Low-carbon transition of electric power system plays an important role in meeting national greenhouse gas (GHG) emission reduction goals. Analyzing the effects of low-carbon transition of the electric power system on various sectors could provide targeted and effective mitigation policy recommendations at sectoral level. In this study, a factorial optimization-driven input-output model has been developed to explore socio-economic and environmental (SEE) effects of GHG emission reduction in Canada's electric power systems under uncertainty and their interactions. Results highlight the importance of optimizing the structure of a certain system (e.g., energy system or electric power system) on the emission reduction of the whole society under a specific mitigation target. Significance of indirect GHG emissions for sectoral emission reduction policy formulation is further emphasized, especially for agriculture and manufacturing-related sectors. In addition, factors with significant interactive effects on total outputs have been identified. Increasing the proportion of renewable power generation (i.e., wind/solar power, small modular reactor power, and coal-fired power with carbon capture and storage technology) is conducive to increase in sectoral total outputs and reduction of GHG emissions by 2050. The modelling framework can be extended and applied to other regions to help analyze SEE effects under various emission mitigation policies.