[Spatio-temporal Evolution and Driving Forces of Transportation Carbon Emissions in Jiangxi, Fujian, and Guangdong Regions].

The Jiangxi, Fujian, and Guangdong regions are located close to the southeast coastal area and serve as the hinterland for the Pearl River Delta; Yangtze River Delta; and Guangdong, Fujian, and Zhejiang regions. With the rapid economic development and urbanization in Jiangxi, Fujian, and Guangdong, transportation-related high carbon emissions have become increasingly prominent. The 14th Five-Year Plan proposes to deepen the implementation of the regional coordinated development strategy and improve the mechanism for regional coordination. Academic research and policy attention have long focused on economically developed regions, such as the Yangtze River Delta, Pearl River Delta, and Beijing-Tianjin-Hebei Region. The economic development models and mechanisms in these regions have been extensively studied and validated. However, the Jiangxi, Fujian, and Guangdong regions exhibit characteristics of uneven economic development, with both economically developed areas, such as Guangdong Province and relatively underdeveloped inland regions like Jiangxi Province. Research on the Jiangxi, Fujian, and Guangdong regions could contribute to a comprehensive understanding of the diversity and imbalance in regional economic development, providing references for other underdeveloped areas. Therefore, facing challenges of spatial-temporal differences in transportation carbon emissions in Jiangxi, Fujian, and Guangdong regions with unclear driving forces, this study introduces standard deviation ellipse analysis to explore the spatial distribution characteristics of transportation carbon emissions (2009-2021). Additionally, logarithmic mean divisia index (LMDI) and multi-regional spatial decomposition (M-R) models are constructed to explore temporal-spatial drivers contributing towards spatial differentiation of carbon emissions. The findings are revealed below: ① The total traffic-related carbon emissions within the Jiangxi, Fujian, and Guangdong regions have been increasing annually and continue to shift toward the "northeast-southwest" direction, with the epicenter of carbon emission lying at the border between the Guangdong and Fujian provinces. ② The level of economic development and population size were the main driving factors for transportation carbon emissions, whereas energy intensity was a key restraining factor. ③ Notable spatial disparities existed between carbon emissions and average levels across the three provinces. The research findings can offer crucial insights for formulating tailored emission reduction policies and collaborative governance measures in the regions of Jiangxi, Fujian, and Guangdong.

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Publication Details

Journal
PubMed
Published
2025-05-08
DOI
https://doi.org/10.13227/j.hjkx.202404215
Primary Topic
Vehicle emissions and performance
Type
article
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[Spatio-temporal Evolution and Driving Forces of Transportation Carbon Emissions in Jiangxi, Fujian, and Guangdong Regions].

Xisheng Hu, Lanyi Zhang, Shuo Wang, Zhanwu Lu et al.
PubMed
Vehicle emissions and performance
article

[Spatio-temporal Evolution and Driving Forces of Transportation Carbon Emissions in Jiangxi, Fujian, and Guangdong Regions].

Xisheng Hu, Lanyi Zhang, Shuo Wang, Zhanwu Lu, Dawei Weng, Yi-Nuo Xu, C. L. Luo
article en

Abstract

The Jiangxi, Fujian, and Guangdong regions are located close to the southeast coastal area and serve as the hinterland for the Pearl River Delta; Yangtze River Delta; and Guangdong, Fujian, and Zhejiang regions. With the rapid economic development and urbanization in Jiangxi, Fujian, and Guangdong, transportation-related high carbon emissions have become increasingly prominent. The 14th Five-Year Plan proposes to deepen the implementation of the regional coordinated development strategy and improve the mechanism for regional coordination. Academic research and policy attention have long focused on economically developed regions, such as the Yangtze River Delta, Pearl River Delta, and Beijing-Tianjin-Hebei Region. The economic development models and mechanisms in these regions have been extensively studied and validated. However, the Jiangxi, Fujian, and Guangdong regions exhibit characteristics of uneven economic development, with both economically developed areas, such as Guangdong Province and relatively underdeveloped inland regions like Jiangxi Province. Research on the Jiangxi, Fujian, and Guangdong regions could contribute to a comprehensive understanding of the diversity and imbalance in regional economic development, providing references for other underdeveloped areas. Therefore, facing challenges of spatial-temporal differences in transportation carbon emissions in Jiangxi, Fujian, and Guangdong regions with unclear driving forces, this study introduces standard deviation ellipse analysis to explore the spatial distribution characteristics of transportation carbon emissions (2009-2021). Additionally, logarithmic mean divisia index (LMDI) and multi-regional spatial decomposition (M-R) models are constructed to explore temporal-spatial drivers contributing towards spatial differentiation of carbon emissions. The findings are revealed below: ① The total traffic-related carbon emissions within the Jiangxi, Fujian, and Guangdong regions have been increasing annually and continue to shift toward the "northeast-southwest" direction, with the epicenter of carbon emission lying at the border between the Guangdong and Fujian provinces. ② The level of economic development and population size were the main driving factors for transportation carbon emissions, whereas energy intensity was a key restraining factor. ③ Notable spatial disparities existed between carbon emissions and average levels across the three provinces. The research findings can offer crucial insights for formulating tailored emission reduction policies and collaborative governance measures in the regions of Jiangxi, Fujian, and Guangdong.

PubMedVol. 46(5)
Fujian Agriculture and Forestry University (CN)
Vehicle emissions and performance
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