Analysis of Air Pollution from Swine Production by Using Air Dispersion Model and GIS in Quebec
Bibliographic record
Abstract
Swine production, the second most important contributor to Quebec's agricultural revenue, faces many problems. Intensive piggeries, with up to 599 animal units, are used to raise finishing pigs for slaughter. Among the great number of gaseous species emitted to the atmospheric environment from livestock buildings and manure storage units is NH3, which is one of the most important and most offensive with respect to human health. Under appropriate meteorological and topographical conditions, gaseous contaminants can spread and cause a public nuisance--up to a 1-km radius around the farm. To mitigate these effects, the Quebec Government adopted regulations that set minimum buffer distances to be observed by any expansion of an existing or new pig farm. The objectives of this study were (i) to assess the efficiency of the current buffer distance prescriptions in Quebec in mitigating effects of air pollution from swine units and (ii) to identify potential areas for establishing pig farm operations that will not be offensive to people. The air dispersion American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) with receptors distributed at 1.6 km around each source was used first, followed by a spatial geographic information system (GIS) model. Results from the dispersion model showed that the highest hourly concentration with a 99.5% compliance frequency for a single farm was 3078.1 microg/m3 and exceeded the NH3 odor criterion hourly standard set by the Quebec Government at 183.4 microg/m3. Thus, for public safety, densely populated areas like housing developments must be located >1300 m from a pig farm. This distance is in the range of setback distances (723 to 1447 m) obtained by using abacuses defined in the L'Erable Regional County Municipality. That is why we can say the current rules established by the Quebec Government, if rigorously applied, can prevent odor nuisance, due to NH3 emission, from swine farms. In the spatial model, buffer zones were established around houses, roads, waterways, and drinking water intakes. By combining layers of information in the ArcGIS Model Builder, potential areas in which pig farms can be installed, without public odor nuisance, were identified.
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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 | 0.000 |
| 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".