气候变化研究进展2024，Vol.20Issue(1)：62-74,13.DOI:10.12006/j.issn.1673-1719.2023.185
中国出口贸易隐含碳的趋势预测及结构转移研究
Research on the trend prediction and structure transfer of embodied carbon in China's export trade
摘要
Abstract
Based on the Lasso method of feature selection,the core indicators affecting the total amount and intensity of embodied carbon emissions(CO2)in China's export trade are determined respectively,and the BO-BiLSTM model was constructed to predict the trend of total amount change and intensity evolution.At the same time,the Markov chain was used to further explore the structural transfer phenomenon of embodied carbon emissions in China's export trade.The results are as follow.(1)From 2021 to 2035,the total amount of carbon emissions embodied in China's export trade shows a trend of gradient reduction.It is expected to reach 1.98 Gt in 2030 and further decrease to 1.83 Gt in 2035.The expansion of export trade scale and the improvement of international economic and trade situation are the key influencing factors.(2)From 2021 to 2035,the embodied carbon emission intensity in China's export trade has maintained a steady and declining trend.It is expected to drop to 0.91 t per CNY 10000 in 2030,which is 67%lower than that in 2005.The change of export trade structure and the increase of environmental regulation intensity are important driving factors.(3)From 2021 to 2035,the structure of embodied carbon emissions in China's export trade still focuses on knowledge-intensive manufacturing industry,which has great potential for emission reductions,while capital-intensive service industry and capital-intensive manufacturing industry have the characteristics of long cycle of carbon emission reductions.关键词
出口贸易隐含碳/投入产出模型/机器学习预测Key words
Export trade embodied carbon/Input-output model/Machine learning prediction引用本文复制引用
胡剑波,麦骏南..中国出口贸易隐含碳的趋势预测及结构转移研究[J].气候变化研究进展,2024,20(1):62-74,13.基金项目
国家社会科学基金项目"中国隐含碳全要素生产率动态演进与提升策略研究"(23XJY022) （23XJY022）
