Nitrate and phosphate removal in sulphur-coral stone autotrophic denitrification packed-bed reactors
Bibliographic record
Abstract
The removal effect on nitrate and phosphate of a sulphur-based autotrophic denitrifying bioreactor in composite packing of sulphur with coral stone were investigated on a pilot scale. The results showed that the optimal influent loading rate of the bioreactor (the ratio of sulphur volume to coral stone volume was 1:1) was in the range of 0·080 – 0·244 kg NO3−-N/(m3·d) when the water temperature was 29 ± 1 °C. In this range, the removal efficiency of nitrates was higher than 95% and no nitrite accumulation occurred in the effluent. The maximum nitrate volumetric removal rate of 0·594 kg NO3−-N / (m3·d) was achieved at an influent loading rate of 0·716 kg NO3−-N/(m3·d) with obvious nitrite accumulation in the effluent. Along with the autotrophic denitrifying reaction, an influent loading rate between 0·070 – 0·210 kg PO43−-P/ (m3·d) achieved the removal efficiency and volumetric removal rate of phosphates were 50·5% – 89·2% and 0·045 – „0·179 kg PO43−-P/(m3·d), respectively. The phosphates related to the resistance ability of the bioreactor (the ratio of sulphur volume to coral stone volume was 1:1) was stronger than that of bioreactors (the ratio of sulphur volume to coral stone volume was 1:2 and 1:4).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 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".