# Assessing the Carbon Intensity of e-fuels Production in European Countries: A Temporal Analysis
## 2 Material & Methods  
### Methodological Framework Overview  
Figure 2 represents the approach to assess the greenhouse gas emissions from e-fuel production. The e-fuel can be e-H\({}_{2}\), the simplest form of e-fuel, or any synthetic fuel derived from it. As the last steps are optional, dashed arrows were used in Figure 2. When an e-fuel is derived from H\({}_{2}\), the GHG emissions are calculated as the sum of emissions from H\({}_{2}\) production and from all other inputs, such as the energy required for the final transformation or emissions from carbon capture. However, the scope of this paper covers H\({}_{2}\) production only, while the GHG emissions from all other potential e-fuels can be calculated by expanding the boundaries to cover all subsequent conversion steps. Although further transformation steps induce additional emissions and losses, the effects of H\({}_{2}\) production can be generalised to other e-fuels since the carbon intensity of electricity has the highest impact on their production. The GHG emissions of hydrogen are calculated from the GHG emissions associated with electricity used for hydrogen production. The amount of electricity consumed is directly calculated considering the efficiency of water electrolysis. The thermodynamic limit for dissociating water at ambient temperature through electrolysis is around 40 kWh/kgH\({}_{2}\). For low-temperature electrolysis, around 50 to 55 kWh of electricity is needed to produce 1 kg of hydrogen. The typical electrolysis efficiency ranges from about 60% for proton exchange membrane (PEM) electrolysers to 65 % for alkaline electrolysers [36; 37; 38]. Considering the potential future improvements in terms of efficiency, this value of 65% is considered by default in the later calculations in this paper. One can easily adjust this parameter in the code and generate all the graphs considering other electrolyser efficiency values. Previous studies highlighted the fact that the carbon intensity of H\({}_{2}\) is dominated by the impact of electricity used [39] and the impact of the equipment and infrastructure can be neglected; only emissions related to the use of electricity for H\({}_{2}\) production are considered in the scope of this work. In this paper, the carbon intensity of electricity is calculated as the electricity mix multiplied by the emission factors of each electricity source. While emission factors exclude emissions related to equipment and infrastructure, they include both combustion emissions and upstream emissions related to fuel supply (extraction, transport, and refining for fossil fuels and enrichment for nuclear fuel). The calculations were made for the production mix of each country member of ENTSO-E, listed in Appendix A, at 1-h resolution using the ENTSO-E production data, and then for the tracked consumption mix calculated based on the production and exchange of ENTSO-E data. The most recent ENTSO-E data available (for the year 2023) were used. By using the tracking algorithm [31] implemented in the _EcoDynElec_ tool [35], it is possible to obtain the tracked electricity consumption mix. The algorithm was re-implemented in the developed _EcoDynElec_xr_ tool. With the assumption that H\({}_{2}\) electrolysis uses electricity at a high-voltage level, as expected for a Gigawatt scale project, the calculations considered only the losses after transport, based on the grid loss data sourced from the EUROSTAT dataset NRG_CB_E. Those transport losses referred to the difference between the fed-in (generation) electricity at a high-voltage grid and the electricity delivered to distributors. The tool also enables the inclusion of the grid distribution losses on top of the transport losses in the case where an electrolyser is connected to a lower voltage grid. The use of the EUROSTAT data [40] enables the calculation of average annual grid losses, which is a simplification in the calculation of the hourly carbon intensity of electricity.