背景(考古学)
具身认知
碳循环
碳纤维
环境科学
自然资源经济学
计算机科学
经济
生态学
地质学
生态系统
人工智能
生物
古生物学
算法
复合数
作者
Xiaoyun Zhang,Feng Dong
标识
DOI:10.1080/17583004.2023.2176005
摘要
Under accelerated domestic economic cycle, it is significant to predict the embodied carbon transfer network (ECTNs) to identify key emission regions to improve emission reduction efficiency. Based on the existing China Multi-regional Input-Output Table (CMRIOs) for 2002, 2007, 2010, 2012, 2015 and 2017, the CMRIOs for 2002-2017 were updated, then the ECTNs were predicted and constructed from 2018 to 2025 through Particle Swarm Optimization- Support Vector Model. Finally, the spatial and temporal evolution trends of the ECTNs' features were explored through complex networks analysis. The results showed that carbon leakage between provinces has been becoming increasingly serious. The small-world features of the ECTNs were becoming increasingly obvious. The distribution of provinces with great influence on carbon transfer was transferred from north to south, and then to the central region. Hebei, Jiangsu, Henan, Zhejiang, Inner Mongolia, and other resource-intensive and manufacturing provinces played an important "bridge" role in the trade between economic developed and developing provinces. Trade ties between non neighboring provinces have become increasingly close, which means the development of China's integration has strengthened. This study provides a theoretical reference for the formulation of China's overall carbon emission reduction policy.
科研通智能强力驱动
Strongly Powered by AbleSci AI