Characterizing the packaging waste generation patterns and carbon emissions of university delivery service
Bibliographic record
Abstract
As the main consumer group for online shopping and ordering fast food, young people—particularly university students—have contributed to a substantial amount of packaging waste. In the present study, the material flow method was employed to quantify the generation and end-of-life flows of packaging waste from both the express delivery and food delivery sectors at universities in China. Moreover, this study takes reusable packaging materials for food delivery services as a case study to evaluate their environmental benefits through a simplified life cycle assessment approach. The results show that approximately 1.7 (±0.3) million metric tons and 123 (±1.0) kilo metric tons of packaging waste were generated from express delivery and food delivery services, respectively, for university students in 2021. Although reusable food packaging is more complex and costly than regular disposable food packaging is, our modeling results show that reusable food packaging has significant emission reduction benefits under the current practice of 63 cycles per year of actual operation at a specific university. The reusable packaging mode in universities is feasible from an environmental perspective; however, it faces significant challenges due to a few concerns among stakeholders, such as high costs and inadequate recycling supply systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".