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Abstract There is a strong impetus to establish a circular phosphorus economy by securing internally renewable phosphate (Pi) resources for use as agricultural fertilizers. Reversible Piadsorption technologies such as ion exchange can remove and recover Pifrom water/wastewater for reuse. However, existing reversible adsorbents cannot effectively discriminate against arsenate (As(V)) due to the similarity between As(V) and Pichemical structure. If As(V) is co‐recovered with Pi, the value of the recovered products for agricultural reuse is low. The objective of this study was to construct an immobilized phosphate‐binding protein (PBP)‐based Piremoval and recovery system and analyze its selectivity for Piadsorption in the presence of As(V). A range of conditions was tested, including independent, sequential, and simultaneous exposure of the two oxyanions to immobilized PBP (PBP resin). The purity of the recovered Piproduct was assessed after inducing controlled desorption of the adsorbed oxyanions at high pH (pH 12.5). Piconstituted more than 97% of the adsorbed oxyanions in the recovered product, even when As(V) was initially present at twofold higher concentrations than Pi. Therefore, PBP resin has potential to selectively remove Pi, as well as release high‐purity Pifree of As(V) contamination suitable for subsequent agricultural reuse. Practitioner pointsExisting reversible phosphate (Pi) adsorbents cannot effectively discriminate against arsenate (As(V)) due to the similarity in their chemical structure.Co‐recovery of As(V) with Pican reduce the recovered product's reuse as a fertilizer.An immobilized phosphate‐binding protein (PBP)‐based system can be highly selective for Pieven in the presence of As(V).Piconstituted more than 97% of the recovered product, even when As(V) was present at 2‐fold higher concentrations than Pi.Immobilized PBP offers advantages over existing Piadsorbents by providing high‐purity Piproducts free of As(V) contamination for reuse.
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Weathering Environmental Change Through Advances in AI
Developing trustworthy artificial intelligence for weather and ocean forecasting, as well as for long-term environmental sustainability, requires integrating collaborative efforts from many sources.
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- Award ID(s):
- 2019758
- PAR ID:
- 10512822
- Publisher / Repository:
- AGU
- Date Published:
- Journal Name:
- Eos
- Volume:
- 101
- ISSN:
- 2324-9250
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1029/2020EO147065
