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Groundbreaking tools and models to reduce air pollution in urban areas

Description du projet

Un nouvel outil d’IA pour résoudre le problème grandissant que pose la pollution atmosphérique urbaine

La majorité de la population urbaine de l’Europe est exposée à des niveaux de polluants atmosphériques supérieurs à ceux prévus par les nouvelles lignes directrices de l’Organisation mondiale de la santé (OMS). L’Agence européenne pour l’environnement (AEE) a constaté que les activités anthropiques sont les principales responsables de ces niveaux dangereux. Dans ce contexte, le projet MODELAIR, relevant des Actions Marie Skłodowska-Curie, dispensera une formation spécialisée à dix doctorants pour concevoir de nouvelles technologies de rupture pour lutter contre la pollution atmosphérique à la disposition des conseils municipaux et des secteurs industriels concernés. MODELAIR élaborera un outil d’intelligence artificielle (IA) qui permettra de prendre des décisions éclairées et sensées dans la lutte contre la pollution atmosphérique dans les zones urbaines.

Objectif

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.

Coordinateur

UNIVERSIDAD POLITECNICA DE MADRID
Contribution nette de l'UE
€ 503 942,40
Adresse
CALLE RAMIRO DE MAEZTU 7 EDIFICIO RECTORADO
28040 Madrid
Espagne

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Région
Comunidad de Madrid Comunidad de Madrid Madrid
Type d’activité
Higher or Secondary Education Establishments
Liens
Coût total
Aucune donnée

Participants (5)

Partenaires (5)