The formation of disinfection by-products (DBPs) in drinking water has become an issue
of greater concern in recent years. Bench-scale jar tests were conducted on a surface water to evaluate the impact of enhanced coagulation on the removal of organic DBP precursors and the formation of trihalomethanes (THMs) and haloacetic acids (HAAs). The results of this testing
indicate that enhanced coagulation practices can improve treated water quality without
increasing coagulant dosage. The data generated were also used to develop artificial neural networks (ANNs) to predict THM and HAA formation. Testing of these models showed high correlations between the actual and predicted data. In addition, an experimental plan was developed to use ANNs for treatment optimization at the Peterborough pilot plant.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/31630 |
| Date | 04 January 2012 |
| Creators | Wassink, Justin |
| Contributors | Andrews, Robert C. |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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