Farm practices survey and modelling to estimate monthly NH<sub>3</sub> emissions from swine production in 12 Ecoregions of Canada
Notice bibliographique
Résumé
The swine industry in Canada has undergone rapid growth in some areas, but has also been restricted by a variety of environmental issues. Ammonia (NH 3 ) emissions are seldom mentioned among these issues, but emissions do occur and atmospheric NH 3 causes a number of impacts including contributing to odour, deposition into sensitive ecosystems and formation of secondary particulate matter, which is a health concern in some regions of North America. This paper describes a new model to estimate NH 3 emissions from the swine sector, relying heavily on a recent survey of swine producers to determine the present N and manure management practices. The key hypothesis was that NH 3 emission rates vary across Ecoregions and over time in a way that affects the degree of impact. The survey showed many differences across Ecoregions, most importantly related to feed crude protein and landspreading practices. The model estimated that grower pigs (>20 kg to market size) excreted on average about 8.5 kg total ammoniacal N (TAN) per (occupied) pig place per year, and based on the national average farm practices, 25% of this TAN was emitted from barns, 5. 3 % was emitted from manure storage, and 17% was emitted during landspreading for a total of 4.8 kg NH 3 pig-place -1 yr -1 . The total loss for grower pigs ranged from 40 to 53% of excreted TAN across the 12 Ecoregions. Nursing sows emitted over twice as much per pig. Regions varied in reliance on homegrown feeds, which affected crude protein feeding and TAN excretion rates. Western regions had relatively low emissions from land application of slurry because of more extensive use of injectors. Emissions from grower pigs in winter were about 0.2 kg NH 3 pig-place -1 month -1 , mostly from barns, to as high as 0.7 kg NH 3 pig-place -1 month -1 in May, mostly from landspreading. Total emission for all of Canada in 2006 was 73 × 106 kg NH 3 or about 13% of agricultural emissions in Canada. The results indicate that emission reductions can be achieved with greater use of low-emission application methods and reduced crude protein in feed. The emissions model can be used in future to assess the impacts from changes in feeding regimes and barn designs, and changes in practices such as animal density and increased access to outdoor spaces.Key words: Swine, ammonia, nitrogen, manure, emissions
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».