<p>A data assimilation system for aerosol, based on an ensemble Kalman filter, has been developed for the global aerosol model ECHAM-HAM and applied to POLDER derived observations of optical properties. The advantages of this assimilation system is that the ECHAM-HAM aerosol modal scheme carries both aerosol particle numbers and mass which are both used in the data assimilation system as state vector, while POLDER retrievals in addition to Aerosol Optical Depth (AOD) and Angstrom Exponent (AE) provide also information related to aerosol absorption like Aerosol Absorption Optical Depth (AAOD) and Single Scattering Albedo (SSA). The developed scheme can assimilate simultaneously combinations of multiple variables (e.g. AOD, AE, SSA), to optimally estimate mass mixing ratio and number mixing ratio of different aerosol species. We investigate the added value of assimilating AE, AAOD and SSA, in addition to the commonly used AOD, by conducting multiple experiments where different combinations of retrieved properties are assimilated. Results are evaluated with (independent) POLDER, MODIS Dark Target, MODIS Deep Blue and AERONET observations. The experiment where POLDER AOD, AE and SSA are assimilated shows systematic improvement in mean error, mean absolute error and correlation for AOD, AE, AAOD and SSA compared to the experiment where only AOD is assimilated. The same experiment reduces the global ME against AERONET from 0.072 to 0.001 for AOD, from 0.273 to 0.009 for AE and from -0.012 to 0.002 for AAOD. Additionally, sensitivity experiments reveal the benefits of assimilating AE over AOD at a second wavelength or SSA over AAOD, possibly due to a simpler observation covariance matrix in the present data assimilation framework. We conclude that the currently available AE and SSA do positively impact data assimilation.</p>