[Temporal and Spatial Heterogeneity and Its Influencing Factors of Carbon Surplus and Deficit at County-Level Areas in Shaanxi Province].

Carbon source and sink monitoring is an important prerequisite for realizing the dual-carbon target and the evolution of its spatial-temporal pattern and the spatial-temporal heterogeneity of the driving factors are the scientific basis for the implementation of the emission reduction and sink enhancement policy according to the local conditions, which is of great importance for the sustainable development of the region. Based on the carbon balance of payment relationship, the carbon surplus and deficit of Shaanxi Province counties were calculated in 2000, 2010, and 2020 from land use, and a series of exploratory spatial and temporal analysis methods (ESTDA), including spatial autocorrelation, cold and hot spot analysis, standard deviation ellipse, and LISA-time pathway, were used to study the dynamics of carbon surplus and deficit in Shaanxi Province at different spatial-temporal scales. From the 21 indicators, six types of major driving factors were selected by principal component analysis, and the geographical spatio-temporal weighted regression model (GTWR) was used to identify their spatio-temporal heterogeneity to construct a comprehensive system of indicators to analyze the carbon deficit and its spatio-temporal heterogeneity in Shaanxi Province. The results showed that: ① A carbon surplus of 8.56 million tons in 2000, a carbon deficit of 3 296 tons in 2010, and a deficit of 33.34 million tons occurred in 2020 in Shaanxi Province, and the growth rate of carbon emissions was much larger than that of carbon sinks, which indicates that it was gradually moving towards carbon peaks in Shaanxi Province; however, there is a long way to go to achieve the goal of carbon neutrality. ② The geographical distribution of the "north deficit and south surplus" phenomenon was visually represented. A carbon deficit was concentrated in the wind and sand area along the Great Wall and Guanzhong plain. The spatial-temporal leap characteristics were more stable. In conclusion, efforts aimed at emission reduction and carbon sink enhancement were strategically directed towards the northern Shaanxi Region. ③ Among various indicator systems including urban construction, natural resources, anthropogenic activities, energy consumption, industrial development, and ecological protection indicator systems, only ecological protection positively drove carbon profit and deficit. Notably, natural resources had the strongest spatial and temporal heterogeneity in their impact on carbon deficit, and energy consumption was positively driven in some areas of Shaanxi Province. The results will provide accurate policy directions for the development of carbon neutral strategies in Shaanxi Province.

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Publication Details

Journal
PubMed
Published
2025-03-08
DOI
https://doi.org/10.13227/j.hjkx.202401161
Primary Topic
Air Quality and Health Impacts
Type
article
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[Temporal and Spatial Heterogeneity and Its Influencing Factors of Carbon Surplus and Deficit at County-Level Areas in Shaanxi Province].

Ling Han, Xin Huang, Yu Lin Ding
PubMed
Air Quality and Health Impacts
article

[Temporal and Spatial Heterogeneity and Its Influencing Factors of Carbon Surplus and Deficit at County-Level Areas in Shaanxi Province].

Ling Han, Xin Huang, Yu Lin Ding
article en

Abstract

Carbon source and sink monitoring is an important prerequisite for realizing the dual-carbon target and the evolution of its spatial-temporal pattern and the spatial-temporal heterogeneity of the driving factors are the scientific basis for the implementation of the emission reduction and sink enhancement policy according to the local conditions, which is of great importance for the sustainable development of the region. Based on the carbon balance of payment relationship, the carbon surplus and deficit of Shaanxi Province counties were calculated in 2000, 2010, and 2020 from land use, and a series of exploratory spatial and temporal analysis methods (ESTDA), including spatial autocorrelation, cold and hot spot analysis, standard deviation ellipse, and LISA-time pathway, were used to study the dynamics of carbon surplus and deficit in Shaanxi Province at different spatial-temporal scales. From the 21 indicators, six types of major driving factors were selected by principal component analysis, and the geographical spatio-temporal weighted regression model (GTWR) was used to identify their spatio-temporal heterogeneity to construct a comprehensive system of indicators to analyze the carbon deficit and its spatio-temporal heterogeneity in Shaanxi Province. The results showed that: ① A carbon surplus of 8.56 million tons in 2000, a carbon deficit of 3 296 tons in 2010, and a deficit of 33.34 million tons occurred in 2020 in Shaanxi Province, and the growth rate of carbon emissions was much larger than that of carbon sinks, which indicates that it was gradually moving towards carbon peaks in Shaanxi Province; however, there is a long way to go to achieve the goal of carbon neutrality. ② The geographical distribution of the "north deficit and south surplus" phenomenon was visually represented. A carbon deficit was concentrated in the wind and sand area along the Great Wall and Guanzhong plain. The spatial-temporal leap characteristics were more stable. In conclusion, efforts aimed at emission reduction and carbon sink enhancement were strategically directed towards the northern Shaanxi Region. ③ Among various indicator systems including urban construction, natural resources, anthropogenic activities, energy consumption, industrial development, and ecological protection indicator systems, only ecological protection positively drove carbon profit and deficit. Notably, natural resources had the strongest spatial and temporal heterogeneity in their impact on carbon deficit, and energy consumption was positively driven in some areas of Shaanxi Province. The results will provide accurate policy directions for the development of carbon neutral strategies in Shaanxi Province.

PubMedVol. 46(3)
Chang'an University (CN)
Air Quality and Health Impacts
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