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Impacts of Energy Structure on Carbon Emissions in China, 1997–2019

To mitigate climate change, reducing carbon dioxide (CO(2)) emissions is of paramount importance. China, the largest global CO(2) emitter, proposes to peak carbon emissions by 2030 and become carbon neutral by 2060; transforming the energy structure represents one of the primary means of addressing...

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Detalles Bibliográficos
Autores principales: Ge, Fengjian, Li, Jiangfeng, Zhang, Yi, Ye, Shipeng, Han, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140871/
https://www.ncbi.nlm.nih.gov/pubmed/35627387
http://dx.doi.org/10.3390/ijerph19105850
Descripción
Sumario:To mitigate climate change, reducing carbon dioxide (CO(2)) emissions is of paramount importance. China, the largest global CO(2) emitter, proposes to peak carbon emissions by 2030 and become carbon neutral by 2060; transforming the energy structure represents one of the primary means of addressing carbon emissions; thus, it is essential to investigate the impacts of alternate energy sources throughout the country. Based on energy consumption and carbon emissions data from 30 provincial-level administrative regions in China (excluding Tibet, Hong Kong, Taiwan, and Macau, due to the lack of data), the study here investigated the shares of coal, petroleum, natural gas, and non-fossil energy sources (i.e., hydropower, nuclear power, wind power, solar power, and biomass power), as they relate to total, per capita, and per unit GDP CO(2) emissions via spatial regression. The results showed that: (1) The epicenters of coal and carbon emissions have shifted from the east to the central and western regions; (2) There is a significant correlation between energy structure and carbon emissions: coal has a positive effect, petroleum’s effects are positive at first, and negative subsequently; while both natural gas and non-fossil energy sources have a negative impact; (3) Provincial-level carbon emissions are affected by energy structure, carbon emissions in neighboring regions, and other factors.