No description available.

No description available.

No description available.

No description available.

A mean sea level (MSL) and 500 hPa height field synoptic climatology of ozone is developed for the Montreal region over the period 1980-1992 using the Kirchhofer computer-assisted map-pattern technique. Synoptic class air quality signatures are examined on an annual, seasonal and interannual basis. Residual cumulative dose analysis confirms that the "Back of the High" synoptic types are responsible for above average ozone concentrations in the summer months. In contrast, during the winter, the stable conditions and cold temperatures associated with these same synoptic types promote ozone scavenging and below average ozone concentrations. Above average winter ozone levels are associated with cyclonic synoptic types, possibly as a result of stratospheric ozone intrusion. Synoptic sequencing confirms the importance in stability in upper level features (particularly an upper level trough to the northeast of Montreal) and stagnation of surface features (primarily the "Back of the High") for the development of elevated ozone concentrations in Montreal. Finally, a declimatizing technique is evaluated as a means of removing the synoptic signal from the ozone time series. Results of this study are in broad agreement with similar investigations elsewhere in northeastern North America.

The increased application of digital terrestrial microwave radio links in communication networks has renewed attention in techniques of estimating the probability of multipath fading distributions. Nevertheless, the unpredictable variation of the wireless transmission medium remains a challenge. It has been ascertained that the refraction of electromagnetic waves is due to the inhomogeneous spatial distribution of the refractive index, and causes adverse effects such as multipath and diffraction fading. The knowledge of the characteristics of such causes of these fading phenomena is essential for the accurate design of terrestrial line of sight (LOS) links of high performance and availability. Refractivity variation is random in space and time and cannot be described in a deterministic manner and has to be considered as a random variable with probabilistic characteristics. In this dissertation, radiosonde soundings data is used in characterizing the atmospheric conditions and determining the geoclimatic factor K used in predicting the distribution of multipath fading for five locations in South Africa. The limitations of radiosonde measurements are lack of time resolution and poor spatial resolution. The latter has been reduced by spatial interpolation techniques in our study, specifcally, the Inverse Distance Weighting (IDW) method. This is used in determining the point refractivity gradient not exceeded for 1 % of the time from which the geoclimatic factor is estimated. Fade depth and outage probability due to multipath propagation is then predicted from the International Telecommunications Union Recommendations (ITU-R) techniques. The results are compared with values from Central Africa. The results obtained using the ITU-R method are also compared with region-based models of Bannett-Vigants of USA and Morita of Japan. Three spatial interpolation techniques (Kriging, Thin-Plate Spline and Inverse Distance Weighting) are then used in interpolating the geoclimatic factor K in places where radiosonde data is not available. The estimated values have been used to develop contour maps for geoclimatic factor K for South Africa. Statistical assessment of these methods is done by calculating the root mean square error (RMSE) and the mean absolute error (MAE) between a set of control points and the interpolated results. The best performing method is used to map the seasonal geoclimatic factor K for the entire study region. The estimated values of geoclimatic factor will improve accuracy in predicting outage probability due to multipath propagation in LOS links in the region which is a key contribution of this work. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2013.

No abstract available. / Thesis (M.Sc.)-University of Natal, Durban, 1993.

No description available.

Concern over the occurrence of micropollutants in drinking water and their health effects is increasing. Therefore, there is a growing interest in understanding micropollutant removal during drinking water treatment. Ozonation and advanced oxidation processes (AOPs) have been found to be effective in the degradation of many micropollutants. Ozonation involves reactions with both molecular ozone (direct pathway) and hydroxyl radicals (indirect pathway), while hydroxyl radicals are the main oxidants in advanced oxidation processes. Reaction rate constants of micropollutants with molecular ozone (kO3) and hydroxyl radicals (kOH) are indicators of their reactivity and are therefore useful in assessing their removal efficiency in ozonation and AOPs. However, to date, only a limited number of rate constants are available for micropollutants, especially emerging micropollutants such as endocrine disrupting chemicals (EDCs) and pharmaceuticals. Quantitative structure-property relationships (QSPR) are therefore desirable for predicting rate constants of numerous untested micropollutants without experimentation. The overall objective of this thesis was to develop predictive QSPR models which correlate the rate constants of a wide range of structural diverse micropollutants to their structural characteristics. To ensure the wide applicability of the QSPR models, the training set compound selection is critical and a group of heterogeneous compounds which are structurally representative of many others is preferred. A systematic compound selection approach which involves principal component analysis (PCA) and D-optimal onion design was applied for the first time in water treatment research. As a result, 22 micropollutants with diverse structures were selected as representatives from a large pool of micropollutants of interest (182 compounds). In addition, 12 molecular descriptors were identified which link relevant structural features to the removal mechanisms of oxidation processes. The kO3 and kOH values of the 22 selected micropollutants were then determined experimentally in bench-scale reactors at neutral pH using high performance liquid chromatography equipped with a photodiode array detector (HPLC-PDA). Three methods, competition kinetics, compound monitoring, and ozone monitoring were used for kO3 measurement, and competition kinetics was used for kOH measurement. As expected, kO3 values span a wide range from 10-2 to 107 M-1 s-1 because of the selective nature of molecular ozone. The general trends of micropollutant reactivity with ozone can be explained by the micropollutant structures and the electrophilic nature of ozone reactions. The kOH values range from 108 to 1010 M-1 s-1 because hydroxyl radicals are relatively non-selective in their reactions. For the majority of these micropollutants kO3 and kOH values were not reported prior to this study. Thus they provide valuable information for modeling and designing of ozonation and AOP treatment. QSPR models for kO3 and kOH prediction were then developed with special attention to model validation, applicability domain and mechanistic interpretation. With the experimentally determined rate constants, QSPR models were developed for predicting kO3 values using the selected 22 micropollutants as the training set and the 12 identified descriptors as model variables. As a result, two QSPR models were developed using piecewise linear regression (PLR) both showing an excellent goodness-of-fit. Model 1 was governed by average molecular weight and number of phenolic functional groups, and Model 2 was dominated by two principal components extracted from the descriptor matrix. The models were then validated using an external validation set collected from the literature, showing good predictive power of both models. Prior to applying these models to unknown micropollutants they need to be classified as high-reactive (logkO3 > 2 M-1 s-1) or low-reactive (logkO3  2 M-1 s-1), so that the appropriate submodel of the PLR can be applied. A classification function using linear discriminant analysis (LDA) was therefore developed which worked very well for both training and validation sets. With the help of additional compounds collected from the literature, and DRAGON molecular descriptors, a QSPR model for kOH prediction in the aqueous phase was developed using multiple linear regression. As a result, 7 DRAGON descriptors were found to be significant in modeling kOH, which related kOH of micropollutants to their electronegativity, polarizability, presence of double bonds and H-bond acceptors. The model fitted the training set very well and showed great predictive power as assessed by the external validation set. In addition, the model is applicable to a wide range of micropollutants. The model’s applicability domain was defined using a leverage approach. The main contributions of this thesis lie in the successful development of QSPR models for kO3 and kOH value prediction which, for the first time, can be used for a wide range of structurally diverse micropollutants. In addition, all QSPR models were externally validated to verify their predictive power, and the applicability domains were defined so that the applicability of the models to new compounds can be determined. Finally, the applicability of the model to natural water was explored by combining the QSPR models with the established Rct concept which predicts micropollutant removals during ozone treatment of natural water but requires kinetic data as input. Results show that the kinetic data from the QSPR model predictions worked well in the Rct model providing reliable estimations for most of the selected micropollutants. This approach can therefore be used in water treatment for initial assessment and estimation of ozonation efficiency.

Charge-induced adsorption is a subject of significance to environmental and biological systems. Ice surface is believed to get charged with potassium deposition. Compared to uncharged ice film, the work function of charged ice film is significantly reduced due to the formation of metastable delocalized excess surface electrons donated by potassium atoms on ice. This charging effect is found to be dependent on temperature. It is also reported that adsorption of carbon tetrachloride would occur drastically on charged ice surface while almost no adsorption was observed on uncharged ice surface at low temperature. In addition, the results strongly agree with the cosmic-ray-driven electron-induced reaction (CRE) model for ozone depletion.