Long-term monitoring reveals improvements in nitrogen removal and energy efficiency with MABR upgrade at full scale
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Bibliographic record
Abstract
Membrane aerated biofilm reactors (MABR) are emerging to be a popular alternative for intensifying wastewater treatment . However, the performance of the technology has not yet been investigated at full-scale where mixing conditions and biofilm thickness control strategies differ from those employed in smaller-scale MABRs. This study investigated the long-term performance of one of the largest MABR installations in North America and reported key performance metrics related to nitrogen removal, aeration tank operations, and electricity consumption. Upgrading of the plant from a conventional activated sludge to a hybrid MABR configuration improved nitrification from seasonal to year-round performance. Denitrification in the hybrid MABR doubled the total nitrogen removal in the plant from 30 to 40 % before upgrade to 70–80 % afterwards. Operation at reduced MABR airflow (4.5 NL m −2 h −1 ) resulted in lower nitrification rates due to insufficient biofilm thickness control that led to diffusional limitations. Temperature was found to impact nitrification in the MABR with a 22 % decrease in nitrification rate from 1.8 ± 0.2 g-N m −2 d −1 during warm weather to 1.4 ± 0.2 g-N m −2 d −1 during cold weather conditions. The hybrid MABR denitrification efficiency was not substantially impacted by ammonia loading, process airflow, or wastewater temperature. Operation at a higher biofilm scouring intensity increased the NH 4 -N removal efficiency in the aeration tank during cold weather conditions suggesting increased nitrifier seeding due to enhanced sloughing of biofilm into the suspended sludge. Aeration related electricity consumption decreased by 50 % after the upgrade due to the efficiency of oxygen supply by the MABR and the reduction of aeration requirements in the downstream aeration basin . Overall, the improved nitrogen removal under reduced electricity consumption at full scale demonstrated the potential of MABR as a process intensification technology.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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