A comprehensive deposition and dispersion model was built for the South African Highveld and Waterberg areas using CALPUFF with the aim of studying the effects of biogenic NOx emissions on sulphur and nitrogen deposition. The effect of industrial H2S emission on sulphur deposition was also investigated for the Highveld. Emission sources inventoried or the Highveld and Waterberg area included industrial sources, vehicle exhaust emissions, household fuel burning emissions and emissions from power stations. The Highveld model was the most extensive. Three scenarios were modelled: average rainfall year (2001), below average rainfall year (2003) and above average rainfall year (2010). The modelling domain was 350 km × 350 km. The Waterberg priority area was only modelled for 2006 and the domain size was 130 km ×100 km. To quantify biogenic soil NOX emissions, models was constructed for both areas using land use data from CALMET, rainfall data and atmospheric ground level temperatures covering each modelling domain. Use was made of work done by Yienger and Levy (1995). To accommodate CALPUFF each area was divided into smaller area sources, each with a specific hourly NOX emission rate. The biogenic NOx emitted made up 3.96 %, 4.14 % and 3.34 % of total released NOx for 2001, 2003 and 2010 respectively. This is significantly more than is released by household fuel burning, small industrial sources and biomass burning. Dry nitrogen deposition rates were affected most, adding between 1.69 - 6.19 % at various receptor locations. Wet deposition rates were affected very little (0.13 % to 0.75 %). Effect on total nitrogen deposition rates ranged from 0.32 % to 1.77 %. CALPUFF was unable to account for H2S conversion to SO2 in its reaction scheme model, therefore conversion rates had to be approximated from observations made on the Highveld by Igbafe (2007). Assuming different conversion percentages for each season, and inputting the converted emissions rates as SO2 emissions sources into CALPUFF, it was predicted that H2S contributes an average of 4.85 %, an average of 5.95 %, and an average of 5.15 % for wet S, dry S and total S deposition respectively Highveld dispersion and deposition predictions are reported on for the three modelling periods of 2001, 2003 and 2010. The modelled biogenic emissions were included in the model. Spatial plots for wet, dry and total S and N deposition were produced. Wet, dry and total S and N deposition rates at specific receptor locations are reported on. Waterberg biogenic emission are only 2.3 % of total NOx emissions for the Waterberg area and would affect nitrogen deposition values very little compared to the nitrogen deposition produced by the emissions from Matimba and Medupi power stations. Because of this it was decided not to run a CALPUFF dispersion and deposition model for the Waterberg area. / Dissertation (MEng)--University of Pretoria, 2017. / Chemical Engineering / MEng / Unrestricted

A megacity is generally defined as a city that, together with its suburbs or recognised metropolitan area, has a total population of more than 10 million people. Air pollution in megacities is a major concern due to large increases of populations over the past decades. Increases of air pollution result from more anthropogenic emission sources in megacities, which include energy production, transportation, industrial activities and domestic fuel burning. In the developing parts of Africa, urbanisation is increasing rapidly, with growth rates of populations in cities of up to 5% per annum. The major driving forces for these population increases in African countries can be attributed to population growth, natural disasters and armed ethnic conflicts. In South Africa, 62% of the total population lived in cities in 2010. The rate of urbanisation growth is predicted to be 1.2% per annum. The largest urbanised city in South Africa is the Johannesburg-Pretoria conurbation (referred to as Jhb-Pta megacity) that has more than 10 million inhabitants. Johannesburg is considered to be the central hub of economic activities and -growth in South Africa. The larger conurbation includes all the suburbs of Johannesburg and Pretoria. In South Africa, household combustion and traffic emissions are major sources of pollutants in urbanised areas. The major pollutants emitted from these activities include nitrogen oxide (NO), nitrogen dioxide (NO 2 ), sulphur dioxide (SO2 ), carbon monoxide (CO), particular matter (PM) and various organic compounds. The Jhb-Pta megacity is also located relatively close to large industrialised regions in South Africa, i.e. the Mpumalanga Highveld and the Vaal Triangle. Very few air quality modelling studies have been conducted for the Jhb-Pta megacity. According to the knowledge of the author, no literature existed in peer-reviewed publications at the time of the study. An in-depth modelling study was therefore conducted to assess the current state of air quality within the Jhb-Pta megacity. The main objectives were to optimise an existing photochemical box model for the Jhb-Pta megacity and to utilise the model to investigate the photochemical processes in the Jhb-Pta megacity and surrounding areas. In this investigation, ground-based measurements of criteria atmospheric pollutant species representative of the Jhb- Pta megacity were obtained to utilise as input data in the model, as well as to compare to results determined with the model. From the ground-based measurements, the possible contribution of the Jhb-Pta megacity to the NO2 hotspot observed over the South African Highveld from satellite retrievals was also contextualised. Five ground-based monitoring sites were situated strategically within the boundaries of the Jhb- Pta megacity to measure the direct influences of urban air pollution, e.g. traffic emissions, biomass burning and residential pollution. One measurement site was situated outside the modelling domain in order to collect rural background data in close proximity to the Jhb-Pta megacity. All the air quality stations continuously measured the criteria pollutants NOx, SO2 and O3. In addition, benzene, toluene, ethylbenzene and xylene (BTEX) were measured at four sites. Passive sampling of NOx, SO2 , O3 and BTEX was also conducted in March and April 2010. Active data was obtained for March to May 2009, since no active measurements were available for the same year that passive sampling was performed due to logistical reasons. Meteorological parameters that included temperature, pressure and relative humidity were also measured at the monitoring stations Ground-based measurements provided a good indication of the state of the air quality in the Jhb-Pta megacity. The air quality levels of NO2 , SO2 , O3 and BTEX could be compared to other cities in the world. A distinct diurnal cycle was observed for NO2 at most of the stations. An early morning peak between 6:00 and 9:00 coincided with the time that commuters travel to work, whereas an evening peak between 18:00 and 21:00 could be attributed to traffic emissions and household combustion. Levels of O3, which is a secondary pollutant, peaked between 13:00 and 15:00. This diurnal pattern could be attributed to the photochemical formation of O3 from precursor species NO and VOCs. Toluene was predominantly higher than the other BTEX species. Benzene and xylene concentrations were in the same order, while the lowest levels were measured for ethyl benzene Ground-based measurements also indicated that the NO2 Highveld hotspot, which is well known in the international science community due to its prominence in satellite images, is accompanied by a second hotspot over the Jhb-Pta megacity. Peak NO2 pollution levels in the Jhb-Pta megacity exceeded the maximum daily Highveld values during the morning and evening rush hours. This result is significant for the more than 10 million people living in the Jhb-Pta megacity. Although satellite instruments have been extremely valuable in pointing out global hotspots, a limitation of satellite retrievals due to their specific overpass times has been presented. Chemical processes in the Jhb-Pta megacity were investigated by utilising an existing photochemical box model, i.e. MECCA-MCM. This model was further developed in this study and was termed the MECCA-MCM-UPWIND model. This model included horizontal and vertical mixing processes in the atmosphere. These processes were included to simulate the advection of upwind air masses into the modelling domain, as well as the entrainment from the troposphere resulting from the diurnal mixing layer (ML) height variation. Three processes, i.e. horizontal mixing, vertical mixing and ML height variation, were built into the MECCA-MCM- UPWIND model. The model was tested and evaluated to determine the efficiency of the model to represent atmospheric mixing processes. MECCA-MCM-UPWIND simulated horizontal mixing, vertical entrainment and ML height variations as expected. The input data for the model runs for the Jhb-Pta megacity modelling runs were either obtained from ground-based measurements or literature. Input data included meteorology, emission inventory, ML height and mixing ratios of the atmospheric chemical species. The chemical composition of the air mass entering the Jhb-Pta megacity was determined with MECCA-MCM- UPWIND. The concentrations and diurnal variability of criteria pollutant species were well predicted with the MECCA-MCM-UPWIND model. The day-time chemistry, especially, compared well, while slight under-predictions were observed for the night-time chemistry for most of the species. The differences observed between modelled and measured data could partially be ascribed to uncertainties associated with some of the input data obtained from literature used. The MECCA-MCM-UPWIND model was used to perform sensitivity studies on the influence of different parameters on O3 levels in the Jhb-Pta megacity. Possible scenarios to alter or mitigate pollution were also investigated. The results from the sensitivity analyses showed that O3 mixing ratios decreased within the Jhb-Pta megacity with increasing wind speeds. The contribution of local emissions to the change in the concentration of pollutants is reduced at higher wind speeds. It also indicated that the Mpumalanga Highveld can potentially be a source of NOx in the Jhb-Pta megacity that can lead to the titration of O3 . This also implies that if the air quality of the surrounding area improves, the concentration of the secondary pollutant O 3 will increase in the Jhb-Pta megacity due to the decrease in the titration of O3 . Sensitivity analyses also indicated that the Jhb-Pta megacity is a VOC-limited (or NOx-saturated) regime. Therefore, O3 reduction in the Jhb-Pta megacity will mostly be effective if VOC emissions are reduced. The same effect was observed in various cities world-wide where O3 increased when NOx emissions the Jhb-Pta megacity on the instantaneous production of O 3 was also investigated. A significant increase of approximately 23ppb O3 production was observed when changing from Euro-0 to Euro-3 vehicles with lower emissions of VOCs, NOx and CO. This compares with other modelled sensitivity studies of traffic emissions that also predict that future urban O 3 concentrations will increase in many cities by 2050 due to the reduction in the NOx titration of O3 despite the implementation of O3 control regulations / Thesis (PhD (Environmental Sciences))--North-West University, Potchefstroom Campus, 2013

A megacity is generally defined as a city that, together with its suburbs or recognised metropolitan area, has a total population of more than 10 million people. Air pollution in megacities is a major concern due to large increases of populations over the past decades. Increases of air pollution result from more anthropogenic emission sources in megacities, which include energy production, transportation, industrial activities and domestic fuel burning. In the developing parts of Africa, urbanisation is increasing rapidly, with growth rates of populations in cities of up to 5% per annum. The major driving forces for these population increases in African countries can be attributed to population growth, natural disasters and armed ethnic conflicts. In South Africa, 62% of the total population lived in cities in 2010. The rate of urbanisation growth is predicted to be 1.2% per annum. The largest urbanised city in South Africa is the Johannesburg-Pretoria conurbation (referred to as Jhb-Pta megacity) that has more than 10 million inhabitants. Johannesburg is considered to be the central hub of economic activities and -growth in South Africa. The larger conurbation includes all the suburbs of Johannesburg and Pretoria. In South Africa, household combustion and traffic emissions are major sources of pollutants in urbanised areas. The major pollutants emitted from these activities include nitrogen oxide (NO), nitrogen dioxide (NO 2 ), sulphur dioxide (SO2 ), carbon monoxide (CO), particular matter (PM) and various organic compounds. The Jhb-Pta megacity is also located relatively close to large industrialised regions in South Africa, i.e. the Mpumalanga Highveld and the Vaal Triangle. Very few air quality modelling studies have been conducted for the Jhb-Pta megacity. According to the knowledge of the author, no literature existed in peer-reviewed publications at the time of the study. An in-depth modelling study was therefore conducted to assess the current state of air quality within the Jhb-Pta megacity. The main objectives were to optimise an existing photochemical box model for the Jhb-Pta megacity and to utilise the model to investigate the photochemical processes in the Jhb-Pta megacity and surrounding areas. In this investigation, ground-based measurements of criteria atmospheric pollutant species representative of the Jhb- Pta megacity were obtained to utilise as input data in the model, as well as to compare to results determined with the model. From the ground-based measurements, the possible contribution of the Jhb-Pta megacity to the NO2 hotspot observed over the South African Highveld from satellite retrievals was also contextualised. Five ground-based monitoring sites were situated strategically within the boundaries of the Jhb- Pta megacity to measure the direct influences of urban air pollution, e.g. traffic emissions, biomass burning and residential pollution. One measurement site was situated outside the modelling domain in order to collect rural background data in close proximity to the Jhb-Pta megacity. All the air quality stations continuously measured the criteria pollutants NOx, SO2 and O3. In addition, benzene, toluene, ethylbenzene and xylene (BTEX) were measured at four sites. Passive sampling of NOx, SO2 , O3 and BTEX was also conducted in March and April 2010. Active data was obtained for March to May 2009, since no active measurements were available for the same year that passive sampling was performed due to logistical reasons. Meteorological parameters that included temperature, pressure and relative humidity were also measured at the monitoring stations Ground-based measurements provided a good indication of the state of the air quality in the Jhb-Pta megacity. The air quality levels of NO2 , SO2 , O3 and BTEX could be compared to other cities in the world. A distinct diurnal cycle was observed for NO2 at most of the stations. An early morning peak between 6:00 and 9:00 coincided with the time that commuters travel to work, whereas an evening peak between 18:00 and 21:00 could be attributed to traffic emissions and household combustion. Levels of O3, which is a secondary pollutant, peaked between 13:00 and 15:00. This diurnal pattern could be attributed to the photochemical formation of O3 from precursor species NO and VOCs. Toluene was predominantly higher than the other BTEX species. Benzene and xylene concentrations were in the same order, while the lowest levels were measured for ethyl benzene Ground-based measurements also indicated that the NO2 Highveld hotspot, which is well known in the international science community due to its prominence in satellite images, is accompanied by a second hotspot over the Jhb-Pta megacity. Peak NO2 pollution levels in the Jhb-Pta megacity exceeded the maximum daily Highveld values during the morning and evening rush hours. This result is significant for the more than 10 million people living in the Jhb-Pta megacity. Although satellite instruments have been extremely valuable in pointing out global hotspots, a limitation of satellite retrievals due to their specific overpass times has been presented. Chemical processes in the Jhb-Pta megacity were investigated by utilising an existing photochemical box model, i.e. MECCA-MCM. This model was further developed in this study and was termed the MECCA-MCM-UPWIND model. This model included horizontal and vertical mixing processes in the atmosphere. These processes were included to simulate the advection of upwind air masses into the modelling domain, as well as the entrainment from the troposphere resulting from the diurnal mixing layer (ML) height variation. Three processes, i.e. horizontal mixing, vertical mixing and ML height variation, were built into the MECCA-MCM- UPWIND model. The model was tested and evaluated to determine the efficiency of the model to represent atmospheric mixing processes. MECCA-MCM-UPWIND simulated horizontal mixing, vertical entrainment and ML height variations as expected. The input data for the model runs for the Jhb-Pta megacity modelling runs were either obtained from ground-based measurements or literature. Input data included meteorology, emission inventory, ML height and mixing ratios of the atmospheric chemical species. The chemical composition of the air mass entering the Jhb-Pta megacity was determined with MECCA-MCM- UPWIND. The concentrations and diurnal variability of criteria pollutant species were well predicted with the MECCA-MCM-UPWIND model. The day-time chemistry, especially, compared well, while slight under-predictions were observed for the night-time chemistry for most of the species. The differences observed between modelled and measured data could partially be ascribed to uncertainties associated with some of the input data obtained from literature used. The MECCA-MCM-UPWIND model was used to perform sensitivity studies on the influence of different parameters on O3 levels in the Jhb-Pta megacity. Possible scenarios to alter or mitigate pollution were also investigated. The results from the sensitivity analyses showed that O3 mixing ratios decreased within the Jhb-Pta megacity with increasing wind speeds. The contribution of local emissions to the change in the concentration of pollutants is reduced at higher wind speeds. It also indicated that the Mpumalanga Highveld can potentially be a source of NOx in the Jhb-Pta megacity that can lead to the titration of O3 . This also implies that if the air quality of the surrounding area improves, the concentration of the secondary pollutant O 3 will increase in the Jhb-Pta megacity due to the decrease in the titration of O3 . Sensitivity analyses also indicated that the Jhb-Pta megacity is a VOC-limited (or NOx-saturated) regime. Therefore, O3 reduction in the Jhb-Pta megacity will mostly be effective if VOC emissions are reduced. The same effect was observed in various cities world-wide where O3 increased when NOx emissions the Jhb-Pta megacity on the instantaneous production of O 3 was also investigated. A significant increase of approximately 23ppb O3 production was observed when changing from Euro-0 to Euro-3 vehicles with lower emissions of VOCs, NOx and CO. This compares with other modelled sensitivity studies of traffic emissions that also predict that future urban O 3 concentrations will increase in many cities by 2050 due to the reduction in the NOx titration of O3 despite the implementation of O3 control regulations / Thesis (PhD (Environmental Sciences))--North-West University, Potchefstroom Campus, 2013