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Identifying Microplastics in Laboratory and Atmospheric Aerosol Mixtures via Optical Photothermal Infrared and Raman Microspectroscopy
Summary
Researchers developed optical photothermal infrared spectroscopy methods to identify microplastics in both laboratory-prepared and real atmospheric aerosol samples, demonstrating the technique's ability to distinguish plastic particles from other aerosol components in complex air quality monitoring contexts.
The widespread release of plastic waste into the environment, combined with its chemical stability, has resulted in microplastics (MPs) being observed in diverse locations, ranging from urban centers to remote areas. However, the impacts of MPs on human health, ecosystems, and the climate are still being discovered. Infrared (IR) microscopy is widely used to identify MPs in water and soil samples, but it struggles to measure atmospheric MPs due to their smaller size and the diffraction limit of IR radiation. Herein, optical photothermal IR coupled with Raman (O-PTIR+Raman) microspectroscopy is used to classify MPs by polymer type at atmospherically relevant sizes (≤10 μm). Detecting changes in elastic scattering of visible photons after IR absorption and photothermal expansion improves O-PTIR spatial resolution and enables analysis of particles with diameters ≥ ∼0.8 μm. A recently developed computer-controlled (CC) particle analysis module was used, which decreased analysis time by at least 30%. O-PTIR and Raman independently identified and distinguished high-density polyethylene (HDPE), polypropylene (PP), and polystyrene (PS) within the same sample and within samples containing particles generated with atmospherically relevant standards (ammonium sulfate, sodium nitrate, and sucrose). CC-O-PTIR+Raman was also able to distinguish MPs impacted onto an already collected sample of ambient atmospheric particles. All three samples (MPs-Only, MPs+Standards, and MPs+Ambient) were comprised of particles ≤10 μm. Our results demonstrate how CC-O-PTIR+Raman can expand capabilities for MP identification to cover atmospherically-sized particles and reduce analysis time, thereby improving understanding of atmospheric MP exposure and potential impacts on human health and the environment.
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