Impact of Urban Morphology on Carbon Emission Differentiation at County Scale in China

Chong Liu, Guangzhou Chen (), Haiyang Li, Jiaming Li and Gubu Muga
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Chong Liu: School of Public Policy & Management, Anhui Jianzhu University, Hefei 230022, China
Guangzhou Chen: Cultivated Land Protection Innovation Demonstration Center of Anhui Province, Anhui Jianzhu University, Hefei 230601, China
Haiyang Li: School of Public Policy and Management, Tsinghua University, Beijing 100084, China
Jiaming Li: School of Public Administration, China University of Geosciences, Wuhan 430074, China
Gubu Muga: College of Economics and Management, Mianyang Teachers’College, Mianyang 621000, China

Land, 2025, vol. 14, issue 6, 1-21

Abstract: Urban morphology’s effects on carbon dioxide reduction and sustainable development have drawn more attention. The county scale is crucial in influencing urban development and is the central element of China’s recent urbanization. To achieve scientific urban planning and fully explore its potential in carbon emission reduction, local governments need to investigate the impact of urban morphology on carbon emissions (CE). However, previous studies have predominantly focused on provincial capitals and urban clusters. To address this gap, this study quantified four aspects of urban form, combined energy consumption, and nighttime light data to estimate CE in Chinese counties from 2000 to 2020 and analyzed the effects of these factors on CE using multiscale geographically weighted Regression(MGWR) models and geographic detectors. The following are the main findings: (1) Total CE at the county scale in China has consistently increased from 2000 to 2020. (2) The largest patch index (LPI) is the most influential urban morphological factor on CE, while the impact of Class Area (CA) has been increasing. (3) Bi-factor enhancement and nonlinear enhancement are the two primary interaction types of urban morphological factors; the most important interaction is between LSI and CA. (4) The urban morphological factors exhibit varying degrees of spatial heterogeneity, with the influencing factors ranked as CA > LPI > path density (PD) > edge density (ED) > patch cohesion index (COHESION), where LPI and CA consistently show a positive effect on CE. This study’s findings establish a scientific foundation for land spatial planning and tailored emission reduction methods at the county scale in China.

Keywords: urban morphology; carbon emissions; MGWR; county scale; China (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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