Life-cycle assessment of greenhouse gas emissions from dairy production in Eastern Canada: A case study
Bibliographic record
Abstract
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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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".