Toward Trustworthy and Efficient Carbon Emissions Trading: A Stable Matching and Privacy-Preserving Framework

Carbon emissions trading (CET) requires not only efficient allowance allocation but also stable transactions and protection of sensitive trading information. This study proposes a trustworthy CET framework that integrates stable matching with privacy-preserving computing. Carbon trading is modeled as a dynamic many-to-many matching problem in which reservation prices, trading quantities, and time priority are used to construct bilateral preferences, while blocking-pair elimination ensures pairwise stability. Paillier homomorphic encryption, zk-SNARKs, and blockchain are further incorporated to support secure declaration, matching, and settlement. Real-market-calibrated simulations based on China’s national carbon market show that the proposed SMCETS mechanism maintains zero blocking pairs under excess-supply, excess-demand, and equilibrium conditions, including under reservation-price perturbations and trading-quantity variations. It also achieves higher Benefit Index and total surplus values than the Vickrey and discriminatory-price auction benchmarks in the tested settings. Prototype evaluation further demonstrates practical runtime feasibility. These results suggest that stable matching and privacy-preserving technologies can be jointly incorporated into digital carbon-trading mechanisms to support more reliable and trustworthy market operation.