Comparative life cycle assessment of alternative heating, ventilation and air-conditioning (HVAC) systems for poultry houses
Bibliographic record
Abstract
Most non-renewable energy use in poultry house operations is attributable to heating, ventilation, and air conditioning (HVAC) systems. Alternative HVAC systems have been well studied for commercial and residential applications, but their feasibility and sustainability impact mitigation potential in the livestock sector is largely unaddressed. This represents a significant knowledge gap. In this work, the potential for ground source heat pumps (GSHP) and earth-air heat exchangers (EAHE) to improve sustainability outcomes in layer hen poultry houses is quantified using an ISO 14044-based life cycle assessment. The life cycle impact assessment methods used were ReCiPe 2016 midpoint (H) and Cumulative Energy Demand. A scenario analysis was conducted to investigate the systems' application in various Canadian provinces. The results showed that alternative HVACs' environmental impact reduction potential varied with climatic regions and electricity grid mix sources. EAHEs always reduce total life cycle impacts of egg production compared to conventional HVAC systems across all impact categories and provinces, except for terrestrial ecotoxicity in British Columbia. EAHEs reduce the average environmental burden per tonne of eggs in Ontario and Alberta by 1.2 %, Quebec and Nova Scotia by ∼1 % and British Columbia by 0.6 %. GSHPs only reduce conventional HVACs' impacts in provinces with "green" electricity grids (i.e. driven primarily by renewable energy). GSHPs reduce the average total life cycle impacts of conventional HVAC systems per tonne of eggs by 2 % for Quebec and <0.5 % for British Columbia. However, environmental trade-offs were identified. In "dirty" electricity grid contexts (i.e. driven primarily by non-renewable energy), GSHPs increase conventional HVAC's average total life cycle impacts by <0.01 %, 3 %, and 1 % in Ontario, Alberta and Nova Scotia, respectively.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".