Lately, the European Union has reinforced the targets set to cut back carbon emissions. The energy generation sector and particularly, the district heating (DH) system, is still prevailed by combustion of fossil fuels that heavily contributes to such emissions. This paper presents a system-based approach to study the coupling between electricity and DH sector for effective mitigation of emissions. A mixed integer linear programming framework is proposed that aims to exploit the flexibility of electricity cogeneration together with partial electrification of the DH system by investing in renewable technologies. The objective is to simultaneously minimize the investment cost and emissions. Both the electricity and DH load profiles are segregated into critical and flexible types. Comprehensive demand response (DR) framework of thermostatically controlled loads and electric vehicles is considered while preserving the chronology. The framework is applied to the Finnish energy system considering the generation mix. Results prove that coordinating the electricity cogeneration with renewable generation combined with partly shifting from DH to electrified heating has a great potential in reducing the emissions. For an average weather scenario under DR, the least-cost solution guarantees an annual emission reduction of 12.04% relative to the total emissions of Finland against the total investment of ¿13.24Bn in wind and solar power generation.ARSLAN AHMAD BASHIR received the bachelor's degree in electrical engineering from the University of Engineering and Technology Lahore, Pakistan, in 2011, and the master's degree in electrical engineering and electrical systems from Aalto University, Finland, in 2016, where he is currently pursuing the Ph.D. degree in electrical engineering. He has worked as a Design Engineer with the Electricity Transmission System Operator of Pakistan, from 2012 to 2014, and from 2016 to 2017. His research interests include demand response modeling of thermostatically controlled loads, renewable energy integration, power and heat sector coupling, time-period clustering, as well as power system operation, planning, and economics.