THESIS TITLE: Spatiotemporal Analysis of Aerosol Total, Absorptive, Scattering and Radiative Characteristics Over East Africa from Model-and Spectroscopic-Based Measurements

 STUDENT NAME: Khamala Geoffrey Wanjala

 SUPERVISORS NAME:

1. Prof John W. Makokha

2. Dr. Richard K. Boiyo

ABSTRACT

The unprecedented increase in anthropogenic activities coupled with the prevailing climatic conditions has increased the aerosol load over East Africa (EA). The aerosols have had detrimental effect to the local climate, human health and environment. There is therefore need for intensive characterization of aerosols properties over different domains, especially those that have lagged behind the rest of the world, such as EA. Given this, the present study has presented a spatiotemporal analysis of total aerosol optical depth (TAOD), absorptive aerosol optical depth (AAOD), scattering aerosol optical depth (SAOD) and direct aerosol radiative forcing (DARF) aerosol characteristics together with microphysical properties at distinct spatio-temporal scales over East Africa. The aerosol characteristics and net fluxes from multiple satellite sensors, Modern-Era Retrospective Analysis for Research and Applications (MERRA-2) model and AErosol RObotic NETwork (AERONET) data from January 2001 to December 2019 were used to achieve its objectives. Further, the correlation between aerosol characteristics and selected meteorological parameters has been determined and trend prediction in aforementioned parameters achieved using Autoregressive Integrated Moving Average (ARIMA) model. The Coupled Ocean and Atmospheric Radiative Transfer (COART) model and First Law of Thermodynamics equations together with Hydrostatic Balance equation were utilized in computing spatial-temporal radiative forcing as coerced by aerosols. The spatial patterns of seasonal mean AOD from the Moderate-resolution Imaging Spectroradiometer (MODIS) and MERRA-2 were characterized with high (>0.35) and low (<0.2) AOD centers over EA observed during the local dry and wet seasons, respectively. While on trends, the spatial trend revealed a significant increase in TAOD over arid and semi-arid zones of the northeastern part of EA with local dry (wet) months generally experiencing positive (negative) trends. High and significant positive trends in AAOD dominated the study domain, attributed to an increased biomass burning, vehicular emissions and changes in the rainfall pattern. The DARF at TOA and BOA were notably negative and positive at ATM with the annual mean forcing of -3.572 Wm⁻², -8.637 Wm⁻² and 5.065 Wm⁻² respectively. Aerosol absorption, size and volume properties exhibited a bimodal distribution with substantial seasonal assortment in peak values being low (high) during the local wet (dry) seasons. The classification of absorbing aerosols over the study domain showed varying absorption strength ranging from strongly absorbing fine-mode aerosols to strongly absorbing coarse-mode aerosols. However, mixed absorbing aerosols dominated most EA. Lastly, stochastic behavior of TAOD, SAOD, AAOD and DARF in ARIMA portrays a clear seasonal variation with the analysis of the statistical parameters (RMSE, MAE, MAPE, MASE and normalized BIC) showing model to be adequate for forecasting. The model ascertained has been used to forecast aerosol characteristics and can therefore be applied to other fields of study such as climatology, climate change among other areas to predict the future values so that timely control measures can effectively be planned.