## 3 Materials and Methods
### Estimation of Air Pollutants by Remote Sensing  
Air pollution is one of the most important environmental problems, concentrated mainly in cities. Aerosols are liquid and solid particles suspended in the air that originate from natural sources or are produced by pollution, including pollution caused by traffic. Air pollution is measured by a network of sensors established at the European level to monitor the main pollutants and the European Environment Agency (EEA) provides official data for European countries. To assess air pollution, the European Air Quality Index (EAQI) is used, which consists of a combination of five different air pollutants and indicates the current state of air quality in Europe (SO\({}_{2}\), NO\({}_{2}\), O\({}_{3}\), PM2.5, PM10) [35; 36]. The EEA uses only data for NO\({}_{2}\) and PM (either PM2.5, PM10, or both) to calculate the index for traffic stations because SO\({}_{2}\) can distort the picture of local air quality, while ozone levels at traffic stations are usually very low. EPA and the EEA carry out measurements of air pollution, but this information is not accessible for the areas investigated in this study, only average values for the city or country are available. Therefore, to understand trends in air quality only open-source data were used for all analyses.  
Monitoring the Earth from satellites can provide remote sensing information by using infrared or ultraviolet light to detect pollutants or by calculating indicators of air pollution, such as atmospheric opacity measured by the optical thickness of atmospheric aerosol. Satellites have the advantage of providing global coverage and long-term observations. However, it should be noted that the usage of satellite observations is associated with a high degree of uncertainty due to cloud contamination, uncertainties in the determination of AOD, lack of sensor-specific data, etc. [37].  
For air-quality assessment, we propose two methods: a holistic analysis of the imagery provided by the Sentinel-2 monitoring tools and the use of modern era retrospective analysis for research and applications aerosol reanalysis (MERRAero) data to estimate surface PM2.5 levels  
To estimate surface PM2.5 pollution from satellite measurements, we use aerosol optical depth (AOD) from MERRAero. MERRAero provides aerosol grid data from Mera, starting in 2002 and continuing to the present, over platforms from NASA EOS.  
We have chosen the band combinations for atmospheric penetration and atmospheric removal for the image analysis. Atmospheric penetration is a band combination that provides similar results to conventional false-color infrared photography, but with greater clarity. It contains no visible bands, but penetrates atmospheric particles, smoke, and haze, reducing the atmospheric influence on the image. Water attenuates NIR and SWIR wavelengths and ice and snow provide well-defined coastlines and highlighted water sources in the image. Vegetation in the band combination, which appears in blue, indicates the vitality of the vegetation. Healthy vegetation is shown in light blue, whereas stressed, sparse or/and dry vegetation appears in a dull blue. Urban structures are white, grey, cyan, or purple. The band combination can be used to determine moisture, texture, and soil properties. Each band in the combination plays a significant role in representing different features and gives them different characteristics in the appearance of the image.  
Atmospheric effect removal is the result of the combination of SWIR 2, NIV and green bands used to correct for atmospheric effects. Each band combination plays a critical role in the appearance of the image. The shortwave infrared (SWIR2) is strongly absorbed by water. Because different types of clouds contain different amounts of water, the spectrum is useful for distinguishing between clouds.