Comparing the effect of carbon media on nutrient removal and greenhouse gas production in laboratory-scale bioreactors
Bibliographic record
Abstract
Abstract The performance of locally available agricultural carbon media (barley straw and hemp straw) was compared to woodchips for removing nitrate (NO3-N) and orthophosphate (PO4-P) in up-flow laboratory bioreactors. These media were tested in three replicates to quantify variability. The production of greenhouse gases nitrous oxide (N2O), methane (CH4) and carbon dioxide (CO2) were quantified. Influent water with NO3-N and PO4-P flowed continuously through bioreactors at a 4-h hydraulic retention time at 20 °C for 16 weeks. Nitrate removal reached up to 37% across all carbon media after the fifth week, with a removal rate of 64 g N m−3 d−1. Nitrate removal was affected by the type of carbon media in the order of barley straw > hemp straw > woodchips (P < 0.05). Most of the PO4-P rates declined rapidly after the first week for all carbon media meaning none were superior. Greenhouse gas production was dominated by CO2 with less CH4 and N2O produced. Production of N2O relative to nitrate removal for the three media remained low at 0.16 to 0.75%. The findings suggest that agricultural residues could perform better than woodchips for NO3-N removal although there was slightly higher N2O and CO2 production for these residues than woodchips.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".