## 1 Introduction
According to [23], the AEF is correctly applied when the load to be analyzed is part of the existing demand or when the consequences of an existing electricity use are to be calculated. However, if the load to be analyzed represents a new change in demand, the use of MEFs is recommended [23]. If the new future demand is taken into account in the planning of power production, according to [25], then the AEF can also be used for this new demand. The authors of [26] conclude that the calculation of the emission factor should always be based on net power consumption rather than on power production, otherwise the results may be misinterpreted when applying the factors. The GHG emissions presented by the AEF in this paper are thus based on the net power consumption. Net power consumption is defined as gross power production plus imports and minus exports, auxiliary consumption, pumping, and grid losses. The MEF is used to determine the impact of a change in demand. The MEF represents the emissions generated by the reacting generation units due to the change in demand and is usually considerably higher than the AEF [27; 28]. The general power supply system is a highly interconnected network in which electricity is supplied by various producers to different locations in the area of supply. The system is dynamic and responds to economic signals (e.g., fuel and stock exchange prices), technical restrictions (e.g., start-up times and frequency control), and transmission constraints [29]. The challenge is therefore to identify which power plants respond to changes in demand at a given point in time and to what extent (marginal electricity mix or marginal power plant) [27]. In contrast to the AEF, the MEF approach is an ecological assessment method that more realistically reflects the response of the power generation system [30]. Some of the established methods for calculating the MEF are divided into two groups, the \"top-down\" and the \"bottom-up\" approaches [29]. In the first group, the normative economic behavior of power plants in the event of a change in demand is examined. For this purpose, a permanent marginal power plant can be defined in a simple manner, to which the entire change in demand is attributed, or a merit order of the power plants employed can be formed [31]. However, more than just one generation unit, but not all of them as in the case of the AEF, reacts to changes in demand. Because of grid restrictions or must-run feed-in, the generating units do not always react according to the theoretical merit order [23; 30; 32]. The second group of methods comprises the top-down approaches. Simulation or optimization models (electricity market models) are often used to assess the effects of load changes when investigating future emission factors in order to capture the effects of the entire power generation system. For a consideration of long-term changes, such as new power plant construction and its dispatch, two scenarios are formed in energy system models with a shifted demand. The principle of this approach is to investigate the effects of a shifted load or demand in simulation or optimization models under otherwise constant input parameters but dynamic conditions [8]. [PERSON], [PERSON] et al., and [PERSON] and [PERSON] demonstrate this methodology for Germany [33; 34; 35]. For the creation of detailed and complex energy system models, a considerable number of parameters and input data have to be defined and many assumptions have to be made in order to obtain reproducible results [36]. The associated computing and workload are huge, and depending on the complexity of the investigation, not feasible and not necessarily practicable for LCA [37; 38]. Another less-complex methodology in the top-down approach is that of the average MEF using the linear regression method, which is used in this paper. References [27; 30] calculate the difference between two consecutive hours from the amount of conventional (fossil) power generation and the emissions produced.