Abstract
Urban low-carbon advancement is vital to alleviate global warming and foster environmental sustainability. This study constructed a county-level evaluation model for low-carbon development by using a combined AHP-CRITIC method and conducted GIS spatial analysis to study the temporal and spatial progression and spatial variation of low-carbon development levels in 40 counties of Jiangsu Province from 2015 to 2022. Subsequently, the K-means algorithm was utilized to categorize the 40 counties into distinct spatial clusters. The findings showed consistent growth in the low-carbon development of Jiangsu's counties. However, since 2021, this improvement had shown signs of slowing down. Spatially, Jiangsu Province's county-scale low-carbon progress showed a distinct "north-south gradient," with higher levels in the south. Notably, southern counties such as Kunshan, Taicang, and Changshu formed stable "high-high" clusters. However, this regional disparity gradually weakened, as cold-spot areas in the north shifted toward sub-cold-spot zones and increasingly deviated from the previous "low-low" homogeneity. The center of gravity for low-carbon development consistently shifted northwestward from 2015 to 2022. Ultimately, the 40 counties were classified into five distinct spatial clustering types, each displaying significant differences across various development dimensions. It is crucial to enhance inter-regional resource complementarity and coordinated development to ensure that low-carbon transition strategies align with local conditions and enable the implementation of differentiated transition pathways. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.
| Original language | English |
|---|---|
| Number of pages | 39 |
| Journal | Environment, Development and Sustainability |
| Online published | 13 Sept 2025 |
| DOIs | |
| Publication status | Online published - 13 Sept 2025 |
Funding
This work was supported by the Jiangsu Province Carbon Summit Carbon Neutral Science and Technology Innovation Special Funds [grant numbers BM2022035]; the 2024 Jiangsu Province Construction System Research Project [grant number 2024JH]; and Research on Establishment and Measurement of Carbon Footprint Management System in Nanjing Building Sector.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Research Keywords
- Low-carbon evaluation
- Low-carbon development
- Spatiotemporal pattern
- Spatial clustering
- County level
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