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The objective of this study was to present a methodology for integrating mathematical models, bench-scale tests, and pilot column tests to obtain the maximum benefit from each with the least cost and effort. Thisapproach was applied in a 12-month study conducted for the City of Scottsdale, Arizonato develop granular activated carbon (GAC) design criteria for a proposed 30-mgd surface water treatment plant.Methylisoborneol (MIB) and DBP precursor removal were the primary GAC treatmentobjective. Bench- and pilot-scale testing and computer modeling were used together as follows:RSSCTs were conducted to establish baseline pilot testing conditions for DBPprecursor removal (different GAC types such as bituminous and lignite, and brands, werescreened to select GACs for the pilot study and pilot test conditions for empty bedcontact time (EBCT) and hydraulic loading rate (HLR) were selected based on RSSCT results);both bituminous and lignite GACs were tested (with and without ozone) in a 6-monthpilot study to determine GAC performance for full-scale application with seasonalwater quality changes and biodegradation;simulated distribution system (SDS) tests were conducted to establish seasonal TOCeffluent targets based on TTHM and HAA5 formation; and,regression analyses were performed to fit the General Logistic Function model to thepilot-column data. This mathematical model was used to evaluate a range of designparameters on either side of the test conditions to find the least cost design. Includes 7 references, figures.

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Edition: Vol. - No. Published: 11/02/2003 Number of Pages: 11File Size: 1 file , 280 KB