The Effect of Biofuel Production on Swine Farm Methane and Ammonia Emissions
Bibliographic record
Abstract
Methane (CH) and ammonia (NH3) are emitted to the atmosphere during anaerobic processing of organic matter, and both gases have detrimental environmental effects. Methane conversion to biofuel production has been suggested to reduce CH4 emissions from animal manure processing systems. The purpose of this research is to evaluate the change in CH4 and NH3 emissions in an animal feeding operation due to biofuel production from the animal manure. Gas emissions were measured from swine farms differing only in their manure-management treatment systems (conventional vs. biofuel). By removing organic matter (i.e., carbon) from the biofuel farms' manure-processing lagoons, average annual CH4 emissions were decreased by 47% compared with the conventional farm. This represents a net 44% decrease in global warming potential (CO2 equivalent) by gases emitted from the biofuel farms compared with conventional farms. However, because of the reduction of methanogenesis and its reduced effect on the chemical conversion of ammonium (NH4+) to dinitrogen (N2) gas, NH3 emissions in the biofuel farms increased by 46% over the conventional farms. These studies show that what is considered an environmentally friendly technology had mixed results and that all components of a system should be studied when making changes to existing systems.
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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) | 0.000 | 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) | 0.001 | 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".