The main objective of this study was to investigate the vertical distribution of aerosols over Durban in relation to the vertical stability structure and horizontal transport of air masses. The importance of aerosols in the region is well recognised and recently there have been many international experiments which have focused on aerosol distribution over the subcontinent. Durban is situated at the approximate centre of a giant plume that is known to transport aerosols and trace gases off the east coast of southern Africa and is therefore strategically located for an investigation of the vertical distribution of aerosols. The vertical distribution of aerosols over Durban was measured using a LIDAR (Light Detection And Ranging) system on selected cloud free days in 1997. Backward trajectory modelling was used at selected pressure (standard) levels to determine the origin and transport pathways of aerosols. Six case studies are presented in an attempt to gain insight into the relationship between the vertical distribution of aerosols and absolutely stable layers. The results of the study revealed that the occurrence of absolutely stable layers governs the vertical distribution of aerosols in the troposphere. An absolutely stable layer at ~5km (~500hPa) appears to be the most effective in capping and trapping aerosols in the atmosphere. Below 5km, the atmosphere was charcterised by marked stratification and relatively higher concentration of aerosols. Above 5km, the concentrations were much lower, but generally increased slightly with height. Low aerosol concentrations are observed during post-frontal situations and relatively higher concentrations during anticyclonic conditions. The background to the problem and the objectives of this investigation are elaborated in Chapter 1. A description of the data sets and derived meteorological variables, along with the methodologies applied in this thesis, are given in Chapter 2. A theoretical review of aerosols, including their sources, effects and distribution over the globe and southern Africa, is discussed in Chapter 3. Atmospheric circulation and weather patterns and their relationship to the transport and dispersion of aerosols are described in Chapter 4. The results of the study and an analysis of the major findings are presented in Chapter 5. Finally, Chapter 6 summarises the major findings of this dissertation. / Thesis (M.Sc.)-University of Natal, Durban, 2000.

Organic aerosols have significant effects on human health, air quality and climate. Secondary organic aerosols (SOA) are produced by the oxidation of primary-volatile organic compounds (VOC). For example, α-pinene reacts with oxidants such as hydroxyl radical (OH), ozone (O3), and nitrate radical (NO3), accounting for a significant portion of total organic aerosol in the atmosphere. Experimental studies have shown that the oxidation process between α-pinene and ozone has the most significant impact in the formation of SOA (Hoffmann et al., 1997). Most of the models used to predict SOA formation, however, are limited in that they neglect the role of water due to uncertainty about the structure and nature of organic compounds, in addition to uncertainty about the effect of varying relative humidity (RH) on atmospheric organic particulate matter (OPM) (Kanakidou et al., 2005). For this study, structures of organic compounds involved in the formation of SOA are estimated, and the role of water uptake is incorporated in the process. The Combinatorial Aerosol Formation Model (CAFM) is a deterministic model used to determine the amount of organic mass (Mo µg m-3) formation based on the predicted structures. Results show that the amount of SOA that is formed is almost negligible when the amount of parent hydrocarbon involved in the reaction is low (i.e. around 5 µg m-3), especially at lower RH. Observing compounds with a greater number of polar groups (alcohol and carboxylic acid) indicates that structure has a significant effect on organic mass formation. This observation is in agreement with the fact that the more hydrophilic the compound is, the higher RH, leading to more condensation into the PM phase.

Potential determinants of exposure to culturable airborne fungal and bacterial aerosols and carbon dioxide were examined as an aid to the interpretation and evaluation of indoor air quality assessments. Concentration measurments for culturable bioaerosols and CO2 were evaluated against published standards and guidelines. METHOD: All 39 schools from one British Columbia school district were enrolled in the study to ensure different building ages and construction materials, but the same maintenance protocols, were included. Schools were randomly assigned to winter, spring or fall sampling. Data collected included: number of occupants and patterns of occupancy, CO2 levels, temperature and relative humidity, total suspended particles, and air exchange rates using tracer gas (SF6) decay. Other characteristics of the classrooms included the presence or absence of forced air heat, carpets, live animals or aquaria, plants, and the siting of the school or portable classroom. Culturable indoor and outdoor aerosols of fungi and bacteria were collected. Determinants of exposure were modelled by constructing multiple linear regression equations for indoor fungi, indoor bacteria and indoor carbon dioxide. RESULTS: The multiple regression models were able to explain a considerable proportion of the variance for the outcomes of interest (total R2 = 0.59 for mesophilic fungi, 0.61 for bacteria, and 0.68 for CO2). Increased outdoor temperature and outdoor fungal counts were associated with higher concentrations for indoor fungi. Variables describing ventilation and conditions of occupancy were significant to all outcomes of interest but functioned differently in the models. For example, fungal concentration was higher in the presence of natural ventilation, but lower with increased mechanical ventilation. In contrast, CO2 was lower with both ventilation types, and lower with higher outdoor temperature. CONCLUSIONS: Using variables measured during an indoor air quality investigation, predictive models can be constructed which are useful in identifying determinants of bioaerosol and bioeffluent concentrations. Ranges of bioaerosol and bioeffluent concentrations for high occupancy buildings in a coastal temperate zone may differ from guidelines written for other indoor settings and climate zones.

Potential determinants of exposure to culturable airborne fungal and bacterial aerosols and carbon dioxide were examined as an aid to the interpretation and evaluation of indoor air quality assessments. Concentration measurments for culturable bioaerosols and CO2 were evaluated against published standards and guidelines. METHOD: All 39 schools from one British Columbia school district were enrolled in the study to ensure different building ages and construction materials, but the same maintenance protocols, were included. Schools were randomly assigned to winter, spring or fall sampling. Data collected included: number of occupants and patterns of occupancy, CO2 levels, temperature and relative humidity, total suspended particles, and air exchange rates using tracer gas (SF6) decay. Other characteristics of the classrooms included the presence or absence of forced air heat, carpets, live animals or aquaria, plants, and the siting of the school or portable classroom. Culturable indoor and outdoor aerosols of fungi and bacteria were collected. Determinants of exposure were modelled by constructing multiple linear regression equations for indoor fungi, indoor bacteria and indoor carbon dioxide. RESULTS: The multiple regression models were able to explain a considerable proportion of the variance for the outcomes of interest (total R2 = 0.59 for mesophilic fungi, 0.61 for bacteria, and 0.68 for CO2). Increased outdoor temperature and outdoor fungal counts were associated with higher concentrations for indoor fungi. Variables describing ventilation and conditions of occupancy were significant to all outcomes of interest but functioned differently in the models. For example, fungal concentration was higher in the presence of natural ventilation, but lower with increased mechanical ventilation. In contrast, CO2 was lower with both ventilation types, and lower with higher outdoor temperature. CONCLUSIONS: Using variables measured during an indoor air quality investigation, predictive models can be constructed which are useful in identifying determinants of bioaerosol and bioeffluent concentrations. Ranges of bioaerosol and bioeffluent concentrations for high occupancy buildings in a coastal temperate zone may differ from guidelines written for other indoor settings and climate zones. / Graduate and Postdoctoral Studies / Graduate