A new research algorithm is presented here as the second part of a two-part study to retrieve aerosol microphysical properties from the multi-spectral and multi-angular photo-polarimetric measurements taken by AERONET's new-generation SunPhotometer. The algorithm uses an advanced UNified and Linearized Vector Radiative Transfer Model (UNL-VRTM), and incorporates a statistical optimization approach. While the new algorithm has heritage from AEROENT operational inversion algorithm in constraining a priori and retrieval smoothness, it has two new features. First, the new algorithm retrieves the effective radius, effective variance, and total volume of aerosols associated with a continuous bi-modal particle size distribution (PSD) function, while the AERONET operational algorithm retrieves aerosol volume over 22 size bins. Second, our algorithm retrieves complex refractive indices for both fine and coarse modes, while the AERONET operational algorithm assumes a size-independent aerosol refractive index. Mode-resolved refractive indices can improve the estimate of the single scattering albedo (SSA) for each aerosol mode, and thus facilitate the validation of satellite products and chemistry transport models. We applied the algorithm to a suite of real cases over Beijing_RADI site, and found that our retrievals are overall consistent with AERONET operational inversions, but can offer mode-resolved refractive index and SSA with acceptable accuracy for the aerosol composed by spherical particles. Along with the retrieval using both radiance and polarization, we also performed radiance-only retrieval to demonstrate the improvements by adding polarization in the inversion. Contrast analysis indicates that with polarization, retrieval error can be reduced by over 50% in PSD parameters, 10–30% in the refractive index, and 10–40% in SSA, which is consistent with theoretical analysis presented in the companion paper of this two-part series study.