A spatiotemporal-coupled accounting framework for product carbon footprint and benefit analysis considering green electricity consumption

Traditional Product Carbon Footprint (PCF) accounting heavily relies on annual static emission factors and the idealized copper-plate grid assumption. This approach not only neglects temporal source-load mismatch and spatial network congestion but also exposes enterprises to severe asset mismatch and compliance cost risks in carbon and green certificate markets. This study proposes a novel dual-track PCF accounting and benefit analysis framework strictly constrained by spatiotemporal physical realities and dynamic additionality. First, an exponential time kernel function and a spatial damping model based on the Linear DistFlow equations are integrated and solved using Mixed-Integer Linear Programming (MILP) to quantify the physical accessibility of green power. Second, a decoupled carbon reduction attribution model is established, differentiating the actual physical displacement of emissions via Locational Marginal Emission Factors (LMEF) from the financial compliance constraints tied to dynamic asset additionality. Rollout simulations on a practical 7-bus distribution network in Xinjiang reveal that the traditional market-based method severely underestimates actual carbon emission responsibilities, yielding an annual average Greenwashing Index (GWI) reaching 70%. This underestimation translates into significant sunk costs in green power investments and potential carbon tax penalties. This methodology successfully bridges the gap between financial instruments and physical realities, providing robust pricing signals and decision support for energy-intensive enterprises to mitigate economic risks of greenwashing, optimize investments in flexible resources, and transition toward 24/7 Carbon-Free Energy (CFE).