Spatially-resolved in-situ quantification of biofouling using optical coherence tomography (OCT) and 3D image analysis in a spacer filled channel

Luca Fortunato, Szilard Bucs, Rodrigo Valladares Linares, Corrado Cali, Johannes S. Vrouwenvelder, TorOve Leiknes

Research output: Contribution to journalArticlepeer-review

62 Scopus citations


The use of optical coherence tomography (OCT) to investigate biomass in membrane systems has increased with time. OCT is able to characterize the biomass in-situ and non-destructively. In this study, a novel approach to process three-dimensional (3D) OCT scans is proposed. The approach allows obtaining spatially-resolved detailed structural biomass information. The 3D biomass reconstruction enables analysis of the biomass only, obtained by subtracting the time zero scan to all images. A 3D time series analysis of biomass development in a spacer filled channel under representative conditions (cross flow velocity) for a spiral wound membrane element was performed. The flow cell was operated for five days with monitoring of ultrafiltration membrane performance: feed channel pressure drop and permeate flux. The biomass development in the flow cell was detected by OCT before a performance decline was observed. Feed channel pressure drop continuously increased with increasing biomass volume, while flux decline was mainly affected in the initial phase of biomass accumulation. The novel OCT imaging approach enabled the assessment of spatial biomass distribution in the flow cell, discriminating the total biomass volume between the membrane, feed spacer and glass window. Biomass accumulation was stronger on the feed spacer during the early stage of biofouling, impacting the feed channel pressure drop stronger than permeate flux.
Original languageEnglish (US)
Pages (from-to)673-681
Number of pages9
JournalJournal of Membrane Science
StatePublished - Nov 21 2016

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This study was supported by funding from King Abdullah University of Science and Technology (KAUST).


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