Micron-size tire tread particles leach organic compounds at higher rates than centimeter-size particles: Compound identification and profile comparison
Bibliographic record
Abstract
Tire tread particles (TTP) are environmentally prevalent microplastics and generate toxic aqueous leachate. We determined the total carbon and nitrogen leachate concentrations and chemical profiles from micron (∼32 μm) and centimeter (∼1 cm) TTP leachate over 12 days. Dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) were used to measure the concentration of leached compounds. Nontargeted chemical analysis by comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC/TOF-MS) was used to compare the chemical profiles of leachates. After leaching for 12 days, DOC was 4.0 times higher in the micron TTP leachate than in the centimeter TTP leachate, and TDN was 2.6 times higher. The total GC×GC/TOF-MS chromatographic feature peak area was 2.9 times greater in the micron TTP leachate than the centimeter TTP leachate, and similarly, the total relative abundance of 54 tentatively identified compounds was 3.3 times greater. We identified frequently measured tire-related chemicals, such as 6PPD, N-cyclohexyl-N'-phenylurea (CPU), and hexa(methoxymethyl)melamine (HMMM), but nearly 50% of detected chemicals were not previously reported in tire literature or lacked toxicity information. Overall, the results demonstrate that smaller TTP have a greater potential to leach chemicals into aquatic systems, but a significant portion of these chemicals are not well-studied and require further risk assessment.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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; both teacher heads agree on what is shown here.
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".