DETERMINING THE IMPACT OF MOTOR VEHICLES ON ATMOSPHERIC AIR USING EXISTING PREDICTIVE MODELS

In recent years, air pollution by motor vehicles has become an increasingly serious environmental problem, especially in large industrial cities such as Kryvyi Rih, the constant increase in the number of vehicles, and industrial activities have a significant impact on air quality. Despite the fact that air quality is continuously monitored in such areas, accurate assessment of the direct impact of motor vehicles remains difficult. Vehicle pollution is characterized by the complex and variable nature of vehicle emissions, which are influenced by factors such as vehicle type, fuel type, traffic density and weather conditions. It should be noted that automobile pollution creates a unique problem: harmful pollutants present in exhaust gases are released into the surface layers, where the main human activity takes place. Various forecasting methods based on mathematical models are used to assess the impact of motor vehicles on air pollution. These models allow estimates of atmospheric pollutant concentrations based on a variety of variables, including the number of vehicles, traffic intensity, vehicle types, fuel characteristics, and meteorological conditions. A study in Kryvyi Rih identified specific areas with heavy traffic for a detailed analysis of pollutant dispersion, focusing on key emissions such as carbon monoxide (CO) and nitrogen dioxide (NO₂). This study used CALRoads View software, which uses the CALINE4 model, and EOL Plus software, which implements the CIS-86 methodology. By comparing the results of these modeling tools, the study established an understanding of the potential applications of each model for estimating urban vehicle emissions. A comparative approach not only improves the understanding of emission sources, but also allows for more informed decisions regarding air quality management in urban environments. This dual model strategy provides a comprehensive framework for assessing the impact of motor vehicles on air quality, improving the ability to develop targeted and effective air quality management policies in large cities and industrialized areas. Keywords: motor vehicles, atmospheric air, pollutant emissions, predictive models, mathematical models.