Photocatalysis is an advanced oxidation process for the purification and remediation of contaminated waters and wastewaters, and is advantageous over conventional treatment technologies due to its ability to degrade emerging and recalcitrant pollutants. In addition, photocatalytic disinfection is less chemical-intensive than other methods such as chlorination, and can inactivate even highly resistant microorganisms with good efficacy. Process sustainability and cost-effectiveness may be improved by utilizing solar irradiation as the source of necessary photons for photocatalyst excitation. However, solar-induced activity of the traditionally-used titania is poor due to its inefficient visible light absorption, and recombination of photo-excited species is problematic. Additionally, mass transfer limitations and difficulties separating the catalyst from the post-treatment slurry hinder conversions and efficiencies obtainable in practice. In this research, various strategies were explored to address these issues using novel visible light active photocatalysts. Two classes of carbon-enhanced photocatalytic materials were studied: activated carbon adsorbent photocatalyst composites, and carbon-doped TiO2. Adsorbent photocatalyst composites based on activated carbon and plasmonic silver/silver chloride structures were synthesized, characterized, and experimentally investigated for their photocatalytic activity towards the degradation of model organic pollutants (methyl orange dye, phenol) and the inactivation of a model microorganism (Escherichia coli K-12) under visible light. The adsorptive behaviour of the composites towards methyl orange dye was also studied and described according to appropriate models. Photocatalytic bacterial inactivation induced by the prepared composites was investigated, and the inactivation mechanisms and roles of incorporated antimicrobial silver on disinfection were probed and discussed. These composites were extended towards magnetic removal strategies for post-use separation through the incorporation of magnetic nanoparticles to prepare Ag/AgCl-magnetic activated carbon composites, and the effect of nanoparticles addition on the properties and photoactivities of the resulting materials was explored. Another silver/silver halide adsorbent photocatalyst composite based on activated carbon and Ag/AgBr exhibiting visible light absorption due to both localized surface plasmon resonance and optical band gap absorption was synthesized and its photocatalytic activity towards organics degradation and microbial inactivation was studied. Carbon-doped mixed-phase titania was also prepared and experimentally investigated.

The aim of this study was to investigate the efficacy of purification processes at the Rand Water Zuikerbosch treatment plant near Vereeniging. Raw water is abstracted via a canal and gravity pipeline from the Vaal Dam (in the upper Vaal River) and purified to ensure it meets the stringent standards set for drinkable water. The first step was to determine the ecological status of the raw water and it was done by measuring chemical, physical and biological variables as well as to identify and enumerate the different algal groups that occur in the raw water. The turbidity of the raw water was low but the phosphorous and ortho–phosphate levels were high. The Cyanophyceae (blue–green bacteria) especially Anabaena species were dominant in the raw water for the duration of the study. Potential problems such as relatively high alkalinity, chemical oxygen demand (COD) and total dissolved solids (TDS) as well as potentially hazardous chemicals such as cadmium and lead were observed in the raw water. The Zuikerbosch Water Treatment Plant (ZWTP) is a conventional water treatment plant which involves the following stages: coagulation, flocculation, sedimentation, sand filtration and chlorination. The use of pre–treatment chemicals ensures better water quality and effective removal of particles from the water. Only five of the variables (methylisoborneol (MIB); geosmin; chlorophyll–a; chlorophyll–665 and total organic carbon (TOC) were measured before filtration, after filtration and in the final water. Samples from the raw water, before and after filtration, as well as final water were collected weekly for a period of two years to measure the environmental variables as well as to do algal identification and enumeration. The purification processes at ZWTP were not able to remove MIB, geosmin, chlorophyll–a and TOC from the final water. Algal concentration was reduced but not totally removed by the purification processes. Although some variables were not totally removed by the purification processes, ZWTP produce potable water that complies with the Rand Water guidelines. / Thesis (M. Environmental Science)--North-West University, Potchefstroom Campus, 2011.

South Africa's water resources are, in global terms, scarce and extremely limited (DWAF, 2004). Groundwater is a valuable source of potable water in South Africa. It was found that most of the health facilities in the Limpopo Province depend on groundwater as sole source of potable water. Groundwater quality is to a great extent influenced by the dominant land use in the vicinity of an aquifer. It is therefore important to carefully manage possible pollution sources of anthropogenic origin. This may be seen as pro–active water quality management that may result in significant saving on water treatment. This aim of this study is to obtain a regional view of the water quality situation at clinics and other health facilities in the Limpopo Province. It was found that the general water quality at health facilities in the Province is questionable. It is of concern to note that 56% of health facilities use water that is unacceptable for human consumption. Water quality may be managed by introducing appropriate treatment options to treat the water to ideal water quality standards. This dissertation explores some treatment options used at health facilities in the Province. The efficiency of these treatment systems is also investigated. / Thesis (M.Sc. (Geography and Environmental Studies))--North-West University, Potchefstroom Campus, 2011.

N-nitrosamines are considered as a group of emerging disinfection byproducts (DBPs) with potential carcinogenicity at ng/L level. The presence of nitrosamines in drinking water is most commonly associated with chloramination of amine-based precursors. This research investigates the potential of amine-based pharmaceuticals and personal care products (PPCPs) as nitrosamine precursors under practical drinking water disinfection conditions, as well as some critical factors that may affect the nitrosamine formation via PPCPs. All of the twenty selected PPCPs were able to form the corresponding nitrosamines upon chloramine disinfection, and eight of them rendered molar conversions higher than 1 % under practical disinfection conditions. Ranitidine had the highest N-nitrosodimethylamine (NDMA) molar conversion among the tested PPCPs. A three-parameter kinetic model was proposed to describe and predict the NDMA formation from pharmaceuticals during chloramination in various water matrices. The model accurately reflected all three significant characteristics of the NDMA formation curve, including an initial lag phase, followed by a fast increase in NDMA formation, and eventually reaching a plateau. In lab-grade water, the NDMA formation from pharmaceuticals was affected by the Cl2:NH4-N mass ratio, pH, and prechlorination. The NDMA formation increased with the Cl2:NH4-N mass ratio, indicating an enhancement effect of dichloramine. The pH affected both the ultimate NDMA conversion and the reaction rate. The reaction rate is mainly determined by the level of non-protonated amine species, and it increased consistently with increasing pH. The ultimate NDMA conversion is limited by the level of dichloramine, and the maximum NDMA formation occurred in the pH range of 7 to 8. The application of prechlorination may increase or reduce the NDMA conversion, depending on the chlorine reactivity towards the amine group and its surrounding structures. Water matrix components can slow down the initial NDMA formation from selected pharmaceuticals most likely due to the formation of natural organic matter (NOM)-pharmaceutical complexes, while they had less impact on the ultimate NDMA molar conversion. The application of prechlorination may enhance the initial reaction by destroying the NOM-pharmaceutical complexes, but prolonged prechlorination may further inhibit the NDMA formation due to the binding between pharmaceuticals and NOM breakdown products.

Filtration is an important process in drinking water treatment to ensure the adequate removal of particle-bound pathogens (i.e. Giardia and Cryptosporidium). Filtration performance is typically monitored in terms of filtered water turbidity. However, particle counts may provide further insight into treatment efficiency, as they have a greater sensitivity for detecting small changes in filtration operation. To optimize the filtration process at the Elgin Area WTP in terms of post-filtration particle counts, artificial neural network (ANN) models were applied. Process models were successfully developed to predict settled water turbidity and particle counts. Additionally, two inverse process models were developed to predict the optimal coagulant dosage required to attain target particle counts. Upon testing each model, a high correlation was observed between the actual and predicted data sets. The ANNs were then integrated into an optimization application to allow for the transfer of real-time data between the models and the SCADA system.

The formation of disinfection by-products (DBPs) in drinking water has become an issue of greater concern in recent years. Bench-scale jar tests were conducted on a surface water to evaluate the impact of enhanced coagulation on the removal of organic DBP precursors and the formation of trihalomethanes (THMs) and haloacetic acids (HAAs). The results of this testing indicate that enhanced coagulation practices can improve treated water quality without increasing coagulant dosage. The data generated were also used to develop artificial neural networks (ANNs) to predict THM and HAA formation. Testing of these models showed high correlations between the actual and predicted data. In addition, an experimental plan was developed to use ANNs for treatment optimization at the Peterborough pilot plant.

N-nitrosamines are considered as a group of emerging disinfection byproducts (DBPs) with potential carcinogenicity at ng/L level. The presence of nitrosamines in drinking water is most commonly associated with chloramination of amine-based precursors. This research investigates the potential of amine-based pharmaceuticals and personal care products (PPCPs) as nitrosamine precursors under practical drinking water disinfection conditions, as well as some critical factors that may affect the nitrosamine formation via PPCPs. All of the twenty selected PPCPs were able to form the corresponding nitrosamines upon chloramine disinfection, and eight of them rendered molar conversions higher than 1 % under practical disinfection conditions. Ranitidine had the highest N-nitrosodimethylamine (NDMA) molar conversion among the tested PPCPs. A three-parameter kinetic model was proposed to describe and predict the NDMA formation from pharmaceuticals during chloramination in various water matrices. The model accurately reflected all three significant characteristics of the NDMA formation curve, including an initial lag phase, followed by a fast increase in NDMA formation, and eventually reaching a plateau. In lab-grade water, the NDMA formation from pharmaceuticals was affected by the Cl2:NH4-N mass ratio, pH, and prechlorination. The NDMA formation increased with the Cl2:NH4-N mass ratio, indicating an enhancement effect of dichloramine. The pH affected both the ultimate NDMA conversion and the reaction rate. The reaction rate is mainly determined by the level of non-protonated amine species, and it increased consistently with increasing pH. The ultimate NDMA conversion is limited by the level of dichloramine, and the maximum NDMA formation occurred in the pH range of 7 to 8. The application of prechlorination may increase or reduce the NDMA conversion, depending on the chlorine reactivity towards the amine group and its surrounding structures. Water matrix components can slow down the initial NDMA formation from selected pharmaceuticals most likely due to the formation of natural organic matter (NOM)-pharmaceutical complexes, while they had less impact on the ultimate NDMA molar conversion. The application of prechlorination may enhance the initial reaction by destroying the NOM-pharmaceutical complexes, but prolonged prechlorination may further inhibit the NDMA formation due to the binding between pharmaceuticals and NOM breakdown products.

Filtration is an important process in drinking water treatment to ensure the adequate removal of particle-bound pathogens (i.e. Giardia and Cryptosporidium). Filtration performance is typically monitored in terms of filtered water turbidity. However, particle counts may provide further insight into treatment efficiency, as they have a greater sensitivity for detecting small changes in filtration operation. To optimize the filtration process at the Elgin Area WTP in terms of post-filtration particle counts, artificial neural network (ANN) models were applied. Process models were successfully developed to predict settled water turbidity and particle counts. Additionally, two inverse process models were developed to predict the optimal coagulant dosage required to attain target particle counts. Upon testing each model, a high correlation was observed between the actual and predicted data sets. The ANNs were then integrated into an optimization application to allow for the transfer of real-time data between the models and the SCADA system.

The formation of disinfection by-products (DBPs) in drinking water has become an issue of greater concern in recent years. Bench-scale jar tests were conducted on a surface water to evaluate the impact of enhanced coagulation on the removal of organic DBP precursors and the formation of trihalomethanes (THMs) and haloacetic acids (HAAs). The results of this testing indicate that enhanced coagulation practices can improve treated water quality without increasing coagulant dosage. The data generated were also used to develop artificial neural networks (ANNs) to predict THM and HAA formation. Testing of these models showed high correlations between the actual and predicted data. In addition, an experimental plan was developed to use ANNs for treatment optimization at the Peterborough pilot plant.

Point-of-use (POU) and point-of-entry (POE) water treatment are forms of decentralized water treatment that are becoming increasingly sought alternatives for ensuring the safety of drinking water. Although the acceptance of POU and POE systems is still the subject of some debate, it is generally acknowledged that they have a role to play in drinking water treatment. However, some of the main drivers for the increase in the use of POU and POE alternatives include: (1) the emergence of new technologies with high removal efficiencies of target contaminants; (2) the enhanced certification system of POU and POE treatment devices and components which ensures that devices have been well engineered to achieve defined contaminant removal targets and do not add contaminants from materials of construction; (3) the inclusion of POU and POE systems as acceptable means to comply with drinking water standards; and (4) the concerns voiced by consumers in several surveys regarding the safety of centrally treated drinking water; which, regardless of whether or not these concerns are justified, have led to an increase in the use of POU and POE treatment systems. With the commercialization of these devices the task of selecting a suitable device for treatment has become cumbersome. When the inherent complexity of a particular drinking water treatment task is added to the mix, a complex decision making situation is created. Thus the need for designing a decision support tool to compare and select POU and POE treatment systems was evident. Currently the best decision aid for selecting POU and POE systems is NSF International’s listing of the devices and their contaminant reduction claims. A significant contribution of this research is the depiction of an appropriate conceptual framework for developing usable and valid decision support systems (DSSs) to select or design water or wastewater treatment systems. A thorough investigation of the methods used to develop DSSs benchmarked a systematic approach to developing DSSs, which includes the analysis of the treatment problem(s), knowledge acquisition and representation, and the identification and evaluation of criteria controlling the selection of optimal treatment systems. Finally, it was concluded that there is a need to develop integrated DSSs that are generic, user-friendly and employ a systems analysis approach. Another significant contribution of this research is applying a systems analysis approach to outline aspects of implementation, management, and governance of POU and POE water treatment systems. The analysis also included a timeline of the progress of POU and POE treatment from regulatory, industry and certification, and research perspectives. Results of the analysis were considered the first step of a conceptual framework for the sustainability assessment of POU and POE treatment systems which acts as the basis for developing a decision support system that will help select sustainable POU or POE treatment systems. In the context of POU and POE treatment, sustainability encompasses providing: (a) safe drinking water to help maintain good human health and hygiene; (b) minimum negative impact on the environment; (c) better use of human, natural, and financial resources; (d) a high degree of functional robustness and flexibility; and (e) cultural acceptance thus encouraging responsible behavior by the users. The most significant contribution of this research is developing, for the first time, a set of sustainability criteria, objectives, and quantifiable indicators to properly assess the sustainability of the various POU and POE alternatives. Twenty five quantitative and qualitative indicators covering technical, economic, environmental, and socio-cultural aspects of implementing a POU or a POE system were defined. Results of a survey of experts’ judgment on the effectiveness of the developed list of indicators generated 52 comments from 11 experts, which helped in refining and enhancing the list. The conceptual framework for assessing the sustainability of POU and POE systems represented a blueprint for building the decision support system. Decision logic and cognitive thinking was used to formulate the calculation of the 20 refined indicators. The Analytical Hierarchy Process (AHP), a recognized Multi-criteria Decision Analysis (MCDA) tool, was employed to construct the structural hierarchy of sustainability indicators. Pairwise comparison was used to help in the analysis of indicators' relative importance and develop the indicators’ weights. A survey was designed to develop the relative weights of the indicators based on the average response of 19 stakeholders to a series of pairwise comparison questions pertaining to the relative importance of the indicators. Finally, the practical contribution of this research is the development of, for the first time, a new Decision Support System for Selecting Sustainable POU and POE Treatment Systems (D4SPOUTS) suitable for a particular water treatment case. The MCDA technique explained above is combined with designed screening rules, constraints, and case characteristics to be applied to a knowledgebase of POU and POE treatment systems incorporated in the DSS. The components of the DSS were built using Microsoft® Excel® and Visual Basic® for Applications. The quality of the DSS and aspects of its usability, applicability, and sensitivity analysis are demonstrated through a hypothetical case study for lead removal from drinking water. This research is expected to assist water purveyors, consultants, and other stakeholders in selecting sustainable and cost effective POU and POE treatment systems.