摘要
将经济投入产出生命周期评价与最小流分析方法结合构建了中国工业碳排放网络.结合社会网络分析方法,从网络整体特征、节点中心性以及块结构3个方面分析了中国工业碳排放网络结构特征,并基于链路动态变化的建模思想,在有向加权网络形式下预测了2022年中国工业碳排放网络.结果表明:1997~2017年之间,中国工业各子行业之间碳排放关联越来越密切,普通机械制造业等行业在网络中体现出较强“桥梁”作用,黑色金属冶炼及压延加工业等行业在网络中扮演“中心行动者”角色.块模型结果显示,因不同行业在工业系统中的产业链位置不同,在整个网络中的块结构中扮演的角色不同.链路预测得到的2022年中国工业碳排放网络密度显著下降,板块结构进一步复杂化,黑色金属冶炼及压延加工业等5个行业的中介中心性与接近中心性均排名前5位.在碳减排政策的制定、完善和实施过程中,要重视发挥碳排放网络节点特征对跨行业协同减排的作用,充分捕捉利用碳排放网络中聚类特征与碳转移路径等信息,制定具有差异化的行业部门分类管理政策,以达到节约减排成本与提高减排效率的效果.
China’s industrial carbon emission network was constructed by combining the life cycle assessment of economic inputs and outputs by the minimum flow analysis method.Combined with the social network analysis method,the structural characteristics of China's industrial carbon emission network were analyzed from three aspects,namely,the overall network characteristics,node centrality and block structure.In addition,China's industrial carbon emission network in 2022 was predicted in the form of a directed weighted network based on the idea of modeling the dynamic change of links.The results showed that between 1997 and 2017,the carbon emissions of Chinese industries had become more and more closely related to each subsector;the general machinery manufacturing industry and other industries played a stronger"bridge"role in the network,while the ferrous metal smelting and calendering industry and other industries played the role of"central actor"in the network.The results of the block model showed that different industries played different roles in the block structure of the whole network due to their different industrial chain positions in the industrial system.From the link prediction in 2022,the density of China's industrial carbon emission network decreased significantly,the block structure was further complicated,and the intermediary centrality and near-centrality of five industries,including ferrous metal smelting and rolling processing industry,were ranked in the top five.In the process of formulating,improving and implementing carbon emission reduction policies,it is necessary to pay attentions to the role of the node characteristics of the carbon emission network on cross-industry collaborative emission reduction,the clustering characteristics of the carbon network and carbon transfer paths.Other information needed to be fully captured and utilized,and differentiated policies needed to be formulated for the classification and management of industry sectors,so as to achieve the effect of saving emission reducti
作者
彭邦文
郑闳方
朱磊
胡文倩
PENG Bang-wen;ZHENG Hong-fang;ZHU Lei;HU Wen-qian(School of Economics and Trade,Hunan University of Technology and Business,Changsha 410205,China;College of Electronics and Information Engineering,Shenzhen University,Shenzhen 518060,China;School of Public Administration,Xi’an University of Architecture and Technology,Xi'an 710055,China)
出处
《中国环境科学》
EI
CAS
CSCD
北大核心
2024年第3期1718-1731,共14页
China Environmental Science
基金
国家社会科学基金资助重大项目(22&ZD051)
湖南省自然科学基金青年项目(2021JJ40156)。
关键词
碳排放
网络
投入产出模型
链路预测
carbon emissions
network
input-output model
link prediction
