Estimating consumption-based electricity carbon emission intensity from public data: A cleaner production framework for the Tokyo Metropolitan Area

This study develops a reproducible framework to estimate synthetic 30-min electricity-related CO 2 emissions intensity (CEI) across 14 zones in the Tokyo Metropolitan Area (TMA), addressing gaps in urban emission accounting for decarbonization planning. The primary contribution is an economic dispatch-based electricity carbon emission (ED-CE) model implemented under both Monthly and Intra-day demand allocation approaches using publicly available data. The ED-CE model combines a merit-order dispatch algorithm with a neighbor-priority allocation approach in which surplus electricity is redistributed to the closest zones based on geographical proximity. The Intra-day approach incorporates synthetic half-hourly demand profiles to represent short-term electricity consumption variability. To assess robustness, a network-constrained electricity carbon emission (NC-CE) model is implemented using power-flow information. Results show that while system-level CEI estimates are consistent across ED-CE and NC-CE, spatial patterns are more sensitive to allocation assumptions under ED-CE, whereas NC-CE produces comparatively smoother spatial variability due to power flow constraints and flow-traced emission attribution. In addition, a sensitivity analysis using random surplus allocation indicates that major emission hotspots are generally robust, although absolute zonal magnitudes remain uncertain. The results reveal spatial and temporal heterogeneity in electricity-related emissions and annual emissions (33.2 MtCO 2 /year), increasing 37.0 MtCO 2 /year under the Intra-day approach, while suburban regions show lower or redistributed emissions under intra-day allocation. Southern Ibaraki maintains the lowest CEI (0.26 kgCO 2 /kWh) across all model configurations, indicating a robust low-carbon supply pattern. Industrial and commercial emissions exceed Tokyo Cap-and-Trade value due to differing boundaries and methods, while electricity CEI shows temporal variability from renewables.