This paper examines the emerging paradigm of the“Carbon Digital Twin”as a response to the global“measurement crisis”in climate governance.Traditional methods such as LCA and IOA are increasingly inadequate in addr...This paper examines the emerging paradigm of the“Carbon Digital Twin”as a response to the global“measurement crisis”in climate governance.Traditional methods such as LCA and IOA are increasingly inadequate in addressing the demands of dynamic,data-intensive carbon gover-nance.The Carbon Digital Twin integrates real-time sensing,AI-driven cognitive analysis,and blockchain-based trust mechanisms to provide granular,predictive,and verifiable carbon account-ing.However,this paradigm shift raises tensions between techno-scientific legitimacy and legal-procedural legitimacy,challenging the authority of institutions like the WTO.Comparative analysis of the EU’s CBAM,the US IRA,and China’s state-led model reveals the fragmentation of green trade governance into competing techno-economic blocs.The paper highlights key dilemmas,in-cluding the“carbon paradox”of AI’s own footprint and risks of environmental data injustice,while proposing a hybrid governance framework to balance technological efficiency with demo-cratic accountability and global equity.展开更多
文摘This paper examines the emerging paradigm of the“Carbon Digital Twin”as a response to the global“measurement crisis”in climate governance.Traditional methods such as LCA and IOA are increasingly inadequate in addressing the demands of dynamic,data-intensive carbon gover-nance.The Carbon Digital Twin integrates real-time sensing,AI-driven cognitive analysis,and blockchain-based trust mechanisms to provide granular,predictive,and verifiable carbon account-ing.However,this paradigm shift raises tensions between techno-scientific legitimacy and legal-procedural legitimacy,challenging the authority of institutions like the WTO.Comparative analysis of the EU’s CBAM,the US IRA,and China’s state-led model reveals the fragmentation of green trade governance into competing techno-economic blocs.The paper highlights key dilemmas,in-cluding the“carbon paradox”of AI’s own footprint and risks of environmental data injustice,while proposing a hybrid governance framework to balance technological efficiency with demo-cratic accountability and global equity.
