This study assesses the impact of dust on surface solar radiation focussing on an extreme dust event. For this purpose, we exploited the synergy of AERONET measurements and passive and active satellite remote sensing (MODIS and CALIPSO) observations, in conjunction with radiative transfer model (RTM) and chemical transport model (CTM) simulations and the 1-day forecasts from the Copernicus Atmosphere Monitoring Service (CAMS). The area of interest is the eastern Mediterranean where anomalously high aerosol loads were recorded between 30 January and 3 February 2015. The intensity of the event was extremely high, with aerosol optical depth (AOD) reaching 3.5, and optical/microphysical properties suggesting aged dust. RTM and CTM simulations were able to quantify the extent of dust impact on surface irradiances and reveal substantial reduction in solar energy exploitation capacity of PV and CSP installations under this high aerosol load. We found that such an extreme dust event can result in Global Horizontal Irradiance (GHI) attenuation by as much as 40–50 % and a much stronger Direct Normal Irradiance (DNI) decrease (80–90 %), while spectrally this attenuation is distributed to 37 % in the UV region, 33 % in the visible and around 30 % in the infrared. CAMS forecasts provided a reliable available energy assessment (accuracy within 10 % of that obtained from MODIS). Spatially, the dust plume resulted in a zonally averaged reduction of GHI and DNI of the order of 150 W m⁻² in southern Greece, and a mean increase of 20 W m⁻² in the northern Greece as a result of lower AOD values combined with local atmospheric processes. This analysis of a real-world scenario contributes to the understanding and quantification of the impact range of high aerosol loads on solar energy and the potential for forecasting power generation failures at sunshine-privileged locations where solar power plants exist, are under construction or are being planned.

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.