Projet MODELAIR (Horizon Europe, appel à projets 2021)
Action : Doctoral Networks
Panel : Information Science and Engineering
Statut du projet : SIGNED

MODELAIR proposes a combination of theoretical, experimental, numerical, and data-driven science that will simulate, control and design new disruptive technologies for future sustainable cities and will provide specialized training to 10 doctoral candidates (DCs) to make these new technologies available to city Councils and relevant industrial sectors. MODELAIR contributes to EU Mission: Climate-neutral and smart cities, reducing gas emissions and offering cleaner air to citizens. MODELAIR will develop an Artificial Intelligence (AI) - based tool to help make informed and sensible decisions to control air pollution in urban areas. For such aim, MODELAIR will develop novel analysis tools and new Reduced Order Models (ROMs) based on both non-intrusive sensing and innovative data sources. Assessed by the industry and city councils from Bristol, Brussels and Madrid, MODELAIR will improve the current state-of-the-art modeling capability, taking into account the influence that buildings, roadways and other structures have on the flow and dispersion of air pollution . The limits of applicability of the novel AI-based tool will be tested in three specific problems related to air pollution in urban areas by: (i) studying the influence of the urban topology on air pollution, (ii) characterizing the Ixelles District (Brussels-BE) to develop a real-time decision-making tool that will assess about the disposition and maintenance of the sensor network to provide a high-quality air pollution monitoring service, and (iii) investigating the influence of the pollutant emission source (strength and location) to optimize traffic routes to reduce air pollution. The final aim is to obtain transferable outputs using novel tools and methodology approaches (addressing three different challenges) to improve air quality dispersion models that will serve to city councils and industry to develop new regulations to control air pollution.

Mots clés : air pollution reduced order modelling computational fluid dynamics machine learning data driven methods

Participants :
- Microflown Technologies (Netherlands) (Pays-Bas) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 320098.8 €
- Université de Bristol (Royaume-Uni) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Université libre de Bruxelles (Belgique) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 525240.0 €
- Ayuntamiento de Madrid (Espagne) — Partner, associated partner, Organismes publics (hors enseignement & recherche), subvention : 0.0 €
- Université polytechnique de Madrid (Espagne) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 503942.4 €
- Ove arup & partners sa (Espagne) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 251971.2 €
- Air quality consultants ltd (Royaume-Uni) — Partner, associated partner, Organismes privés (hors enseignement), subvention : 0.0 €
- Buildwind (Belgique) — Partner, associated partner, Organismes privés (hors enseignement), subvention : 0.0 €
- Université polytechnique de Catalogne (Espagne) — Partner, beneficiary, Recherche, subvention : 251971.2 €
- Bristol City Council (Royaume-Uni) — Partner, associated partner, Organismes publics (hors enseignement & recherche), subvention : 0.0 €
- KTH Institut royal de technologie (Suède) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 832177.2 €