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A carbon-neutrality-capactiy index for evaluating carbon sink contributions

The accurate determination of the carbon-neutrality capacity (CNC) of a region is crucial for developing policies related to emissions and climate change. However, a systematic diagnostic method for determining the CNC that considers the rock chemical weathering carbon sink (RCS) is lacking. Moreove...

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Detalles Bibliográficos
Autores principales: Bai, Xiaoyong, Zhang, Sirui, Li, Chaojun, Xiong, Lian, Song, Fengjiao, Du, Chaochao, Li, Minghui, Luo, Qing, Xue, Yingying, Wang, Shijie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9937913/
https://www.ncbi.nlm.nih.gov/pubmed/36820152
http://dx.doi.org/10.1016/j.ese.2023.100237
Descripción
Sumario:The accurate determination of the carbon-neutrality capacity (CNC) of a region is crucial for developing policies related to emissions and climate change. However, a systematic diagnostic method for determining the CNC that considers the rock chemical weathering carbon sink (RCS) is lacking. Moreover, it is challenging but indispensable to establish a fast and practical index model to determine the CNC. Here, we selected Guizhou as the study area, used the methods for different types of carbon sinks, and constructed a CNC index (CNCI) model. We found that: (1) the carbonate rock chemical weathering carbon sink flux was 30.3 t CO(2) km(−2) yr(−1). Guizhou accounted for 1.8% of the land area and contributed 5.4% of the carbonate chemical weathering carbon sink; (2) the silicate rock chemical weathering carbon sink and its flux were 1.44 × 10(3) t CO(2) and 2.43 t CO(2) km(−2) yr(−1), respectively; (3) the vegetation-soil ecosystem carbon sink and its flux were 1.37 × 10(8) t CO(2) and 831.70 t CO(2) km(−2) yr(−1), respectively; (4) the carbon emissions (CEs) were 280 Tg CO(2), about 2.8% of the total for China; and (5) the total carbon sinks in Guizhou were 160 Tg CO(2), with a CNCI of 57%, which is 4.8 times of China and 2.1 times of the world. In summary, we conducted a systematic diagnosis of the CNC considering the RCS and established a CNCI model. The results of this study have a strong implication and significance for national and global CNC determination and gap analysis.