Predicting membrane fouling in membrane bioreactor systems using viscosity: Impacts of environmental conditions and antifouling agents

This study attempted to establish a viscosity-based prediction of membrane fouling. Various factors, including pH, temperature, MLSS concentration, and the addition of NaOCl and citric acid were identified, and their effect on sludge properties such as EPS concentration and wastewater viscosity were estimated. There was a very good correlation between these parameters with EPS concentration and viscosity. The increase in EPS concentration and viscosity significantly affected the membrane flux and filtration time for all the different experimental conditions. However, there were fluctuations in results obtained from experiments related to change in pH, including the addition of antifouling agents NaOCl and citric acid. Such variations accompanied by low correlation in these experiments indicated the influence of pH that may pose difficulty in a viscosity-based estimation of membrane fouling. However, if such large variations in operating conditions could be avoided and the reactor could be operated under optimal conditions, a much better correlation could be obtained between viscosity and membrane fouling. Data from continuously operated MBR systems support this observation, where even a linear equation defining relation between viscosity and transmembrane pressure (TMP) could be obtained. Overall, findings from this study provide a great insight into membrane fouling prediction using viscosity-based methods.

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Publication Details

Journal
Journal of Environmental Management
Published
2024-10-16
DOI
https://doi.org/10.1016/j.jenvman.2024.122868
Citations
6
Primary Topic
Membrane Separation Technologies
Type
article
Field-Weighted Citation Impact
1.21
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article

Predicting membrane fouling in membrane bioreactor systems using viscosity: Impacts of environmental conditions and antifouling agents

Seung Hui Kim, Chong Min Chung, Arindam Sinahroy
6 citations
Journal of Environmental Management
Membrane Separation Technologies
1.21
article

Predicting membrane fouling in membrane bioreactor systems using viscosity: Impacts of environmental conditions and antifouling agents

Seung Hui Kim, Chong Min Chung, Arindam Sinahroy
article en
6 citations

Abstract

This study attempted to establish a viscosity-based prediction of membrane fouling. Various factors, including pH, temperature, MLSS concentration, and the addition of NaOCl and citric acid were identified, and their effect on sludge properties such as EPS concentration and wastewater viscosity were estimated. There was a very good correlation between these parameters with EPS concentration and viscosity. The increase in EPS concentration and viscosity significantly affected the membrane flux and filtration time for all the different experimental conditions. However, there were fluctuations in results obtained from experiments related to change in pH, including the addition of antifouling agents NaOCl and citric acid. Such variations accompanied by low correlation in these experiments indicated the influence of pH that may pose difficulty in a viscosity-based estimation of membrane fouling. However, if such large variations in operating conditions could be avoided and the reactor could be operated under optimal conditions, a much better correlation could be obtained between viscosity and membrane fouling. Data from continuously operated MBR systems support this observation, where even a linear equation defining relation between viscosity and transmembrane pressure (TMP) could be obtained. Overall, findings from this study provide a great insight into membrane fouling prediction using viscosity-based methods.

Journal of Environmental ManagementVol. 370
Jeonju University (KR)
Openalex Percentile: Top 22%
Membrane Separation Technologies
1.21
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Predicting membrane fouling in membrane bioreactor systems using viscosity: Impacts of environmental conditions and antifouling agents — Seung Hui Kim, Chong Min Chung, et al. · Journal of Environmental Management (2024) | TGRS Research Map | TGRS