Atmospheric aerosol distributions from 2000 to 2007 are simulated with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model to attribute light absorption by aerosol to its composition and sources from pollution, dust, and biomass burning. The 8-year, global averaged total aerosol optical depth (tau), absorption optical depth (tau(a)), and single scattering albedo (omega) at 550 nm are estimated at 0.14, 0.0086, and 0.95, respectively, with sulfate making the largest fraction of tau (37%), followed by dust (30%), sea salt (16%), organic matter (OM) (13%), and black carbon (BC) (4%). BC and dust account for 43% and 53% of tau(a), respectively. From a model experiment with "tagged" sources, natural aerosols are estimated to be 58% of tau and 53% of tau(a), with pollution and biomass burning aerosols to share the rest. Comparing with data from the surface sun-photometer network AERONET, the model tends to reproduce much better the AERONET direct measured data of tau and the Angstrom exponent (alpha) than its retrieved quantities of omega and tau(a). Relatively small in its systematic bias of tau for pollution and dust regions, the model tends to underestimate tau for biomass burning aerosols by 30-40%. The modeled alpha is 0.2-0.3 too low (particle too large) for pollution and dust aerosols but 0.2-0.3 too high (particle too small) for the biomass burning aerosols, indicating errors in particle size distributions in the model. Still, the model estimated omega is lower in dust regions and shows a much stronger wavelength dependence for biomass burning aerosols but a weaker one for pollution aerosols than those quantities from AERONET. These comparisons necessitate model improvements on aerosol size distributions, the refractive indices of dust and black carbon aerosols, and biomass burning emissions in order to better quantify the aerosol absorption in the atmosphere.