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Assessing Biofiltration Pretreatment for Ultrafiltration Membrane Processes

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Date Issued:
2015
Abstract/Description:
An engineered biological filtration (biofiltration) process treating a nutrient-enriched, low-alkalinity, organic-laden surface water downstream of conventional coagulation-clarification and upstream of an ultrafiltration (UF) membrane process was assessed for its treatment effectiveness. The impact of biofiltration pretreatment on UF membrane performance was evaluated holistically by investigating the native source water chemistry and extending the analysis into the drinking water distribution system. The biofiltration process was also compared in treatment performance to two alternative pretreatment technologies, including magnetic ion exchange (MIEX(&)#174;) and granular activated carbon (GAC) adsorption.The MIEX(&)#174;, GAC adsorption, and biologically active carbon (BAC) filtration pretreatments were integrated with conventional pretreatment then compared at the pilot-scale. Comparisons were based on collecting data regarding operational requirements, dissolved organic carbon (DOC) reduction, regulated disinfection byproduct (DBP) formation, and improvement on the downstream UF membrane operating performance. UF performance, as measured by the temperature corrected specific flux or mass transfer coefficient (MTC), was determined by calculating the percent MTC improvement relative to the existing conventional-UF process that served as the control. The pretreatment alternatives were further evaluated based on cost and non-cost considerations.Compared to the MIEX(&)#174; and GAC pretreatment alternatives, which achieved effective DOC removal (40 and 40 percent, respectively) and MTC improvement (14 and 30 percent, respectively), the BAC pretreatment achieved the lowest overall DOC removal (5 percent) and MTC improvement (4.5 percent). While MIEX(&)#174; relies on anion exchange and GAC relies on adsorption to target DOC removal, biofiltration uses microorganisms attached on the filter media to remove biodegradable DOC.Two mathematical models that establish an empirical relationship between the MTC improvement and the dimensionless alkalinity to substrate (ALK/DOC) ratio were developed. By combining the biofiltration results from the present research with findings of previous studies, an empirical relationship between the MTC improvement versus the ALK/DOC ratio was modeled using non-linear regression in Minitab(&)#174;. For surface water sources, UF MTC improvement can be simulated as a quadratic or Gaussian distribution function of the gram C/gram C dimensionless ALK/DOC ratio. According to the newly developed empirical models, biofiltration performance is optimized when the alkalinity to substrate ratio is between 10 and 14. For the first time a model has thus been developed that allows for a predictive means to optimize the operation of biofiltration as a pretreatment prior to UF membrane processes treating surface water.
Title: Assessing Biofiltration Pretreatment for Ultrafiltration Membrane Processes.
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Name(s): Cumming, Andrea, Author
Duranceau, Steven, Committee Chair
Cooper, David, Committee Member
Randall, Andrew, Committee Member
Wang, Dingbao, Committee Member
Yestrebsky, Cherie, Committee Member
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2015
Publisher: University of Central Florida
Language(s): English
Abstract/Description: An engineered biological filtration (biofiltration) process treating a nutrient-enriched, low-alkalinity, organic-laden surface water downstream of conventional coagulation-clarification and upstream of an ultrafiltration (UF) membrane process was assessed for its treatment effectiveness. The impact of biofiltration pretreatment on UF membrane performance was evaluated holistically by investigating the native source water chemistry and extending the analysis into the drinking water distribution system. The biofiltration process was also compared in treatment performance to two alternative pretreatment technologies, including magnetic ion exchange (MIEX(&)#174;) and granular activated carbon (GAC) adsorption.The MIEX(&)#174;, GAC adsorption, and biologically active carbon (BAC) filtration pretreatments were integrated with conventional pretreatment then compared at the pilot-scale. Comparisons were based on collecting data regarding operational requirements, dissolved organic carbon (DOC) reduction, regulated disinfection byproduct (DBP) formation, and improvement on the downstream UF membrane operating performance. UF performance, as measured by the temperature corrected specific flux or mass transfer coefficient (MTC), was determined by calculating the percent MTC improvement relative to the existing conventional-UF process that served as the control. The pretreatment alternatives were further evaluated based on cost and non-cost considerations.Compared to the MIEX(&)#174; and GAC pretreatment alternatives, which achieved effective DOC removal (40 and 40 percent, respectively) and MTC improvement (14 and 30 percent, respectively), the BAC pretreatment achieved the lowest overall DOC removal (5 percent) and MTC improvement (4.5 percent). While MIEX(&)#174; relies on anion exchange and GAC relies on adsorption to target DOC removal, biofiltration uses microorganisms attached on the filter media to remove biodegradable DOC.Two mathematical models that establish an empirical relationship between the MTC improvement and the dimensionless alkalinity to substrate (ALK/DOC) ratio were developed. By combining the biofiltration results from the present research with findings of previous studies, an empirical relationship between the MTC improvement versus the ALK/DOC ratio was modeled using non-linear regression in Minitab(&)#174;. For surface water sources, UF MTC improvement can be simulated as a quadratic or Gaussian distribution function of the gram C/gram C dimensionless ALK/DOC ratio. According to the newly developed empirical models, biofiltration performance is optimized when the alkalinity to substrate ratio is between 10 and 14. For the first time a model has thus been developed that allows for a predictive means to optimize the operation of biofiltration as a pretreatment prior to UF membrane processes treating surface water.
Identifier: CFE0005595 (IID), ucf:50260 (fedora)
Note(s): 2015-05-01
Ph.D.
Engineering and Computer Science, Civil, Environmental and Construction Engineering
Doctoral
This record was generated from author submitted information.
Subject(s): Surface water -- biofiltration -- pretreatment -- ultrafiltration -- membrane fouling -- modeling
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0005595
Restrictions on Access: public 2015-05-15
Host Institution: UCF

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