A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophy. September 2016. / Numerous studies on the sources, transport and fates of criteria air pollutants and greenhouse gases have been done in southern Africa. However, debate on the priority pollutants and areas of concern continue despite a growing national air quality monitoring network. This study attempts a novel approach to characterise sources and ambient air quality over major industrial and urban areas using a single suite of instrumentation to provide information to improve management of air quality. Over 200 hours of data were collected from an airborne platform. Another 5 ground-based campaigns characterised sources and areas out of reach of the aircraft. The central aim of this study is to prioritise sources and areas of concern with regards to air quality management, using a mobile platform. This complements other modelling and spatial assessments and provides in situ validation for many contemporary debates. The specific aims were to characterise major anthropogenic sources; estimate the state of air quality; investigate the vertical distribution of pollutants; and prioritise sources and areas of concern for effective air quality management in South Africa. The research has delivered many original contributions to the body of knowledge of air quality over South Africa. These findings can be divided into spatial and temporal relationships between sources and receptors, characterising source contributions and understanding the contribution of atmospheric emissions. High resolution measurements show that spatial scales of prominent atmospheric plumes are much smaller than current remote sensing estimates.This underscores the difficulty of accurately assessing environments with diverse, clustered sources and complex meteorology through modelling studies and satellite based remote sensing. The current conceptual model of absolute stable layers is biased because of limited data availability where a limited number of levels are reported. At least 60 levels should be reported in soundings to study absolutely stable layers. The inclusion of the standard reporting levels, (850 hPa, 700 hPa, 500 hPa and 300 hPa), further biases the detection of atmospheric stable layers. The number of observed persistent levels change in number and character when these are omitted from the analysis. Numerous vertical profiles further show that the thermodynamic model of stability as the main driver of stratification is oversimplified, especially close to source regions where different pollutants are observed to peak at different levels unrelated to absolutely stable layers. This suggests that the original buoyancy which is governed by the release temperature, exit velocity and height are important drivers for the stratification of pollutants. The overall conclusion is made that a small team with a set of regular instrumentation can prioritise pollutants and areas of concern on a national scale. This method could be valuable for countries with limited resources and infrastructures and could be used in combination with modelling and satellite based remote sensing to assess priorities. The ability to obtain in situ data of a large number of variables over vast areas in a short time may offsets the caveats associated with mobile measurements and a limited sample volume. / LG2017

A thesis submitted to the Faculty of Geography, Archaeology, and Environmental Studies University of the Witwatersrand, Johannesburg, in fulfilment of the requirements of the degree of Doctor of Philosophy. 2015. / An imaging DOAS instrument, along with in situ trace-gas and aerosol instrumentation was deployed on board a research aircraft over the Highveld region of South Africa, to make regional-scale measurements of nitrogen dioxide (NO2). The presence of a “hotspot” of NO2 over the Highveld is confirmed. Case-study estimates of NO2 emission flux were made downwind of a power station (10 tons.hr−1), a petrochemical plant (36 tons.hr−1) and the entire Highveld region (395 tons.hr−1). Vertical profile measurements were used to develop scenarios for a radiative transfer sensitivity study. From this, suitable air-mass factors for the DOAS measurements were determined. Comparisons between the airborne DOAS and satellite instruments show a good agreement where the spatial scales of the satellite ground pixels and the features in the two-dimensional trace-gas distribution are matched. A long-term record of satellite data was analysed. Analysis of radiative transfer revealed a possible artefact in the adjacent positive and negative trends evident on the Highveld. A correction to the satellite record for a seasonal bias was made, and found to be important over biomass burning regions in Angola and Zambia. Spatial features in a seasonal model of the satellite record are shown to correspond with known urban, industrial and biomass burning sources in the region. Signatures of soil emissions are also detected.

Graduation date: 1987

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Matched weight polyvinyl chloride (PVC) filters are currently available for use in total dust air sampling. This paper studies the utility of employing two superimposed filters in a cassette. Cassettes containing "paired" PVC filters were employed, in the same way matched weight filters would be used, during side by side sampling studies with cassettes housing single PVC filters, to determine whether the presence of two filters in a cassette presented problems during sampling. The effects of dust type, particle breakthrough, moisture concentration, and increased pressure drop from the addition of a second filter were studied. The presence of static electricity between filter pairs was also noted. Under recommended loading conditions "paired" filters seemed to perform as well as single filters in all aspects studied. Due to large filter weight variations found within individual batches of PVC filters, randomly selected filter pairs should not be used as actual matched weight filters.

A field study was conducted to determine the applicability of multivariate geostatistical methods to the problem of estimating and simulating pesticide concentrations in groundwater from measured concentrations of nitrate and pesticide, when pesticide is undersampled. Prior to this study, no published attempt had been made to apply multivariate geostatistics to groundwater contamination. The study was divided into two complementary aspects of geostatistics: estimation and simulation. The use of kriging and cokriging to estimate nitrate and the herbicide dimethyl tetrachloroterepthalate (DCPA) contaminant densities is described in Chapter I. Measured concentrations of nitrate and the DCPA were obtained for 42 wells in a shallow unconfined alluvial and basin-fill aquifer in a 16.5 km² agricultural area in eastern Oregon. The correlation coefficient between log(nitrate) and log(DCPA) was 0.74. Isotropic, spherical models were fitted to experimental direct- and cross-semivariograms with correlation ranges and sliding neighborhoods of 4 km. The relative gain for estimates obtained by cokriging ranged from 14 to 34%. Additional sample locations were selected for nitrate and DCPA using the fictitious point method. A simple economic analysis demonstrated that additional nitrate samples would be more beneficial in reducing estimation variances than additional DCPA samples, unless the costs of nitrate and DCPA analysis were identical. These estimates are by definition, the Best Linear Unbiased Estimates (i.e., the estimates with minimized estimation variance), however the requirement of minimized variance smoothes the variability of contaminant values. The application of conditional simulations to groundwater contamination is described in Chapter 11. Conditional simulation allows the degree of fluctuation of nitrate and DCPA between sample points to be assesed. With knowledge of both the 'best' estimates and the of the variability between sample points, nitrate and DCPA groundwater contamination in the study area can be characterized Based on the semivariogram models found in Chapter I, univariate and multivariate conditional simulations of nitrate and DCPA were generated using the turning bands method and the kriging or cokriging system. Kriging was used to condition the univariate simulations, while cokriging was used to cross-correlate and condition the multivariate simulations. The mean of 25 conditional and coconditional simulations at 8 different locations in the study area were generated and compared to kriging and cokriging estimates and 95% confidence intervals. Both conditional and coconditional simulation of the DCPA and nitrate contaminant densities showed large variations when values in different simulations were compared. The fluctuation in values demonstrate the uncertainties in the contaminant distributions when sample sizes are small. As a result of this unkown component, simulated values vary widely. Coconditional simulation displayed the cross-correlation imposed by using the cokriging system to condition the simulations. After 25 simulations, the mean remained unstable indicating that more simulations would be required to enable comparisons with kriging and cokriging estimates. / Graduation date: 1989

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