Occurrences of Tire Rubber-Derived Contaminants in Cold-Climate Urban Runoff
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Recent findings that 2-anilo-5-[(4-methylpentan-2-yl)amino]cyclohexa-2,5-diene-1,4-dione (6PPD-quinone), the transformation product of a common tire rubber antioxidant, is acutely toxic in stormwater-impacted streams has highlighted the need for a better understanding of contaminants in urban runoff. This study represents one of the first reports of 6PPD-quinone and other tire rubber-derived compounds in stormwater and snowmelt of a cold-climate Canadian city (Saskatoon, 2019–2020). Semiquantification of the five target compounds, N,N′-diphenylguanidine (DPG), N,N-dicyclohexylmethylamine (DCA), N,N′-dicyclohexylurea (DCU), 1-cyclohexyl-3-phenylurea (CPU), and 6PPD-quinone, revealed DPG was most abundant, with average concentrations of 60 μg L –1 in stormwater and 1 μg L –1 in snowmelt. Maximum observed concentrations of DPG were greater than 300 μg L –1, equivalent to loadings of 15 kg from a single rain event. These concentrations of DPG represent some of the highest reported in urban runoff globally. 6PPD-Quinone was detected in 57% (12/21) of stormwater samples with a mean concentration of approximately 600 ng L –1 (2019) and greater than 80% (28/31) of snowmelt samples with mean concentrations of 80–370 ng L –1 (2019 and 2020). Concentrations of 6PPD-quinone exceeded the acute LC 50 for coho salmon (0.8–1.2 μg L –1 ) in greater than 20% of stormwater samples. Mass loadings of all target chemicals correlated well with roads and residential land-use area.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".