Thesis (M. A.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Thesis (M.E.S.)--The Evergreen State College, 2007. / Title from title screen (viewed 3/27/2008). Includes bibliographical references (leaves 51-52).

Thesis (M.Sc. Earth and Ocean Sciences)--University of Waikato, 2007. / Includes bibliographical references (leaves 139-148) Also available via the World Wide Web.

Major Paper (M.U.R.P.)--Virginia Polytechnic Institute and State University, 1993. / Abstract. Includes bibliographical references (leaves 68-71). Also available via the Internet.

Thesis (M. Sc.)--University of Hong Kong, 1994. / Includes bibliographical references (leaves 48-52).

Thesis (M. Sc.)--University of Hong Kong, 1998. / Includes bibliographical references (leaf 94-97).

Thesis (Ph. D.)--University of Toronto, 2001. / Includes bibliographical references (leaves 355-377).

Call number: LD2668 .T4 1979 C525 / Master of Science

Eight natural waters from throughout the United States were subjected to different degrees of alum coagulation and activated carbon adsorption treatment (not in series). The concentration of trihalomethanes (THMs) formed by the reaction between the natural aquatic organics and doses of free chlorine were determined by gas chromatography at ten discrete time intervals over a total of 168 hours of reaction time. Since bromide ion concentration and temperature were held constant, and the chlorine dose was based on the final nonvolatile total organic carbon (NVTOC) concentration, THM formation was modeled with the independent variables: reaction time, pH, and a surrogate parameter for organic precursor. Several surrogate parameters were investigated to quantify the THM formation potential. A multiplicative surrogate (UV*TOC) representing the product of the NVTOC concentration and the UV adsorbance at 254 nm was found to be the best surrogate for activated carbon treated waters and was found to be approximately equivalent to NVTOC for alum treated waters. The THM formation was found to fit a two stage reaction with respect to reaction time; relatively rapid formation in the first eight hours followed by a slower formation from 24 to 168 hours. The data base was analyzed with a statistical software package that performs multiple linear regression analysis. Three types of models were developed: a linear model, a nonlinear model and a logarithm transform model. The models were checked for predictive accuracy by a number of methods including the examination of statistics from the regression analyses, scatterplots of predicted versus observed THM values, and the number of predicted values within 20% of the observed value. The logarithm transform model was found to be the best overall model, although other models were more accurate for specific applications as to reaction time or water type. Gel permeation chromatography (GPC) was employed to examine the molecular weight distribution of the aquatic organics in three of the eight waters and to determine the effects of alum coagulation and activated carbon adsorption on these distributions. In general, alum coagulation preferentially removed high molecular weight organics while activated carbon removed a broad spectrum of molecular weight organics.

M.A. / South Africa is situated within a semi-arid part of the world which is characterised by high seasonal variability in terms of rainfall and runoff, with high evaporation rates. This causes streamflow to be relatively low for most of the year, with seasonal sporadic high flows. Further stress is applied to the water resource through population growth, increased urbanisation and industrial activities. The study area is considered to be the most populated of the Upper Vaal Water Management Area (WMA), which is the most important WMA in terms of economic productivity in South Africa. This research report focused on assessing the temporal and spatial variations of pollution between four different sampling points located in the Vaal Barrage Reservoir, which is located in the heart of the Upper Vaal WMA. The Vaal River Barrage Reservoir forms a 64 kilometres long water body with an estimated total storage capacity of 63 million litres of water. The four sampling points are V2 (Vaal River at Engelbrechts Drift Weir); VRB 24 (Vaal River Barrage at 24 km); VRB 37 (Vaal River Barrage at 37 km) and V17 (Vaal Barrage Reservoir Outlet). The aim of this research is to determine the type of physical and chemical pollutants within the Vaal River Barrage which currently poses the biggest problem to river health. The spatial and temporal differences of the pollutant loads are established and discussed. In addition, it is determined what the seasonal influence of rainfall has on the water quality measured at the four different sampling points. Chemical pollutants which currently pose the biggest threat in terms of water quality for the Vaal Barrage Reservoir are Phosphates, Electrical Conductivity and Sulphates. These three water quality variables do not comply with the minimum standards as set by Rand Water. The occurrence of these pollutants in the Vaal River can be explained by the vast inputs of return flow water from sewage treatment plants, underground mine water and discharge from industries. Microbiological factors were not taken into consideration for this dissertation, due to the unavailability of the data for most of the sampling sites for the majority of the study period. It was found that there are seasonal variations in terms of water quality at three sampling points: VRB24, VRB37 and V17. Sample point V17 had the highest inverse correlation for the three pollutants which pose the biggest threat to the health of the Vaal Barrage Reservoir water body. This implies that high seasonal variability occurs in the pollutant load at this sampling point. Sample point V2 had extremely low inverse correlation figures, which implies that rainfall has little or no impact on the level/concentration of a pollutant. This can be explained by two factors. Firstly the dilution effect which water released from the Vaal Dam has due to the close proximity to V2. Secondly because urban, mining and industrial activities are much less evident at this point, and subsequently return flows are less.