Thesis (MTech (Environmental Health))--Cape Peninsula University of Technology, 2019. / Background: A recent review on the effects of ambient air pollution on human health in sub-Saharan Africa, specifically calls for an urgent need for more epidemiological studies in developing countries due to a lack of data in these countries. Air pollution information on exposure is important for understanding and addressing its public health impact in developing countries. In many African countries, the spatial distribution of air pollutants has not been quantified even though air pollution is a global public health risk. The main goal of the study was to quantify and compare the seasonal spatial variation of household air pollution in the 4 Western Cape neighbourhoods. Methods: Weekly indoor and outdoor measurements of Particulate Matter (PM2.5), Sulphur dioxide (SO2), Ozone (O3), Carbon monoxide (CO) and Nitrogen dioxide (NO2) were conducted at 127 households in four informal settlement areas (Khayelitsha, Marconi-Beam, Masiphumulele and Oudtshoorn) during one month each in summer and winter. PM2.5 measurements were conducted using Mesa Labs GK2.05 (KTL) cyclone with the GilAir Plus Air Sampling Pump, Gases were measured using Passam passive samplers. Statistical analyses were performed using Stata V12. Simple linear regression was used to evaluate the relationship between continuous exposure levels and the respective predictor variables. These include distance to major roads, bus routes, open grills and waste burning sites. Results: The highest average weekly outdoor PM2.5 and NO2 concentrations for summer were recorded in Milnerton (8.76 µg/m3 and 16.32 µg/m3 respectively). However, the highest average concentrations during winter for PM2.5 were recorded in Oudtshoorn (PM2.5: 16.07 µg/m3), whilst the highest NO2, was recorded in Khayelitsha (NO2: 35.69 µg/m3). SO2 levels were consistently low during both seasons. Noordhoek generally recorded the lowest average levels for all pollutants. Winter average weekly concentrations were generally higher than the levels recorded in summer for all pollutants. In a sub-sample of indoor and outdoor measurements, the results were comparable for PM2.5, NO2 and CO. However, the results of Ozone (O3) showed relatively higher (~10 times) outdoor compared to indoor levels. Linear regression modelling results revealed that significant predictors of elevated exposure to PM2.5 were proximity to construction activities and open grills. Analysis demonstrated a clear dose-response relationship with distance, with open grills within 1000m associated with a 0.33 µg/m3 increase in PM2.5 to 6.77 µg/m3 at a distance of 25 meters. Results from the linear regression modelling revealed that significant predictors of exposure to NO2 were proximity to rapid transport bus stops, bus routes, taxi routes and major routes. Distance to rapid transport bus stops demonstrated an increase in NO2 between 0.09 µg/m3 (at 1km) to 2.16 µg/m3 (at 50m) during summer. A similar pattern was observed for taxi routes and bus routes displaying an increase of 6.26 μg/m3and 6.82 μg/m3 respectively within the proximity of 1000 meters. / MAUERBERGER Foundation Scholarship

South Africa is coming under increasing pressure to conform to the rest of the world in terms of emissions regulations. The pressure is caused by a number of factors: international organisations requiring local companies to adhere to environmental conservation policies, evidence from within South Africa that efforts are being made to reduce environmental pollution in line with other countries and keeping abreast of the latest technologies that have been incorporated into vehicles to reduce emissions. In light of these problems associated with emiSSions, a study was initiated by the Department of Transport and the School of Bioresources Engineering and Environmental Hydrology at the University of Natal to investigate and develop a method of predicting emissions from a diesel engine. The main objective of this research was to incorporate this model into SimTrans in order to estimate emissions generated from a vehicle while it is travelling along specific routes in South Africa. SimTrans is a mechanistically based model, developed at the School, that simulates a vehicle travelling along a route, requiring input for the road profile and vehicle and engine specifications. After a preliminary investigation it was decided to use a neural network to predict emissions, as it provides accurate results and is more suitable for a quantitative analysis which is what was required for this study. The emissions that were predicted were NOx (Nitric oxide-NO and Nitric dioxide-N02), CO (carbon monoxide), HC (unbumt hydrocarbons) and particulates. The neural netWork was trained on emissions data obtained from an ADE 447Ti engine. These neural networks were then integrated into the existing SimTrans. Apart from the neural network, an algorithm to consider the effect of ambient conditions on the output of the engine was also included in the model. A sensitivity analysis was carried out using the model to prioritise the factors affecting emissions. Finally using the data for the ADE 447Ti engine, a trip with a Mercedes Benz 2644S-24 was simulated using different scenarios over the routes from Durban to Johannesburg and Cape Town to Johannesburg in South Africa to quantify the emissions that were generated. / Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 2002.

Seed-oil based biodiesel production particularly biodiesel production from the nonedible oil seed bearing plant - Jatropha curcas L. - is a key strategic direction outlined in the biofuels strategy of the Government of Ethiopia. The main objective underlying the strategy include substitution of imported diesel oil used in the road transport sector while at the same time contributing to the local and global greenhouse gasses (GHG) reduction efforts. In this study the environmental benefits and costs of production and use of Jatropha biodiesel in the road transport sector of Ethiopia is assessed using a life cycle analysis (LCA) methodology. The analysis focused on determining the potential environmental impacts and net non-renewable energy saving potential of biodiesel from Jatropha oil-seeds using the following metrics: (i) Net Greenhouse Gas (GHG) reduction, and (ii) Net Energy Balance (NEB) relative to diesel oil. The study shows that the net GHG emissions reduction potential of Jatropha Methyl Ester (JME) is highly influenced by the magnitude of initial carbon loss occurring in the process of conversion of different land uses to Jatropha plantation, and less so on other unit processes of JME production system analysed. The NEB of JME relative to use of diesel oil per functional unit of one GJ is less sensitive to impacts of land use change and is generally positive. Where no land use change impacts is considered, or where Jatropha is grown on lands with low carbon stock such as grasslands, substitution of diesel oil with JME in Ethiopia can provide GHG emission reduction of about 43%, and for each MJ of JME produced the nonrenewable energy requirement will be 0,38 MJ. Production of JME by converting lands with high above ground, below ground and/or soil carbon stocks such as shrub lands or well stocked forest lands will result in net loss of carbon and require ecological carbon payback time of 50 to hundreds of years. The impact of introducing and use of JME-diesel oil blends by Anbassa City Bus Services Enterprise (ACBSE) bus fleets shows that, displacement of diesel oil with JME that have positive GHG reduction potential, will also contribute to the reduction of air pollutants and improvement of ambient air quality in Addis Ababa. Two key recommendations of this research work are that to ensure environmental sustainability of biodiesel production from Jatropha seeds (i) land availability and land suitability assessment for estimating the potential available land for Jatropha (and other oil-seed bearing plants) shall be conducted, and (ii) minimum requirements on GHG reduction and NEB requirements on biodiesel shall be established. / Environmental Sciences / M. Sc. (Environmental Management)