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The performance of the AERMOD and ADMS dispersion models was tested using PM10 (thoracic dust) emissions from Rössing Uranium Mine open pit in Namibia. The performance of the two models was evaluated against the observations and also against each other using various statistical measures. The models were tested under different case scenarios (cases explained in chapter 4) with the aim of evaluating their performances as well as their inter model variability. The study was undertaken from the 13 July 2009 – 14 August 2009. The results from the study showed that the performance of ADMS was superior to that of AERMOD. In general, the performance of AERMOD was very poor and simulated extremely high concentration values. AERMOD performed even more poorly during calm conditions. ADMS performance was superior to AERMOD as was evident from the values of various performance statistical measures and a conclusion reached was that ADMS is likely to be a better model to use in cases where prolonged calm conditions are experienced. Copyright / Dissertation (MSc)--University of Pretoria, 2012. / Chemical Engineering / unrestricted

As U.S. landfills continue to grow in size, concerns about odorous gas emissions from landfills are increasing. For states that are expanding in population, such as Florida, odors from landfills are a major concern because new housing developments, needed to accommodate the rapid population growth, are creeping closer and closer to the existing landfills. As homes get closer to landfills, odor complaints are likely to become more frequent, causing landfill managers increased problems with public interactions. Odor buffer zones around landfills need to be established to give municipalities tools to help prevent the building of future homes too close to landfills. Using the latest air dispersion model, AERMOD, research predicted downwind odor concentrations from a Central Florida landfill. Accurate estimates of methane emissions throughout a Central Florida landfill were determined using a new technique developed as part of this research that uses hundreds of ambient air VOC measurements taken within a landfill, as receptors. Hundreds of point sources were placed on the landfill, and the standard Gaussian dispersion equations were solved by matrix inversion methods. The methane emission rates were then used as surrogates for odor emissions to predict downwind odor concentrations via AERMOD. By determining a critical zone around a landfill with regards to odor, stakeholders will be able to meet regulatory issues and assist their communities. Other beneficial uses from this research include: determination of existing gas collection system efficiencies, calculation of fugitive greenhouse gas emissions from municipal solid waste (MSW) landfills, and improved landfill gas management.

Doctor of Philosophy / Department of Biological and Agricultural Engineering / Ronaldo G. Maghirang / Emission of particulate matter (PM) and various gases from open-lot beef cattle feedlots is becoming a concern because of the adverse effects on human health and the environment; however, scientific information on feedlot emissions is limited. This research was conducted to estimate emission rates of PM[subscript]10 from large cattle feedlots. Specific objectives were to: (1) determine feedlot PM[subscript]10 emission rates by reverse dispersion modeling using AERMOD; (2) compare AERMOD and WindTrax in terms of their predicted concentrations and back-calculated PM[subscript]10 emission rates; (3) examine the sensitivity of both AERMOD and WindTrax to changes in meteorological parameters, source location, and receptor location; (4) determine feedlot PM[subscript]10 emission rates using the flux-gradient technique; and (5) compare AERMOD and computational fluid dynamics (CFD) in simulating particulate dispersion from an area source. PM[subscript]10 emission rates from two cattle feedlots in Kansas were determined by reverse dispersion modeling with AERMOD using PM[subscript]10 concentration and meteorological measurements over a 2-yr period. PM[subscript]10 emission rates for these feedlots varied seasonally, with overall medians of 1.60 and 1.10 g /m[superscript]2 -day. Warm and prolonged dry periods had significantly higher PM emissions compared to cold periods. Results also showed that the PM[subscript]10 emissions had a diurnal trend; highest PM[subscript]10 emission rates were observed during the afternoon and early evening periods. Using particulate concentration and meteorological measurements from a third cattle feedlot, PM[subscript]10 emission rates were back-calculated with AERMOD and WindTrax. Higher PM[subscript]10 emission rates were calculated by AERMOD, but their resulting PM[subscript]10 emission rates were highly linear (R[superscript]2 > 0.88). As such, development of conversion factors between these two models is feasible. AERMOD and WindTrax were also compared based on their sensitivity to changes in meteorological parameters and source locations. In general, AERMOD calculated lower concentrations than WindTrax; however, the two models responded similarly to changes in wind speed, surface roughness, atmospheric stability, and source and receptor locations. The flux-gradient technique also estimated PM[subscript]10 emission rates at the third cattle feedlot. Analyses of PM[subscript]10 emission rates and meteorological parameters indicated that PM[subscript]10 emissions at the feedlot were influenced by friction velocity, sensible heat flux, temperature, and surface roughness. Based on pen surface water content measurements, a water content of at least 20% (wet basis) significantly lowered PM[subscript]10 emissions at the feedlot. The dispersion of particulate from a simulated feedlot pen was predicted using CFD turbulence model ([kappa]-[epsilon] model) and AERMOD. Compared to CFD, AERMOD responded differently to wind speed setting, and was not able to provide detailed vertical concentration profiles such that the vertical concentration gradients at the first few meters from the ground were negligible. This demonstrates some limitations of AERMOD in simulating dispersion for area sources such as cattle feedlots and suggests the need to further evaluate its performance for area source modeling.