Dynamic Analysis of China’s Urban Economic Spatial Network and Its Multidimensional Impact on Building Carbon Emissions

Juan Li and Mei Sun ()
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Juan Li: Institute of Carbon Neutrality Development, Jiangsu University, Zhenjiang 212013, China
Mei Sun: Institute of Carbon Neutrality Development, Jiangsu University, Zhenjiang 212013, China

Mathematics, 2025, vol. 13, issue 21, 1-21

Abstract: With the continuous development of cities, the network connections between Chinese cities have rapidly strengthened, and cities are gradually transforming from traditional production bases into economic platforms within dynamic spaces. In this process, urban building carbon emissions are not only determined by the city’s own resource and industrial advantages but are increasingly influenced by its position within the urban economic space network. This study constructs an urban economic spatial network using the gravity model, and based on dynamic data of building carbon emissions in Chinese cities from 2008 to 2020, develops a new analytical framework from the perspective of dynamic network evolution to examine the impact mechanisms of urban network position and residential activity intensity on building carbon emissions. The findings indicate that both residents’ activity intensity and city’s network position have a significant positive impact on per capita building carbon emissions, The impact coefficient between residential activity intensity and per capita building carbon emissions is 0.278 ( p < 0.01). This conclusion remains valid after robustness and endogeneity tests. The city’s network position can mitigate the detrimental impact that residents’ activity intensity has on per capita building carbon emissions, particularly in the dynamic decision-making process, where cities can adjust their strategies based on their network position. The influence of city’s network position on per capita building carbon emissions exhibits multidimensional heterogeneity, with its effect being more significant in megalopolis and metropolis compared to large city and medium & small city. Specifically, in megalopolis, the network position impact coefficient is 0.22, significantly higher than 0.039 in medium & small city. These findings provide new perspectives for reducing building carbon emissions at the urban-level in the context of dynamic spatial mobility.

Keywords: urban economic spatial correlation network; city’s network position; building carbon emissions; residents’ activity intensity (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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