• • The proposed GC-carbon reduction association model systematically classifies GC transaction types and establishes corresponding accounting criteria, resolving the double-counting deficiency where China's current regional grid emission factors fail to deduct renewable energy environmental attributes already transferred through GC transactions—a flaw that inflates renewable energy carbon reduction claims by up to 100% for the same green power.
• • Kalman filtering and inversion techniques are applied to thermal power plant carbon emission monitoring data, improving data accuracy for source-side carbon accounting. This addresses the critical industrial bottleneck where direct measurement data from fossil fuel combustion contains noise and systematic errors that propagate through the entire accounting chain, affecting compliance and trading decisions.
• • The differentiated accounting framework based on transaction characteristics enables spatial matching between GC transactions and regional power grids, operationalized through the IEEE 30-bus system and a geographic region in China. This provides a replicable methodology for mapping market-based environmental attribute transfers onto physical grid infrastructure, essential for implementing Japan's dual emission factor system (basic and adjusted factors) in China's context.
• • The framework establishes a mapping relationship between the power network and geographic regions, enabling carbon accounting that distinguishes between physical consumption and market-based transactions. This directly addresses the EU's concern regarding green certificates in CBAM, where unclear rights-responsibility relationships between GCs, green power usage, and carbon emissions create double-counting risks that undermine carbon border adjustment integrity.