Cutting-edge research, the European Research Council funds the DANTE project that aims to develop a new paradigm to predict the microclimate in an urban context. Florence as the first case study
The project is coordinated by Giovanni Stabile, associate professor at The BioRobotics Institute, Sant'Anna School (Pisa): "I will develop a digital twin of the Florence urban context to improve the climate and susainability of the city"
How does the climate change within urban contexts? And what are the tools to make cities more sustainable? These questions are answered by DANTE (Data Aware efficient models of the urbaN microclimaTE), the new project funded by the European Research Council (ERC) with ERC Starting Grants, which aims to develop innovative numerical techniques to predict the microclimate in urban environments, through mathematical models, machine learning and data assimilation.
The project, which officially started on 1 April 2024 and will run for five years with an investment of €1.4 million, is coordinated by Giovanni Stabile, associate professor at the Institute of BioRobotics of the Scuola Superiore Sant'Anna. After obtaining a joint doctorate from the University of Florence and the Institute of Scientific Computing at TU Braunschweig, Stabile worked as a post-doc at SISSA in Trieste (it was during this period that Stabile submitted the project to the European Research Council) and as a researcher at the University of Urbino, before moving to Scuola Superiore Sant'Anna.
Population growth in urban areas
The percentage of the world's population living in cities is increasing rapidly and is expected to reach 80% by 2050. It is therefore crucial to develop new methods to model the urban microclimate and to help professionals involved in the urban planning process (architects, engineers, politicians) to make cities more sustainable and comfortable. The DANTE project fits into this context and aims to create a new paradigm for fast and reliable numerical simulations. Special emphasis will be placed on advanced machine learning tools, incorporating knowledge of physics, with the aim of improving the accuracy, interpretability and reliability of predictive models.
The methods developed will have a significant impact on digital transformation, enabling digital twins of urban environments.
Florence as the first case study of the project
The city of Florence will be the first case study of the DANTE project, with the creation of a digital twin that will reproduce the microclimate of the urban context of the Tuscan capital and will focus in particular on the diffusion of pollutants, both from mobile sources such as cars and from fixed sources such as industries, and on the modelling of complex phenomena such as heat islands and extreme weather events.
"Why Florence? The Tuscan capital has a particularly unfavourable meteorological context that leads to an accumulation of atmospheric pollution with recorded values of nitrogen dioxide, ozone and particulate matter that exceed the legal objectives to be reached by 2030," explains Giovanni Stabile. "This project, whose acronym already reveals its homage to Florence and the Tuscan land, aims to provide concrete solutions to improve the city's climate and sustainability".
