Theoretical Framework for Quantifying and Monetising Carbon Emission Reduction Benefits of the Nigerian National Grid Decarbonisation Programme

This research develops a comprehensive theoretical framework for quantifying and monetising the carbon emission reduction benefits of Nigeria's National Grid Decarbonisation Programme under the country's Nationally Determined Contributions to the Paris Agreement, making original contributions to the methodology for emission accounting and carbon finance in complex power systems with high measurement uncertainty and data quality limitations. Nigeria's electricity sector emissions accounting is complicated by fuel consumption data gaps at power plants, non-linear emission factors for ageing thermal generators operating below design efficiency, and the methodological challenges of attributing emission reductions to specific grid interventions in a network with multiple simultaneous changes. The research framework develops three original theoretical contributions: a Bayesian emission factor estimation methodology that propagates measurement uncertainty and plant condition variability into probabilistic emission intensity estimates for each generator unit in the NESI fleet; a counterfactual baseline construction method tailored to Nigerian grid data availability constraints that robustly estimates what emissions would have been in the absence of decarbonisation interventions; and an original carbon benefit monetisation model that translates probabilistic emission reduction estimates into carbon finance asset valuations under multiple carbon market access scenarios including the voluntary carbon market, CORSIA, and an anticipated Article 6 bilateral mechanism with European purchasers. The framework is demonstrated on three completed grid decarbonisation projects covering 400MW of solar capacity addition and a 220km transmission expansion. Keywords: carbon accounting, decarbonisation, Nigerian grid, Bayesian estimation, carbon finance.