Long-Term Leaching of 6PPD-Quinone from Recycled Rubber Mulch and Crumb in a Cold-Region Climate
Bibliographic record
Abstract
The antiozonant 6PPD is commonly added to rubber tires to protect the rubber from ozone attack. Recent studies have illustrated the acute toxicity of its transformation product 6PPD-quinone (6PPD-Q) toward various salmonid fishes. Most studies measuring environmental levels of 6PPD-Q have focused on release from tire wear particles generated on paved roads, with less emphasis on recycled tires at the end of service life. Recycled tires are often converted into landscaping materials, resulting in 6PPD-containing rubber being exposed to ozone and rain, potentially leaching 6PPD-Q. However, the magnitude and duration of these additional releases are presently not known. To address this, we designed a long-term outdoor leaching study to quantify 6PPD-Q release from rubber tire crumb and rubber tire mulch under environmental conditions using liquid chromatography high-resolution mass spectrometry. Measured concentrations ranged from 1.81 to 34.5 μg/L, with a median concentration of 10.6 μg/L. Environmental factors potentially affecting 6PPD-Q concentrations in the leachate were identified using multiple linear regression models. In this way, we could demonstrate that unintended leaching of 6PPD-Q can occur under environmental conditions and highlight multiple factors that influence those outcomes. Ultimately, this paper contributes much-needed data on the sources of 6PPD-Q beyond paved roads.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".