Ammonia separation from wastewater using bipolar membrane electrodialysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Nitrogen pollution is a serious environmental challenge in natural water and thus selective ammonia separation in wastewater treatment is of great importance to decrease the nitrogen load to natural water systems. Bipolar membrane electrodialysis (BMED) is a relatively new ion exchange membrane technology that can be used for ammonia recovery from wastewater as a beneficial substance. A bench‐scale BMED stack with seven pairs of bipolar membrane (BPM) and a cation exchange membrane (CEM) was operated under various voltage applications to separate ammonia from dewatering centrate (liquid downstream from dewatering of anaerobically digested wastewater sludge). Ammonia in the wastewater was rapidly separated (up to 87% in 30 min) and recovered as ammonium hydroxide solution using the BMED stack. We found that the maximum rate of ammonium separation was governed by the concentration polarization near CEMs rather than water transport into BPMs. In addition, even with the significantly high organic level in dewatering centrate (408 mg/L as total suspended solids), high efficient ammonia separation was maintained over 8 repeated BMED operations without any pretreatment of the feed wastewater, indicating effective organic fouling control with regular chemical cleaning. Furthermore, BMED operation for 30 minutes at 5.0 V per cell pair was found to be ideal for high purity ammonium hydroxide production and low electrical energy consumption. Based on the high separation efficiency and low energy consumption, we suggest that BMED be further investigated as an attractive option for ammonia separation and recovery from wastewater.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it