Contribution to a standardized economic and ecological assessment methodology for e-fuel production in Germany

Nathanael Heimann^1*Moritz Raab¹Niklas Wulff¹Sofia Haas²Simon Pichlmaier²Ralph-Uwe Dietrich¹

• ¹German Aerospace Center (DLR), Cologne, Germany
• ²Forschungsstelle fur Energiewirtschaft e V, Munich, Germany

The transport sector worldwide still does not meet the international obligations to become climate neutral. One of the countries lacking behind their set goals is Germany. In 2021, the German transport sector contributed to 19.4 % of Germany's greenhouse gas emissions (German Environment Agency, 2022). In order to reach the maximum target of 85 Mt CO2 equivalents by 2030, emissions need to be reduced by about 79 Mt CO2 equivalents compared to 2020. Also, other European countries do have a long way to go, to reach net zero emissions in the transport sector as depicted in Figure 1.Figure 1: Share of renewable energy in the transport sector of selected European countries (adapted from (Eurostat, 2019)).In order to explore pathways for the de-fossilization of the transport sector on national and global level, the German federal ministry for economic affairs and climate action (BMWK) launched the initiative "energy transition in the transport sector: sector coupling through the use of e-fuels" (EiV) in 2017 with a total funding of 99 M€ and 16 projects (BMWK, 2017). Since each project started with its own goals to find a solution for a certain part of the transport sector, it was not ensured whether their analysis concerning costs or environmental impacts would be comparable. To propose the most promising pathways for the short, mid and long term, these pathways needed to be assessed technically, economically and ecologically. Here, a standardized methodology and a framework of basic assumptions, based on previous work (e.g. Albrecht et al., 2017), had to be provided. This was done by the authors within the additional project "accompanying research on the EiV" (BEniVer) (Energiesystem-Forschung, 2021).A comparable analysis of power-to-x production (PtX) routes is only possible if the underlying assumptions and methodologies are consistent and are reported. However, due to different levels of detail and assumption, this is often not the case as illustrated by the following examples.In the absence of all technical information, reproduction of results is limited: In Gorre et al. (2020) information about the catalyst, used for methanation, is missing. Furthermore, the compressors are only defined by a share of total energy consumption. The target purity of the product is not reported, as also in Moioli and Schildhauer (2022) for their methanol synthesis. Tremel et al. (2015) provides neither flow diagram nor simulation data. Furthermore, information on the thermodynamic model used, the purity of the product and the reactor model is missing. Adnan and Kibria (2020) do not specify product purity. Even though many economic values in Gorre et al. (2019) are listed in a very good manner, not mentioning the product's purity and assuming that both, different electrolysis technologies and also different methanation processes had "minor technological differences," makes their technical insight questionable.Incomparable approaches and assumption in economic analysis prevent comparability of results beyond the certain publication. Even though there are good examples for economic analysis, such as for Parigi et al. (2019), Dahiru et al. (2022) state in their review on techno-economic analysis of powerto-X production: "[…] there is not yet any globally accepted method for TEA due to lack of consistency and comparability between different studies." For instance, Adnan and Kibria (2020) do not report hydrogen costs, annual operating time, or base year for the synthetic methanol production. Schemme et al. (2020) perform an analysis with a consistent system boundary and the same assumption for internal comparability. However, e.g. the data for the CO2 costs and the amount of energy required to extract the CO2 have been taken from different sources and thus are inherently inconsistent. Furthermore, the factors underlying the techno-economic analysis (TEA), e.g. Lang factors, are missing. Peters et al. (2019) give no information on plant operating time and capital costs.Even in ecological analysis, data are often neither collected uniformly nor based on the same assumption: In a meta-study of various publications on the life cycle assessment (LCA) of synthetic fuels, Kigle et. al. stated: "Despite the large number of publications and normalized LCA standards, comparison of results between different fuels across different studies proves difficult" (translated) (Kigle et al., 2019 p. 7). The greenhouse gas (GHG) emissions for methane fuel, for example, range from just under 200 g CO2-equivalent km -1 (CO2-eq. km -1 ) for Wettstein (2018) to 650 g CO2-eq. km -1 for Reiter and Lindorfer (2015). A significant influencing factor is the GHG intensity of the electricity supply and the associated share in the synthetic fuels. Wettstein (2018) consider a photovoltaic (PV)plant as the power source, Reiter and Lindorfer (2015) assume the electricity mix. The choice of the system boundary, to which functional unit the results refer, also influences the comparability of the results, as well as to which process possible captured CO2 is attributed (Kigle et al., 2019). The publication of the methodology guideline for LCA of e-fuels was already a step further (Pichlmaier et al., 2021). Also, the work of Müller et al. (2020) gives a good overview over LCA-guidelines. But still, an LCA can be done following the standards but still not be comparable, if basic assumptions are not defined identical and the methodology is not set.In order to address the non-comparability, a comprehensive summary of necessary criteria for TEA and LCA was presented by Langhorst et al. (2022). They require, that "the target audience for the study shall be stated". Which seems to imply different qualities of scientific work for different audiences. This should not be done. Due to their focus on using the definitions of LCA for TEA, the definitions for economic analysis are sometimes not sufficient. For instance, in order to define the products, they require to state the intended application. This is not necessary for the calculation of costs and environmental impacts of the production. Even if they wanted the application of the product to define its quality, they do not define to which extend the application should be stated. So, if, for instance, methanol as fuel for cars would be the application, it could be used in an internal combustion engine or in a methanol fuel-cell. Between both cases, the water content can differ a lot. Similarly, they state, that the functional unit of the product should be defined. Here also, the quality of that definition is not stated. So, if, for instance, the functional unit would be 1 kg synthetic natural gas for heating, the composition or the lower heating values are still not defined. Natural gas has a lower heating value of 8.9 or 12.5 kWh/kg in Europe, and about 13.1 kWh/kg in the USA (Fluessiggas1, 2023) (The Engineering Tool Box, 2024). So, even if the functional unit is defined, the results are not comparable, if a standard is not defined. Better is a definition by composition (pressure and temperature) of the product. Also, they did not mention the net production costs (NPC) as economic result. They instead only focus on "profitability," which highly relies on unknown future market conditions. No one knows how future taxes will look like, whether the demand for one product will be higher than for another. Currently, there is no market for renewable fuels. Furthermore, they did not define the methodology of cost calculation. So, if several analysis are carried out based on their guidelines, different methodologies of cost calculation can be selected. These methodologies can differ a lot, for instance in surcharge factors. So, if the calculation methodology is not defined, the results are not comparable. Also, they allow for different qualities of input data, as well as analysis. Analysis, based on different standards, are not comparable.The same applies for Michailos et al. (2018) andZimmermann et al. (2020), since they are based on Langhorst et al. (2022).In order to be able to perform a TEA and LCA of renewable fuels, the balance limit, assumptions and assessment methodologies needed to be standardized and equal. In this work, we give a defined methodology of TEA and LCA, which is defined enough to allow for comparable results but flexible enough to asses several different production paths and scenarios. It aims to facilitate comparability between various research on PtX production in a fair and unbiased manner. In Table 1, a set of all necessary assumption for one methodology of the TEA and of the LCA is presented with example values for a German production in 2018. Forecasted values for the years 2030 and 2045 are included as well. The methodology can be applied to any other location, plant size, operating hours and manufacturing process with the adjustment of a few input parameters (see Table 1 and chapter 4.5) and is therefore generally valid not only for e-fuels but also for PtX-processes worldwide (see also Garche (2024)).For explanatory cause, an over-simplified example process is presented at the end of this publication.A realistic analysis of the given process using the here presented methodology can be found in Rahmat et al. (2023).Even though the energy transition includes production, logistics, retrofitting, acceptance, utilization, etc. only the production is considered here. Other aspects are planned to be published by the project BEniVer The following chapter describes the methodology which can be used for the standardized technical, economic and ecological analysis of PtX-products. In Figure 2 general production path of PtX-products is shown with easy comparable balance limits. The process starts with the supply of H2, which is usually produced with the aid of electricity. Since electricity usually constitutes the highest share of NPC, a valid base for the electricity price is crucial. In chapter 3.2 the cost data and the environmental impact of the electricity are listed. For more details see SI chapter 3. H2 is a PtX-product. To improve storage capability and/or to enable desired applications, another reaction partner can be added to the hydrogen in a synthesis process. These could be for instance CO2 or N2, which have to be purified beforehand. After the synthesis, a purification might be necessary. Within a PtX-plant heat, electrical power and material should be integrated for better efficiency. Depending on the location of a PtX-plant, it might even be possible to use waste heat locally, e.g. for district heating.There are two preferable balance limits: Ether electrolysis and CO2/N2-purification are within, then the PtX-route can be compared. If the focus of comparison is the synthesis processes itself, CO2/N2 and H2 can be viewed as educts leaving their production and purification outside the balance limit. In order to compare this approach, the cost and environmental impacts of respective streams have to be set equal. For the case of H2 and CO2 see 3.3 and 3.4.To analyze a PtX-process techno-economically and techno-ecologically, a procedure can be carried out as presented schematically in Figure 3. In the first step, the technical basis of the process is defined so that a detailed process simulation can be set up. Whenever possible, this step should be accompanied by industry partner participation, since they have detailed knowledge of the process. Further information can be collected by literature research. In the second step, a detailed process simulation is created in order to identify existing dependencies in the production process and to be able to estimate the minimum equipment requirement. The validation of the simulation is optimally done together with industrial partners. In the third step, the calculation of the cost data and environmental impact is carried out as well as the analysis of technical key performance indicators (TKPI). This step is executed on the basis of the technical analysis, literature data, databases and generally accepted calculation methods. In the fourth step key parameters are analyzed and in the fifth step results can be communicated back to project partners in order to optimize the process further, if possible. A validated process model is the basis for every further analysis not only for PtX-processes. Experimentally derived performance maps of reactors and other equipment should be included in a rigorous process flow diagram (PFD) simulation. Commercial software packages like Aspen Plus ® provide chemical component properties and thermodynamic methods to calculate their interactions.The user has to assemble and interlink all required units, define the operating points and set specifications to achieve an overall system performance at the end. For transparency and reproducibility, it is viable to share all necessary data. A good example is to be found in Parigi et al. (2019).In the technical analysis of a PtX-process, the necessary equipment and their sizes, pressures, temperatures, flow rates, efficiencies, exchange rates, energy losses, kinetic models, catalysator degradation and achievable temperatures have to be set. Some of which might also be technical results which have to be shared transparently. All simplifications should be communicated as well as all assumptions. For comparison of technical results TKPI are used. For a carbon based PtX-process the energetic efficiency ηe and carbon efficiencies YC (and ZC) should be calculated as described in the next equations.Energetic efficiency, ηe, of the fuel production process is calculated as:□□ □□ = ∑ □□ ̇□□□□□□□□ •□□□□□□ □□□□□□□□ ∑ □□ ̇□□□□□□□□□□ •□□□□□□ □□□□□□□□□□ +□□ □□□□ (1)Here □□̇□□ □□□□□□ is the mass flow of the product and LHVProd the lower heating value of the product. They are divided by the mass flows of the educts □□̇□□ □□□□□□□□ multiplied with their lower heating values, LHVEduc, and the sum of electrical power inputs □□ □□□□ . In case of the electrolysis being inside the balance limit (as in Figure 4), □□̇□□ □□□□□□□□ equals zero and the efficiency is called the "power to fuel" efficiency ηPtF as in equation ( 2). This efficiency is useful in comparing different PtX-processes concerning the use of "precious" electricity.□□ □□□□□□ = ∑ □□ ̇□□□□□□□□ •□□□□□□ □□□□□□□□ ∑ □□ □□□□(2)Since there are various electrolysis systems with system-specific efficiencies, using ηPtF for comparison can be misleading, if PtX-processes use different electrolysis systems. By excluding the electrolysis from the efficiency, the rest of the PtX-process can be compared. Also, if hydrogen would be supplied from another source, other than an electrolyzer, this balance limit could be used. In a minimal-example in chapter 4, the corresponding balance limit is depicted in Figure 4. In this case, the efficiency is called "hydrogen to fuel efficiency" □□ H□□□□ , see equation ( 3).□□ □□□□□□ = ∑ □□ ̇□□□□□□□□ •□□□□□□ □□□□□□□□ □□ ̇□□□□ •□□□□□□ □□ □□(3)The carbon yield, YC, is given by:□□ □□ = ∑ □□̇□□ □□ ∑ □□̇□□ □□ (4)Here is □□̇□□ □□ is the carbon mole flow in the products, excluding waste and □□Ċ □□ is the carbon mole flow in the educt. If there is a reaction with several products, e.g. Fischer-Tropsch-path, the carbon efficiency to each product, ZC, can be calculated using the following equation.□□ □□ = □□̇□□ □□ ∑ □□̇□□ □□(5)Here is □□̇□□ □□ the carbon mole flow of the target product.Heat integration potentials are further determined in the technical analysis. This is crucial in order to achieve high efficiencies. A widely used method is the PINCH-analysis as explained in Linnhoff and Lenz (1987).The underlying heat transfer coefficients of the heat exchangers are listed in section 2.2 of the supporting information (SI), as well as other technical parameters. Depending on the localization of a PtX-plant, it could be possible to sell heat via steam. For this case, assumed pressure levels for a German plant are listed in the SI section 1.4. Only if balance limit and other technical assumptions are disclosed completely, technical results, such as energetic efficiencies and carbon yields, can be compared. Chemical engineering cost estimation is a well-known procedure for standard large-scale chemical plants (Peters et al., 2004). In PtX-processes it is often applied to small-scale decentralized plants because of high costs and low availability of renewable power and electrolyzer. That is only partially correct as the error bar of that estimation increases largely toward small scale demo units and results are harder to compare. The main results of the economic analysis are: capital expenditures (CAPEX), operating expenses (OPEX) and net production costs (NPC).Depending on the available information, an economic analysis can be performed according to different levels of detail and thus estimation accuracy. Using the factor method and parameter models presented here, the estimation accuracy of a feasibility study, can be achieved (Christensen et al., 2005). For higher estimation classes, more extensive, cost-intensive, site-specific, non-generalizable and significantly longer planning efforts would need to be carried out. However, since "semi-detailed costs" are used for major components, an estimation accuracy of CAPEX between 3 and 4 can be achieved, about ± 30 % (Christensen et al., 2005). For more detailed information on the accuracy of cost estimations, see Adelung (2022).From the process parameters determined in the technical analysis, the CAPEX and OPEX are calculated. The CAPEX is reflected in the annual capital costs (ACC). In order to calculate the ACC, individual equipment items (pumps, heat exchangers, etc.) need to be calculated using the equipment cost (ECi) function ( 6) for the respective years with the given physical characteristics (Albrecht et al., 2017).□□□□ □□ = □□ □□ (□□ □□,□□ ; □□ □□,□□ ; … □□ □□,□□ ) ⋅ ( □□□□□□□□□□ □□□□□□□□□□ □□□□□□ ) ⋅ □□ □□□□□□,□□ ⋅ □□ □□□□□□,□□ □□, □□, □□ ∈ ℕ (6)Here □□ □□ (S i,1 ; S i,2 ; … S i,k ) is the cost function of the individual pieces of equipment with defining properties. □□ □□,□□ are the respective input variables, such as pressure, temperature, throughput, etc. The inflation adjustment can be determined in equation using the chemical engineering plant cost index (CEPCI), where the current CEPCI is divided by the CEPCIref at the reference year. Pressure and material factors Fpre,i and Fmat,i are used to adjust the previously calculated results to certain pressure levels or materials used. For further information, see SI chapter 1. Knowing the individual ECi, fixed capital investment (FCI) needs to be determined using equation (7).□□□□□□ = ∑ □□□□ □□ ⋅ (□□ + ∑ □□ □□□□□□,□□,□□ □□□□ □□=□□ ) ⋅ □□ □□=□□ (□□ + ∑ □□ □□□□□□,□□,□□ □□□□ □□=□□□□ ) □□, □□ ∈ ℕ(7)A proposal of standard empirical factors F ind,i,j are to be found in the SI in Table S1. To calculate the total capital investment (TCI),equation ( 8) is used.□□□□□□ = □□□□□□ □□-□□□□□□□□□□□□□□ □□□□□□□□□□□□□□ (8)With the given values and the interest rate (IR), the annual capital cost (ACC) can be calculated according to equation (9). € □□ ] = □□□□□□ ⋅ □□□□ ( (□□+□□□□) □□ (□□+□□□□) □□ -□□ + □□ □□-□□ -□□) (9)Here, y is the plant operation time in years and IR is the interest rate. For further information on production costs and cash flows during construction see also Giglio et al. (2015). A subsequent sensitivity analysis allows the influence of different process parameters and input data on production costs to be investigated.With the plant operating time and the annual production quantities, the net production costs (NPC) can then be calculated according to equation (10).□□□□□□ [ € □□□□ ] = □□□□□□+ ∑ □□□□□□□□ □□□□□□ +∑ □□□□□□□□ □□□□□□ +□□ □□□□□□□□□□ □□ □□□□□□□□□□ □□ ̇□□□□□□□□ (10)Where tlabor is the sum of man-hours and clabor is the mean hourly labor costs. The product □□ □□□□□□□□□□ □□ □□□□□□□□□□ is referred to as operating labor (OL)). In order to normalize the costs of the product several bases can be used: volume-, energy-or mass-flow of the product amongst others. The following reference quantities are proposed: €year/L, €year/MJLHV or €year /kg. To account for inflation, the year should always be specified. Furthermore, it is important to state the concentration of the target product within the presentation of the results or in the assumptions. For a sustainable PtX-production an economic analysis or LCA should be done to get information on the environmental impacts. It should be carried out standardized according to DIN ISO 14040 (DIN, 2020) and 14044 (DIN, 2018). The following scope of the calculations is proposed:• System boundary: The LCA is done for the most relevant input flows for the PtX-process. For the supply of electricity, hydrogen and CO2 the environmental impacts from cradle-to-gate of the technologies and materials are considered. This means, that the resource and energy supply as well as the emissions associated with the construction of the plants are included. • Functional unit: Depending on the technology, following functional units are proposed: 1 kWh electricity, 1 kg hydrogen or 1 t CO2. For the PtX-process a functional unit can be defined by the LCA practitioner. In our exemplary calculation in section 4, all emissions refer to the flow of the produced methanol in one hour. • Data: The data used for the LCA is based on the results of the calculation of the electricity.Example data for a German production are based on the German electricity grid mix and the subsequent technological assessment of the hydrogen and carbon dioxide supply. Data for the production of the plants can be either be derived from technical analysis or from literature or a given production plant. The sources are documented in the chapters of each technology respectively. Besides this foreground-data some data is form secondary databases. The socalled background data includes the supply chain e. g. of material supply. In this work, this is done using the database ecoinvent ® 3.6 (Wernet et al., 2016). • Allocation: In the production of PtX co-products can occur. The environmental impacts have to be allocated to all products. Therefore, an energetic allocation is proposed. • Impact category: For the life cycle impact assessment only one impact category, "climate change", is chosen, since the reduction of greenhouse gas emissions is the main motivation of the energy transition. To obtain the CO2-equivalent of all greenhouse gases the characterization factors from Intergovernmental Panel on Climate Change (2014) for global warming potential over a integration period of 100 years are used.More and detailed information on the here used methodology and data for LCAs for PtX-products can be found in the methodology guide for LCAs for e-fuels (Pichlmaier et al., 2021). For comparable results, balance limits and other assumption have to be identical. The here presented assumption are partly standard approaches, partly assumption, which have been proven valuable in projects with several project partners (e.g. BEniVer). Set example values, like year, size, interest rate and lifetime, are exchangeable. It is important for comparison, that they are defined equally for all analyzed processes. For assessment of PtX-processes, a list of necessary assumptions is presented in Table 1 in column one.If not all of these information are given in an assessment, there is no comparability. The second column includes example values, which have been set within BEniVer. These could be used for comparison to results of the BEniVer-project. In the third column, explanations and further information (sources) are given. An example of how to use the methodology and assumptions, a simplified example in included in chapter 4. A comprehensive study using the here presented methodology and the example values as well as additional input values has been done by Rahmat et al. (2023). To account for changes due to technological progress, the following approach is proposed: The plant is designed for a total nominal capacity of 3 MWel or 300 MWel in 2018. In the further years, the plant is operated with the same material flows, but other efficiencies are assumed so that the input power decreases while the product flow remains the same. This approach allows simulations to be easily adapted to other years. Electricity represents the most important energetic input to a PtX-process. Depending on the electricity source, electricity costs, availability and environmental impact have to be considered. Detailed explanation and presentation of the underlying data can be found in the SI in chapter 3.Levelized cost of electricity (LCOE ) is calculated according to equation ( 11), (IRENA, 2020):□□□□□□□□ = ∑ □□ □□ +□□ □□ +□□ □□ (□□+□□) □□ □□ □□=□□ ∑ □□ □□ (□□+□□) □□ □□ □□=□□ (11)Here, lt is the CAPEX of the power plant in year t, Mt the operating and maintenance costs in year t, Ft the fuel-expenses in the year t and Et the full-load hours in year t. r represents the imputed interest rate, n the depreciation period or the life of the system. With the assumption defined in the SI Table S11 and the minimum and maximum rates for taxes and levies the following possible retail prices for grid electricity have been calculated: At the moment, the German grid mix is not 100 % renewable, therefore PtX-products based on that are not "green" per se. For more in-depth information and data for 100 % renewable sources see the SI section 3. GHG emissions from electricity production are determined using LCA, including the upstream chain of energy sources (e.g. coal) as well as plant construction (e.g. coal power plant, wind turbine) and disposal. Based on the composition of the respective electricity mix and year, the share of each technology is calculated with the appropriate emission factor from the LCA database ecoinvent ® (Wernet et al., 2016). The exact allocation is explained in 3.5 of the SI. For the renewable technologies, the emission factors from ecoinvent ® are also used. In case of electrolysis being outside the balance limit, example cost and environmental impact data for a German production are presented below. Considered electrolysis technologies are: Alkaline electrolysis (AEL), proton exchange membrane electrolysis (PEM) and high temperature solid oxide electrolyzer cell (SOEC). The AEL and PEM electrolysis processes can produce pure oxygen, which can potentially be sold. In this work, it is proposed that this is feasible at a scale of about 300 MWel and thus the revenue is deducted from the H2 costs. Based on the technical and economic parameters of the electrolysis as well as the electricity costs from chapter 3.2 an individual TEA has been calculated for each electrolysis according to the methodology from chapter 2.2. The economic values include capital expenditures for the entire system, the stack's share of capital expenditures and specific maintenance costs. The individual results of the respective types of electrolysis are listed in the SI section 4. Individual LCA for each process has been carried out as well using the methodology of chapter 2.3.For the GHG emissions, energy and material flows from the technical analysis and the plant construction are considered. The material input of plant construction is based on the following studies: AEL (Liebich et al., 2020), PEM (Bareiß, 2019) and SOEC (Wulf and Kaltschmitt, 2018). Considering the stack and plant lifetime, the plant construction is normalized to kg of hydrogen produced. Furthermore, the purchased electrical energy, water consumption and consumption of other operating materials, such as potassium hydroxide, are considered for the operating phase. The energy and material flows in the operating phase were linked to data sets from the ecoinvent ® database and calculated using LCA software.For a generalized German hydrogen production, it is yet unknown, which technology will take up which market share, since each technology has its advantages and disadvantages. Therefore, generic values have been defined and proposed which assume that AEL, PEM and SOEC take up one third each. In Table 4 the costs for a large-scale generic production of hydrogen at the specified transfer pressure of 50 bar and a temperature of 50 °C as well as the energetic and ecologic values are given.The anion exchange membrane (AEM) electrolysis is not considered here, since the technology was only available at the beginning of EiV in "single-digit kW range" (Sunfire GmbH, 2023). Calculating equivalent results can be done in the same manner as described for the other electrolysis technologies. kgCO₂-eq. kgH₂ -1 24.8 6.1 2.3 *Rounding to two decimals should not be understood as an indication of accuracy. a) Full-load hours. b) For 8,000 FLH electricity, German grid mix. c) For 8,000 FLH electricity, German grid mix. d) AEL, PEM SOEC each 1/3 Carbon dioxide Considered CO2-sources are direct air capture (DAC), and the extraction from point sources. The compositions of point sources are listed in Table S24 in the SI. Within BEniVer, the following CO2 sources were assumed to exist until 2045: cement plant, combined gas and steam plant (GS), waste-toenergy plant (MVA). Based on the technical and economic parameters of the DAC and the process simulations of an ethanolamine (MEA)-scrubber, an individual TEA is performed for each CO₂ supply option. The results are presented in the SI section 5. In order to make different approaches more comparable, "generic CO₂" is proposed in addition to data for specific CO2 sources. Lacking informed data, educated guesses of the contribution of CO2-sources to the average German CO2 mix are shown in Table 5Table . 15 % 20 % 25 % MEA -MVA 15 % 15 % 20 % a) gas and steam power plant (GS).In Table 6, the resulting costs for a large-scale generic supply of carbon dioxide at transfer conditions of 3 bar and 35 °C, as well as the energy and environmental impacts are presented.The ecological impact considers the energy and material flows determined in the TEA, such as raw materials and auxiliaries and the plant construction. Material data from the following sources are used for the ecological balance of plant construction DAC: (Lozanovski, 2019). For the selection of the background processes from ecoinvent ® , the process designations from the appendix of (Liebich et al., 2020). For flue gas scrubbing with MEA (Liebich et al., 2020) was used. Considering the plant lifetime, the plant construction was related to one ton of CO2. In the operation phase, the purchased electrical energy, water consumption and consumption of other operating materials, such as cooling water and MEA, were considered.Captured CO2 enters the life cycle assessment as negative emissions. Captured CO2 can be attributed ether to the supply side, if it is capture from air, or to process related emissions, or to the fuel itself (Ausfelder and Dura, 2018). Since this has not yet been decided in regulations, the results are shown in Table S29 in the SI. The resulting values are depicted in Table 6 in case it is allocated to energy and material flows. t CO 2-eq. tCO2 -1 0.07 0.03 0.02 GHG emissions (incl. CO2 capture) a) t CO 2 -eq. tCO2 -1 -0.93 -0.97 -0.98 *Rounding to two decimals should not be understood as an indication of accuracy. a) For 8,000 FLH electricity, German grid mix. b) For 4,000 FLH electricity, German grid mix. To illustrate the application of the methodology and the proposed assumptions, a simplified and idealized example of a methanol synthesis is presented. Here, the application of the presented methodology can be seen. Furthermore, the presented cost data (H2, CO2 and electricity) for a German production are integrated so that their use can be understood as well. In contrast to realistic plants, no recycle-streams are included, no catalyst is considered as well as no reaction kinetics. All these effects are neglected, knowing that the result will be idealized. However, for a basic understanding of the methodology the example is sufficient. For deeper insight in to the methanol synthesis see for example Rahmat et al. (2023). For the stoichiometric direct conversion of CO2 and H2 to methanol, the chemical sum equation is defined as follows:□□□□ □□ + □□□□ □□ ⇌ □□□□ □□ □□□□ + □□ □□ □□ ΔR H° (300 K) = -49.6 kJ mol -1 (12)For simplicity, not the chemical equilibrium is considered, but a theoretical 100 % yield in an artificial super reactor. CO2 and H2 with min costs for 8,000 FLH (see Table 4 andTable 6) are mixed stoichiometrically and compressed to 40 bar by a compressor. Then, the reaction with an assumed 100 % conversion rate takes place with no by-products but water. In the next step, a 100 % separation of water and methanol is assumed. It is known to the authors that the separation of the product in reality would take place in a two-to three-stage rectification where product losses occur. Here, for simplification, no energy or material losses are assumed, nor are costs and revenues for heat, water, by-products and waste. In order to present the methodology for calculating equipment cost, the cost calculation of one compressor is shown in Table . All other equipment costs for synthesis or purification are calculated similarly for a valid process model but are not necessary for the presentation of the methodology here and are therefore assumed to be zero.Furthermore, the following values where assumed:Table 7. Assumption of the over-simplified example process (values not mentioned: set as in Table 1). Resulting from overall power demand CO2 mass-flow 42.72 t h -1 Stoichiometry If one of these values is missing or if main input values are defined differently, a comparable analysis cannot be achieved: For instance, if the hydrogen source is defined differently it will have influence on the technology (depending on the quality of H2), on the costs, as well as on the GWP. Different target purity of methanol has a huge influence on the technology as well as on energy demand. Here, an over-simplified has been selected. In reality, several distillation columns would be needed. With equation ( 2), the values given in Table 7 and the simulation, the energy efficiency ηPtF is 57 %. □□□□,□□□□□□ □□□□ □□ -□□ ⋅ □□.□□ □□□□□□ □□□□ -□□ □□□□□□,□□□□□□ □□□□ (□□□□□□□□□□□□□□□□□□□□□□□□) + □□,□□□□□□ □□□□ (□□□□ □□ □□□□□□□□□□□□□□□□□□□□□□□□ )+□□,□□□□□□□□□□ (□□□□□□□□□□□□□□□□□□□□□□) = □□□□ % (2)In the literature ηPtF efficiencies range from 40 % (Adnan and Kibria, 2020) up to 56 % (Andersson et al., 2014). With a generic hydrogen source for 2018, 66.8 % of the electrical energy is transferred into the LHV of hydrogen. Other losses occur in the CO2 purification, due to compression and due to the exothermic reaction, as also indicated in Figure 4. Excluding the electrolysis process, the here calculated hydrogen to fuel efficiency as in equation ( 3) is 88 %, which is in the range of literature data which is between 82 % (Rahmat et al., 2023) and 88 % (Schemme et al., 2020).□□ □□□□□□ = □□□□,□□□□□□ □□□□ □□ -□□ ⋅ □□.□□ □□□□□□ □□□□ -□□ □□,□□□□□□□□□□ □□ □□ □□ -□□ •□□□□.□□ □□□□ □□ □□□□ -□□ = □□□□ %(3)Since, no heat and no electricity are included in the equation mostly the product losses are indicated in this efficiency. For full conversion, the carbon yields, as described in equations (4-5) are equal to 100 %, since no purge is included, thus no carbon loss occurs.□□ □□ = □□.□□□□ □□□□□□□□ □□□□□□□□□□□□□□□□ □□ -□□ □□ .□□□□ □□□□□□□□ □□□□ □□ □□ -□□ = 100 %(4)In a real process, by-products would form. Unreacted educts would also have to be recycled. To prevent inert gases from accumulating in a recycle, a purge stream had to be included. Both effects result in a lower carbon efficiency as 73 % in (Schemme et al., 2020) and up to 96 % in (Rahmat et al., 2023). For equation ( 6) the following information are needed as listed in Table . Table 8. Example process compressor ECi. (Peters et al., 2004). With the resulting ECi, and the factors given in the SI in Table S1, the FCI can be calculated as shown in Table 9. (Peters et al., 2004) Given the flows over the balance limit, Table 7, and the exemplary cost data for a German production in 2018, the OPEXdir results in the values of Table 10. The calculated NPC could be compared to other production processes which are using the same input parameters and methodology.Additionally, calculations of net present values could be carried out. These however, have the disadvantages of adding high uncertainties, since future market prices of the products are not known.An overview of the flows and resulting costs is depicted in Figure 4. These results are only for illustrative purpose. What can be seen is, that each of the costs for the input flows have to be set uniformly as well as the calculation methodology, in order to make other process analysis comparable. A TEA of a Power-to-Methanol based on rigorous process simulation and two reaction kinetic approaches done with BEniVer assumptions by Rahmat et al. (2023) results in slightly higher NPC between 1.13 € kg -1 and 1.48 € kg -1 . The TEA is independent of the target audience and the intended application (see comments on Langhorst et al. (2022) in the introduction). For a comprehensive LCA, each material used for construction or within the process, has to be assessed. Since a lifetime of 20 years, no by-products, no catalyst etc. are assumed and only one compressor is considered, its influence on the environmental impact on the production in neglectable for the minimal example. Therefore, a simplified LCA is conducted. Since a separate LCA for H2, CO2 and electricity has already been done for a German production, mass and energy flows from the technical analysis of the example process are used and connected with their CO2-eq. footprint as shown in Figure 5. The underlying relative CO2-eq. footprints for the streams are already presented in Table 3, Table 4, Table 6 and the SI in Table S23 and Table S29. Resulting total GHG emissions are calculated to deliver the functional unit, in this case the mass flow of 31.1 t h -1 . The main influence on the overall GHG-emissions is to be seen in the H2 production. Since German grid electricity in 2018 is selected, it has a high share of non-renewable energy, which is reflected in the high CO2-eq. allocated to the H2. The share of renewable energy is expected to rise in the future, see Table S13 of the SI. 100 % renewable electricity for a German production facility currently comes with the drawback of reduced full-load hours which would have to be assessed more in detail including storages. For more information see (Raab et al., 2022, Ibáñez-Rioja et al., 2023). The here assumed negative CO2-eq. of the 2018 generic German CO2-source can be achieved, if it is allocated to the fuel. Currently, the regulations do not define where the CO2 has to be allocated to. The here presented exemplary result excluded materials such as steel, catalysts, concrete etc. in the LCA. These would increase the environmental impacts. Unless all material an energy streams are produced carbon neutral, the product will always have a GWP greater than zero but might be lower than for fossil products. Additionally, transportation of the final product would have to be assessed as well. A comparison of how close the simplified example is to more realistic processes is difficult, since the main assumptions (CO2 and H2-source, etc.) are selected differently. Further impact categories might even be higher. For further information on LCA of PtX-production as well as other impact categories, see Pichlmaier et al. (2021), Weyand et al. (2023).The LCA is independent of the target audience and the intended application (see comments on Langhorst et al. (2022) in the introduction) but highly on the setting of input parameters and the calculation methodology. The analysis can be adapted to other conditions as country, prices etc., by changing the input parameters, required in Table 1. For a first analysis, sensitivity study can be carried out as shown in Figure 6 for the example process for ±80 % of variance. Figure 6. Sensitivity study NPC for the example process.Here you can see, that the products output has the highest influence on the NPC. So, if the plant runs with less FLH, the cost of the product would increase. But still, this might be necessary, if fluctuating renewable energy has to be used. However, the electricity price for renewable energy and therefor the H2-price could be lower as well. For other countries, the H2-or CO2-sources could vary, as well as labor costs and interest rates. For a thorough analysis, all these parameters would be changed and an analysis carried out, but the sensitivity study gives first insights of the magnitude of influence on the result. Equal analysis could be carried out for the LCA.For comparing other products or production processes, another synthesis would have to be defined, which is state of the art. All economic and ecologic input values, like year, H2-source lifetime, etc. would have to be set equally. The subsequent analysis would follow the same steps as defined in this work.If "greenfield" is selected instead of "brownfield," additional information would be needed. These include: preparation of the land, foundations, road, sewage treatment, electricity connection, steam generation, safety equipment, car parks, ecological compensation areas, additional storages, fees and taxes. For all of these data, costs had to be defined and to be included into CAPEX-and OPEXcalculations, see also Peters et al. (2004). This publication addresses the problem of non-comparable analysis results of PtX-production pathway in the current literature, by sharing a compact list of minimal required data, which are needed for a TEA and LCA (see Table 1). Its completeness and consistency provide the basis for standardized assessment. This represents a significant improvement on the current status of assessment comparability, as stressed out in the introduction. For instance, in contrast to Langhorst et al. (2022) a definition of how the product is defined is included, as well as a definition of the calculation methodology and additional uncertainties are reduced by calculating the NPC instead of the net present value. A methodology for TEA and basic information for an LCA concerning the GWP was presented, based on DIN ISO 14040 (DIN, 2020) and 14044 (DIN, 2018). Furthermore, an easy-to-handle set of data and assumption, used in the EiV-project (BMWK, 2017), was shared. It represents a defined setpoint from which all processes can be compared, if intended. If an analysis is carried out at another setpoint, the values for this new setpoint would have to be presented completely. Table 1 helps to not forget a value. With the new setpoint new comparable analysis could be carried out.Within the presented data set, estimated forecasts are presented. These have been calculated carefully, but technology and cost estimations for 2030 and 2045 are subject to great uncertainty. Current crises highlight the volatility of energy prices and commodity markets. Nevertheless, processes can be compared based on identical assumption and its potential contribution to the climate change, mitigation efforts in the transport sector locally or worldwide, can be quantified. Finally, a minimized example, has been presented for explanatory purpose, knowing that the result is an over-simplification.As impact category example of the LCA, the GWP was selected, as this is the main target parameter for decarbonizing the transport sector. A standardized assumption of the GWP for electricity, H2 and CO2 also enables better comparability. The analysis of further impact categories is necessary for real pathway assessment. Unfortunately, not all underlying data of the LCA could be shared, due to the terms of use of the ecoinvent ® database.Adjustments, such as plant dimensions, synergies through suitable site selection, influences of individual process stages on the overall result and other basic assumption can be addressed via sensitivity studies using the methodology presented, see chapter 4.5. This work presents a step towards a comprehensive comparison of all options for de-fossilization of transport sector in Germany. However, this still requires an evaluation of the use and other aspects such as logistics, further environmental impacts categories, infrastructure, taxation or subsidies, the application in the means of transport and regulatory framework conditions.In order to reach climate goals, multi-megawatt scale plants are required to produce alternative fuels if current demand remains. But neither renewable electricity volumes nor electrolyzer capacity are currently available at a refinery scale, so plants were considered at the scale of available demonstration plants and first commercial scale.6 Appendix The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The project was funded by the BMWK under grant number 03EIV116A.