Observing air quality and flow in cities for public health in times of climate change

With my co-authors Pablo Torres, Sergio Hoyas (both from Instituto Universitario de Matemática Pura y Aplicada, Universitat Politécnica de Valencia, Spain) and Ricardo Vinuesa (from Engineering Mechanics, KTH Royal Institute of Technology, Sweden), we have written a book chapter which focuses on the key role of machine learning (ML) methods to analyze air quality and air flow in urban environments (especially in dense cities) which might be an indicator of public health [1]. We have provided a review of the ML methods used in this field and we have highlighted the relevance of the urban air quality and air flow to the number of hospitalizations and respiratory diseases as they were reported in the literature. Here is a mini lecture which summarizes our book chapter in a video [4].