Analyzing Integrated Carbon Emissions from Regional Transport and Land Use in the Context of National Spatial Planning

Weiwei Liu (), Xiuhong Zhang, Yangyang Zhu, Xiaomei Li, Liang Jin and Sijie Hu
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Weiwei Liu: Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China
Xiuhong Zhang: Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China
Yangyang Zhu: Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China
Xiaomei Li: Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China
Liang Jin: Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China
Sijie Hu: Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China

Sustainability, 2025, vol. 17, issue 17, 1-21

Abstract: Against the backdrop of intensified governance of territorial spatial planning, investigating carbon emissions from the perspective of territorial spatial planning for transport-land use integration holds significant academic and practical value. Taking Cangnan County as the case study, this research first dissects the reciprocal feedback mechanism between regional transport and land use at the territorial spatial planning level, while exploring transport-influencing factors. Subsequently, it constructs an integrated reciprocal feedback system for regional transport and land use by integrating accessibility drivers, cost matrices, and neighborhood weights through land use simulation–prediction models and the four-stage transport model. Finally, based on critical land use factors, diverse development scenarios under this integrated system are formulated; carbon emissions from transport and land use under each scenario are quantified; and their interrelationships are analyzed across multiple dimensions to explore the nexus of carbon emissions in transport–land use integration. Results indicate the following: (1) Integrated feedback enhances model accuracy (Kappa: 0.795→0.893; overall accuracy: 0.893→0.915), facilitating more precise land use simulation. (2) The county’s core construction area demonstrates the highest carbon emissions across all scenarios, meriting prioritized attention. (3) As deduced from the analysis of territorial spatial land use patterns, the significantly higher transport carbon emissions under the ecological protection priority scenario, compared to other scenarios, originate from over-concentrated construction land and imbalanced planning of carbon source land. These findings offer insights for regional planning; policy recommendations for Cangnan County include expanding carbon sink land, scientifically planning carbon source land, optimizing transport structures, and promoting new energy vehicles to advance carbon emission reduction and sustainable development.

Keywords: national spatial planning; transport and land use integration; artificial neural networks; cellular automata simulation; carbon emission (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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