Using Automated On-Site Monitoring to Calibrate Empirical Models of Trihalomethanes Concentrations in Drinking Water
An automated, on-site trihalomethanes concentration data set from a conventional water treatment plant was used to optimize powdered activated carbon and pre-chlorination doses. The trihalomethanes concentration data set was used with commonly monitored water quality parameters to improve an empiric...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2015-10-01
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| Series: | Beverages |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2306-5710/1/4/225 |
| _version_ | 1817981080323489792 |
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| author | Thomas E. Watts III Robyn A. Snow Aaron W. Brown J. C. York Greg Fantom Paul S. Simone Jr. Gary L. Emmert |
| author_facet | Thomas E. Watts III Robyn A. Snow Aaron W. Brown J. C. York Greg Fantom Paul S. Simone Jr. Gary L. Emmert |
| author_sort | Thomas E. Watts III |
| collection | DOAJ |
| description | An automated, on-site trihalomethanes concentration data set from a conventional water treatment plant was used to optimize powdered activated carbon and pre-chlorination doses. The trihalomethanes concentration data set was used with commonly monitored water quality parameters to improve an empirical model of trihalomethanes formation. A calibrated model was used to predict trihalomethanes concentrations the following year. The agreement between the models and measurements was evaluated. The original model predicted trihalomethanes concentrations within ~10 μg·L−1 of the measurement. Calibration improved model prediction by a factor of three to five times better than the literature model. |
| first_indexed | 2024-04-13T23:01:15Z |
| format | Article |
| id | doaj.art-de0ee3b3a59d474187ebc4e344aa5e70 |
| institution | Directory Open Access Journal |
| issn | 2306-5710 |
| language | English |
| last_indexed | 2024-04-13T23:01:15Z |
| publishDate | 2015-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Beverages |
| spelling | doaj.art-de0ee3b3a59d474187ebc4e344aa5e702022-12-22T02:25:50ZengMDPI AGBeverages2306-57102015-10-011422524710.3390/beverages1040225beverages1040225Using Automated On-Site Monitoring to Calibrate Empirical Models of Trihalomethanes Concentrations in Drinking WaterThomas E. Watts III0Robyn A. Snow1Aaron W. Brown2J. C. York3Greg Fantom4Paul S. Simone Jr.5Gary L. Emmert6Department of Chemistry, The University of Memphis, Rm 213 Smith Chemistry Bldg., Memphis, TN 38152, USADepartment of Chemistry, The University of Memphis, Rm 213 Smith Chemistry Bldg., Memphis, TN 38152, USADepartment of Chemistry, The University of Memphis, Rm 213 Smith Chemistry Bldg., Memphis, TN 38152, USAThe City of Lebanon, TN Water Treatment Plant, 7 Gilmore Hill Road, Lebanon, TN 37087, USAThe City of Lebanon, TN Water Treatment Plant, 7 Gilmore Hill Road, Lebanon, TN 37087, USADepartment of Chemistry, The University of Memphis, Rm 213 Smith Chemistry Bldg., Memphis, TN 38152, USADepartment of Chemistry, The University of Memphis, Rm 213 Smith Chemistry Bldg., Memphis, TN 38152, USAAn automated, on-site trihalomethanes concentration data set from a conventional water treatment plant was used to optimize powdered activated carbon and pre-chlorination doses. The trihalomethanes concentration data set was used with commonly monitored water quality parameters to improve an empirical model of trihalomethanes formation. A calibrated model was used to predict trihalomethanes concentrations the following year. The agreement between the models and measurements was evaluated. The original model predicted trihalomethanes concentrations within ~10 μg·L−1 of the measurement. Calibration improved model prediction by a factor of three to five times better than the literature model.http://www.mdpi.com/2306-5710/1/4/225disinfection by-productstrihalomethaneson-line monitoringprocess controlempirical models |
| spellingShingle | Thomas E. Watts III Robyn A. Snow Aaron W. Brown J. C. York Greg Fantom Paul S. Simone Jr. Gary L. Emmert Using Automated On-Site Monitoring to Calibrate Empirical Models of Trihalomethanes Concentrations in Drinking Water Beverages disinfection by-products trihalomethanes on-line monitoring process control empirical models |
| title | Using Automated On-Site Monitoring to Calibrate Empirical Models of Trihalomethanes Concentrations in Drinking Water |
| title_full | Using Automated On-Site Monitoring to Calibrate Empirical Models of Trihalomethanes Concentrations in Drinking Water |
| title_fullStr | Using Automated On-Site Monitoring to Calibrate Empirical Models of Trihalomethanes Concentrations in Drinking Water |
| title_full_unstemmed | Using Automated On-Site Monitoring to Calibrate Empirical Models of Trihalomethanes Concentrations in Drinking Water |
| title_short | Using Automated On-Site Monitoring to Calibrate Empirical Models of Trihalomethanes Concentrations in Drinking Water |
| title_sort | using automated on site monitoring to calibrate empirical models of trihalomethanes concentrations in drinking water |
| topic | disinfection by-products trihalomethanes on-line monitoring process control empirical models |
| url | http://www.mdpi.com/2306-5710/1/4/225 |
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