## 5 Conclusions  
The main results of this paper are the generated prospective hourly AEF and annual MEF. In order to improve the adequate ecological assessment of electrification measures over their lifetime, the emission factors were calculated from two scenarios with different degrees of decarbonization up to the year 2050. This was accomplished by utilizing an electricity market model (optimization model) based on CO\({}_{2}\) caps and by creating brownfield scenarios with possible future developments. From this data basis, the effects of electricity trading and the storage facilities could be integrated into the AEF using the emissions model. In combination with the grid losses, the GHG emissions were correctly applied to the power consumption. This has the consequence that imported and exported power is given an emissions intensity and thus the impact of an electricity import can also be credited in proportion to the final consumer of the electricity. The discharged power from storage facilities is assigned an emission intensity depending on the emission intensity of the stored power. Thus, the hourly AEF is significantly less distorted by the discharged power. The emission factors can also be used to demonstrate the influence of the German coal phase-out implemented in the scenarios. The additional use of upstream emission factors for the energy sources used in power production show that the influence of upstream emissions plays an increasing role in a strongly decarbonized power production system. The hourly emission factors have been made available for open-access use in life cycle inventories. The AEF generated takes into account, through the calculation method, effects from electricity trading, GHG emissions caused and delayed by electricity storage, the varying efficiency of the power plants, and varying specific emissions from the power generation of individual power plants (partial load behavior) caused by constraints on the electricity market. Although the AEF falls substantially in all scenarios, the value remains constant in the BAU scenario (\(-74\%\) GHG emissions) in the later years at a level just below \(200~{}g_{\text{CO2 eq}}/k\text{Wh}_{\text{hel}}\) and can only fall significantly further in the CAP scenario after 2040. A significant number of hours per year of almost emission-free power only occurs in the CAP scenario in the latter years. The generally higher MEF, compared to the AEF, will decrease with the phasing out of coal-fired power generation but will not fall below \(368~{}g_{\text{CO2 eq}}/k\text{Wh}_{\text{hel}}\). An important finding is the initially higher MEF of the CAP scenario, while more CO\({}_{2}\) is reduced overall. Gas-fired power plants are increasingly used to provide base load, and coal-fired power plants have to respond more flexibly. This is the only way to meet the stricter CO\({}_{2}\) cap, although the MEF is higher. The exchange of power, mainly imported power, with the rest of Europe has a significant impact on the AEF. Together with the lower-emission electricity from the discharge of storage facilities, the AEF is also significantly reduced, and this is despite a small share of RES in net power production. With the high temporal resolution of dynamic factors, flexibility options, sector coupling technologies, and specific decarbonization measures, such as power-to-gas and power-to-heat, can be analyzed with regard to their GHG reduction effects. With these technology options it is decisive determining when lower-emission power can be used to replace fossil energy carriers. With the hourly prospective AEF for Germany, for example, the effects of the electrification of industrial process heat on greenhouse gas emissions can be calculated. The few annual averages used so far, as in [PERSON] and [PERSON] [69], do not make it possible to determine the deployment strategy and GHG emissions of hybrid heat generation technologies. In addition, the dynamic charging profiles of battery electric vehicles, as in [PERSON] et al.