## 3 Results
### Comparison of Satellite and In Situ AOT  
The next stage of this study was the processing of the Ocean Color L2 files. These data were used to analyze the variability of the optical characteristics depending on the error  
Figure 2: Results of the airmass transfer modeling according to data from the AERONET and HYSPLIT networks on 12 September 2017 and 8 September 2017.  
flags. In addition to AOT and Angstrom data, remote sensing data provide data on the chlorophyll-a concentration (2 OSI and OC3 models) and diffuse attenuation coefficient at a wavelength of 490 nm. L3 data can be considered as being the most reliable for the selected dates. In total, 173,182 pixels were analyzed for the eastern part of the Black Sea on the day of dust transfer. The statistics did not consider the error flags of a purely technical nature (PRODFAILE, MAXITER, etc.) nor errors that made up less than 1% of the data according to the L2 level data. Thus, on the day of dust transfer (12 September 2017) and the day with a clean atmosphere (8 September 2017), an array of Rrs data were obtained for statistical analysis (Table 1). An analysis of the data results from the 2 tables shows that during the dust transfer, AOT at a wavelength of 869 nm (AOT(869)) increased by more than 5-fold. This is due to the absorption capacity of dust. So, according to the SPM data obtained in Sevastopol, it was demonstrated that on 12 September 2017, the Angstrom parameter values did not differ from the Angstrom parameter values on the day with a clean atmosphere. The dust that reached Sevastopol on this day contained a lot of fine-mode aerosol fractions and the values of \(\alpha\) decreased by 17-20% relative to the monthly average. The chlorophyll data recorded on the day on which dust aerosols were present in the atmosphere were overestimated by 9% according to the results from the calculation of the 2 models for L2 and L3. When analyzing the error flags, the largest number of pixels was noted for MODGLINT (moderate pollution due to Sun glare). On the day of dust transfer, the percentage of pixels with this flag was 59% of the level 2 data and 69% of the eastern part of the Black Sea with a clear atmosphere. Low-quality Rrs(\(\lambda\)) in the clear OZ of the southern IO in the second half of the year may be attributed to contamination due to residual Sun glint signals. During MODIS and VIIRS image processing from level 1 to level 2 implemented by the NASA Ocean Biology Processing Group (OBPG), pixels are flagged as \"HIGLINT\" and \"MODGLINT\" if the normalized Sun glint surface-reflected radiance (LGN) exceeds 0.005 and 0.0001 sr\({}^{-1}\), respectively, and then a glint correction is applied according to the wind. Pixels with a \"HIGLINT\" flag are masked during level 2 to level 3 processing while those with a \"MODGLINT\" flag are reserved. The statistics indicate the impact of residual Sun glint contamination. Hence, the development of an advanced algorithm to remove residual Sun glint is still needed ([PERSON] et al., 2021). Since the number of MODGLINT pixels was not significantly different between 12.09.2017 and 08.09.2017, we can conclude that the MODGLINT flag equally contributed to the calculations of Rrs(\(\lambda\)) on and before the