Because of the EU-wide CO ₂ reduction obligations and further energy policy framework conditions in the future, a significant growth of natural gas demand for electricity by the EU member states is expected. The growth could come in large part from the increased use of gas-and-steam power plants. The forecasts of the markets for natural gas, electricity, and CO ₂ emissions certificates often are not simultaneously modeled so that their interdependence is given only a limited consideration. A survey covers the linear multi periodic Perseus-EEM (Program Package for Emission Reduction Strategies in Energy Use and Supply; EEM: European Energy Model) optimization model that enables a simultaneous analysis of these three markets. Also, model results for two scenarios are discussed. A central associated element of the markets for electricity, natural gas and CO ₂ certificates is the increasing natural gas electrification in the EU that now accounts for about 20% of the total electricity demand. Natural gas power plants are favored because of their relatively short construction time, small specific capacity investment costs, flexible control, and capability of being installed that are advantageous especially in the liberalized markets. Also, in the combustion of natural gas compared with other fossil fuels, natural gas produces the least specific emissions. Natural gas electrification is thus perceived as an important option to reduce CO ₂ emissions in the EU. Because of the structural age of the power plants in the EU and with consideration in Germany of the withdrawal from nuclear power up to 2020 there will be a need to add about 200 Gw. Because the fuel costs of natural gas power plants are a significant component of electricity generation costs, the relative advantages of natural gas electrification can also be negatively influenced. The optimizing, multi-periodic and inter-temporal Perseus-EEM model based on existing energy flow models of the Perseus model family developed at the University of Karlsruhe and used and further developed in research and industrial projects has an optimizing approach consisting in the minimization of the linear intertemporal objective function that is described through the discounted sum of all system relevant outputs. These comprise investments for new facilities, fixed and variable operating costs, fuel costs, transport costs, and transit taxes.