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• W2893020899 abstract "Decadal studies (2004–2014) of various aerosols were carried out over South Africa (SA) using various satellite data and model simulations. The aerosols investigated included black carbon (BC), sulphate, dust and marine aerosols. BC aerosols were observed to be dominant in the northeastern parts of SA while sulphate aerosols were dominant in eastern parts of the country. Seasonal studies revealed that BC aerosols were more dominant in the eastern parts of SA during spring and less dominant in autumn. Sulphate also showed dominance in the eastern parts of SA during summer and less dominance in winter. The high sulphate concentration in summer is a result of an increase in relative humidity which favours the production of sulphates. Air masses from the north and northeastern parts of the subcontinent were responsible for the transport of BC resulting from biomass burning into SA. The Goddard Chemistry Aerosol Radiation and Transport model indicated that there was no significant change in the sulphate aerosol trends from 2004 to 2007. The highest sulphate aerosol levels were observed in the summer whilst the lowest sulphate aerosol levels were observed in winter. The Council for Scientific and Industrial Research (CSIR) Light Detection and Ranging (LIDAR) was used to carry out measurements in Lephalale during July 10–18, 2014. Aerosol extinction co‐efficient profiles were retrieved by the CSIR mobile LIDAR and were compared to aerosol extinction co‐efficient profiles retrieved from the Cloud‐Aerosol LIDAR and Infrared Pathfinder Satellite Observations (CALIPSO). The aerosol extinction co‐efficients of 0.26 and 0.17/km on July 14 and 16, 2014, respectively could be identified as dust aerosols." @default.
• W2893020899 created "2018-10-05" @default.
• W2893020899 creator A5016177658 @default.
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• W2893020899 date "2018-12-17" @default.
• W2893020899 modified "2023-10-16" @default.
• W2893020899 title "Investigation of various aerosols over different locations in South Africa using satellite, model simulations and LIDAR" @default.
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• W2893020899 doi "https://doi.org/10.1002/met.1761" @default.
• W2893020899 hasPublicationYear "2018" @default.
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