## 4 Discussion
### Comparison with Other Research  
The results of the relevant publications described hereafter are presented comparatively in Table 3. The fuel-specific emission factors used in [18] are derived from ecoinvent's LCI, taking into account life cycle emissions and assessing the amount of electricity produced, whereas in this paper, the used fuel-specific emission factors were determined for the combustion of fossil fuels prior to their conversion in thermal power plants. This way, different efficiencies and a partial load operation of the power plants could be considered. Similar to [18], the effect could be observed that lower AEFs occurring at times of increased photovoltaic feed-in and also at weekends at lower load (Figure 6a). However, the more prospective consideration here shows that the load-dependent effect is reversing further in the future. The AEF\({}_{\text{fc}}\) calculated by [50] is higher in both comparable scenarios. The calculation is based on several energy scenarios with information on the installed capacity of the generation units in the future power plant park. The average annual CO\({}_{2}\) emissions from power production are determined using the capacity factor and a power plant-specific emission factor. The authors consider different values of fuel-specific emission factors using a Monte Carlo simulation. The available emission factors of this research work were formed on the basis of the National Inventory Report for Germany, taking into account regional and technological specifications (Table 1). Furthermore, the hourly values with different power plant efficiencies (partial load behavior) and the data basis of an hourly optimization model of the German electricity market are not necessarily comparable with the annual calculations of [50]. In [51], hourly emission factors of power production were calculated using three type days per season in an energy system model. The time horizon extends to the year 2030 with the aim of determining different charging times based on the emission intensity of the electricity used at the same time. No trading effects were considered, and specific emission factors per generation class (coal, lignite,... ) were applied. To determine the indirect MEF, a specific load profile derived from the charging cycles of battery electric vehicles is added \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & & & \multicolumn{4}{c}{**Yearly Average in \(\text{gCO}_{2 eq}\)/kWhel**} \\ \hline
**Type** & **Reference** & **Scenario** & **2020** & **2030** & **2040** & **2050** \\ \hline \multirow{4}{*}{AEF\({}_{\text{fc}}\)} & Seckinger and Radgen & BAU & 420 & 358 & 194 & 182 \\  & & CAP & 380 & 301 & 170 & 29 \\  & Boing and Regett [35] & Trend & 357 & 238 & 97 & 75 \\  & [PERSON] et al. [51] & - & 380 & 290 & - & - \\  & & Reference & 460 & 460 & - & - \\  & & Target & 400 & 360 & - & - \\ \hline \multirow{4}{*}{MEF\({}_{\text{fc}}\)} & Seckinger and Radgen & BAU & 774 & 526 & 472 & 475 \\  & & CAP & 808 & 592 & 462 & 368 \\ \cline{1-1}  & Boing and Regett [35] & Trend & 633 & 434 & 375 & 332 \\ \cline{1-1}  & [PERSON] et al. [51] & - & - & 550 & - & - \\ \hline \hline \end{tabular}  
* Emission factors of power production. 2 Yearly average, no hourly values.  
\end{table} 
Table 3: Comparison of the AEF and MEF with other research examining prospective emission factors for Germany. to the conventional load in the optimization model. From this, an emission difference due to a changed dispatch and newly built power plants was calculated. Hence, the indirect MEF here is only valid for that particular load change and cannot essentially be compared to a more general MEF. The exploratory scenario used by [35] for the generated hourly prospective emission factors is most comparable to the CAP scenario. However, the exploratory type is recommended for modeling indirect MEF [7]. In the normative scenarios presented here, the linear optimization model determined the expansion of power plant capacity endogenously for each unit by meeting the CO\({}_{2}\) caps.