Life-cycle assessment of greenhouse gas emissions from dairy production in Eastern Canada: A case study
Notice bibliographique
Résumé
The objective of this study was to conduct a life-cycle assessment (LCA) of greenhouse gas (GHG) emissions from a typical nongrazing dairy production system in Eastern Canada. Additionally, as dairying generates both milk and meat, this study assessed several methods of allocating emissions between these coproducts. An LCA was carried out for a simulated farm based on a typical nongrazing dairy production system in Quebec. The LCA was conducted over 6 yr, the typical lifespan of dairy cows in this province. The assessment considered 65 female Holstein calves, of which 60 heifers survived to first calving at 27 mo of age. These animals were subsequently retained for an average of 2.75 lactations. Progeny were also included in the analysis, with bulls and heifers in excess of replacement requirements finished as grain-fed veal (270 kg) at 6.5 mo of age. All cattle were housed indoors and fed forages and grains produced on the same farm. Pre-farm gate GHG emissions and removals were quantified using Holos, a whole-farm software model developed by Agriculture and Agri-Food Canada and based on the Intergovernmental Panel for Climate Change Tier 2 and 3methodologies with modifications for Canadian conditions. The LCA yielded a GHG intensity of 0.92 kg of CO(2) Eq/kg of fat- and protein-corrected milk yield. Methane (CH(4)) accounted for 56% of total emissions, with 86% originating from enteric fermentation. Nitrous oxide accounted for 40% of total GHG emissions. Lactating cows contributed 64% of total GHG emissions, whereas calves under 12 mo contributed 10% and veal calves only 3%. Allocation of GHG emissions between meat and milk were assessed as (1) 100% allocation to milk, (2) economics, (3) dairy versus veal animals, and (4) International Dairy Federation equation using feed energy demand for meat and milk production. Comparing emissions from dairy versus veal calves resulted in 97% of the emissions allocated to milk. The lowest allocation of emissions to milk (78%) was associated with the International Dairy Federation equation. This LCA showed that greatest reductions in GHG emissions would be achieved by applying mitigation strategies to reduce enteric CH(4) from the lactating cow, with minimal reductions being achievable in young stock. Choice of coproduct allocation method can also significantly affect the relative allocation of GHG emissions to milk and meat.
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,002 |
| 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 ».