- Project ID FlyATM4E
- Project duration 2020-06-01 > 2022-11-30
- EU Contr.
- Status Ongoing
The main objective of the FlyATM4E project is to expand approved climate-assessment methods and optimization of aircraft trajectories in order to identify promising mitigation options suitable to solve the task of reducing overall climate impact of aircraft operations. The project will assess the feasibility of a concept for environmental assessment of ATM operations working towards environmental optimisation of air traffic operations.
FlyATM4E will develop a concept to identify climate-optimised aircraft trajectories which enable a robust and eco-efficient reduction in aviation’s climate impact. Climate optimization will take into account CO2 and non-CO2 effects, such as contrails and contrail-cirrus, water vapour, NOx and particulate emissions. FlyATM4E will identify those weather situations and aircraft trajectories, which lead to a robust climate impact reduction despite uncertainties in atmospheric science that can be characterised by ensemble probabilistic forecasts. This will improve the assessment of aviation’s climate impact. It will further identify those situations where there is a large potential to reduce the climate impact with only little or even no cost changes (“Cherry-Picking”) and those situations where both, climate impact and costs can be reduced (“Win-Win”).
As a synthesis, FlyATM4E will formulate recommendations how to implement these strategies in meteorological (MET) products and enable not only the understanding of ATM possibilities to reduce aviation’s climate impact, but moreover how to implement such eco-efficient routing. To this end, the FlyATM4E consortium builds on its expertise covering the whole spectrum from atmospheric science and climate research to aviation operations research and aircraft trajectory optimisation
Deutsches Zentrum für Luft- und Raumfahrt e.V. (Coordinator)
Technische Universiteit Delft
Technische Universität Hamburg
Universidad Carlos III de Madrid
This project has received funding from the SESAR Joint Undertaking under the European Union's Horizon 2020 research and innovation programme under grant agreement No 891317