The gap in knowledge regarding the radiative effects of aerosols in the UV region of the solar spectrum is large, mainly due to the lack of systematic measurements of the aerosol single scattering albedo (SSA) and absorption optical depth (AAOD). In the present study, spectral UV measurements performed in Thessaloniki, Greece by a double monochromator Brewer spectrophotometer in the period 1998–2017 are used for the calculation of the aforementioned optical properties. The main uncertainty factors have been described and there is an effort to quantify the overall uncertainties in SSA and AAOD. Analysis of the results suggests that the absorption by aerosols is much stronger in the UV relative to the visible. SSA follows a clear annual pattern ranging from ~0.7 in winter to ~0.85 in summer at wavelengths 320–360 nm, while AAOD peaks in summer and winter. The average AAOD for 2009–2011 is ~50% above the 2003–2006 average, possibly due to increased emissions of absorbing aerosols related to the economic crisis and the metro-railway construction works in the city center.
The gap in knowledge regarding the radiative effects of aerosols in the UV region of the solar spectrum is large, mainly due to the lack of systematic measurements of the aerosol single scattering albedo (SSA) and absorption optical depth (AAOD). In the present study, spectral UV measurements performed in Thessaloniki, Greece by a double monochromator Brewer spectrophotometer in the period 1998 - 2017 are used for the calculation of the aforementioned optical properties. The main uncertainty factors have been described and there is an effort to quantify the overall uncertainties in SSA and AAOD. Analysis of the results suggests that the absorption by aerosols is much stronger in the UV relative to the visible. SSA follows a clear annual pattern ranging from ~0.7 in winter to ~0.85 in summer at wavelengths 320 – 360 nm, while AAOD peaks in summer and winter. The average AAOD for 2009 – 2011 is ~50% above the 2003 – 2006 average, possibly due to increased emissions of absorbing aerosols related to the economical crisis and the metro-railway construction works in the city center. A detailed analysis of the uncertainties in the retrieval of the SSA and the AAOD from the Brewer spectrophotometer has been also performed.
In this study, we present an aerosol classification technique based on measurements of a double monochromator Brewer spectrophotometer during the period 1998–2017 in Thessaloniki, Greece. A machine learning clustering procedure was applied based on the Mahalanobis distance metric. The classification process utilizes the UV Single Scattering Albedo (SSA) at 340 nm and the Extinction Angstrom Exponent (EAE) at 320–360 nm that are obtained from the spectrophotometer. The analysis is supported by measurements from a CIMEL sunphotometer that were deployed in order to establish the training dataset of Brewer measurements. By applying the Mahalanobis distance algorithm to the Brewer timeseries, we automatically assigned measurements in one of the following clusters: Fine Non Absorbing Mixtures (FNA): 64.7%, Black Carbon Mixtures (BC): 17.4%, Dust Mixtures (DUST): 8.1%, and Mixed: 9.8%. We examined the clustering potential of the algorithm by reclassifying the training dataset and comparing it with the original one and also by using manually classified cases. The typing score of the Mahalanobis algorithm is high for all predominant clusters FNA: 77.0%, BC: 63.9%, and DUST: 80.3% when compared with the training dataset. We obtained high scores as well FNA: 100.0%, BC: 66.7%, and DUST: 83.3% when comparing it with the manually classified dataset. The flags obtained here were applied in the timeseries of the Aerosol Optical Depth (AOD) at 340 nm of the Brewer and the CIMEL in order to compare between the two and also stress the future impact of the proposed clustering technique in climatological studies of the station.
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