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Record W2581702223

Safe Drinking Water Supply for Small & Rural Communities in NL with a Case Study of Pouch Cove

2016· article· en· W2581702223 on OpenAlexaboutno aff
Jinjing Ling, He Zhang, Tahir Husain

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsnot available
Fundersnot available
KeywordsHaloacetic acidsTotal organic carbonEnvironmental chemistryChlorineChemistryWater treatmentEnvironmental scienceCoveLeaching (pedology)Environmental engineeringSoil waterGeographyOrganic chemistry
DOInot available

Abstract

fetched live from OpenAlex

Chlorine is the most common disinfectant used in the province of Newfoundland and Labrador.However, in the presence of natural organic matter (NOM) in drinking-water sources,disinfection by-products (DBPs) are formed when chlorine is used to treat drinking water. The two largest groups of DBPs, trihalomethanes (THMs) and haloacetic acids (HAAs), are frequently studied by researchers because of their toxicity and high levels in drinking water. In 1998 Newfoundland and Labrador began monitoring THMs and HAAs and it was found that several water utilities had THMs and HAAs above the specified Canadian guidelines, mostly in small, rural drinking-water systems. Pouch Cove was selected for this study as elevated levels of THMs and HAAs were found in their drinking-water system. This study focused on the development of a simple and affordable filtration technology. A passive carbon barrier was studied in the lab to remove NOM, commonly measured as total organic carbon (TOC), before chlorination. The carbon barrier was made from extracted unburned carbon from oil fly ash (OFA), which is abundant within Canada and abroad. The passive nature of this barrier makes it easy to operate and its extremely low cost makes the system affordable for small communities. The OFA samples used for this study were obtained from the Rabigh power plant in Saudi Arabia, which currently generates about 60 tons of OFA daily and currently being disposed into landfills. Since raw OFA contains organic and inorganic impurities, study samples were cleaned and treated through one of two processes, acid leaching or NaOH modification, followed by physical activation. Activated carbon (AC) samples were then applied to reduce the TOC and UV in the Pouch Cove drinking-water samples. In this adsorption treatment, a Split Plot design was employed to investigate the effects of different factors (pH, temperature, carbon dosage, sample volume, and contact/adsorption time), as well as the interaction effects among these factors. The results indicate that pH, temperature, carbon dosage, and sample volume are significant factors in designing a filtration technology. The optimal condition for TOC and UV reduction is a low temperature and a low pH. When the temperature is over 35°C, or the pH is greater than 8, no reduction was observed. The overall TOC removal by activated OFA is relatively low; the maximum removal rate can reach 66% within 30 minutes. Compared with NaOH-modified AC, acid-leached AC is a better adsorbent to achieve TOC and UV reductio

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.799
Threshold uncertainty score0.400

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.220
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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