The Fossil Energy and CO2 Emissions Budget for the Barnyard Operations of Livestock Farms in Canada
Bibliographic record
Abstract
This paper describes fossil fuel energy use for on-farm transportation, heating of farm buildings, electricity generation, machinery supply and the spreading of manure. These four terms describe the barnyard energy budget. Calculations for this energy budget were driven by population data for beef and dairy cattle, hogs and poultry in Canada. Prior to comparing this energy budget for 2001 and 2011, the year-to-year trends from 1990 to 2014 were analysed. The declines in all livestock populations, except poultry, between 2001 and 2011 reduced the size of the Canadian barnyard energy budget from 25 PJ to 22 PJ. The resulting change in the fossil CO2 emissions between 2001 and 2011 was from 1.62 MtCO2 to 1.36 MtCO2. A sensitivity analysis based on future elimination of coal for generating electricity, introduction of electric pickup trucks (e-pickups) and increased use of electric heat, reduced fossil CO2 emissions during 2011 from dairy farms by 29%, beef farms by 24%, hog farms by 19% and poultry by 13%. The most affected provinces by this test were Alberta and Saskatchewan because of the heavy dependence on coal in electricity generation in these two provinces. This scenario test suggests a Canada-wide potential reduction of 0.30 MtCO2. A second sensitivity test based on a Canada-wide 20% reallocation of protein production from beef to pork revealed a very modest potential to actually reduce barnyard fossil CO2 emissions by 0.09 MtCO2 for Canada.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".