Description du projet
Estimation des dommages environnementaux autres que le CO2 causés par l’aviation
On sait que l’aviation a un impact négatif sur le climat en raison de ses émissions nocives. Toutefois, des études et des recherches menées récemment ont mis en évidence d’autres effets, notamment en ce qui concerne le rôle des traînées de condensation et des cirrus anthropiques dans le refroidissement de l’atmosphère et la formation des nuages. Malheureusement, les recherches sur ce sujet sont limitées en raison de la complexité des différentes variables impliquées. Le projet E-CONTRAIL, financé par l’UE, entend mener une étude approfondie sur les traînées de condensation et la nébulosité induite par l’aviation en s’appuyant sur des images satellites de pointe, afin d’examiner leur impact potentiel sur l’environnement. En outre, le projet vise à développer un réseau neuronal artificiel capable de prédire les dommages autres que le CO2 causés à l’environnement par l’aviation. Pour atteindre cet objectif, les chercheurs s’appuieront sur leurs vastes connaissances en matière d’apprentissage profond et de climatologie afin de minimiser les incertitudes.
Objectif
Contrails and aviation-induced cloudiness effects on climate change show large uncertainties since they are subject to meteorological, regional, and seasonal variations. Indeed, under some specific circumstances, aircraft can generate anthropogenic cirrus with cooling. Thus, the need for research into contrails and aviation-induced cloudiness and its associated uncertainties to be considered in aviation climate mitigation actions becomes unquestionable.
We will blend cutting-edge AI techniques (deep learning) and climate science with application to the aviation domain, aiming at closing (at least partially) de existing gap in terms of understanding aviation-induced climate impact.
The overall purpose of E-CONTRAIL project is to develop artificial neural networks (leveraging remote sensing detection methods) for the prediction of the climate impact derived from contrails and aviation-induced cloudiness, contributing, thus, to a better understanding of the non-CO2 impact of aviation on global warming and reducing their associated uncertainties as essential steps towards green aviation.
Specifically, the objectives of E-CONTRAIL are:
O-1 to develop remote sensing algorithms for the detection of contrails and aviation-induced cloudiness.
O-2 to quantify the radiative forcing of ice clouds based on remote sensing and radiative transfer methods.
O-3 to use of deep learning architectures to generate AI models capable of predicting the radiative forcing of contrails based on data-archive numerical weather forecasts and historical traffic
O-4 to assess the climate impact and develop a visualization tool in a dashboard
Upon successful achievement of the objectives described above, we ambition to provide aviation stakeholders with an early and accurate (thus, reducing the associated uncertainty) prediction of those volumes of airspace with the conditions for large global warming impact due to contrails and aviation-induced cloudiness.
Champ scientifique
- natural sciencesearth and related environmental sciencesatmospheric sciencesmeteorology
- engineering and technologyenvironmental engineeringremote sensing
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- natural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changes
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
Programme(s)
- HORIZON.2.5 - Climate, Energy and Mobility Main Programme
Thème(s)
Régime de financement
HORIZON-JU-RIA - HORIZON JU Research and Innovation ActionsCoordinateur
28903 Getafe (Madrid)
Espagne