Life cycle assessment of returnable mailers used for apparel electronic commerce: A case study in Canada
Bibliographic record
Abstract
E‐commerce is increasingly popular in the fashion industry in Canada. Based on a case study, this research analysed the environmental sustainability of the returnable e‐commerce package format distributed in Canadian apparel retail channels. The case study compared the environmental impacts of a returnable polypropylene mailer to those of two different expendable packaging formats currently used by a brand owner, such as a corrugated paperboard package and a low‐density polypropylene mailer. A life cycle assessment (LCA) was conducted to examine the environmental impacts of the three packaging scenarios. The foreground data of the LCA were obtained from a brand owner and packaging suppliers in 2021. TRACI 2.1, including 10 life cycle impact categories, was used for the LCA. The comparative LCA results showed that the returnable mailer generated the lowest environmental impact for eight out of 10 impact categories when the final consumers' locations were relatively close to the brand owner or returnable packaging service provider. The expendable corrugated paperboard packaging format contributed the greatest environmental burden in all the impact categories primarily because it used a large amount of material and was relatively heavy. However, the comparative results were changed for some impact indicators depending on the final consumer's location and the number of reuse cycles for the returnable mailer. Specifically, the returnable mailer had a higher environmental impact than the expendable mailer for half of the 10 impact categories when the number of reuses for the returnable mailer was decreased to 10 cycles.
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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 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".