Shuaixi Xu, Zeyan Lv, Jiezhen Wu, Lijun Chen, Junhong Wu, Yi Gao, Chengmiao Lin, Yan Wang, Die Song, Jiecan Cui
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引用次数: 0
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.
期刊介绍:
The aim of Meteorological Applications is to serve the needs of applied meteorologists, forecasters and users of meteorological services by publishing papers on all aspects of meteorological science, including:
applications of meteorological, climatological, analytical and forecasting data, and their socio-economic benefits;
forecasting, warning and service delivery techniques and methods;
weather hazards, their analysis and prediction;
performance, verification and value of numerical models and forecasting services;
practical applications of ocean and climate models;
education and training.