4.7 Article

Coordinated development and driving factor heterogeneity of different types of urban agglomeration carbon emissions in China

Journal

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
Volume 30, Issue 12, Pages 35034-35053

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-022-24679-x

Keywords

Carbon emissions; Urban agglomerations; Coupling coordination; GTWR

Ask authors/readers for more resources

This study uses a decoupling model and coupling coordination model to measure the relationship between the development levels of different types of urban agglomerations (UAs) and carbon emissions (CEs) in China. The findings show that most UAs have the potential to decouple CEs from economic growth and are in a state of coordinated development. There are spatial and temporal differences in the impacts of various driving factors on UAs' CEs, with land urbanization and investment in fixed assets promoting CEs, while population urbanization and industrial structure restrain CEs. This research provides important insights for UAs to achieve differentiated low-carbon development.
Carbon emission (CE) reduction has become the primary task of China's urban agglomerations (UAs) in achieving sustainable development goals. This paper uses a decoupling model and coupling coordination model to measure the relationship between the development levels of different types of UAs and CEs in China from 2004 to 2016. Concurrently, the geographically and temporally weighted regression model is used to explore the spatial heterogeneity of the impact of different driving factors on the CEs of UAs. The results show the following: Most UAs have the potential to further decouple CEs and economic growth. Most UAs are still in coordinated development (> 0.5). Among the service innovation UAs, the Yangtze River Delta UA has a coupling coordination of less than 0.3, while the Pearl River Delta UA has a coupling coordination of more than 0.8, showing polarization. Manufacturing and resource-based UAs are still in the grinding adaptation stage (0.5-0.8). There are apparent spatiotemporal differences in the impacts of various driving factors on the CE of UAs. The level of land urbanization and investment in fixed assets promote CEs. However, the level of population urbanization and industrial structure restrain CEs. Therefore, reducing land development and industrial transformation can be an effective means to reduce CEs in UAs. These findings will provide extensive insights for different UAs to achieve differentiated low-carbon development.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available