According to recent studies, internal mixing of black carbon (BC) with other aerosol materials in the atmosphere alters its aggregate shape, absorption of solar radiation, and radiative forcing. These mixing state effects are not yet fully understood. In this study, we characterize the morphology and mixing state of bare BC and BC internally mixed with sodium chloride (NaCl) using electron microscopy and examine the sensitivity of optical properties to BC mixing state and aggregate morphology using a discrete dipole approximation model (DDSCAT). DDSCAT is flexible in simulating the geometry and refractive index of particle aggregates. DDSCAT predicts a higher mass absorption coefficient (MAC), lower single scattering albedo (SSA), and higher absorption Angstrom exponent (AAE) for bare BC aggregates that are lacy rather than compact. Predicted values of SSA at 550 nm range between 0.16 and 0.27 for lacy and compact aggregates, respectively, in agreement with reported experimental values of 0.25 ± 0.05. The variation in absorption with wavelength does not adhere precisely to a power law relationship over the 200 to 1000 nm range. Consequently, AAE values depend on the wavelength region over which they are computed. The MAC of BC (averaged over the 200–1000 nm range) is amplified when internally mixed with NaCl (100–300 nm in radius) by factors ranging from 1.0 for lacy BC aggregates partially immersed in NaCl to 2.2 for compact BC aggregates fully immersed in NaCl. The SSA of BC internally mixed with NaCl is higher than for bare BC and increases with the embedding in the NaCl. Internally mixed BC SSA values decrease in the 200–400 nm wavelength range, a feature also common to the optical properties of dust and organics. Linear polarization features are also predicted in DDSCAT and are dependent on particle size and morphology.
This study shows that DDSCAT predicts complex morphology and mixing state dependent aerosol optical properties that have been reported previously and are relevant to radiative transfer, climate modeling, and interpretation of remote sensing measurements.