Tracking the Environmental Consequences of Circular\nEconomy over Space and Time: The Case of Close- and Open-Loop Recovery\nof Postconsumer Glass
Bibliographic record
Abstract
With the increasing globalization of waste-derived raw materials,\nregion-oriented circular economy measures that stimulate resource\nrecovery can cause far-reaching ripple effects in geographically dispersed\nmarkets, with unintended environmental effects. Identifying, quantifying,\nand characterizing these implications in a multiregional economic\nsystem remains challenging. This Policy Analysis aims to track these\nmarket-mediated environmental consequences over space and time with\nhigh material resolution. It explores a novel avenue of coupling consequential\nlife cycle assessment and a time-series multiregional material–product\nchains model. The model is applied to two measures to recover postconsumer\nglass waste in the province of Quebec (Canada): improving closed-loop\nbottle-to-bottle resource recovery systems and deploying open-loop\nsystem for the marketing of glass powder as a supplementary cementitious\nmaterial. Their environmental consequence trajectories (2030–2050)\nacross a seven-industry and six-region competing symbiosis are examined.\nIn both cases, cost-based optimized results highlight widespread adjustments\nin eastern North America trade patterns that are expanding over time\nin response to the coevolution of symbiotic industries. Between 55%\nand 94% of the environmental benefits are felt beyond Quebec borders.\nThis information can help decision makers better anticipate the in-\nand cross-border scope of their measures and coordinate across jurisdictions\nto maximize overall environmental benefits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.024 | 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".