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The study presents the efforts on including the polarimetric data to the routine inversion of the radiometric ground-based measurements for characterization of the atmospheric aerosols and analysis of the obtained advantages in retrieval results. First, to operationally process the large amount of polarimetric data the data preparation tool was developed. The AERONET inversion code adapted for inversion of both intensity and polarization measurements was used for processing. Second, in order to estimate the effect from utilization of polarimetric information on aerosol retrieval results, both synthetic data and the real measurements were processed using developed routine and analyzed. The sensitivity study has been carried out using simulated data based on three main aerosol models: desert dust, urban industrial and urban clean aerosols. The test investigated the effects of utilization of polarization data in the presence of random noise, bias in measurements of optical thickness and angular pointing shift. The results demonstrate the advantage of polarization data utilization in the cases of aerosols with pronounced concentration of fine particles. Further, the extended set of AERONET observations was processed. The data for three sites have been used: GSFC, USA (clean urban aerosol dominated by fine particles), Beijing, China (polluted industrial aerosol characterized by pronounced mixture of both fine and coarse modes) and Dakar, Senegal (desert dust dominated by coarse particles). The results revealed considerable advantage of polarimetric data applying for characterizing fine mode dominated aerosols including industrial pollution (Beijing). The use of polarization corrects particle size distribution by decreasing overestimated fine mode and increasing the coarse mode. It also increases underestimated real part of the refractive index and improves the retrieval of the fraction of spherical particles due to high sensitivity of polarization to particle shape. Overall, the study demonstrates a substantial value of polarimetric data for improving aerosol characterization. (C) 2016 Elsevier Ltd. All rights reserved.