Lidar backscattering model for soot aerosols

Aerosol lidar remote sensing relies on the interpretation of backscattered light to retrieve particle properties of interest. This study presents a novel analytical backscattering model for soot or black carbon aerosols, based on the Rayleigh-Debye-Gans for Fractal Aggregates (RDG-FA) approximation. This model is used to derive simple expressions for common lidar-relevant parameters, including differential backscattering cross section, lidar ratio (LR), mass-backscattering coefficients (MBC), backscattering color ratio (CR), and Å ngström exponent (BAE). The behavior of these lidar parameters is investigated as a function of wavelength, size, and aging. Key findings include a general decrease in LR, along with a clear dependence of CR and BAE on aerosol size as black carbon aggregates grow, for both freshly emitted and aged soot. These findings have highlighted the ability to model the variations of these parameters throughout the life cycle of black carbon, capturing the evolution from chain-like freshly emitted particles to more spherical aged particles. Furthermore, this study demonstrates the potential of the RDG-FA backscatter model to calculate key lidar parameters and improve the retrieval of soot aerosol products. • The Rayleigh-Debye-Gans for Fractal Aggregates (RDG-FA) approximation is used to derive a backscattering model for soot aerosols, modeled as fractal aggregates. • Simple analytical expressions are derived for common lidar parameters for soot aerosols, including black carbon. • A decrease in the lidar ratio as soot ages and an increase of the color ratio and decrease of the BAE with aggregate size is found. • A differentiation between freshly emitted soot and aged soot is reported in terms of LR, CR, and BAE as aggregates increase in size.