No description available.

Algae and cyanobacteria occur naturally in source waters and are known to cause extensive problems in the drinking water treatment industry. Cyanobacteria (especially Anabaena sp. and Microcystis sp.) are responsible for many water treatment problems in drinking water treatment works (DWTW) all over the world because of their ability to produce organic compounds like cyanotoxins (e.g. microcystin) and taste and odour compounds (e.g. geosmin) that can have an adverse effect on consumer health and consumer confidence in tap water. Therefore, the monitoring of cyanobacteria in source waters entering DWTW has become an essential part of drinking water treatment management. Managers of DWTW, rely heavily on results of physical, chemical and biological water quality analyses, for their management decisions. But results of water quality analyses can be delayed from 3 hours to a few days depending on a magnitude of factors such as: sampling, distance and accessibility to laboratory, laboratory sample turn-around times, specific methods used in analyses etc. Therefore the use of on-line (in situ) instruments that can supply real-time results by the click of a button has become very popular in the past few years. On-line instruments were developed for analyses like pH, conductivity, nitrate, chlorophyll-a and cyanobacteria concentrations. Although, this real-time (on-line) data has given drinking water treatment managers a better opportunity to make sound management decisions around drinking water treatment options based on the latest possible results, it may still be “too little, too late” once a sudden cyanobacterial bloom of especially Anabaena sp. or Microcystis sp. enters the plant. Therefore the benefit for drinking water treatment management, of changing the focus from real-time results to future predictions of water quality has become apparent. The aims of this study were 1) to review the environmental variables associated with cyanobacterial blooms in the Vaal Dam, as to get background on the input variables that can be used in cyanobacterial-related forecasting models; 2) to apply rule-based Hybrid Evolutionary Algorithms (HEAs) to develop models using a) all applicable laboratory-generated data and b) on-line measureable data only, as input variables in prediction models for harmful algal blooms in the Vaal Dam; 3) to test these models with data that was not used to develop the models (so-called “unseen data”), including on-line (in situ) generated data; and 4) to incorporate selected models into two cyanobacterial incident management protocols which link to the Water Safety Plan (WSP) of a large DWTW (case study : Rand Water). During the current study physical, chemical and biological water quality data from 2000 to 2009, measured in the Vaal Dam and the 20km long canal supplying the Zuikerbosch DWTW of Rand Water, has been used to develop models for the prediction of Anabaena sp., Microcystis sp., the cyanotoxin microcystin and the taste and odour compound geosmin for different prediction or forecasting times in the source water. For the development and first stage of testing the models, 75% of the dataset was used to train the models and the remaining 25% of the dataset was used to test the models. Boot-strapping was used to determine which 75% of the dataset was to be used as the training dataset and which 25% as the testing dataset. Models were also tested with 2 to 3 years of so called “unseen data” (Vaal Dam 2010 – 2012) i.e. data not used at any stage during the model development. Fifty different models were developed for each set of “x input variables = 1 output variable” chosen beforehand. From the 50 models, the best model between the measured data and the predicted data was chosen. Sensitivity analyses were also performed on all input variables to determine the variables that have the largest impact on the result of the output. This study have shown that hybrid evolutionary algorithms can successfully be used to develop relatively accurate forecasting models, which can predict cyanobacterial cell concentrations (particularly Anabaena sp. and Microcystis sp.), as well as the cyanotoxin microcystin concentration in the Vaal Dam, for up to 21 days in advance (depending on the output variable and the model applied). The forecasting models that performed the best were those forecasting 7 days in advance (R2 = 0.86, 0.91 and 0.75 for Anabaena[7], Microcystis[7] and microcystin[7] respectively). Although no optimisation strategies were performed, the models developed during this study were generally more accurate than most models developed by other authors utilising the same concepts and even models optimised by hill climbing and/or differential evolution. It is speculated that including “initial cyanobacteria inoculum” as input variable (which is unique to this study), is most probably the reason for the better performing models. The results show that models developed from on-line (in situ) measureable data only, are almost as good as the models developed by using all possible input variables. The reason is most probably because “initial cyanobacteria inoculum” – the variable towards which the output result showed the greatest sensitivity – is included in these models. Generally models predicting Microcystis sp. in the Vaal Dam were more accurate than models predicting Anabaena sp. concentrations and models with a shorter prediction time (e.g. 7 days in advance) were statistically more accurate than models with longer prediction times (e.g. 14 or 21 days in advance). The multi-barrier approach in risk reduction, as promoted by the concept of water safety plans under the banner of the Blue Drop Certification Program, lends itself to the application of future predictions of water quality variables. In this study, prediction models of Anabaena sp., Microcystis sp. and microcystin concentrations 7 days in advance from the Vaal Dam, as well as geosmin concentration 7 days in advance from the canal were incorporated into the proposed incident management protocols. This was managed by adding an additional “Prediction Monitoring Level” to Rand Waters’ microcystin and taste and odour incident management protocols, to also include future predictions of cyanobacteria (Anabaena sp. and Microcystis sp.), microcystin and geosmin. The novelty of this study was the incorporation of future predictions into the water safety plan of a DWTW which has never been done before. This adds another barrier in the potential exposure of drinking water consumers to harmful and aesthetically unacceptable organic compounds produced by cyanobacteria. / PhD (Botany), North-West University, Potchefstroom Campus, 2015

Algae and cyanobacteria occur naturally in source waters and are known to cause extensive problems in the drinking water treatment industry. Cyanobacteria (especially Anabaena sp. and Microcystis sp.) are responsible for many water treatment problems in drinking water treatment works (DWTW) all over the world because of their ability to produce organic compounds like cyanotoxins (e.g. microcystin) and taste and odour compounds (e.g. geosmin) that can have an adverse effect on consumer health and consumer confidence in tap water. Therefore, the monitoring of cyanobacteria in source waters entering DWTW has become an essential part of drinking water treatment management. Managers of DWTW, rely heavily on results of physical, chemical and biological water quality analyses, for their management decisions. But results of water quality analyses can be delayed from 3 hours to a few days depending on a magnitude of factors such as: sampling, distance and accessibility to laboratory, laboratory sample turn-around times, specific methods used in analyses etc. Therefore the use of on-line (in situ) instruments that can supply real-time results by the click of a button has become very popular in the past few years. On-line instruments were developed for analyses like pH, conductivity, nitrate, chlorophyll-a and cyanobacteria concentrations. Although, this real-time (on-line) data has given drinking water treatment managers a better opportunity to make sound management decisions around drinking water treatment options based on the latest possible results, it may still be “too little, too late” once a sudden cyanobacterial bloom of especially Anabaena sp. or Microcystis sp. enters the plant. Therefore the benefit for drinking water treatment management, of changing the focus from real-time results to future predictions of water quality has become apparent. The aims of this study were 1) to review the environmental variables associated with cyanobacterial blooms in the Vaal Dam, as to get background on the input variables that can be used in cyanobacterial-related forecasting models; 2) to apply rule-based Hybrid Evolutionary Algorithms (HEAs) to develop models using a) all applicable laboratory-generated data and b) on-line measureable data only, as input variables in prediction models for harmful algal blooms in the Vaal Dam; 3) to test these models with data that was not used to develop the models (so-called “unseen data”), including on-line (in situ) generated data; and 4) to incorporate selected models into two cyanobacterial incident management protocols which link to the Water Safety Plan (WSP) of a large DWTW (case study : Rand Water). During the current study physical, chemical and biological water quality data from 2000 to 2009, measured in the Vaal Dam and the 20km long canal supplying the Zuikerbosch DWTW of Rand Water, has been used to develop models for the prediction of Anabaena sp., Microcystis sp., the cyanotoxin microcystin and the taste and odour compound geosmin for different prediction or forecasting times in the source water. For the development and first stage of testing the models, 75% of the dataset was used to train the models and the remaining 25% of the dataset was used to test the models. Boot-strapping was used to determine which 75% of the dataset was to be used as the training dataset and which 25% as the testing dataset. Models were also tested with 2 to 3 years of so called “unseen data” (Vaal Dam 2010 – 2012) i.e. data not used at any stage during the model development. Fifty different models were developed for each set of “x input variables = 1 output variable” chosen beforehand. From the 50 models, the best model between the measured data and the predicted data was chosen. Sensitivity analyses were also performed on all input variables to determine the variables that have the largest impact on the result of the output. This study have shown that hybrid evolutionary algorithms can successfully be used to develop relatively accurate forecasting models, which can predict cyanobacterial cell concentrations (particularly Anabaena sp. and Microcystis sp.), as well as the cyanotoxin microcystin concentration in the Vaal Dam, for up to 21 days in advance (depending on the output variable and the model applied). The forecasting models that performed the best were those forecasting 7 days in advance (R2 = 0.86, 0.91 and 0.75 for Anabaena[7], Microcystis[7] and microcystin[7] respectively). Although no optimisation strategies were performed, the models developed during this study were generally more accurate than most models developed by other authors utilising the same concepts and even models optimised by hill climbing and/or differential evolution. It is speculated that including “initial cyanobacteria inoculum” as input variable (which is unique to this study), is most probably the reason for the better performing models. The results show that models developed from on-line (in situ) measureable data only, are almost as good as the models developed by using all possible input variables. The reason is most probably because “initial cyanobacteria inoculum” – the variable towards which the output result showed the greatest sensitivity – is included in these models. Generally models predicting Microcystis sp. in the Vaal Dam were more accurate than models predicting Anabaena sp. concentrations and models with a shorter prediction time (e.g. 7 days in advance) were statistically more accurate than models with longer prediction times (e.g. 14 or 21 days in advance). The multi-barrier approach in risk reduction, as promoted by the concept of water safety plans under the banner of the Blue Drop Certification Program, lends itself to the application of future predictions of water quality variables. In this study, prediction models of Anabaena sp., Microcystis sp. and microcystin concentrations 7 days in advance from the Vaal Dam, as well as geosmin concentration 7 days in advance from the canal were incorporated into the proposed incident management protocols. This was managed by adding an additional “Prediction Monitoring Level” to Rand Waters’ microcystin and taste and odour incident management protocols, to also include future predictions of cyanobacteria (Anabaena sp. and Microcystis sp.), microcystin and geosmin. The novelty of this study was the incorporation of future predictions into the water safety plan of a DWTW which has never been done before. This adds another barrier in the potential exposure of drinking water consumers to harmful and aesthetically unacceptable organic compounds produced by cyanobacteria. / PhD (Botany), North-West University, Potchefstroom Campus, 2015

Submitted in fulfilment of the requirements of the degree of Master of Technology: Environmental Health, Durban University of Technology, 2014. / The study entailed the determination of key water quality parameters significantly influencing treatment cost in uMngeni Basin. Chemical dosage was used as a substitute for treatment cost as the study indicated that cost, in its monetary value, is influenced by market forces, demand and supply, which are both not directly linked to water quality. Chemical dosage is however, determined by the quality of water and thus provides a clear illustration of the effect of pollution on treatment cost. Three specific objectives were set in an effort to determine key water quality parameters influencing treatment costs in uMngeni Basin. The fourth objective was to develop a model for predicting chemical dosages. The first approach was analysis of temporal and spatial variability of water quality in relation to chemical dosage during production of potable water. The trends were explained in relation to river health status. For this purpose, time-series, box-plot, and the Seasonal-Kendal test were employed. The results showed that the quality of water significantly deteriorated from upstream to downstream in relation to algae, turbidity and Escherichia coli (E. coli). High mean range of E. coli (126-1319 colony count/100mL) and turbidity (2.7-38.7 NTU) observed indicate that the quality of water along the basin is not fit for human consumption as these parameters exceeded the target range stipulated in South Africa’s guidelines for domestic use. For water intended for drinking purpose, turbidity should be below 5 NTU, while zero E. coli count is expect in 100 mL. Among the six sampling stations considered along the uMngeni Basin, three dam outflows (Midmar, Nagle and Inanda) showed an improved quality compared with their respective inflow stations. This was expected and could be attributed to the retention and dilution effects. These natural processes help by providing a self-purification process, which ultimately reduces the treatment cost. While considering the importance of disseminating water quality information to the general public and non-technical stakeholders, the second objective of the study was to develop two water quality indices. These were; (1) Treatability Water Quality Index and (2) River Health Water Quality Index. The Treatability Water Quality Index was developed based on the Canadian Council Minister of Environment Water Quality Index (CCME-WQI). The technique is used to determine fitness of water against a set of assigned water quality resource objectives (guidelines). The calculated Harmonised Water Quality Resource Objectives (HWQRO) were used to compare the qualities of the raw water being abstracted at Nagle and Inanda Dam for the purpose of treatment. The results showed that Nagle Dam, which supplies Durban Heights, is significantly affected by E. coli (42% non-compliance), turbidity (20% non-compliance) and nitrate (18% non-compliance) levels. Wiggins Water Treatment Plant which abstracts from Inanda Dam has a problem of high algae (mean 4499 cell/mL), conductivity (mean 26.21 mS/m) and alkalinity (mean 62.66 mg/L) levels. The River Health Water Quality Index (RHWQI) was developed using the Weighted Geometric Mean (WQM) method. Eight parameters, namely, E. coli, dissolved oxygen, nitrate, ammonia, turbidity, alkalinity, electrical conductivity and pH were selected for indexing. Rating curves were drawn based on the target ranges as stipulated in South Africa’s guidelines for freshwater ecosystems. Five classes were used to describe the overall river health status. The results showed that the water is still acceptable for survival of freshwater animals. A comparison of the RHWQI scores (out of 100) depicted that dam inflow station (MDI(61.6), NDI(74.6) and IDI(63.8)) showed a relatively deteriorated quality as compared with their outflows (MDO(77.8), NDO(74.4) and IDO(80)). The third objective was to employ statistical analysis to determine key water quality parameters influencing chemical dosage at Durban Heights and Wiggins Water Treatment Plants. For each of the two treatment plants, treated water quality data-sets were analysed together with their respective raw water data-set. The rationale was to determine parameters showing concentration change due to treatment. The t-test was used to determine the significance of concentration change on each of the 23 parameters considered. Thereafter, the correlations between water quality parameters and the three chemicals used during treatment (polymer, chlorine and lime) were analysed. The results showed that the concentrations of physical parameters namely, algae, turbidity and total organic carbon at both treatment showed a significant statistical (p<0.05) reduction in concentration (R/Ro<0.95). This results implies that such parameters were key drivers for chemical dosage. From the results of the first three objectives, it is recommended that implementing measures to control physical parameter pollution sources, specifically sewage discharges and rainfall run-off from agricultural lands along the uMngeni Basin should assist in reducing the chemical dosage and ultimately cost. The fourth objective was to develop chemical dosage models for prediction purposes. This was achieved by employing a polynomial non-linear regression function on the XLStat 2014 program. The resultant models showed prediction power (R2) ranging from 0.18 (18%) up to 0.75 (75%). However, the study recommends a comparative study of the developed models with other modelling techniques.

Thesis submitted in fulfillment of the academic requirement for the degree of (M.Tech.: Chemical Engineering), Durban University of Technology, South Africa, Durban, 2015. / Woven Fibre Microfiltration (WFMF) membranes have several advantages over its competitors with respect to durability, making it a favourable alternative for the developing world and operation during rough conditions. Wide application of membrane technology has been limited by membrane fouling. The durability of the WFMF membrane allows more options for flux enhancement and cleaning methods that can be used with the membranes even if they are vigorous. Therefore, the purpose of this work was to develop and evaluate flux enhancement and cleaning strategies for WFMF membranes. Feed samples with high contents of organics and turbidity were required for the study. Based on this, two rivers which are Umkomaasi and Duzi River were identified to satisfy these criteria. A synthetic feed with similar fouling characteristics as the two river water was prepared and used for this study. The synthetic feed solution was made up of 2 g/ℓ of river clay in tap water and 0.5% domestic sewerage was added into the solution accounting for 2% of the total volume. A membrane filtration unit was used for this study. The unit consisted of a pack of five membrane modules which were fully immersed into a 100 litres filtration tank. The system was operated under gravity and the level in the filtration tank was kept constant by a level float. The study focused on evaluating the performance of the woven fibre membrane filtration unit with respect to its fouling propensity to different feed samples. It also evaluated and developed flux enhancement and cleaning strategies and flux restoration after fouling. The results were compared to a base case for flux enhancement and pure water fluxes for cleaning. The WFMF membrane was found to be prone to both internal and external fouling when used in the treatment of raw water (synthetic feed). Internal fouling was found to occur quickly in the first few minutes of filtration and it was the major contributor for the loss of flux from the WFMF membrane. The fouling mechanism responsible for internal fouling was found to be largely pore blocking and pore narrowing due to particle adsorption on/in the membrane pores. The structure (pore size, material and surface layout) of the WFMF membrane was found to be the main cause that made it prone to internal fouling. The IV major fouling of the WFMF membrane was due to internal fouling, a high aeration rate of 30 ℓ/min had minimal effect on the fouling reduction. An aeration rate of 30 ℓ/min improved the average flux by only 36%, where a combination of intermittent backwashing with brushing and intermittent backwashing with aeration (aeration during backwashing only) improved average flux by 187% and 135% respectively. Pre-coating the WFMF membrane with lime reduced the effects of pore plugging and particle adsorption on the membrane and improved the average flux by 66%. The cleaning strategies that were most successful in pure water flux (PWF) recovery were high pressure cleaning and a combination of soaking and brushing the membrane in a 0.1% NaOCl (desired) solution. PWF recovery by these two methods was 97% and 95% respectively. Based on these findings, it was concluded that the WFMF membrane is susceptible to pore plugging by colloidal material and adsorption/attachment by microbiological contaminants which took effect in the first hour of filtration. This led to a 50% loss in flux. Also, a single flux enhancement strategy proved insufficient to maintain a high flux successfully. Therefore, combined flux enhancement strategies yielded the best results.

Submitted in fulfillment of the requirements of the degree of Master of Engineering: Chemical Engineering, Durban University of Technology, Durban, South Africa, 2016. / River water is a life supporting watercourse to most communities in rural areas. It is used for both human and animal consumption, and is well becoming a collection channel for defecation and urination due to shortage or lack of access to running water and sanitation facilities. This has resulted to the contamination of water sources, which poses a great risk to human health. This has motivated researchers to study simple but yet robust systems to produce safe drinking water. Photocatalysis is one of such emerging disinfection technologies. Titanium dioxide (TiO2) which is one of the basic materials used for paint manufacturing has emerged as an excellent photocatalyst material for water purification. TiO2 was selected in this study because it is locally available with a potential to open a new market in water purification for the manufacturers. The setback in previous studies is the recovery of nano-scaled TiO2 (nTiO2) after purification when used as a suspension in treated water. Thus this study evaluates the performance of four grades of micro-scaled TiO2 (mTiO2) on the degradation of organic matters, Escherichia coli (E. coli) and total coliform in river water and to investigate the percentage recovery of the mTiO2 using a locally manufactured Polyester Woven Fabric Microfiltration (PWFMF) membrane. The PWFMF though uncharacterized has been used in a number of studies for treating domestic and industrial waste waters. The best-performing grade was used to optimize the degradation efficiency of E. coli in river water using the Design of Experiments (DOE) methodology. Grade 2 of the mTiO2, which is hydrated titanium dioxide with additions (ahTiO2) of particle size range of 0.2 – 53 µm at a concentration of 2.5 g/l displayed an advantageous photocatalytic activity. The results show that 80 % of the organics were removed in 3 hours and increased to 93% after 6 hours. Two particle size ranges of 0.2 – 53 µm and 54 – 75 µm at a concentration of 5 g/l degraded organic matters to 90 % and 77 % in 3 hours respectively. The particle size range of 0.2 – 53 µm at a concentration of 5 g/l was then filtered using a PWFMF and turbidities went below 1 NTU after 20 minutes from feed turbidity of 470 NTU for all three trials. The average percentage recovery in 2 hours was 98.91 %. The four grades of mTiO2 were analyzed for E. coli and total coliform for 4 hours at concentrations of 2, 5 and 7 g/l. Grade 2 achieved the E. coli specification of 0 count/ 100 mL at 5 g/l in 2 hours and at 7 g/l in 0.5 hours. Grade 4 E. coli specification was achieved with 7g/l in 4 hours. Grades 2 and 4 performed better since they both achieved the E. coli and total coliform specifications. Grade 2 was the best performing grade and was considered for statistical studies. Grade 2 was then used on a comparative study between the Central Composite Design (CCD) and Box-Behnken Design (BBD), which are two of the major Response Surface Methodologies (RSM). The CCD compared to BBD provides high quality predictions over the entire design space. The CCD obtained optimum results for concentration of mTiO2 (X1), temperature (X2), initial pH (X3) and aeration (X4) which were 6.94 g/l, 28.75 OC, pH = 6.04, and 13.35 L/min for the maximum degradation efficiency of 99.85 % which showed comparable optimum results to the BBD that were 6.45 g/l, 28.28 OC, pH = 6.02 and 12.21 L/min for the maximum degradation efficiency of 99.80%. These theoretical model results were validated by practical experiments that produced the maximum degradation efficiency for CCD and BBD of 99.67 and 99.26 % respectively. Grade 2 of the mTiO2 can be used as a photocatalyst for river water purification due to its strong ability for the removal of E. coli. The additions used in grades 2 and 4 during production improved the photocatalytic activity. The PWFMF membrane showed a great performance of above 98 % particle recovery of mTiO2 from treated water, although there was an indication that the smallest particles were passing through the membrane. The RSM results gave approximately the same optimum results that were well within the limits, which were experimentally validated and showed that the models were sustainable. It is recommended that the effect of additions be studied on the structures or the charge stability of the two grades. / M

M. Tech. (Chemical Engineering, Faculty of Engineering and Technology), Vaal University of Technology. / A novel technology in the treatment of river water, which involves an electrochemical treatment technique to produce domestic or drinking water is being investigated using aluminium and iron electrodes in an electrochemical circuit. Coagulation and flocculation are traditional methods for the treatment of polluted water. Electrocoagulation presents a robust novel and innovative alternative in which a sacrificial metal anode treats water electrochemically. This has the major advantage of providing mainly active cations required for coagulation and flocculation, without increasing the salinity of the water. Electrocoagulation is a complex process with a multitude of mechanisms operating synergistically to remove pollutants from the water. A wide variety of opinions exist in the literature for key mechanisms. A lack of a systematic approach has resulted in a myriad of designs for electrocoagulation reactors without due consideration of the complexity of the system. A systematic, holistic approach is required to understand electrocoagulation and its controlling parameters. An electrocoagulation-flotation process has been developed for water treatment. This involved an electrolytic reactor with aluminium and/or iron electrodes. The water to be treated (river water) was subjected to coagulation, by Al(III) and Fe(II) ions dissolved from the electrodes, resulting in floes floating after being captured by hydrogen gas bubbles generated at the cathode surfaces. Apparent current efficiencies for AI and Fe dissolution as aqueous Al(III) and Fe(II) species at pH 6.5 and 7.8 were greater than unity. This was due to additional chemical reactions occurring parallel with electrochemical AI and Fe dissolution: oxygen reduction at anodes and cathodes, and hydrogen evolution at cathodes, resulting in net (i.e. oxidation plus reduction) currents at both anodes and cathodes. Investigation results illustrate the feasibility of ferrous and aluminium ion electrochemical treatment as being a successful method of water treatment. Better results were achieved under conditions of relatively high raw water alkalinity, relatively low raw water turbidity, and when high mixing energy conditions were available.

Thesis (Master of Engineering in Mechanical Engineering)--Cape Peninsula University of Technology, 2018. / The present study was centred on the design of a thermal multistage solar still desalination system. The design is a multistage with new configurations such as direct vapour input into each stage using vapour make-up tubes and the integration of a multistage with a basin type solar still. The incorporation of float a valve in the secondary seawater tank to regulate the seawater in the assembly eliminated the need of pumps to the system. The circulation of seawater between the evaporator and the evacuated tube solar collector (ETC) was through the pressure difference and the flow back was controlled through the incorporation of oneway flow valve. The ETC was used as a heat source to supply the thermal energy into the multistage system. The system had no electrical connections and therefore, no forced circulation as no pumps or any electrical components were used. The system consisted of six stages in total, the evaporator supplied the vapour to five of the six stages of the system. The system was tested on the roof of Mechanical Engineering Department and this location was chosen because of less sun’s intensity obstructions. The system was tested for nine (9) days but the distillate collection was not performed for the whole each day. This was due to the controlled access to the roof and the minor repairs that had to occur before the tests were conducted. The duration on which the tests were conducted varied in each day. The data was supposed to be logged from 08h00 am to 18h00 pm but this was not so due to the controlled access to where the tests were conducted. This data logging period was chosen based on the assumptions that the sun’s intensity would be at maximum within this period. The longest period of test was approximately 7 hours and the system managed to produce about 1500 ml and the maximum temperature for the day was 28oC. The system produced a minimum of 225 ml in the space of 3 hours and the temperature of the day was 26oC. The total amount of distillate produced was about 7600 ml and this amount was produced within the period of 49 hours. The 49 hours is equivalent to two days and 1 hour. It is anticipated that the system would have produced more should there be no repairs involved during the tests. The system produced a maximum of 48 ml at night and a minimum of 8ml in some nights. The night tests were not controlled and monitored due to limited access. It was noticed that the system was empty in each morning of the first few days of the tests. This emptiness contributed to the leakage occurred to the evaporator. The leakage of the evaporator was caused by unmonitored heat supplied by the ETC. The evaporator was constructed using unsuitable material and this was another factor which contributed towards the failure of the evaporator.

N-Nitrosamines are an emerging group of disinfection byproducts characterized by high carcinogenic risks at ng/L levels and by their frequent detection in water and wastewater treatment systems in the U.S. and other parts of the world. The overall goal of this research is to achieve a better understanding of the roles of common nitrosamine precursors in leading to N-nitrosamine formation in water and wastewater treatment systems. The specific objectives of this research are: (a) To probe the mechanisms of nitrosamine formation from commonly employed water treatment polymers, particularly polyDADMACs, during ozonation, (b) To evaluate the role of dithiocarbamate compounds as nitrosamine precursors in reaction with common water disinfection oxidants, and (c) To investigate the potential enhancement effect of activated carbons (AC) to promote transformation of amines to nitrosamines and identify the involved reaction mechanism. Results of this research show that, upon ozonation, polyDADMACs may yield N-nitrosodimethylamine (NDMA) at levels up to two orders of magnitude higher than current advisory guidelines for NDMA. Radical pathways may be responsible for the degradation of the quaternary ammonium ring groups in polyDADMACs to release of dimethylamine (DMA). Detection of significant amounts of nitrite after ozonation of polyDADMACs and DMA suggests the potential role of nitrosation pathway in NDMA formation. Study results also reveal dithiocarbamates as potent nitrosamine precursors with significant nitrosamine yields upon ozonation and monochloramination. Identification and quantification of reaction products suggest nitrosation and chlorinated-UDMH oxidation as primary reaction mechanisms in nitrosamine formation from ozonation and monochloramination of dithiocarbamates compounds, respectively. This research also demonstrates that many commercial AC materials may catalyze transformation of secondary amines to yield trace levels of N-nitrosamines under ambient aerobic conditions. This is a novel discovery with far-reaching implications because of the widespread usage of AC materials in numerous analytical and environmental applications. The study results show that the properties of AC materials and reaction conditions play a crucial role in the catalyzed nitrosamine formation and should be carefully selected to minimize analytical errors and undesirable nitrosamine formation in water samples. Overall, the mechanistic information obtained in this research will be useful for the water industry and research communities to develop more effective strategies to control undesirable nitrosamine formation in water and wastewater treatment systems and thus better protect the public health.

Endotoxins are a constituent of the lipopolysaccharide (LPS) complexes present in the outer layer of the cell wall of most Gram-negative bacteria and some cyanobacteria. The ingestion by a typical adult of amounts exceeding 1,000 endotoxin units (EUs) can cause fever, diarrhoea, vomiting, acute respiratory illnesses, and lung inflammation. In contrast, much smaller doses may lead to protective immunity against allergic diseases. / Endotoxins can be released in the air as well as in the water; previous studies have mainly focused on airborne endotoxins. Although many studies on endotoxins in raw and treated drinking waters have been performed, few have assessed seasonal variations and none have been conducted in Eastern Canada. Furthermore, a clear understanding of removal of endotoxins by various water treatment processes is still required. / Two methods to measure the concentrations of endotoxin were used and compared, the Limulus Amebocyte Lysate test (LAL) and the recombinant Factor C test (rFC). Raw water samples were taken from various drinking water sources around the Island of Montreal. The effects of free chlorine, UV radiation, and ozone were studied in batch experiments on filtered water samples via typical dosages and fluences used in drinking water treatment facilities. Residual concentrations for free chlorine were 0.8 and 1.6 mg/L; ozone doses were 0.5 and 1 mg/L; UV fluences were 40 and 100 mWs/cm2. Detention times of 20 and 60 minutes were tested for chlorine and 5 and 20 minutes for ozone. Grab sampling from three drinking water treatment plants in the Montreal area was performed during the months of June and late August/September 2006 and January 2007. Processes at these plants include coagulation and flocculation, sand filtration, ozonation and disinfection by chlorine. To test the variation in endotoxin concentrations during a sand filter cycle, samples were withdrawn directly from a filter in one of the treatment plants studied. The filtration cycle, from one backwash to the next one, lasts 72 h. Samples were collected immediately before the backwash, at the beginning and at the end of the ripening period, at the beginning of the filtration cycle and 48 h later, which corresponds to a half cycle period. / Of the two endotoxin detection methods used, LAL consistently gave slightly higher values compared to rFC; rFC also required more expensive hardware, but the method was less tedious and reagent costs were lower. Results presented, unless otherwise stated, were obtained with the rFC method. Endotoxin levels decreased in raw water samples between June and September. Concentrations ranged from 20 to 30 EU/mL in June, and decreased to 10 to 14 EU/mL in August and beyond. For the disinfection processes, the UV and free chlorine doses tested had little or no effect on the endotoxin concentrations, but ozone reduced the concentrations by up to 75%. Sand filtration and flocculation showed significant endotoxin removal efficiencies (50--60%). Levels remained around 5 EU/mL throughout the remaining treatment processes regardless of the influent concentration. Hence, endotoxin inactivation by free chlorine and UV does not occur with typical doses used in drinking water treatment plants; in contrast, flocculation and sand filtration, as well as ozonation, are much more effective.