Life Cycle Assessment of Banned Single-Use Plastic Products and Their Alternatives
Bibliographic record
Abstract
Plastic and microplastic contamination continue to be growing problems across the globe for both ecosystems and human health. Canada has banned single-use plastic products such as bags, cutlery, and foodservice ware (containers) to address and mitigate plastics and microplastic contamination. This study evaluates the life cycle of banned plastic products and their alternatives to determine whether environmental impacts can be mitigated. The environmental impacts of bags (plastic, paper, cotton), cutlery (plastic, wooden, biodegradable), and containers (plastic, styrofoam, biodegradable) were determined considering both domestic and imported products. The bag study saw paper bags having the highest environmental impacts and cotton bags with the lowest due to their reusability. For the cutlery study, plastic cutlery was the most impactful across all categories except for eutrophication and ozone depletion, where biodegradable cutlery was the most impactful by 25% and 35%, respectively. In the case of foodservice ware (containers), styrofoam was found to be the least impactful. Similar to cutlery, the plastic containers had the greatest impact except where the biodegradable container contributed more to ozone depletion and eutrophication by 25% and 45%, respectively. Local production reduced impacts across all categories. Furthermore, on a local scale, biodegradable cutlery had a greater impact on the smog and respiratory effects categories than plastic by 10% and 30%, respectively. The results of this study indicate that future regulations should focus on promoting and educating consumers on the use of reusable products over single-use products, funding research to mitigate challenges associated with waste management, and consider an informed ban on all single-use products and not just those made of plastic material to mitigate environmental impacts.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".