Carbon Emissions and Innovation Cities: A SHAP-Model-Based Study on Decoupling Trends and Policy Implications in Coastal China

Xiaoyu Fang, Lin Ding and Meng Gao ()
Additional contact information
Xiaoyu Fang: School of Mathematics and Information Sciences, Yantai University, Yantai 264005, China
Lin Ding: School of Mathematics and Information Sciences, Yantai University, Yantai 264005, China
Meng Gao: School of Mathematics and Information Sciences, Yantai University, Yantai 264005, China

Sustainability, 2025, vol. 17, issue 8, 1-21

Abstract: This study investigates the spatiotemporal distribution of carbon emissions and the decoupling relationship between emissions and innovation-driven urban development in six coastal provinces and municipalities in China from 2008 to 2022. The main questions of this paper are as follows: What are the spatial and temporal distribution characteristics of carbon emissions in the study area? What is the decoupling relationship between carbon emissions and innovation-driven urban development? What key variables contribute significantly to carbon emissions and urban development? Carbon emissions increased overall, with higher levels in northern regions such as Shandong, northern Jiangsu, and the Yangtze River Delta. Meanwhile, innovation levels rose but disparities widened, with northern cities leading and those in western Fujian and Guangdong lagging behind. The green economy and industrial transformation were key drivers of rapid development in some cities. To identify the driving factors, the SHAP (SHapley Additive exPlanations) model was employed to quantify the contributions of key variables, including energy structure, technological innovation, and industrial upgrading, to both carbon emissions and urban development. This study found that decoupling between carbon emissions and smart city development improved, transitioning from negative to strong decoupling, particularly in coastal cities. These insights can assist governments in formulating sustainable development strategies. High-emission cities should focus on integrating low-emission measures to mitigate their carbon footprint. High-carbon cities need to transition to low-carbon pathways, enhancing resource efficiency and reducing emissions. Low-emission cities should prioritize improving carbon sinks. Cities with weak economies but rich ecological resources should develop tertiary and ecological economies. Developed cities should optimize resource allocation, digitize industries, and pursue low-carbon growth. Additionally, adjustments in transportation and industry can further boost innovation and urbanization.

Keywords: Tapio decoupling model; spatiotemporal evolution; carbon emissions; innovation cities; interpretable machine learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/8/3344/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/8/3344/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:8:p:3344-:d:1631028

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().