Satellite characterization of urban aerosols: Importance of including hygroscopicity and mixing state in the retrieval algorithms

This model study examines the sensitivity of the calculated optical properties of urban aerosols to ( 1) hygroscopicity and ( 2) internal or external mixing state, and it further investigates the associated implications for the accuracy of satellite retrievals of aerosol optical thickness (tau) and aerosol effective radius (r(eff)). State-of-the-art retrieval algorithms widely omit variable hygroscopicity and mixing state. For the study described herein, the modeled urban aerosols are composed of water-soluble sulfates and water-insoluble black carbon ( BC) in the fine mode and of water-insoluble compounds in the coarse mode. The calculations show that external compared to internal mixing of black carbon and sulfate not only significantly affects the single-scattering albedo but also alters the diagnostic relationship of the Angstrom exponent ( a) to the aerosol effective radius. The implication is that over a dark surface of visible reflectance less than 0.1, satellite retrievals of urban aerosols having a BC/sulfate mass ratio of 5% can differ in t and reff by as much as 60% and 0.2 mm, respectively, depending upon the retrieval algorithm's assumptions regarding hygroscopicity and mixing state. For surface reflectances greater than 0.1 or BC/sulfate mass ratios larger than 5%, the retrieval bias, including the possibility of unphysical retrievals, increases further. The calculations also show that hygroscopic growth at elevated relative humidity increases the single-scattering albedo of urban aerosols, decreases their backscattering, and as a consequence reduces the influence of mixing state on t and reff. These results suggest that current operational retrieval algorithms lead to a possibly systematic underestimate of aerosol optical thickness when ambient BC/sulfate aerosols are internally mixed at mass ratios greater than 3%. This study's recommendation is that aerosol retrieval algorithms, when applied to urban aerosols, incorporate in situ knowledge of relative humidity, mixing state, and BC/sulfate mass ratios, either from ground-based measurements or by auxiliary use of chemical transport models.