Dinitrogen and methane gas production during the anaerobic/anoxic decomposition of animal manure
Bibliographic record
Abstract
Trace-gas emissions from animal feeding operations (AFOs) can contribute to air quality and global change gases. Previous and current estimated gas emissions from AFOs vary widely and many do not consider all forms of carbon (C) and nitrogen (N) emissions. Studies have found that as methanogenesis in the lagoons increased, conversion of ammonium (NH4 +) to dinitrogen (N2) also increased. The purpose of this research was to measure N2 and CH4 emissions from swine AFOs in three locations of the U.S. and to evaluate the possible universal relationship between lagoon methanogenesis and the conversion of NH4 + to N2 gas. This relationship was tested by measuring N2 and CH4 emissions in two climates at 22 different farms. Methanogenesis was correlated with NH4 +-to-N2 conversion by a near-constant N2 to CH4 emissions ratio of 0.20, regardless of C loading and climatic effects. The process is shown to be thermodynamically favored when there is competition between NH4 + oxidizing reactions. Under methanogenic conditions (redox potentials of methanogenesis) N2 production is favorable and nitrification/denitrification is not. Thus, N2 production is stimulated in methanogenic conditions. Evaluation of NH3 gas emissions from AFOs must consider other N emissions than NH3. Finally, a statistical model was developed to estimate methane and N2 emissions (kg gas ha−1) given feed input per lagoon surface area (kg feed ha−1) and local air temperature. Further studies are needed to investigate the mechanisms involved in manure processing and isolate the favorable mechanisms into engineering improved manure processing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 teacher head, 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".