Life cycle assessment of poly (butylene adipate-co-terephthalate) (PBAT)-talc Ontario agri-film
Bibliographic record
Abstract
The environmental impacts of a compostable greenhouse film composed of 85% poly (butylene adipate-co-terephthalate) (PBAT) and 15% talc are examined within a cradle-to-grave framework using an environmental life cycle assessment (LCA). This assessment is essential for understanding the sustainability of this solution in relation to the conventional, non-biodegradable plastics commonly used for greenhouse cover materials in Ontario, thereby supporting the resiliency and sustainability of the greenhouse agriculture sector. The Ecoinvent database within SimaPro software was coupled with the key standards of ISO 14040:2006 and 14044:2006 to conduct an environmental LCA per functional unit of 1 kg of PBAT-talc film. Data consisted of primary and secondary inventory sourced from the University of Guelph Bioproducts Discovery and Development Centre and literature, respectively. Using the TRACI 2.1 method, environmental burdens were calculated and mitigated. Key hotspots emerged from the preparation, blown film, and composting stages. By incorporating sustainable energy mixes and biobased components of PBAT instead of petroleum-based compounds, the leading normalized categories of carcinogenic and ecotoxicity impacts were significantly reduced. With these suggested sensitivity modifications, PBAT-talc film proves to be the more sustainable option compared to all other conventional films. The Ontario agricultural greenhouse industry must seek greenhouse cover materials with the least environmental impacts, as this film demonstrates relative to other options. Aligning with global and national initiatives, this study addresses Ontario's greenhouse cover sustainability in the agriculture sector, with additional recommendations to further improve these outcomes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".