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A-Stage process - Challenges and drawbacks from lab to full scale studies: A review
Raja-Sekhar Guthi1, Katharina Tondera2, Sylvie Gillot2
1INRAE, REVERSAAL, Villeurbanne F-69625, France; Saur, Direction Innovation Technologique, Maurepas 78310, France.
Wastewater can be a valuable resource. The A-Stage process recovers organic matter from wastewater for biomaterials or biogas, unlike conventional treatment plants. Optimal operation maximizes resource recovery.
Area of Science:
- Environmental Engineering
- Biotechnology
- Resource Recovery
Background:
- Growing global resource scarcity necessitates viewing wastewater as a resource, not waste.
- Conventional wastewater treatment plants (WWTPs) oxidize organic matter, hindering recovery for biomaterials or biogas.
- The A-Stage process offers a solution by concentrating organic matter for valorisation, suitable for retrofitting existing WWTPs.
Purpose of the Study:
- To summarize peer-reviewed research on the A-Stage process under real conditions.
- To highlight key operational parameters for maximizing resource recovery.
- To critically review modeling efforts and identify areas for future research.
Main Methods:
- Review of pilot-scale and full-scale studies of the A-Stage process.
- Analysis of key operational parameters such as sludge retention time (SRT), hydraulic residence time (HRT), and dissolved oxygen (DO).
- Evaluation of nutrient removal efficiencies and discussion of settling efficiencies and modeling.
Main Results:
- Optimal SRT of 0.3 days maximizes influent COD redirection (up to 50%) to sludge flux while limiting mineralization (<25%).
- Optimal HRT of 30 minutes and DO levels of 0.5 mg/L are identified.
- Observed nutrient removal efficiencies: 15-27% for total nitrogen and 13-38% for total phosphorus.
Conclusions:
- The A-Stage process effectively recovers organic matter from wastewater.
- Sludge retention time is a critical parameter for optimizing resource recovery.
- Further research is needed on mixing, wet weather flow, temperature impacts, and settling processes for improved A-Stage process understanding and modeling.
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