Using Artificial Intelligence as a Predictive Model of Atmospheric Air Pollutant Distribution

The experience of using artificial intelligence (AI) to create a predictive model of atmospheric air pollutant distribution in an urbanized area is presented. Various machine learning algorithms, their advantages and disadvantages in the context of air quality prediction are considered. The possibilities of using historical data accumulated from 2021 to June 2024 on atmospheric air pollution in Togliatti, meteorological conditions, topography and other factors affecting the distribution of pollutants for training of AI models are investigated. Simulation results demonstrating the effectiveness of the developed model in predicting pollution levels at different time scales are presented. A conclusion is made about the significance of using AI in the field of air quality monitoring, and practical recommendations for using the obtained results to optimize pollution management strategies and ensure environmental safety are proposed.