Reducing Environmental Footprint through transformative Multi-scale Aviation Planning

Project Information

REFMAP

Grant agreement ID: 101096698

DOI

10.3030/101096698

Project closed

EC signature date 22 November 2022

Start date 1 February 2023

End date 31 January 2026

Funded under

• Climate, Energy and Mobility

Total cost

€ 4 034 527,00

EU contribution

€ 4 034 527,00

Coordinated by

KUNGLIGA TEKNISKA HOEGSKOLAN
Sweden

Periodic Reporting for period 2 - REFMAP (Reducing Environmental Footprint through transformative Multi-scale Aviation Planning)

Reporting period: 2024-08-01 to 2026-01-31

Summary of the context and overall objectives of the project

REFMAP developed an online analytics platform, built through widespread collaboration with international partners, to optimize both individual flight trajectories at the micro-scale (e.g. unmanned aircraft systems) and overall air traffic at the macro-scale. The research investigated a new aviation business model shaped by environmental data, including weather conditions, local pollution, and wind intensity, alongside emissions from different types of air vehicles, such as CO2 and noise, and their trajectories.
The platform integrates numerical simulations, predictive models, and deep-learning methods to predict optimal trajectories from environmental inputs and to develop a business model aligned with the EU's Green Agenda.

The overall objectives were:
1) Real-time AI for ATM optimization. Robust AI models trained on multi-fidelity flow data to optimize environmental performance in multi-scale air traffic management, including data exchanges with U-space.
2) Sustainable UAS expansion framework. A framework enabling the responsible, sustainable, interoperable, coordinated, and safe growth of the unmanned aircraft systems industry.
3) Noise modeling & trajectory optimization. Modeling noise from commercial aviation and drones, with defined targets for trajectory optimization to minimize impact on exposed communities and wildlife.
4) Environmental KPIs for European aviation. Development of innovative environmental key performance indicators tailored to multi-scale European aviation business operations.
5) Large-scale model validation. Validation of newly developed models, services, and KPIs through large-scale simulations, assessing impact on existing ATM and emerging U-space services.
6) Stakeholder alignment & deployment. Aligning platform capabilities with aviation stakeholder needs to accelerate deployment and enable new aviation business models.

By the end of the project all planned tasks were completed and all deliverables submitted, and the project met these objectives in full. REFMAP results were shared widely, including 46 scientific publications and the creation of the Aviation Twin Transition (ATT) cluster, which brings together projects funded under the same call and met in Athens in July 2025. The project outcomes support cleaner, quieter and more competitive European aviation and drone services.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

REFMAP brought together numerical simulation, measurement and deep learning to reduce the environmental footprint of aviation at two scales: commercial flights connecting European cities, and drones operating in urban areas.

The main achievements were:
- High-fidelity, RANS and multi-fidelity flow simulations, used to train and validate the project's models.
- Climate impact models for aviation, including an assessment of the climate impact of Urban Air Mobility.
- Local air quality models based on pollutant emissions, with a comparison of conventional kerosene and sustainable aviation fuel.
- Aircraft and drone noise models, a model of human perception of drone noise, targets for public acceptance of drone noise in cities, and an assessment of the impact of drone noise on wildlife.
- A deep-learning framework for non-intrusive sensing of the urban wind field, for super-resolution and sensor placement, and for trajectory optimization that minimizes environmental impact, demonstrated in both 2D and 3D.
- Integration of all models into a single large-scale simulation framework, used to test the optimal trajectories in real-case scenarios for both commercial aviation and drone operations.
- A set of environmental key performance indicators, a Minimum Viable Product and a new business model for sustainable European aviation.

These results were brought together in a freely accessible online platform that presents the models and shows how AI-predicted trajectories affect the local environment. By the end of the project all six objectives were fully met, all planned tasks were completed, all milestones achieved and all deliverables submitted.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

REFMAP showed that artificial intelligence can predict optimal flight trajectories that lower environmental impact, and that these trajectories are feasible in real air traffic management scenarios. This was demonstrated at two scales, for commercial aviation and for drones in cities, within a single integrated framework, going beyond earlier work that treated these scales and impacts separately.

For commercial aviation, trajectory optimization targeted the climate impact, which is dominated by non-CO2 effects at cruise altitude. Noise and local air quality, which are set mainly by the phases near the airport, were assessed separately, including a comparison of conventional kerosene with sustainable aviation fuel.

For drones, REFMAP produced models of noise emission and propagation, a model of human perception of drone noise, targets for public acceptance in cities, and a combined assessment of the impact of drone noise on communities and wildlife. Deep learning was also used for non-intrusive sensing and super-resolution of the urban wind field, so that optimal trajectories could account for local weather.

Together these results reduce the overall environmental impact of air transport and provide tools that stakeholders can use for environmentally aware flight planning.