Spatiotemporal Evolution and Influencing Factors of Carbon Footprint in Yangtze River Economic Belt

As an important engine of China’s development, the Yangtze River Economic Belt faces the dual contradiction of economic growth and ecological protection. Addressing the insufficient analysis of the spatiotemporal evolution and driving mechanisms of city-level carbon footprints, this study delves into the concept of carbon footprint from the perspective of ecological footprint theory and carbon cycle dynamics. Using ODIAC and NPP data, it systematically evaluates carbon footprints across 130 cities and examines their spatiotemporal evolution and driving factors using kernel density estimation and the Kaya-LMDI model. The results show (1) a significant growth trend in carbon footprint, with rapid expansion from 2000 to 2012, followed by fluctuating growth from 2012 to 2022; (2) a west-to-east “low–high” spatial pattern, where disparities have narrowed but absolute gaps continue to widen, leading to polarization; and (3) economic growth and urban expansion as the primary drivers of carbon footprint growth, while ecological land use pressure and carbon sequestration capacity played a major role in mitigation, with the impact of carbon sequestration foundations remaining limited. This study conducts precise regional carbon sink accounting and offers a new perspective on the quantitative analysis of carbon footprint drivers. The findings provide insights for low-carbon governance and sustainable urban development in the Yangtze River Economic Belt.

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Publication Details

Journal
Land
Published
2025-03-18
DOI
https://doi.org/10.3390/land14030641
Citations
4
Primary Topic
Environmental Impact and Sustainability
Type
article
Field-Weighted Citation Impact
3.20

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article

Spatiotemporal Evolution and Influencing Factors of Carbon Footprint in Yangtze River Economic Belt

Xiaoshun Li, Ke Zhang, X. Y. Zhai, Ziyu Shao et al.
4 citations
Land
Environmental Impact and Sustainability
3.20
article

Spatiotemporal Evolution and Influencing Factors of Carbon Footprint in Yangtze River Economic Belt

Xiaoshun Li, Ke Zhang, X. Y. Zhai, Ziyu Shao, Jie Zhang, Yiwei Geng, Jiangquan Chen
article en
4 citations

Abstract

As an important engine of China’s development, the Yangtze River Economic Belt faces the dual contradiction of economic growth and ecological protection. Addressing the insufficient analysis of the spatiotemporal evolution and driving mechanisms of city-level carbon footprints, this study delves into the concept of carbon footprint from the perspective of ecological footprint theory and carbon cycle dynamics. Using ODIAC and NPP data, it systematically evaluates carbon footprints across 130 cities and examines their spatiotemporal evolution and driving factors using kernel density estimation and the Kaya-LMDI model. The results show (1) a significant growth trend in carbon footprint, with rapid expansion from 2000 to 2012, followed by fluctuating growth from 2012 to 2022; (2) a west-to-east “low–high” spatial pattern, where disparities have narrowed but absolute gaps continue to widen, leading to polarization; and (3) economic growth and urban expansion as the primary drivers of carbon footprint growth, while ecological land use pressure and carbon sequestration capacity played a major role in mitigation, with the impact of carbon sequestration foundations remaining limited. This study conducts precise regional carbon sink accounting and offers a new perspective on the quantitative analysis of carbon footprint drivers. The findings provide insights for low-carbon governance and sustainable urban development in the Yangtze River Economic Belt.

LandVol. 14(3)
China University of Mining and Technology (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 10%
Environmental Impact and Sustainability
3.20
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Spatiotemporal Evolution and Influencing Factors of Carbon Footprint in Yangtze River Economic Belt — Xiaoshun Li, Ke Zhang, et al. · Land (2025) | TGRS Research Map | TGRS