Room-scale Study of the Effectiveness of Zinc Oxide Nanoparticles in Reducing Gas Emissions from Swine Manure
Bibliographic record
Abstract
Mixing zinc oxide (ZnO) nanoparticles with the slurry was investigated in this study as a possible measure to control gas emissions from swine barns. The objective of this work is to determine the impact of the treatment on reducing the levels of ammonia and hydrogen sulphide gases emitted from swine manure as well as assess its effect on hog performance and manure properties. Two identical and fully instrumented environmental chambers at Prairie Swine Centre Inc. barn facility in Saskatoon, Saskatchewan, that closely represent actual production conditions were used; one was treated with ZnO nanoparticles (Treatment) and the other one was remained untreated (Control). Three replicate trials, each lasting for 30 days, were conducted. During each trial, ammonia (NH3) and hydrogen sulphide (H2S) levels, manure properties and hog performance (average daily gain, average daily feed intake, water usage and manure production rates) were monitored in both chambers. Results showed that the addition of ZnO nanoparticles into the slurry can significantly reduce H2S level by more than 95% but has no significant impact on NH3 emission. The application of the treatment has no considerable effect on pig performance and physicochemical properties of the manure.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".