Carbon Digital Twin: Artificial Intelligence, Green Protectionism, and the Reshaping of Global Trade Governance

Abstract

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 governance. The Carbon Digital Twin integrates real-time sensing, AI-driven cognitive analysis, and blockchain-based trust mechanisms to provide granular, predictive, and verifiable carbon accounting. 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, including 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 democratic accountability and global equity.