Earth's radiation budget is directly influenced by aerosols through the absorption of solar radiation and subsequent heating of the atmosphere. Aerosols modulate the hydrological cycle indirectly by modifying cloud properties, precipitation and ocean heat storage. In addition, polluting aerosols impose health risks in local, regional and global scales. In spite of recent advances in the study of aerosols variability, uncertainty in their spatial and temporal distributions still presents a challenge in the understanding of climate variability. For example, aerosol loading varies not only from year to year but also on higher frequency intraseasonal time scales producing strong variability on local and regional scales. An assessment of the impact of aerosol variability requires long period measurements of aerosols at both regional and global scales. The present dissertation compiles a large database of remotely sensed aerosol loading in order to analyze its spatio-temporal variability, and how this load interacts with different variables that characterize the dynamic and thermodynamic states of the environment. Aerosol Index (AI) and Aerosol Optical Depth (AOD) were used as measures of the atmospheric aerosol load. In addition, atmospheric and oceanic satellite observations, and reanalysis datasets is used in the analysis to investigate aerosol-environment interactions. A diagnostic study is conducted to produce global and regional aerosol satellite climatologies, and to analyze and compare the validity of aerosol retrievals. We find similarities and differences between the aerosol distributions over various regions of the globe when comparing the different satellite retrievals. A nonparametric approach is also used to examine the spatial distribution of the recent trends in aerosol concentration. A significant positive trend was found over the Middle East, Arabian Sea and South Asian regions strongly influenced by increases in dust events. Spectral and composite analyses of surface temperature, atmospheric wind, geopotential height, outgoing longwave radiation, water vapor and precipitation together with the climatology of aerosols provide insight on how the variables interact. Different modes of variability, especially in intraseasonal time scales appear as strong modulators of the aerosol distribution. In particular, we investigate how two modes of variability related to the westward propagating synoptic African Easterly Waves of the Tropical Atlantic Ocean affect the horizontal and vertical structure of the environment. The statistical significance of these two modes is tested with the use of two different spectral techniques. The pattern of propagation of aerosol load shows good correspondence with the progression of the atmospheric and oceanic synoptic conditions suitable for dust mobilization over the Atlantic Ocean. We present extensions to previous studies related with dust variability over the Atlantic region by evaluating the performance of the long period satellite aerosol retrievals in determining modes of aerosol variability. Results of the covariability between aerosols-environment motivate the use of statistical regression models to test the significance of the forecasting skill of daily AOD time series. The regression models are calibrated using atmospheric variables as predictors from the reanalysis variables. The results show poor forecasting skill with significant error growing after the 3rd day of the prediction. It is hypothesized that the simplicity of linear models results in an inability to provide a useful forecast.

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

Aerosols contribute the largest uncertainty to estimates of radiative forcing of the Earth’s atmosphere, which are thought to exert a net negative radiative forcing, offsetting a potentially significant but poorly constrained fraction of the positive radiative forcing associated with greenhouse gases. Aerosols perturb the Earth’s radiative balance directly by absorbing and scattering radiation and indirectly by acting as cloud condensation nuclei, altering cloud albedo and potentially cloud lifetime. One of the major factors governing the uncertainty in estimates of aerosol direct radiative forcing is the poorly constrained aerosol single scattering albedo, which is the ratio of the aerosol scattering to extinction. In this thesis, I describe a new instrument for the measurement of aerosol optical properties using photoacoustic and cavity ring-down spectroscopy. Characterisation is performed by assessing the instrument minimum sensitivity and accuracy as well as verifying the accuracy of its calibration procedure. The instrument and calibration accuracies are assessed by comparing modelled to measured optical properties of well-characterised laboratory-generated aerosol. I then examine biases in traditional, filter-based absorption measurements by comparing to photoacoustic spectrometer absorption measurements for a range of aerosol sources at multiple wavelengths. Filter-based measurements consistently overestimate absorption although the bias magnitude is strongly source-dependent. Biases are consistently lowest when an advanced correction scheme is applied, irrespective of wavelength or aerosol source. Lastly, I assess the sensitivity of the direct radiative effect of biomass burning aerosols to aerosol and cloud optical properties over the Southeast Atlantic Ocean using a combination of offline radiative transfer modelling, satellite observations and global climate model simulations. Although the direct radiative effect depends on aerosol and cloud optical properties in a non-linear way, it appears to be only weakly dependent on sub-grid variability.

<p>A study of air mass origin’s effect on marine stratus and stratocumulus clouds has been performed on clouds north of Scandinavia between 2000 and 2004. The aerosol number size distribution of the air masses has been obtained from measurements in northern Finland. A trajectory model has been used to calculate trajectories to and from the measurement stations. The back trajectories were calculated using the measurement site as receptor to make sure the air masses had the right origin, and forward trajectories were calculated from receptor stations to assure adequate flow conditions. Satellite data of microphysical parameters of clouds from the Moderate Resolution Imaging Spectrometer (MODIS) has been downloaded where the trajectories indicated that clouds could be studied, and where the satellite images displayed low-level clouds. The 25 % days with the highest number of aerosol with a diameter over 80 nm (N₈₀) and the 35% with the lowest N₈₀ have been used to represent polluted and clean conditions respectively. After screening trajectories and satellite imagery, 22 cases of clouds with northerly trajectories that had low N₈₀ values (i.e. clean) and 25 southerly cases with high N₈₀ values (i.e. polluted) where identified for further analysis.</p><p>   The average cloud optical thickness (τ) for all polluted pixels was more than twice that of the clean pixels. This can most likely be related to the differences in aerosol concentrations in accordance with the indirect effect, yet some difference in τ caused by different meteorological situations cannot be ruled out. The mean cloud droplet effective radius (a_ef) was for the polluted pixels 11.2 µm and for the clean pixels 15.5 µm, which results in a difference of 4.3 µm and clearly demonstrates the effect that increased aerosol numbers has on clouds. A non-linear relationship between a_ef and N₈₀ has been obtained which indicates that changes in lower values of aerosol numbers affect a_ef more than changes in larger aerosol loads. The results from this study also indicate that there is a larger difference in the microphysical cloud parameters between the polluted and clean cases in spring and autumn than in summer.</p>

A study of air mass origin’s effect on marine stratus and stratocumulus clouds has been performed on clouds north of Scandinavia between 2000 and 2004. The aerosol number size distribution of the air masses has been obtained from measurements in northern Finland. A trajectory model has been used to calculate trajectories to and from the measurement stations. The back trajectories were calculated using the measurement site as receptor to make sure the air masses had the right origin, and forward trajectories were calculated from receptor stations to assure adequate flow conditions. Satellite data of microphysical parameters of clouds from the Moderate Resolution Imaging Spectrometer (MODIS) has been downloaded where the trajectories indicated that clouds could be studied, and where the satellite images displayed low-level clouds. The 25 % days with the highest number of aerosol with a diameter over 80 nm (N80) and the 35% with the lowest N80 have been used to represent polluted and clean conditions respectively. After screening trajectories and satellite imagery, 22 cases of clouds with northerly trajectories that had low N80 values (i.e. clean) and 25 southerly cases with high N80 values (i.e. polluted) where identified for further analysis.    The average cloud optical thickness (τ) for all polluted pixels was more than twice that of the clean pixels. This can most likely be related to the differences in aerosol concentrations in accordance with the indirect effect, yet some difference in τ caused by different meteorological situations cannot be ruled out. The mean cloud droplet effective radius (aef) was for the polluted pixels 11.2 µm and for the clean pixels 15.5 µm, which results in a difference of 4.3 µm and clearly demonstrates the effect that increased aerosol numbers has on clouds. A non-linear relationship between aef and N80 has been obtained which indicates that changes in lower values of aerosol numbers affect aef more than changes in larger aerosol loads. The results from this study also indicate that there is a larger difference in the microphysical cloud parameters between the polluted and clean cases in spring and autumn than in summer.