Air Pollution Forecasting Using Deep Learning Algorithms: A Review

The emissions from vehicles and factory exhaust and other forms of pollution have caused severe damage to the environment and to people’s health as the rate of urbanization and industrialization has increased at a rapid pace. To safeguard ecosystems and human health, air pollution must be mitigated and prevented. Predicting the future concentration of contaminants in the air can provide more trustworthy data on air pollution. Focusing on fundamental and difficult tasks like preventing and reducing air pollution and addressing extraordinary ecological challenges is essential and difficult now. To effectively predict future air pollution levels, machine learning is a promising method in the field of environmental modelling. In this context, we investigate the state of the art in air pollution forecasting, analyse our findings, provide a critical evaluation of the literature and offer some recommendations for the way forward.