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.
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Osprey: A mmWave Approach to TireWear Sensing
Tire wear is a leading cause of automobile accidents globally. Beyond
safety, tire wear affects performance and is an important
metric that decides tire replacement, one of the biggest maintenance
expense of the global trucking industry. We believe that it is
important to measure and monitor tire wear in all automobiles. The
current approach to measure tire wear is manual and extremely
tedious. Embedding sensor electronics in tires to measure tire wear
is challenging, given the inhospitable temperature, pressure, and
dynamics of the tire. Further, off-tire sensors placed in the well such
as laser range-finders are vulnerable to road debris that may settle
in tire grooves.
This paper presents Osprey, the first on-automobile, mmWave
sensing system that can measure accurate tire wear continuously
and is robust to road debris. Osprey’s key innovation is to leverage
existing, high-volume, automobile mmWave radar, place it in the
tire well of automobiles, and observe reflections of the radar’s signal
from the tire surface and grooves to measure tire wear, even in the
presence of debris. We achieve this through a super-resolution Inverse
Synthetic Aperture Radar algorithm that exploits the natural
rotation of the tire and improves range resolution to sub-mm. We
show how our system can eliminate debris by attaching specialized
metallic structures in the grooves that behave as spatial codes and
offer a unique signature, when coupled with the rotation of the
tire. In addition to tire wear sensing, we demonstrate the ability
to detect and locate unsafe, metallic foreign objects such as nails
lodged in the tire.
We evaluate Osprey on commercial tires mounted on a mechanical,
tire-rotation rig and a passenger car.We test Osprey at different
speeds, in the presence of different types of debris, different levels
of debris, on different terrains, and different levels of automobile
vibration. We achieve a median absolute tire wear error of 0.68
mm across all our experiments. Osprey also locates foreign objects
lodged in the tire with an error of 1.7 cm and detects metallic foreign
objects with an accuracy of 92%.
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- Award ID(s):
- 1823235
- NSF-PAR ID:
- 10195728
- Date Published:
- Journal Name:
- The 18th ACM International Conference on Mobile Systems, Applications, and Services
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/https://doi.org/10.1145/3386901.3389031
