Nitrification Pathways in Membrane Aerated Biofilm Reactors to Treat Municipal Wastewater
Bibliographic record
Abstract
Recently, nitritation-denitritation has been demonstrated as an effective nitrogen removal alternative by reducing oxygen consumption and carbon supply, lowering CO2 emission, decreasing sludge production, and minimising the volume of reactors as compared to conventional nitrification and denitrification process. In the meantime, membrane aerated biofilm reactor (MABR) process becomes increasingly attractive due to the efficient dissolution of oxygen via molecular diffusion into water, resulting in up to five times more energy efficient than conventional aerators and above 75% of oxygen transfer efficiencies. Further potential benefits could be realized by combining partial nitrification with MABR. However, the relative importance of nitrogen removal pathways in MABR is still not well understood, due to the lack of reliable methods to measure the amount of their oxygen consumptions.Three MABR parallel testing systems equipped with ZeelungTM (SUEZ WTS, Hungry) membrane fibres were continuously operated for 230 days to treat synthetic wastewater. They included five sequential stages: biofilm seeding followed by the effects of substrate loadings in hybrid and non-hybrid operating modes, and C/N ratios in hybrid and non-hybrid operating modes. A mathematical MABR model based on wastewater process simulation software GPS-x® and calibrated with experimental data.To determine oxygen fluxes and mass transfer coefficients, three different methods were carried out. Results showed that gas phase mass balance (GPMB) method can be used to determine the oxygen flux reliably for MABRs used in wastewater treatment. Coupling with the liquid phase mass balance (LPMB) approach, the extent of partial nitrification can be estimated. Pressure decay mass transfer (PDMT) method could be applied to determine both mass transfer coefficient and the biofilm thickness. Hybrid MABRs (HMABRs) and MABRs achieved the COD removal of 91%, 87% and TN removal of 57% and 40%, respectively. Up to 14% and 11% of influent NH4+-N could be oxidized by partial nitrification by HMABRs and MABRs, respectively. Partial nitrification by both HMABRs and MABRs increased with the ammonia loading, and C/N ratio, while HMABRs had significant advantages in nitrogen pollutant removal at high substrate loading rates over MABRs. Further characterization of biofilm and suspended solids in HMABRs using fluorescence in situ hybridization (FISH) coupled with confocal laser scanning microscopy (CLSM) showed that the biovolume fractions of nitrite-reducing bacteria were up to 26% and 5%, respectively. The oxygen half saturation constants for AOB and NOB were 0.14 and 0.82 gO2/m3, respectively, after model calibration using GPS-x®. This indicated that AOB can grow in lower dissolved oxygen concentration than NOB.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".