A National-Scale Evaluation of Eco-City Development in China: Spatial Heterogeneity, Obstacle Factors, and Relationship with Carbon Intensity

Yuhui Wu, Deqin Fan (), Yajun Cui, Shouhang Du, Wenbin Sun, Liyuan Guo and Chunhuan Liu
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Yuhui Wu: College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
Deqin Fan: College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
Yajun Cui: Beijing Institute of Surveying and Mapping, Beijing 100091, China
Shouhang Du: College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
Wenbin Sun: College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
Liyuan Guo: College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
Chunhuan Liu: College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China

Land, 2025, vol. 14, issue 11, 1-37

Abstract: Under the national “dual-carbon goal” and the pressing demand for sustainable development, eco-city construction and carbon reduction have become critical issues on China’s urban development agenda, closely aligned with the United Nations Sustainable Development Goals (SDGs). However, most studies focus on regional assessments, lacking national-scale evaluations and spatial heterogeneity analysis of obstacles. This study analyzes 280 Chinese cities using a multi-level evaluation system. Analytic hierarchy process (AHP) and entropy weight methods determine index weights, while the comprehensive evaluation method assesses ecological levels. The obstacle diagnosis model identifies key obstacle factors, and geographically weighted regression (GWR) analyzes spatial heterogeneity, computing carbon intensity to explore relationships with eco-cities development. The findings reveal that (1) the ecological level of Chinese cities exhibits a regional pattern of “high in the east, low in the west”; (2) the primary index-level obstacle factors include total per capita water resources, per capita green space area, college full-time faculty per 10,000 people, the proportion of tertiary industries in gross domestic product (GDP), and college students per 10,000 people; at the element level, the main obstacles are environmental bases, social services, economic potential, and innovative capacity; (3) the GWR model reveals that eastern regions should increase water resources, central regions expand green space, and western and northeastern regions enhance innovative capacity and social services to foster balanced development; and (4) carbon intensity follows a “low in the east, high in the west” pattern, with eco-cities scores significantly negatively correlated with carbon intensity (r = −0.235, p < 0.01). This study provides the first comprehensive national-scale evaluation of eco-cities development, providing reference for the construction of eco-cities.

Keywords: eco-cities; TOPSIS model; obstacle diagnosis model; evaluation index system; geographically weighted regression model (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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