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. This
approach was applied in a 12-month study conducted for the City of Scottsdale, Arizona
to 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 treatment
objective. Bench- and pilot-scale testing and computer modeling were used together as follows:
RSSCTs were conducted to establish baseline pilot testing conditions for DBP
precursor removal (different GAC types such as bituminous and lignite, and brands, were
screened to select GACs for the pilot study and pilot test conditions for empty bed
contact 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-month
pilot study to determine GAC performance for full-scale application with seasonal
water quality changes and biodegradation;
simulated distribution system (SDS) tests were conducted to establish seasonal TOC
effluent targets based on TTHM and HAA5 formation; and,
regression analyses were performed to fit the General Logistic Function model to the
pilot-column data. This mathematical model was used to evaluate a range of design
parameters on either side of the test conditions to find the least cost design.
Includes 7 references, figures.
| Edition : | Vol. - No. |
| File Size : | 1
file
, 280 KB |
| Note : | This product is unavailable in Ukraine, Russia, Belarus |
| Number of Pages : | 11 |
| Published : | 11/02/2003 |
