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Record W4413325331 · doi:10.1021/acs.estlett.5c00726

Occurrence of the Tire-Derived Toxicant 6PPD-Quinone in Road Dust from Unpaved Roads in a Cold-Region Urban Area

2025· article· en· W4413325331 on OpenAlexafffundabout
Leland T. Bryshun, Blake Hunnie, Kerry N. McPhedran, Markus Brinkmann

Bibliographic record

VenueEnvironmental Science & Technology Letters · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsGlobal Institute for Water SecurityUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEnvironmental scienceToxicantEnvironmental engineeringGeographyChemistry

Abstract

fetched live from OpenAlex

In 2021, mortalities of coho salmon were linked to 6PPD-quinone (6PPD-Q), a transformation product formed from an antioxidant in rubber tires. Since then, research concerning 6PPD-Q contamination pathways has focused on paved roads. However, over half of the road network in Canada consists of unpaved roads, which remain unstudied for 6PPD-Q contamination. In this paper, we hypothesize that (1) unpaved road networks can provide a pathway for 6PPD-Q to enter the environment and (2) 6PPD-Q concentrations in unpaved road dust are influenced by location, speed limit, collection date, and total organic carbon (TOC) content of the roads. To investigate this, we collected gravel from the surface of unpaved roads in and around Saskatoon, Saskatchewan, Canada. Chemical extractions of road dust allowed for the detection and quantification of 6PPD-Q within each sample. Concentrations of 6PPD-Q ranged between 0.207 and 1.47 ng/g of dw (median: 0.511 ng/g of dw). When normalized to TOC content, concentrations varied between 9.83 and 342 ng/g of TOC (median: 145 ng/g of TOC). No factor other than the speed limit showed a positive linear relationship with 6PPD-Q concentrations. The results of this study are an initial glimpse into the role unpaved roads play in adding 6PPD-Q into the environment.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.186
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2025
Admission routes3
Has abstractyes

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