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Resource recovery from wastewater by anaerobic membrane bioreactors: Opportunities and challenges

Open access
Song, Xiaoye, Luo, Wenhai, Hai, Faisal I., Price, William E., Guo, Wenshan, Ngo, Hao H., Nghiem, Long D.·2018·Bioresource Technology

Abstract

This review examines the potential of anaerobic membrane bioreactor (AnMBR) to serve as the core technology for simultaneous recovery of clean water, energy, and nutrient from wastewater. The potential is significant as AnMBR treatment can remove a board range of trace organic contaminants relevant to water reuse, convert organics in wastewater to biogas for subsequent energy production, and liberate nutrients to soluble forms (e.g. ammonia and phosphorus) for subsequent recovery for fertilizer production. Yet, there remain several significant challenges to the further development of AnMBR. These challenges evolve around the dilute nature of municipal wastewater, which entails the need for pre-concentrating wastewater prior to AnMBR, and hence, issues related to salinity build-up, accumulation of substances, membrane fouling, and membrane stability. Strategies to address these challenges are proposed and discussed. A road map for further research is also provided to guide future AnMBR development toward resource recovery.

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Metadata

Authors
Song, X., Luo, W., Hai, F. I., Price, W. E., Guo, W., Ngo, H. H., & Nghiem, L. D.
Venue
Bioresource Technology
Publisher
Elsevier BV
Published
2018-12
Volume
270
Pages
669-677
ISSN
0960-8524 (ISSN-L)
OpenAlex
W2891200793
Cited by
191
References
0
FWCI
17.60
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Resource recovery from wastewater by anaerobic membrane bioreactors: Opportunities and challenges. https://app.cochat.ai/papers/10.1016/j.biortech.2018.09.001
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Song, X., Luo, W., Hai, F. I., Price, W. E., Guo, W., Ngo, H. H., & Nghiem, L. D. (2018). Resource recovery from wastewater by anaerobic membrane bioreactors: Opportunities and challenges. Bioresource Technology. https://doi.org/10.1016/j.biortech.2018.09.001

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.