Nitrous Oxide Production from Urea Granules of Different Sizes
Bibliographic record
Abstract
Abstract Three laboratory experiments were conducted to determine if urea granule size or a high concentration of urea prills influence N2O production in soil. Urea hydrolysis results in a localized increase in soil pH and an increase in ammonia concentration. Such conditions may adversely affect the nitrification process, thereby increasing the N2O to NO−3 product ratio. Also, if anaerobic conditions should occur, the N2O to N2 product ratio during denitrification may increase. In general, under aerobic conditions, increasing the urea granule size from a powder to prill (commercial granules) and to larger granules resulted in increased N2O production. The increase in N2O production as granule size increased was accompanied by an increase in NO−2 concentration. The accumulation of NO−2 and the lower rates of disappearance of NH+4, or appearance of NO−3, indicated that the nitrification process was adversely affected. The appearance of N2O was delayed with increasing granule size. A high concentration of urea prills produced a similar but greater effect than large granules. The appearance and rapid production of N2O was closely related to the rapid disappearance of hydroxylamine and the presence of NO−2. The failure to detect hydroxylamine in urea granule‐treated soil may have been due to its rapid oxidation to N2O. The proportion of the added urea N transformed to N2O increased with granule size but did not exceed 1.24% of the urea added. A high concentration of urea prills resulted in 2.80% converted to N2O−N.
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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 | 0.001 |
| 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".