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Record W7084207200

Off the Beaten Path: Are Unpaved Roads and Recycled Tire Materials Pathways for 6PPD-Q to Enter the Environment?

2025· article· en· W7084207200 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicAfro-Latin American Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStormwaterNatural rubberLandscapingLeachateRetrofittingLeaching (pedology)
DOInot available

Abstract

fetched live from OpenAlex

Efforts to expand the operational lifespan of rubber tires have led to the addition of sacrificial antiozonants, including 6PPD, into the rubber material to reduce ozone-induced oxidative damage. Recent studies have demonstrated the acutely toxic effects of the transformation product of 6PPD, 6PPD-Quinone (6PPD-Q), on various salmonids in urban streams. Most of these studies have focused on 6PPD-Q generated on paved roads by tire wear particles. However, over half the road network in Canada consists of unpaved roads, which remain unstudied for 6PPD-Q contamination. Additionally, of the 414,116 tonnes of tires recycled in Canada in 2021, 44% of that mass has been converted into landscaping materials. The use of recycled tire materials as landscaping material exposes 6PPD-containing rubber to ozone and rain, potentially leaching 6PPD-Q into the urban storm drain network. In this thesis, the hypothesis is that recycled tire materials can leach 6PPD-Q into stormwater and that the concentrations found in that stormwater vary depending on environmental factors. The second hypothesis is that gravel roads contain 6PPD-Q within the road dust that comprises the road surface, and that the 6PPD-Q concentrations depend on specific environmental/anthropogenic factors. To address the potential for recycled tire material to leach 6PPD-Q, a long-term leachate study was designed to detect and quantify concentrations of 6PPD-Q in stormwater after it filters through two recycled rubber landscaping materials (mulch and crumb). Solid phase extraction techniques were then used to extract 6PPD-Q from the stormwater leachate. To examine 6PPD-Q in gravel road dust, gravel dust was collected from the surface of unpaved roads in and around Saskatoon, Saskatchewan, Canada. Chemical extractions of the gravel road dust then allowed for the detection and quantification of 6PPD-Q within each sample. 6PPD-Q concentrations in the stormwater leachate and gravel dust chemical extractions were quantified using ultra-high-performance liquid chromatography high-resolution mass spectrometry. The stormwater leachate had 6PPD-Q concentrations ranging from 1.81 µg/L to 34.5 µg/L, with a median concentration of 10.6 µg/L. Multiple linear models and other statistical tests showed that the concentrations in this leachate were affected by particle size, as well as days elapsed, mean temperature, and days between collections. In the gravel road extracts, 6PPD-Q concentrations ranged between 0.21 ng/g dry weight (dw) and 1.47 ng/g dw (median: 0.51 ng/g dw). When normalized to total organic carbon (TOC) content to allow for comparison with similar studies conducted on paved road dust, concentrations varied between 9.83 and 342 ng/g-TOC (median: 145 ng/g-TOC). Location of the roads, seasonality, or TOC content did not affect 6PPD-Q concentrations, whereas speed limit showed a positive linear relationship with 6PPD-Q concentrations. The recycled rubber study demonstrates that unintended leaching of 6PPD-Q can occur under environmental conditions, highlighting multiple factors that influence these outcomes. The 6PPD-Q concentrations in the collected leachate suggest that applications of recycled rubber in outdoor artificial turf fields may be a concentrated source of 6PPD-Q in stormwater. Further work should be conducted using similar techniques to examine the 6PPD-Q concentrations that could be found in rainwater leachate from full-sized artificial turf fields. The gravel road study provides an initial glimpse at the role unpaved roads play in adding 6PPD-Q into the environment. The presence of 6PPD-Q in unpaved road dust suggests that unpaved road dust may act as a pathway for 6PPD-Q to enter the local environment. Future work with 6PPD-Q and gravel roads should confirm whether traffic volume influences 6PPD-Q concentrations in the dust and to understand if dust blown from the road surface could spread 6PPD-Q as it travels. Thus, with the findings presented here, this thesis contributes to the understanding of 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.960
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.010
GPT teacher head0.185
Teacher spread0.175 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2025
Admission routes1
Has abstractyes

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