0
Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Detection Methods Environmental Sources Human Health Effects Sign in to save

On airborne tire wear particles along roads with different traffic characteristics using passive sampling and optical microscopy, single particle SEM/EDX, and µ-ATR-FTIR analyses

Frontiers in Environmental Science 2022 43 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 55 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Zhiqiang Gao, Zhiqiang Gao, Zhiqiang Gao, Zhiqiang Gao, Zhiqiang Gao, Kendall Wontor, Zhiqiang Gao, Zhiqiang Gao, Kendall Wontor, Zhiqiang Gao, James V. Cizdziel James V. Cizdziel James V. Cizdziel James V. Cizdziel Kendall Wontor, James V. Cizdziel James V. Cizdziel James V. Cizdziel James V. Cizdziel James V. Cizdziel James V. Cizdziel James V. Cizdziel James V. Cizdziel James V. Cizdziel James V. Cizdziel Kendall Wontor, Kendall Wontor, David Jaramillo‐Vogel, David Jaramillo‐Vogel, David Jaramillo‐Vogel, David Jaramillo‐Vogel, Juanita Rausch, Juanita Rausch, Kendall Wontor, Kendall Wontor, Juanita Rausch, James V. Cizdziel James V. Cizdziel Kendall Wontor, Kendall Wontor, James V. Cizdziel Kendall Wontor, James V. Cizdziel Kendall Wontor, Juanita Rausch, Juanita Rausch, David Jaramillo‐Vogel, Juanita Rausch, David Jaramillo‐Vogel, James V. Cizdziel James V. Cizdziel Carly Clisham, Carly Clisham, Kendall Wontor, James V. Cizdziel Kaylea Focia, Kaylea Focia, Juanita Rausch, Juanita Rausch, James V. Cizdziel David Jaramillo‐Vogel, Juanita Rausch, David Jaramillo‐Vogel, Juanita Rausch, James V. Cizdziel

Summary

Researchers used passive sampling and advanced analytical techniques including SEM/EDX and micro-ATR-FTIR to characterize airborne tire wear particles along roads with different traffic volumes and speeds. The study found that tire wear particles, a major category of microplastic pollution, varied in concentration and composition depending on traffic characteristics, highlighting roadways as a significant source of airborne microplastic contamination.

Polymers

Tire wear particles (TWPs) are a major category of microplastic pollution produced by friction between tires and road surfaces. This non-exhaust particulate matter (PM) is transported through the air and with runoff leading to environmental pollution and health concerns. Here, we collected airborne PM along paved roads with different traffic volumes and speeds using Sigma-2 passive samplers. Particles entering the samplers deposit onto substrates for analysis, or, as we modified it, directly into small (60 ml) separatory funnels, which is particularly useful with high particle loads, where a density separation aids in isolating the microplastics. We quantified putative TWPs (∼10–80 µm) deposited on the substrates (primarily adhesive tape on glass slides) and in the funnels using stereomicroscopy. Putative TWP deposition rates (particles/cm 2 /day ± SD) at 5 m from the road were highest near a busy highway (324 ± 129), followed by a boulevard with moderate traffic (184 ± 93), and a slow traffic avenue (29 ± 7). We observed that deposition rates increased within proximity to the highway: 99 ± 54, 180 ± 88, and 340 ± 145 at 30, 15, and 5 m, respectively. We show that TWP abundances (i.e., deposition and mass concentration) increase with vehicle braking (driving behavior). We observed no differences ( p > 0.05) between the separatory funnel and adhesive tape collection methods. In addition, we were able to obtain FTIR spectra of TWPs (>10 µm) using µ-ATR-FTIR. Both deserve further scrutiny as novel sampling and analytical approaches. In a separate sampling campaign, we differentiated 1438 particles (∼1–80 µm) deposited on boron substrates into TWP, metal, mineral, and biogenic/organic classes with single particle SEM/EDX analysis based on morpho-textural-chemical classification and machine learning. The results revealed similar concentration trends with traffic (high > moderate > low), with the distribution of particle sources alike for the highway and the moderate road: TWPs (∼38–39%) > biogenic (∼34–35%) > minerals (∼23–26%), and metallic particles (∼2–3%). The low traffic road yielded a much different distribution: biogenic (65%) > minerals (27%) > TWPs (7%) > metallic particles (1%). Overall, this work provides much-needed empirical data on airborne TWPs along different types of roads.

Sign in to start a discussion.

Share this paper