The variation of nitrifying bacterial population sizes in a sequencing batch reactor (SBR) treating low, mid, high concentrated synthetic wastewater
Why this work is in the frame
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Bibliographic record
Abstract
The purpose of this study was to correlate the population size of ammonia-oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB) with nitrification performance under various operational conditions (chemical oxygen demand (COD) concentration, dissolved oxygen (DO), and hydraulic retention time (HRT)) and influent allylthiourea (ATU) shock. The AOB (genera Nitrosomonas and Nitrosospira ) and NOB (genera Nitrobacter and Nitrospira ) communities were analyzed using fluorescent in situ hybridization (FISH). Ammonia-oxidizing bacteria and NOB accounted for 6.2 ± 0.9% and 2.5 ± 0.3% in total biomass, respectively. The population sizes of AOB and NOB varied with different levels of COD, DO, and HRT. Nitrosomonas and Nitrospira were dominant under conditions favorable for nitrification, while Nitrosospira outcompeted Nitrosomonas under adverse conditions (low [NH 4 + ], low DO, short HRT, and ATU shock), and Nitrobacter outcompeted Nitrospira at high substrate concentrations (COD and [NH 4 + ]). Under ATU shock that inhibited the oxidation of NH 4 + to NO 2 – , AOB population was substantially reduced with the stepwise increase of ATU dosage, and led to a corresponding decrease of NOB population. There was a discrepancy between nitrifying bacterial populations and their functions. Although AOB outnumbered NOB in all tests and became more dominant at low DO and short HRT, NH 4 + oxidation, instead of NO 2 – oxidation, was the rate-limiting reaction for nitrification and susceptible to the adverse conditions. The study demonstrated the importance of elucidating the shifts of nitrifying bacterial population to optimize process design and operation at different influent characteristics, aeration intensity, retention time, and potential influent toxic shock.
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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 | 0.001 | 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