This paper develops a system-level techno-economic optimisation framework to assess European aviation transition pathways from 2025 to 2050. The model jointly determines fleet evolution, technology adoption, energy-carrier supply, and infrastructure in a mixed-integer linear programming formulation. A three-objective optimisation over discounted system costs, cumulative well-to-wake CO2 emissions, and upstream clean energy demand is solved using the AUGMECON2 ϵ-constraint method to construct Pareto frontiers, after which a representative compromise is selected via a normalised closest-to-utopia metric. Results show pronounced and asymmetric trade-offs. Cost minimisation yields the lowest expenditures but produces CO2 emissions around six times higher than the emissions-optimal benchmark. Emissions minimisation delivers deep abatement, yet increases both costs and clean energy demand by roughly a factor four due to deployment of capital-intensive and upstream-energy-intensive technologies. Clean-energy minimisation reduces upstream demand but still results in emissions about seven times higher than the emissions-optimal solution. Across scenarios, the relationship between costs and sustainability objectives remains strongly conflicting, while emissions and clean energy demand exhibit a non-monotonic relationship. Closest-to-utopia solutions consistently originate from cost-optimal primary runs, indicating that cost-efficient baselines provide the most flexible starting point for improving emissions and clean energy performance via ϵ-constraints. Sensitivity analysis further shows that emissions outcomes are dominated by well-to-wake assumptions, whereas costs and clean energy demand are mainly driven by market growth and SAF ambition, highlighting clean energy availability as a potential binding constraint. ... Read more