• AWWA WQTC60633
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AWWA WQTC60633

  • Establishing Correlations Between Membrane Fouling and Water Composition
  • Conference Proceeding by American Water Works Association, 11/15/2004
  • Publisher: AWWA

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Analytical methods and equipment were developed to correlate membrane foulingwith feedwater quality parameters under controlled operating conditions. A self-contained,portable bench-scale reverse osmosis (RO) test unit was fabricated and installed atlocations with source waters including surface water, lime-clarified andmicrofiltered secondary treated wastewater, tertiary treated wastewater, brackishgroundwater and agricultural drainage water. Four commercially availablemembranes were tested: three polyamide membranes and one cellulose acetatemembrane. Membranes were operated in a single-pass configuration, each at aconstant flux of 10 gfd and 4 percent recovery. Typical duration of each run was10 to 12 weeks or until the feed pressure to any polyamide membrane exceeded200 psi. Membrane operating parameters (transmembrane pressure, water fluxand solute rejection) were measured daily and water quality grab samples werecollected weekly. Water quality analyses included general minerals, microbialanalysis by heterotrophic plate counts and epifluorescence microscopy,community analysis by 16S rRNA and particle size analysis. At the end of eachtest, membranes were autopsied to determine both the physiochemical properties(ATR/FTIR spectrometry, zeta potential, particle size analysis and scanningelectron microscopy) of the membrane and the nature of the biological materialaccumulated on the membrane surface (protein, carbohydrate, microbiologicalanalysis by heterotrophic plate counts and epifluorescence microscopy,community analysis by 16S rRNA). Collected data were compiled in a database.Chemical, physical, and biological characteristics of the source waters,membranes and fouling layers were measured and used to develop relationshipsbetween source water quality, membrane composition, and membrane foulingusing conventional multivariate analysis and artificial neural net analysis. Includes abstract only.

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