Descrizione del progetto
La stima dei danni ambientali non inerenti alla CO2 causati dal settore dell’aviazione
È noto che il settore aeronautico ha un impatto negativo sul clima a causa delle notevoli emissioni nocive generate. Tuttavia, studi e ricerche recenti hanno scoperto ulteriori effetti, in particolare per quanto riguarda il ruolo svolto dalle scie e dai cirri antropogenici nel raffreddamento dell’atmosfera e nella formazione delle nubi. Sfortunatamente, tuttavia, la ricerca su questi temi è sinora stata limitata a causa della complessità delle diverse variabili coinvolte. Il progetto E-CONTRAIL, finanziato dall’UE, mira a condurre uno studio completo sulle scie e sulla nuvolosità generate dall’aviazione sfruttando immagini satellitari all’avanguardia allo scopo di esplorarne il potenziale impatto sull’ambiente. Inoltre, il progetto si prefigge di sviluppare una rete neurale artificiale in grado di prevedere i danni ambientali non inerenti alla CO2 causati dal settore aeronautico. Per raggiungere questo obiettivo, i ricercatori si avvarranno di ampie conoscenze in materia di apprendimento profondo e climatologia per ridurre al minimo le incertezze al riguardo.
Obiettivo
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.
Campo scientifico
- 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
Parole chiave
Programma(i)
- HORIZON.2.5 - Climate, Energy and Mobility Main Programme
Argomento(i)
Meccanismo di finanziamento
HORIZON-JU-RIA - HORIZON JU Research and Innovation ActionsCoordinatore
28903 Getafe (Madrid)
Spagna