The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
A Forward Osmosis–Membrane Distillation Hybrid Process for Direct Sewer Mining: System Performance and Limitations
Open accessAbstract
This study demonstrates the robustness and treatment capacity of a forward osmosis (FO)-membrane distillation (MD) hybrid system for small-scale decentralized sewer mining. A stable water flux was realized using a laboratory-scale FO-MD hybrid system operating continuously with raw sewage as the feed at water recovery up to 80%. The hybrid system also showed an excellent capacity for the removal of trace organic contaminants (TrOCs), with removal rates ranging from 91 to 98%. The results suggest that TrOC transport through the FO membrane is governed by "solute-membrane" interaction, whereas that through the MD membrane is strongly correlated to TrOC volatility. Concentrations of organic matter and TrOCs in the draw solution increased substantially as the water recovery increased. This accumulation of some contaminants in the draw solution is attributed to the difference in their rejection by the FO and MD systems. We demonstrate that granular activated carbon adsorption or ultraviolet oxidation could be used to prevent contaminant accumulation in the draw solution, resulting in near complete rejection (>99.5%) of TrOCs.
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Self-citationMembrane distillation: A comprehensive review
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Self-citationTaking the “Waste” Out of “Wastewater” for Human Water Security and Ecosystem Sustainability
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Self-citationNovel forward osmosis process to effectively remove heavy metal ions
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Metadata
- Authors
- Xie, M., Nghiem, L. D., Price, W. E., & Elimelech, M.
- Venue
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Published
- 2013-11-15
- Volume
- 47
- Issue
- 23
- Pages
- 13486-13493
- ISSN
- 0013-936X (ISSN-L)
- 1520-5851
- OpenAlex
- W1998968098
- Cited by
- 271
- References
- 26
- FWCI
- 19.18
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
