Analysis of Data on Air Pollutants in the City by Machine-Intelligent Methods Considering Climatic and Geographical Features

In the world, air pollution ranks among primary sources of risk to human health and environment. To assess impact atmospheric pollution, a comprehensive research cycle was designed develop unified ecosystem for monitoring in industrial cities Kazakhstan. Research involves analyzing data winter period from 20 automated stations (AMS) located Almaty conducting chemical-analytical studies snowmelt water samples 22 points identify such pollutants as fine particulate matters, petroleum products, heavy metals. includes bio-experiment involving cultivation watercress on melt collected snow cover examine effects plants. framework this research, we determined API based obtained AMS. order determine influence environment, multiple regression model developed using machine learning algorithms reveal relationship between research. The results revealed wide spread urban correlation airspace city, their negative flora.