F4EClim aimed to characterize the sources of uncertainties of non-CO2 climate effects estimates and their mathematical description, and the development of extended algorithmic Climate Change Functions (aCCFs). F4EClim project delivered a prototype of a probabilistic surrogate model describing the climate impact of NOx emissions via O3 perturbations for the extended NOx-O3 aCCFs. This version enables the estimation of the Average Temperature Response over 20 years associated with this non-CO2 effect of aviation, while providing uncertainty ranges. The modelling chain for the computation of new Climate Change Functions (CCFs) for NOx-induced O3 effects was defined. The radiative forcing caused by local NOx emissions will be simulated using a Lagrangian approach with the ECHAM/MESSy Atmospheric Chemistry Model (EMAC). This will enable the inclusion of a wider range of atmospheric situations in the development of the extended NOx-O3 aCCFs during the next phase of the project.
Furthermore, the project also aimed to enhance in-house flight planning tools (ROC, ROOST, pyTOM) and to perform large-scale trajectory optimization analyses to quantify mitigation potential and associated trade-offs. ROC has achieved major computational improvements, now enhancing efficiency by removing ensemble wind modeling and focusing on meteorological uncertainty in non-CO2 effects, particularly contrails, thereby accelerating function evaluations and improving convergence. ROOST has been extended to include free-routing capabilities within a unified framework for both structured and free airspace, enabling fair comparisons and more robust assessments of route network inefficiencies; the 2D version is complete, with the 3D version expected by the end of 2025. PyTOM, a scalable Python framework based on Dymos+OpenMDAO, enhances convergence via a discrete pre-optimization step and employs a modular cost structure supporting multiple objectives, including time, fuel, operating cost, climate impact, and convective avoidance.
In this reporting period, we focused on designing the final Hindcast analysis, which includes defining a flight scenario based on European air traffic and deriving three representative data sets of varying size and traffic volume, while ensuring broad variability in flight characteristics such as lateral extent and distance. The study for hindcast and similarity analysis identified sensitivity parameters, emphasizing changes in meteorological and operational boundary conditions, and established suitable trajectory distance metrics. The integrated Trajectory Calculation Module (iTCM) was prepared to perform reverse trajectory calculations, with the method demonstrated on exemplary trajectories. In parallel, the F4EClim aviation and climate impact service, representing the project’s final solution, is under active development, with functionalities being implemented using data from the previous project
