A city-scale optimization framework for biomass-to-clean-energy transitions: The KAMPALA-TIMES model

Rapid urbanization in Sub-Saharan African cities is accompanied by persistent reliance on traditional biomass for household energy, posing challenges for climate mitigation, public health, and sustainable development. This study develops the KAMPALA-TIMES model, a city-scale, bottom-up optimization framework that integrates localized energy data with IPCC AR6 SSP-RCP pathways to evaluate long-term energy transition strategies for Kampala, Uganda, from 2022 to 2060. Four scenarios (business-as-usual, enhanced biomass utilization, mixed renewable integration, and policy-driven carbon reduction) are assessed. Results show that efficiency improvements alone stabilize emissions but do not significantly reduce them, whereas electrification combined with renewable expansion substantially lowers system emissions. The policy-driven carbon reduction pathway achieves the deepest mitigation, reducing emissions to approximately 3.4 MtCO₂e by 2060 and nearly eliminating household cooking emissions by 2040. These findings demonstrate that coordinated fuel substitution, infrastructure investment, and policy alignment are critical for urban decarbonization and provide a transferable framework for energy planning in rapidly growing, data-constrained cities.