• AWWA ACE54267
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AWWA ACE54267

  • Modeling and Verification of Hybrid Membrane-Adsorption Processes for Taste and Odor Control in Drinking Water
  • Conference Proceeding by American Water Works Association, 06/01/2001
  • Publisher: AWWA

$12.00$24.00


The use of low-pressure microfiltration (MF) and ultrafiltration (UF) membranes in drinking water treatment has expanded quickly over the last decade because these membranes provide a reliable barrier against microbial pathogens without the byproduct concerns associated with chemical disinfection. Many of the early applications were for relatively high-quality source waters, where the removal of dissolved contaminants that pass through MF and UF membranes was not a primary goal.However, an important emerging application is the combination of MF/UF membranes with powdered activated carbon (PAC) for the efficient removal of both dissolved and particulate contaminants. Using PAC in conjunction with membranes retains the typical advantages of PAC in comparison to fixed bed granular activated carbon (GAC), such as the ability to adjust the level of treatment to match variable influent conditions and low capital costs. In addition, certain hybrid membrane-PAC processes can achieve some of the advantages traditionally associated with GAC, such as longer carbon retention times, because the membrane retains the PAC in the reactor as water flows through it. This paper presents the results of a study investigating the advantages of using a hybrid membrane-PAC system for removing taste and odor. The approach for this study involved the following steps: general discussion of potential advantages of hybrid membrane-PAC processes and what reactor configurations and operational procedures optimize the advantages; computer modeling of the adsorption process with various reactor configurations and operational procedures to quantify the performance for a taste and odor application; and, comparison of model predictions with results from laboratory and pilot-scale experiments to verify the model predictions and suggest model refinements as necessary. Includes 10 references, tables.

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