Seasonal variations in the disinfection by-product precursor profile of a reservoir water
Bibliographic record
Abstract
Research Article| December 01 2002 Seasonal variations in the disinfection by-product precursor profile of a reservoir water Emma H. Goslan; Emma H. Goslan 1School of Water Sciences, Cranfield University, Cranfield, Bedfordshire MK43 0AL, UK Search for other works by this author on: This Site PubMed Google Scholar David A. Fearing; David A. Fearing 1School of Water Sciences, Cranfield University, Cranfield, Bedfordshire MK43 0AL, UK Search for other works by this author on: This Site PubMed Google Scholar Jenny Banks; Jenny Banks 2Water Quality Technology Development Department, Yorkshire Water, Western Way, Halifax Road, Bradford, BD6 2LZ, UK Search for other works by this author on: This Site PubMed Google Scholar Derek Wilson; Derek Wilson 2Water Quality Technology Development Department, Yorkshire Water, Western Way, Halifax Road, Bradford, BD6 2LZ, UK Search for other works by this author on: This Site PubMed Google Scholar Peter Hills; Peter Hills 3United Utilities Service Delivery, Asset Creation—Task Team, Thirlmere House, Lingley Mere, Lingley Green Avenue, Warrington, WA5 3LP, UK Search for other works by this author on: This Site PubMed Google Scholar Andrew T. Campbell; Andrew T. Campbell 3United Utilities Service Delivery, Asset Creation—Task Team, Thirlmere House, Lingley Mere, Lingley Green Avenue, Warrington, WA5 3LP, UK Search for other works by this author on: This Site PubMed Google Scholar Simon A. Parsons Simon A. Parsons 1School of Water Sciences, Cranfield University, Cranfield, Bedfordshire MK43 0AL, UK Fax: +44 1234 751671; E-mail: s.a.parsons@cranfield.ac.uk Search for other works by this author on: This Site PubMed Google Scholar Journal of Water Supply: Research and Technology-Aqua (2002) 51 (8): 475–482. https://doi.org/10.2166/aqua.2002.0041 Article history Received: August 16 2001 Accepted: July 30 2002 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Share Icon Share Twitter LinkedIn Tools Icon Tools Cite Icon Cite Permissions Search Site Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll JournalsThis Journal Search Advanced Search Citation Emma H. Goslan, David A. Fearing, Jenny Banks, Derek Wilson, Peter Hills, Andrew T. Campbell, Simon A. Parsons; Seasonal variations in the disinfection by-product precursor profile of a reservoir water. Journal of Water Supply: Research and Technology-Aqua 1 December 2002; 51 (8): 475–482. doi: https://doi.org/10.2166/aqua.2002.0041 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex A sampling programme has been undertaken to investigate the nature and fate of natural organic matter (NOM) through a water treatment works (WTW). Specific focus has been given to the effect seasonal changes have on NOM. Water samples were collected from the reservoir inlet and after the filters at Albert WTW in Yorkshire. Samples were taken in January, June and November 2000. Changes in the dissolved organic carbon (DOC), ultra-violet (UV) absorbance at 254 nm, specific UV absorbance (SUVA) and trihalomethane formation potential (THM-FP) were measured for both the filtered and raw water. The waters were fractionated by XAD resin adsorption techniques into hydrophobic acid (HPO-A) and hydrophilic acid (HPI-A) fractions. The fractions were analysed for DOC, UV, SUVA and THM-FP. The reactivity of the fractions changed throughout the year with the lowest reactivity (THM-FP) in January, increasing in June and reaching a maximum in November. This corresponded to the water being more difficult to treat in November and an increase in the proportion of hydrophobic acid. Information was obtained through the fractionation that would be impossible to predict from only the bulk water parameters. characterisation, disinfection by-products, fractionation, natural organic matter This content is only available as a PDF. © IWA Publishing 2002 You do not currently have access to this content.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".