Nonlinear associations and potential pathways of urban polycentricity and transportation carbon emissions in the Yangtze River Delta China

Transportation carbon emissions (TCEs) are central to the low-carbon transition of cities, yet the role of urban polycentricity (UP) remains contested. Using data for 41 Yangtze River Delta (YRD) cities in 2005, 2010, 2015, and 2020, this study identifies urban centers from LandScan gridded population data, measures morphological polycentricity by integrating population agglomeration, the relative size of centers, and inter-center spatial distance, and examines its relationship with TCEs using a spatial Durbin model, mechanism tests, and heterogeneity analysis. The results show pronounced spatial heterogeneity in both UP and TCEs. UP exhibits a significant U-shaped association with TCEs. Below the turning point, higher UP is associated with lower TCEs; beyond the turning point, this negative association gradually weakens and becomes positive. Mechanism analysis shows that UP is systematically associated with changes in road network density, patch density, edge density, and the aggregation index. These urban-form variables may serve as potential pathways linking polycentric development to TCEs, while population size and economic development alter the strength of this association. These associations also vary by city size, policy region, and development stage. The findings indicate that a polycentric urban structure is not inherently low-carbon and that differentiated strategies are required for low-carbon spatial planning.

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Journal
Scientific Reports
Published
2026-09-17
DOI
https://doi.org/10.1038/s41598-026-69293-w
Primary Topic
Land Use and Ecosystem Services
Type
article
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Nonlinear associations and potential pathways of urban polycentricity and transportation carbon emissions in the Yangtze River Delta China

Zhiqiang Gan, Xingwu Xi, Yunbin Zhang, Xiaotian Zhang et al.
Scientific Reports
Land Use and Ecosystem Services
article

Nonlinear associations and potential pathways of urban polycentricity and transportation carbon emissions in the Yangtze River Delta China

Zhiqiang Gan, Xingwu Xi, Yunbin Zhang, Xiaotian Zhang, Dan Li, Jingyuan Chen
article en

Abstract

Transportation carbon emissions (TCEs) are central to the low-carbon transition of cities, yet the role of urban polycentricity (UP) remains contested. Using data for 41 Yangtze River Delta (YRD) cities in 2005, 2010, 2015, and 2020, this study identifies urban centers from LandScan gridded population data, measures morphological polycentricity by integrating population agglomeration, the relative size of centers, and inter-center spatial distance, and examines its relationship with TCEs using a spatial Durbin model, mechanism tests, and heterogeneity analysis. The results show pronounced spatial heterogeneity in both UP and TCEs. UP exhibits a significant U-shaped association with TCEs. Below the turning point, higher UP is associated with lower TCEs; beyond the turning point, this negative association gradually weakens and becomes positive. Mechanism analysis shows that UP is systematically associated with changes in road network density, patch density, edge density, and the aggregation index. These urban-form variables may serve as potential pathways linking polycentric development to TCEs, while population size and economic development alter the strength of this association. These associations also vary by city size, policy region, and development stage. The findings indicate that a polycentric urban structure is not inherently low-carbon and that differentiated strategies are required for low-carbon spatial planning.

Scientific Reports
Anhui Agricultural University (CN), Hefei Urban Planning & Design Institute (CN), Guangdong Urban & Rural Planning and Design Institute (CN)
Sustainable cities and communities
Openalex Percentile: Top 14%
Land Use and Ecosystem Services
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Nonlinear associations and potential pathways of urban polycentricity and transportation carbon emissions in the Yangtze River Delta China — Zhiqiang Gan, Xingwu Xi, et al. · Scientific Reports (2026) | TGRS Research Map | TGRS