The Development of Emission Factors for Ammonia and Size-Fractioned Particulate Matter from a Cage-Free Layer Facility in Western Canada
Bibliographic record
Abstract
The Canadian egg industry is currently facing an industry wide transition in layer barn hen housing style from conventional battery-cage barns to cage-free or enriched cage barns. This transition in housing style, although aimed to improve hen welfare, has brought about concerns for the indoor air quality and the environmental impact of these facilities. To assess these concerns, a research study was performed at a free-run aviary layer barn in central Saskatchewan, Canada, periodically spanning August of 2018 to May of 2019. This study measured several barn parameters, meteorological conditions, hen details, and pollutant concentrations to develop emission factors (EFs, g d-1 AU-1, AU – “animal unit” which is equivalent to 500 kg of live mass) for ammonia (NH3) and size-fractioned particulate matter (PM2.5 and PM10). The overall EFs for this facility for ammonia, PM2.5, and PM10 were 13.91 ± 16.04, 16.27 ± 23.40, and 37.74 ± 50.62 g d-1 AU-1, respectively. EFs were found to vary seasonally and diurnally. The ventilation rate, litter conditions, relative humidity, and hen activity all had strong impacts on the emissions from this facility. The ammonia EFs from this facility were less than those found from similar studies performed in Ontario, Canada on a conventional battery-cage barn and on a free-run aviary barn. The PM EFs from this study were greater than those found from the same studies in Ontario. Differences in EFs between the facilities were attributed to differences in housing styles, relative humidity, and temperature. \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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".