Life cycle assessment : Aspenware biodegradable cutlery
Bibliographic record
Abstract
This study was sponsored by UBC SEEDS, Social Ecological Economic Development Studies, a program which aims to address sustainability challenges on campus such as which type of disposable cutlery is the most sustainable choice (SEEDS). In this report, a life cycle assessment was performed for one specific cutlery brand, Aspenware, a manufacturer of disposable and compostable wooden cutlery. The goal of this study is to help UBC and AMS food services determine cutlery consumption habits and impacts in order to make informed decisions when purchasing disposable cutlery. In this study, a full life cycle assessment will be presented for Aspenware, along with a comparison to traditional polystyrene plastic cutlery in terms of greenhouse gas emissions and economic costs. Aspenware will benefit from this study in determining the environmental impact of their products and areas for improvement. The study applies a life cycle assessment based on ISO 14044 standards. The functional unit of this analysis is per utensil, assuming single use, limited to services and events at the University of British Columbia. The results, data and methodology used in this report are incorporated into the Quantis SUITE 2.0 LCA software tool, using the database EcoInvent 2.2 (Quantis Intl). Overall, the production of 2.6 g plastic cutlery and 5 g plastic cutlery results in an approximate increase of 24% and 60% kg CO₂ emissions per piece of cutlery, respectively, when compared to Aspenware. Plastic cutlery is about 43% less expensive than Aspenware. The end-of-life impacts of Aspenware cutlery will have broader implications than simple reductions in carbon dioxide emissions. Plastic may not degrade for many years and this was not quantified in the report’s data (Cruise). Aspenware’s wooden cutlery composts in less than 49 days, making it a more viable option (Aspenware, 2013). Overall, it is recommended that Aspenware be purchased over plastic cutlery due to the reduced greenhouse gas emissions and its compostable nature which results in less space requirements for on campus composting. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".