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Prediction method of regional carbon dioxide emissions in China under the target of peaking carbon dioxide emissions: A case study of Zhejiang.

Authors :
Xu, Shuaixi
Lv, Zeyan
Wu, Jiezhen
Chen, Lijun
Wu, Junhong
Gao, Yi
Lin, Chengmiao
Wang, Yan
Song, Die
Cui, Jiecan
Source :
Meteorological Applications; May/Jun2024, Vol. 31 Issue 3, p1-13, 13p
Publication Year :
2024

Abstract

All provinces of China respond to the central government, predict future carbon dioxide emissions, and formulate action plans detailing how the province intends to fulfill its target of carbon emission peaking before 2030. Based on the bottom‐up energy consumption prediction and top‐down goal verification, this paper constructs a set of regional carbon dioxide emission prediction methods. Compared to the traditional bottom‐up prediction method, this method could simplify the parameters while improving the prediction accuracy. This model is used to predict and analyze the process of carbon dioxide emission peaking in Zhejiang. The results show that the mean absolute percentage error of the retrospective prediction value is only 1.56%. Zhejiang will reach carbon dioxide emission peaking around 2029–2030, and the peak value will be 569.7 million tons. Different factors have different effects on the process of carbon dioxide emission peaking. There is a strong correlation between the peak time of carbon dioxide emission and the production time of major energy‐consuming projects in Zhejiang. Meanwhile, if the 16 nuclear reactors are not put into operation, Zhejiang will not be able to achieve the goal of carbon dioxide emission peaking. Besides, the basic data used in this model is mainly from the local statistical departments of the region. Thus, it can be applied to other provinces and regions conveniently. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13504827
Volume :
31
Issue :
3
Database :
Complementary Index
Journal :
Meteorological Applications
Publication Type :
Academic Journal
Accession number :
178093085
Full Text :
https://doi.org/10.1002/met.2203