Life Cycle Assessment of Industrial Hemp and Hemp-Based Products in Canada
Bibliographic record
Abstract
Industrial hemp is a versatile crop producing nutrient-rich hempseed and a large quantity of biomass. Bast fibre and hurd are excellent materials derived from hemp straw, while bioactive ingredients are extracted from flower heads and leaves. The environmental impacts associated with hemp production were well-studied in the EU. However, Life Cycle Assessment (LCA) studies of hemp produced in Canada were limited despite being one of the largest hemp-producing countries. This thesis aims to evaluate the hemp production system and hemp-based products manufactured in Canada using the LCA approach. With an increasing global focus on sustainability, this research fills an important gap in understanding the environmental impact of hemp production in Canada, and provides necessary data for the development of environmental product declarations (EPDs) of current and future hemp-based products. The production of hempseed and straw was investigated first, followed by assessing the manufacturing of bast fibre, hurd and nonwoven mats. The cradle-to-farm gate assessment of hempseed and straw comprised foreground data collected from growers, the Canadian Hemp Trade Alliance (CHTA), National Hemp Variety Field Trial (NHVFT) 2022 results, and provincial hemp production guides. The cradle-to-factory gate analysis of hemp-based products collected information from the manufacturer. Data for the background processes were taken from LCA databases. One kg of hempseed and straw were used as functional units in the first study, while one tonne of hemp-based products was the functional unit in the second study. The results from the first study showed that dual-purpose production of hempseed had the lowest environmental impacts when allocating by mass, followed by grain-only production scenario and dual-purpose hempseed with economic allocation. Hempseed production from growers had lower footprints than that from NHVFT 2022 results and production guides. The Greenhouse Gas (GHG) emissions associated with hemp production in Canada were comparable to hemp produced in the EU. However, some LCA studies showed lower footprints than the present study due to higher yield, lower nutrient inputs and integration of organic fertilizer. The major contributors to GHG emissions were field emissions, fertilizer production, and field operations. For the second study, bast fibre and hurd from co-harvested straw had the lowest production footprint when allocated by its market value, followed by fibre-only production of feedstock and co-harvested straw allocating by mass. A similar result was applied to the production of hemp-based nonwoven mats. The GHG emissions of hemp-based products were similar to those produced in the EU. Significant contributors to carbon footprints were hemp straw production and electricity consumed during manufacturing. Sensitivity analysis suggested that the use of higher quality and low carbon feedstock, low carbon intensity electrical energy, and dust significantly reduced overall GHG emissions. The finding from this study provides benchmark information regarding hemp materials, which could be used in further investigations of hemp-based products. Long-term tracking of hemp production in Canada and site-specific environmental conditions will improve the accuracy of LCA and provide more representative results.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".