This article presents a dataset generated for a techno-economic assessment (TEA) of the methanol-to-jet (MtJ) fuel production pathway. The dataset was produced using a large-scale Monte Carlo (MC) sampling approach applied to a steady-state process model implemented in Aspen Plus V14. The techno-economic evaluation was conducted using an external cost model, with subsequent data processing performed in Python (Version 3.11). In total, three million individual data points were generated by varying key technical and economic input parameters within predefined ranges and are under public access. For each MC sample, the net production cost on a mass basis (NPC_m, EUR kg_jet-fuel⁻¹) of synthetic jet fuel was calculated as the primary economic performance indicator. The dataset comprises both the sampled input parameters and the corresponding techno-economic output variables and is intended to support transparency, reproducibility, and further uncertainty analysis of MtJ fuel production pathways.

This article presents a dataset generated for a techno-economic assessment (TEA) of the methanol-to-jet (MtJ) fuel production pathway. The dataset was produced using a large-scale Monte Carlo (MC) sampling approach applied to a steady-state process model implemented in Aspen Plus V14. The techno-economic evaluation was conducted using an external cost model, with subsequent data processing performed in Python. In total, three million individual data points were generated by varying key technical and economic input parameters within predefined ranges and are under public access. For each MC sample, the net production cost on a mass basis (NPC_m, EUR _kgjet-fuel^-1) of synthetic jet fuel was calculated as the primary economic performance indicator. The dataset comprises both the sampled input parameters and the corresponding techno-economic output variables and is intended to support transparency, reproducibility, and further uncertainty analysis of MtJ fuel production pathways.

Sustainable Aviation Fuel (SAF) production from lower alcohols via the Methanol-to-Jet (MtJ) and Ethanol-to-Jet (EtJ) pathway offer a promising route for decarbonizing the aviation sector, yet systematic comparisons across multiple process configurations remain scarce, and detailed kinetic modelling of alternative upgrading strategies such as Guerbet coupling are largely absent from the literature. This work presents an Aspen Plus based Techno-Economic Assessment (TEA) of one MtJ (P1) and two EtJ pathways being conventional EtJ (P2) and Guerbet-coupling-based EtJ (P3). Defined scenarios investigate the influence of oligomerization product distribution, recycle configurations, and off-gas utilization on the Net Production Costs (NPC) and key technical performance indicators, including carbon, PtL and global efficiency, and Specific Energy Consumption (SEC). Results show that the conventional EtJ pathway P2 achieves the lowest production costs (2.5-3.7 EUR kg-1), followed by the Guerbet-based route P3 (3.8-4 EUR kg-1), while MtJ P1 exhibits the highest costs (3.5-5.2 EUR kg-1) despite the lowest SEC. Feedstock costs dominate the overall production costs across all pathways, while the oligomerization section holds large technical potential for improving overall process performance. Both EtJ pathways achieve substantially higher carbon efficiencies (51-56%) than MtJ (38-50%), due to carbon losses to methane, CO and aromatics in the Methanol-to-Olefins (MtO) conversion as well as lower selectivity towards kerosene range hydrocarbons (HC) in the single-stage co-oligomerization step. While the Guerbet-based route shows competitive simulated costs relative to MtJ, the limited experimental database for this pathway introduces considerable uncertainty, highlighting key research needs for future development and process validation.

Heavy-duty road transport remains a challenging sector to decarbonize, as full electrification of long-distance trucking is currently constrained by limitations in energy density and charging infrastructure. Alternative fuels such as hydrogen, biodiesel, and e-fuels are thus gaining increasing attention. In parallel, the cement industry is a major source of unavoidable, process-related CO2 emissions, offering an opportunity to use captured industrial CO2 as a feedstock for e-fuel production. This study evaluates the production of e-methanol and Fischer-Tropsch (FT) diesel from captured CO2 at an Austrian cement plant as a base case. Several system configurations are analyzed, including different electricity supply options across Europe and the use of biogenic versus fossil CO2. An integrated framework combining process simulation, techno-economic analysis, and life-cycle assessment is applied to compare both fuel pathways. Results show that the climate impact of e-fuels is highly dependent on the electricity mix. When non-renewable electricity is used, climate impacts are 100-440% higher than those of fossil diesel. In contrast, a wind-based Austrian scenario achieves the lowest impact, corresponding to a 44-50% reduction compared to fossil diesel. Overall, cement-plant-based power-to-liquid concepts offer limited near- to mid-term mitigation potential under current European energy conditions and deliver climate benefits primarily when based on biogenic CO2, high process efficiencies, and low-carbon electricity. The study further highlights key differences between the fuels, with FT-diesel being a certified drop-in fuel, while e-methanol still requires technical and regulatory validation, underscoring the need for technology-specific and system-level assessments.