Respirometric experiments were performed to evaluate the role of nitrogen in aerobic diesel biodegradation. Specific objectives included 1) evaluating the effects of water potential induced by various nitrogen amendments on diesel biodegradation rates in arid region soils, 2) comparing concurrent effects of C:N ratios and soil water potential on diesel degradation rates, and 3), measuring gross rates of nitrogen cycling processes in diesel-contaminated soil to determine duration of fertilizer bioavailability. In all studies, increasing nitrogen fertilization resulted in a decrease in total water potential and correlated with an increase in lag phase and overall reduction in microbial respiration. Highest respiration and estimated diesel degradation was observed in the 250 mg N/kg soil treatments regardless of diesel concentration, nitrogen source, or soil used, suggesting an inhibitory osmotic effect from higher rates of nitrogen application. The depression of water potential resulting in a 50% reduction in respiration was much greater than that observed in humid region soil, suggesting higher salt tolerance by microbial populations of arid region soils. Due to the dependence on contaminant concentrations, use of C:N ratios was problematic in optimizing nitrogen augmentation, leading to over-fertilization in highly contaminated soils. Optimal C:N levels among those tested were 17:1, 34:1, and 68:1 for 5,000, 10,000 and 20,000 mg/kg diesel treatments respectively. Determining nitrogen augmentation on the basis of soil pore water nitrogen (mg N/kg soil H₂0) is independent of hydrocarbon concentration but takes into account soil moisture content. In the soil studied, optimal nitrogen fertilization was observed at an average soil pore water nitrogen level of 1950 mg N/kg H₂0 at all levels of diesel contamination. Based on the nitrogen transformation rates estimated, the duration of fertilizer contribution to the inorganic nitrogen pool at 5,000 mg/kg diesel was estimated at 0.9, 1.9, and 3.2 years in the 250, 500, and 1000 mg/kg nitrogen treatments respectively. The estimation was conservative as ammonium fixation, gross nitrogen immobilization, and nitrification were assumed as losses of fertilizer with only gross mineralization of native organic nitrogen contributing to the most active portion of the nitrogen pool.

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.