Elimination of nitrogen present in swine manure using a high-efficiency biotrickling filter
Bibliographic record
Abstract
Experiments were performed to remove nitrogen as ammonium in biotrickling filters (BTFs) treating synthetic swine manure. Two BTFs packed with polypropylene spheres and ceramic beads were used. BTFs were continuously fed, and leachate obtained was recirculated at different flow rates in the range from 0 to 1.5 L min(-1). When increasing the recirculation flow rate, the carbon dioxide (CO2) production rate increased from 16.5 to 25.6 g CO2 m(-3) h(-1) and nitrogen elimination decreased from 99% to 86% for the polypropylene spheres, whereas for the ceramic beads the CO2 production rate decreased from 20.3 to 15.0 g CO2 m(-3) h(-1) and nitrogen removal from 99% to 90%. The increase of recirculation flow rates also promoted the production of nitrite (NO2(-)) in the leachate. For both packing types, when increasing nitrogen loads from 60 to 240 g N m(-3) day(-1) without recirculation of leachate, the BTFs achieved nitrogen removals of more than 99%. For the same nitrogen loads, nitrogen removal increased from 90% to 99% for the BTF packed with ceramic beads at a recirculation flow rate of 0.6 L min(-1). Operating the BTFs with continuous purge was optimal for biomass production with a maximum level of 71.0 g m(-3) day(-1).
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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) | 0.000 | 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 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".