Ammonia emission from dairy cow manure stored in a lagoon over summer
Bibliographic record
Abstract
It is recognized that volatilized ammonia (NH3) from intensive livestock production can be a significant pathway for nitrogen (N) pollution to land and water, and can contribute to poor air quality. The objectives of our study were to document NH3 emissions from a dairy lagoon and to assess the influence of meteorology on NH3 emissions. Ammonia emissions were determined using a backward Lagrangian Stochastic approach using WindTrax software, an open-path NH3 laser and a sonic anemometer. Results indicate that an average 5.1 ± 1.6 g NH3 m-2 d-1 was released over the summer; however, the emission varied typically over 24 h between 3.6 and 8.6 g NH3 m-2 d-1. Wind speed and surface temperature of the lagoon had similar influences on the magnitude of the release, where their direct impact on NH3 emission accounted for 28 and 31% of the variability, respectively. The main implication of this study is that NH3 losses are significant from dairy lagoons, contributing to the issue of N pollution. As well, NH3 emissions are a loss of valuable N for manure used as fertilizer, which in our study amounted to approximately 13% of the total ammoniacal N content of the manure in the lagoon. Key words: Ammonia, dairy, manure, cattle, dispersion model
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".