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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 Policy & Risk Remediation Sign in to save

Raman Spectral Imaging for the Detection of Inhalable Microplastics in Ambient Particulate Matter Samples

Environmental Science & Technology 2019 143 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.
Stephanie Wright Stephanie Wright Joseph Levermore, Stephanie Wright Stephanie Wright Stephanie Wright Frank J. Kelly, Stephanie Wright Stephanie Wright Stephanie Wright Stephanie Wright Frank J. Kelly, Stephanie Wright Stephanie Wright Stephanie Wright Stephanie Wright Stephanie Wright Stephanie Wright Frank J. Kelly, Frank J. Kelly, Stephanie Wright Joseph Levermore, Joseph Levermore, Joseph Levermore, Stephanie Wright Stephanie Wright Stephanie Wright Stephanie Wright Joseph Levermore, Stephanie Wright Stephanie Wright Joseph Levermore, Stephanie Wright Stephanie Wright Frank J. Kelly, Frank J. Kelly, Stephanie Wright Frank J. Kelly, Stephanie Wright Stephanie Wright Frank J. Kelly, Stephanie Wright Frank J. Kelly, Joseph Levermore, Stephanie Wright Frank J. Kelly, Frank J. Kelly, Stephanie Wright Stephanie Wright Joseph Levermore, Stephanie Wright Stephanie Wright Stephanie Wright Stephanie Wright Stephanie Wright Joseph Levermore, Frank J. Kelly, Frank J. Kelly, Stephanie Wright Stephanie Wright Stephanie Wright Frank J. Kelly, Stephanie Wright Stephanie Wright Frank J. Kelly, Stephanie Wright Frank J. Kelly, Stephanie Wright Stephanie Wright Joseph Levermore, Stephanie Wright Stephanie Wright Stephanie Wright Stephanie Wright

Summary

Researchers developed a filter-based sampling method compatible with Raman spectral imaging to detect inhalable-sized microplastics in ambient air samples. They successfully identified and mapped plastic particles as small as a few micrometers on sampling filters. The study provides a practical new analytical approach for measuring airborne microplastic exposure, an area where reliable detection methods have been lacking.

Body Systems

Microplastics are ubiquitous contaminants, with preliminary evidence indicating they are a novel component of air pollution. This presents a plausible inhalation exposure pathway, should microplastics occur in the inhalable size range; however, this remains an analytical challenge. Here, we develop a filter-based sampling method compatible with both air quality monitoring and Raman spectral imaging (RSI) for the detection of inhalable-sized microplastics. Clean and particulate matter (PM) contaminated filters of a range of compositions were screened. RSI was validated using a plastic microbead suspension (poly(methyl methacrylate) (5-27 μm), polyethylene (10-27 μm), and polystyrene (4 and 10 μm)). Filters were loaded with the suspension before being analyzed. RSI analysis was conducted using a univariate analysis, fitting unique plastic bands to the spectral data sets, where high spatial intensity indicated the presence of microplastics. Inhalable microplastics were not visibly detectable against quartz or spectroscopically detectable against polytetrafluoroethylene (PTFE)- and alumina-based filters. While microplastics were detectable against cellulose, the PM-contaminated filters (4 and 24 h) burned during analysis. The greatest intensities for microplastics were observed against the silver membrane filter, and inhalable microplastics were still detectable in a 24 h PM sample. These findings will facilitate the acquisition of inhalable microplastic concentrations, which are necessary for understanding microplastic exposure and, ultimately, what their potential role in PM-associated health effects might be.

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