This paper presents a methodology for collecting data on the quality of atmospheric air in a populated place with a developed infrastructure and an intensive flow of vehicles. The presence of a large number of vehicles and their mass used, leads to an increase in the levels of harmful emissions above the permissible values. This is essential for the assessment of pollution and the protection of the environment and human health. The methodology examines means for monitoring atmospheric air quality parameters, data on concentrations of polluting substances, such as fine particulate matter PM10, PM2.5, nitrogen dioxide (NO2), sulphur dioxide (SO2), ozone (O3). The authors present a methodology for summarizing and analysing data from various sources such as data from stationary automated measuring stations, data from a literature review of existing research and data obtained from own research. Data sources include air quality sensor networks, data from environmental agencies, satellite imagery, and other similar sources. Combining data sources provides a comprehensive and holistic view of air quality, providing an opportunity to better understand the factors that influence air pollution and their interaction in a given geographic area. Different methods and algorithms are used to analyse the collected data, which allow objective measurement and interpretation of air pollution levels. Statistical data analysis, cluster analysis, regression analysis, time series, geographic data analysis help identify correlations and trends in air pollution data. The expected result of the present work is the creation of a generalized system for the collection, analysis and interpretation of a data base on air pollution in a certain populated place, which will support the consideration of various factors, location and time periods for the assessment and forecast of the ambient air quality