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Spatio-Temporal Variation and Drivers of Land-Use Net Carbon Emissions in Chengyu Urban Agglomeration, China

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Land-use change is an important cause of carbon emissions (CEs). In the context of achieving carbon peaking and carbon neutrality goals, understanding the coupling mechanisms between land-use change and CEs is of great significance for fostering regional low-carbon sustainable development. In this study, the land-use net carbon emissions (LCN) calculation and evaluation model was built based on the perspective of land-use change. The land-use variation matrix, standard deviation ellipse, and spatial autocorrelation analysis were used to analyze the spatio-temporal evolution of land-use and the LCN in the Chengyu urban agglomeration (CUA) from 2000 to 2020. Meanwhile, the economic contribution coefficient and ecological support coefficient were applied to evaluate the alignment among the CEs, socio-economic development, and the ecological environment. In addition, the modified Kaya and Logarithmic Mean Divisia Index (LMDI) models were used to quantitatively analyze the drivers and underlying influence mechanisms of the LCN. The results showed the following: (1) The area of built-up land and forest land expanded rapidly, mainly transforming grassland and farmland to built-up land and forest land in the CUA during the study period. The built-up land was the main source of the regional CEs. The land-use changes led to the migration of the LCN center and the variations in spatial clustering. (2) The growth rate of the LCN decreased after 2010, and the disparities in carbon productivity and the carbon compensation rate among the cities gradually narrowed from 2000 to 2020. The alignment among the regional CEs, socio-economic development, and ecological environmental governance was effectively improved. (3) The economic development level and energy consumption intensity were the primary facilitator and inhibitor of the LCN, respectively. The results could offer valuable references and insights for formulating regional carbon reduction strategies and policies.
Title: Spatio-Temporal Variation and Drivers of Land-Use Net Carbon Emissions in Chengyu Urban Agglomeration, China
Description:
Land-use change is an important cause of carbon emissions (CEs).
In the context of achieving carbon peaking and carbon neutrality goals, understanding the coupling mechanisms between land-use change and CEs is of great significance for fostering regional low-carbon sustainable development.
In this study, the land-use net carbon emissions (LCN) calculation and evaluation model was built based on the perspective of land-use change.
The land-use variation matrix, standard deviation ellipse, and spatial autocorrelation analysis were used to analyze the spatio-temporal evolution of land-use and the LCN in the Chengyu urban agglomeration (CUA) from 2000 to 2020.
Meanwhile, the economic contribution coefficient and ecological support coefficient were applied to evaluate the alignment among the CEs, socio-economic development, and the ecological environment.
In addition, the modified Kaya and Logarithmic Mean Divisia Index (LMDI) models were used to quantitatively analyze the drivers and underlying influence mechanisms of the LCN.
The results showed the following: (1) The area of built-up land and forest land expanded rapidly, mainly transforming grassland and farmland to built-up land and forest land in the CUA during the study period.
The built-up land was the main source of the regional CEs.
The land-use changes led to the migration of the LCN center and the variations in spatial clustering.
(2) The growth rate of the LCN decreased after 2010, and the disparities in carbon productivity and the carbon compensation rate among the cities gradually narrowed from 2000 to 2020.
The alignment among the regional CEs, socio-economic development, and ecological environmental governance was effectively improved.
(3) The economic development level and energy consumption intensity were the primary facilitator and inhibitor of the LCN, respectively.
The results could offer valuable references and insights for formulating regional carbon reduction strategies and policies.

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