A concentration-weighted trajectory method for aerosol source localization based on joint statistical analysis of aerosol column volume concentrations and back-trajectory data was used to estimate the spatial distribution of aerosol sources in the EastEuropean region. The aerosol column volume concentration data measured at five AERONET network sites, Belsk, Minsk, Kyiv, Moldova/Kishinev, and Sevastopol, were used. The geographical areas responsible for increased aerosol content at the monitoring sites were mapped separately for coarse-mode and fine-mode aerosol fractions. The investigated area is located between 42°and 62°N in latitude and between 12°and 50°E in longitude.It was shown that the northeastern territories (in relation to the monitoring stations) give a small contribution to the coarse-mode aerosol content. The events of increased coarse-mode aerosol concentration have been caused by sources in the southeastern regions. On average, the air masses with a large content of coarse-mode aerosol particles were delivered to all stations from regions around Donetsk, Rostov-on-Don, and Kharkiv cities. The fine-mode aerosol fraction originated from areas of Tambov, Voronezh, and Kharkiv cities. The calculated aerosol source regions partly correspond to European Monitoring and Evaluation Programme data for eastern Europe. The cause of difference between calculated regions responsible for increased aerosol content at the monitoring sites and the sources of particle emission according to European Monitoring and Evaluation Programme data are discussed.
Atmospheric correction of satellite optical data is based on an assessment of the optical characteristics of the atmosphere, such as the aerosol optical thickness of the atmosphere and the spectral slope, the so-called Angstrom parameter. Inaccurate determination of these parameters is one of the causes of error in the retrieval of remote-sensed reflectance spectra. In this work, a large array of field and satellite data measured in Sevastopol and the northeastern part of the Black Sea were used, including ship-based measurements of atmospheric characteristics and sea reflectance, MODIS Aqua/Terra, and VIIRS NOAA/NPP Level 2 remote-sensed reflectance and atmospheric data. In total, three episodes of Saharan dust transfer over the Black Sea region were considered, mainly in the autumn-winter period. The purpose of this study was to show the numerical differences between the atmospheric parameters measured at the surface level and by satellites, and show their relationship with the differences between in situ and satellite remote-sensed reflectance. Based on the information identified, we propose an algorithm for additional correction of satellite level 2 data that uses a two-parametric model of the Black Sea remote-sensed reflectance as a first approximation. Moreover, additional correction significantly reduces the discrepancy between in situ and retrieved remote-sensed reflectance, especially in short-wave spectral bands.
Atmospheric correction of satellite optical data is based on an assessment of the optical characteristics of the atmosphere, such as the aerosol optical depth of the atmosphere and the spectral slope of its spectrum, the so-called Angstrom parameter. Inaccurate determination of these parameters is one of the causes of errors in the retrieval of the remote sensing reflectance spectra. In this work, the obtained large array of field and satellite data for the northeastern part of the Black Sea is used, including ship-based measurements of atmospheric characteristics and sea reflectance, MODIS Aqua/Terra and OLCI Sentinel-3 A/B Level 2 remote sensing reflectance and atmospheric data. The purpose of this study is to show the numerical differences between the atmospheric parameters measured from the surface level and from the satellite and demonstrate their relationship with the differences between in situ and satellite remote sensing reflectance. Based on the information received, we propose an algorithm for the additional correction of satellite Level 2 data that uses a two-parametric model of the Black Sea remote sensing reflectance as a first approximation. This method does not require any in situ information. It is shown that additional correction significantly reduces the discrepancy between in situ and retrieved remote sensing reflectance, especially in short-wave spectral bands.
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