Statistical Approaches for Forecasting Air pollution: A Review

With the rapid growth of energy consumption, acceleration of industrialization and urbanization, and the emission of automobile and industrial exhausts, polluting gases are causing incredible harm to nature and also impacting the health of people. The control and prevention of air pollution become required to protect the environment and human lives. Additionally, the prediction of air pollution may offer reliable data on air pollution by predicting the future concentration of pollutants in the air. These days, concentrating on tackling exceptional ecological issues and undertaking activities to forestall and lessen air contamination has become a fundamental and challenging task. Machine learning is an efficient approach in the field of environmental modelling, which can reliably forecast air pollution in advance. Thise chapter focuses on the proposed study, analyzes and reviews forecasting air pollution using different learning techniques and then suggests a possible solution for future work.