Abstract. The Ångström exponent, α, is often used as a qualitative indicator of aerosol particle size. In this study, aerosol optical depth (AOD) and Ångström exponent (α) data were analyzed to obtain information about the adequacy of the simple use of the Ångström exponent for characterizing aerosols, and for exploring possibilities for a more efficient characterization of aerosols. This was made possible by taking advantage of the spectral variation of α, the so-called curvature. The data were taken from four selected AERONET stations, which are representative of four aerosol types, i.e. biomass burning, pollution, desert dust and maritime. Using the least-squares method, the Ångström-α was calculated in the spectral interval 340–870 nm, along with the coefficients α1 and α2 of the second order polynomial fit to the plotted logarithm of AOD versus the logarithm of wavelength, and the second derivative of α. The results show that the spectral curvature can provide important additional information about the different aerosol types, and can be effectively used to discriminate between them, since the fine-mode particles exhibit negative curvature, while the coarse-mode aerosols positive. In addition, the curvature has always to be taken into account in the computations of Ångström exponent values in the spectral intervals 380–440 nm and 675–870 nm, since fine-mode aerosols exhibit larger α675–870 than α380–440 values, and vice-versa for coarse-mode particles. A second-order polynomial fit simulates the spectral dependence of the AODs very well, while the associated constant term varies proportionally to the aerosol type. The correlation between the coefficients α1 and α2 of the second-order polynomial fit and the Ångström exponent α, and the atmospheric turbidity, is further investigated. The obtained results reveal important features, which can be used for better discriminating between different aerosol types.
Multiyear Typology of Long-Range Transported Aerosols over Europe