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Study on the spatialization of anthropogenic carbon emissions in China based on SVR-ZSSR
The spatialization of anthropogenic carbon emissions is of great significance for achieving the goal of "carbon peaking and neutrality" and promoting the development of carbon trading market. The SVR-ZSSR spatialization model is proposed to solve the problems of "insufficient local fe...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894835/ https://www.ncbi.nlm.nih.gov/pubmed/36732578 http://dx.doi.org/10.1038/s41598-023-28462-x |
Sumario: | The spatialization of anthropogenic carbon emissions is of great significance for achieving the goal of "carbon peaking and neutrality" and promoting the development of carbon trading market. The SVR-ZSSR spatialization model is proposed to solve the problems of "insufficient local feature learning" and "scale dependence of driving factors" existing in the single model, and this model is applied to the study of the spatialization of carbon emissions in China in this paper. The results show that: (1) the simulation results of our proposed model show the distribution characteristics of "high in the East and low in the west"; On the micro-scale, the high carbon emission areas in the simulation results are all concentrated in the built-up land, while the carbon emission in the surrounding areas of the city is significantly lower than that in the center, which is similar to the spatial distribution trend of carbon emission in the existing database. (2) Compared with the results of SVR, the results of our proposed model increase the carbon emission ratio of built-up land in each province by 15.9% on average; Compared with the ODIAC database and SVR model, the carbon emission ratio of built-up land in Gansu Province, Qinghai Province, and other low-carbon emission areas has increased by about 25%. |
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