Contrail-aware flight trajectory trade-offs and constraints: data-driven optimization in the United Kingdom airspace

The climate impact of aviation extends beyond carbon emissions, with contrail formation contributing significantly to radiative forcing. This study explores the application of computational trajectory optimization to enable contrail-aware flight routing within United Kingdom airspace. We develop a datadriven framework that integrates aircraft performance models with meteorological forecasts to identify flight paths that reduce contrail formation likelihood. Using a trajectory optimization algorithm, we analyze a dataset of real flights on a high-risk contrail day to evaluate the trade-offs between fuel consumption and contrail mitigation. The results shows that contrail avoidance can be achieved through algorithmic trajectory adjustments that is constrained by atmospheric uncertainties, computational complexity, and airspace management. Our study highlights the role of computational methods in greener air traffic management, emphasizing real-time data and scalable optimization.