| Summary: | Ph. D. University of KwaZulu-Natal, Durban 2015. Aerosols and cloud play a major role in understanding and interpreting the varying earth’s energy budget. It is necessary to characterize these atmospheric particles by their sizes, chemical composition, water content etc. Aerosols can both cause heating and cooling depending on what they are made of; dust will generally tend to scatter leading to cooling effect while some species of black carbon will absorb sunlight thereby causing a heating effect. In order to assess their impact on global climate, a multiple measurement approach is necessary and specifically, we need long and short term ground-based measurements in clean and polluted environment and long term satellite measurements. In this thesis, we have used aerosol measurements from CIMEL Sunphotometer (part of the world-wide network; Aerosol Robotic Network: AERONET) over, Pretoria (25.75º S, 28.28º E) and Skukuza (24.9º S, 31.5º E) in South Africa, and satellite data from Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR). Pretoria is situated in industrial region with adequate influence of urban/industrial aerosols while Skukuza is an agricultural based region with frequent burning of agricultural waste to clear the harvest during the late winter, spring and summer seasons. Thus, the study over industrial and agricultural regions explores more understanding about the regional radiative forcing in relation to aerosol loading and meteorology. MODIS satellite data was utilized for addressing long term trend in aerosol loading and cloud interaction studies over different locations of South Africa where no ground based sunphotometer data are available. Using six months sunphotometer data (July–December 2012), aerosol characteristics over Gorongosa were studied with particular attention to how aerosol loading evolves during the biomass burning season (spring) including pre- and post-months. The results revealed that the monthly mean aerosol optical depth ...
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