by encouraging residents to travel by private transport, thereby increasing energy consumption. The obtained research results provide a sufficient basis for taking appropriate measures to govern haze pollution in Chinese cities from the perspective of polycentric spatial development mode.

This 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.