Effects of Combined Calcium Hypochlorite and Chlorine Dioxide on Drinking Water Quality in Qatar and Disinfection by Products Formation
Bibliographic record
Abstract
Chlorite, chlorate, bromate and trihalomethane's (THMs) are included in WHO guidelines for drinking water quality. This study examined dosing different chlorine concentrations as calcium hypochlorite (Ca(ClO)2) to water containing chlorine dioxide to evaluate the control of water quality in storage and the distribution system in Qatar with emphasis on chlorite, chlorate, bromate, pH and other parameters. Seven water samples were collected from the Ras Laffan-Q Power desalination plant outlet in amber bottles having a chlorine dioxide concentration of 0.3 mg/l in 1 liter. The bottles were spiked with Ca(ClO)2 in sequence to give concentration of 0.2, 0.4, 0.6, 0.8, 1.0, and 1.2 mg/l as free chlorine. The mixtures were stored for 7 days at 25°C in the dark then heated to 45°C for two days more, and analyzed daily for physical and chemical parameters. A total of 312 sub-samples were analyzed for chlorite, chlorate, bromate, bromide, chloride, nitrate, nitrite, sulfate, THMs, temperature, pH, electrical conductivity, and chlorine and chlorine dioxide residuals. Chlorite concentration reductions were observed from the first day forward as 59, 65, 68, 94, 100, and 100%, and 17.4, 22.1, 39.2, 63.9, 66.0, 68.9% (from 0.157 to 0.049 mg/l) respectively based on observed means for seven days the commensurate respective chlorate concentrations increases were 196, 344, 516, 602, 703, 787% (from 0.035 to 0.313 mg/l) based on observed mean values for seven days. These data were statistically analyzed by multivariate regression. There were no significant changes in THMs concentrations and the reductions in chlorite and increases in chlorate concentration are chlorine dosage dependent. No bromate formation was observed. Chlorine dioxide levels decrease as the free chlorine residual levels increased. This study demonstrates that hypochlorite/chlorine can be used as an operational tool to control the chlorite levels, and slow the disappearance of the chlorine dioxide over time during distribution, that is usually faster than chlorine disappearance. The original chlorine dioxide dosage will determine the ultimate chlorate concentration, which must also be managed. References EPA guidance manual Alternative Disinfectants and Oxidants EPA 815-R-99-014, April 1999. 9-1 and 9-25. WHO, Guidelines for drinking-water quality, fourth edition. 2011(1)179,180, 325 and 326. E. Marco. Aieta, Paul V. Roberts; Kinetics of the reaction between molecular chlorine and chlorite in aqueous solution Environ. Sci. Technol., 1986. Daniel P. Hautman and David J. Munch. EPA - Method 300.1. Determination of inorganic anions in drinking water by ion chromatography Revision (1.0) 1997. J.W. Eichelberger, J.W. Munch, and T.A.Bellar EPA Method-524.2. Measurement of Purgeable Organic Compounds In water by capillary column gas chromatography/mass spectrometry, (Revision 4) 1992. Charles Z. Steinbergs, Removal of By-products of Chlorine and Chlorine Dioxide at a Hemodialysis Center 1986. Katherine Alfredo, The Potential Regulatory implications of Chlorate (AWWA), March 2014. C.J. Volk, R. Hofmann, C. Chauret, G.A. Gagnon, G. Ranger, and R.C. Andrews, Implementation of chlorine dioxide disinfection: Effects of the treatment change on drinking water quality in a full-scale distribution system 2002. Mary Ann H. Franson, Standard methods for the examination of water and waste water 2005 (21st, Edition) 4-67 and 4-79. Ron Hofmann, Robert C. Andrews, and Georges Ranger, Water Quality and Disinfection Impact of ClO2 Contamination by free Chlorine: A Case Study (NRC Canada) 2004. Mj Bekink and DJ Nozaic, Assessment of Chlorine Dioxide Proprietary Product for Water and Wastewater Disinfection May 2012.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 source (direct Gemma or distilled Codex), 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".