The sustainability of urban environments is an increasingly relevant problem. Air pollution plays a key role in the degradation of the environment as well as the health of the citizens exposed to it. In this chapter we provide a review of the methods available to model air pollution, focusing on the application of machine-learning methods. In fact, machine-learning methods have proved to importantly increase the accuracy of traditional air-pollution approaches while limiting the development cost of the models. Machine-learning tools have opened new approaches to study air pollution, such as flow-dynamics modelling or remote-sensing methodologies.
@article{arxiv.2112.15115,
title = {Aim in Climate Change and City Pollution},
author = {Pablo Torres and Beril Sirmacek and Sergio Hoyas and Ricardo Vinuesa},
journal= {arXiv preprint arXiv:2112.15115},
year = {2022}
}