Impact of alkalinity on the removal of natural organic matter from raw waters by enhanced coagulation

Abstract Natural organic matter (NOM) in all soils, ground and surface waters cause negative effects in potable water quality (undesired colour, taste, odour, and bacterial re-growth in distribution systems). Numerous studies have also found that the reaction of NOM with oxidative chemicals during drinking water treatment processes can result to the formation of carcinogenic disinfection by-products (DBPs). Many countries including South Africa, have therefore established regulations to control and minimise NOM and its effects. Enhanced coagulation (EC), a multiple-objective chemical dosing strategy, offers a viable option for NOM removal, and this study explores its use for typical South African raw waters. A consistent and reproducible jar test procedure, simulating the actual coagulation and flocculation pre-treatment steps, was developed and used to investigate the treatability of NOM (measured as UV 254 nm) in all the source waters. Ferric chloride was used as the coagulant due to its extensive application in South Africa. Raw water samples representing the various water types found in the country were seasonally collected for investigation, thus corresponding to a year-long data collection period. Since the removal of NOM is linked to strict control of pH, the coagulant dosage for the jar tests aimed at specific pHs (pH 7.0, 6.0, 5.5, 5.0 and 4.5) with the use of titration curves. The response parameters for the tests were temperature, turbidity, pH and UV 254 nm. Algorithms of finding the optimum dosage for both turbidity and UV 254 nm removal were developed from jar tests and consistently applied to subsequent batch tests. The results of the study suggested that low-alkalinity waters are more amenable to coagulation than high-alkalinity waters. The results also led to the conclusion that the alkalinity and pH of a water are key factors influencing coagulation performance. The optimum pH for the waters fell within the range of 5.0 to 6.5

Optimized coagulation for the removal of natural organic matter (NOM) from low alkalinity : hardness South African raw waters

Abstract This example is to demonstrate the layout of the first page of a paper for Water Science and Technology. The authors’ family names should be given in full; their forenames should be given as abbreviations. The title, authors' names and addresses should be indented 1.5 cm from the left-hand margin of the text area; the abstract is indented 1.5 cm from both margins. The abstract itself, set in 10 pt type like the authors' addresses, should start about 9 cm down from the top of the text area. It should be a single paragraph. Please do not make reference citations in the abstract and keep within the limit of 200 words. It is followed by your choice of up to six keywords, listed alphabetically and separated by semi-colons

Track D Social Science, Human Rights and Political Science

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138414/1/jia218442.pd

The response of typical South African raw waters to enhanced coagulation

Abstract: Drinking water treatment plants in South Africa rely almost entirely on surface water sources, which are often compromised due to high return flows and indirect reuse. The typical treatment plants focus on the removal of physical and microbial contaminants which include turbidity, colour, chemical compounds and microorganisms. A relatively new concern to this list is natural organic matter (NOM) which has become a major concern in potable water treatment due to its recent regulation. In this study, eight different raw water samples from the various water types found in the country were seasonally collected and treated for the removal UV absorbance at a wavelength of 254nm (UV254) using enhanced coagulation (EC). The efficacy of EC, which can be employed as a practical technology in the removal of both turbidity and NOM, was evaluated in remaining UV254 from these raw water sources. Jar tests were conducted, with ferric chloride used as the coagulant (due to its extensive use as a coagulant in the water treatment industry in South Africa) and specific pH values (initial water pH, 7.0, 6.0, 5.5, 5.0 and 4.5) were chosen as target values guiding the six different coagulant dosages for the jar tests. The pH of the low-alkalinity (<60mg/l CaCO3) raw waters were adjusted and raised by the addition of sodium carbonate. The response parameters of the tests were turbidity (NTU), pH and UV254. Algorithms for finding the optimum coagulant dosage for UV254 removal were developed and consistently applied to all the results. Results showed large variations in the nature of NOM across the country from SUVA values. From the UV254 values, the concentrations of NOM also varied greatly geographically than temporally. The general trend observed in the EC results suggested that the pH should always be dropped to between 4.5 and 7.0 to lower the amounts of UV254 and turbidity to reasonable levels

The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press