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Raman Microscopy and Pyrolysis GC/MS for Comprehensive Analysis of PM10 Microplastics: Method Development and Urban-Rural Comparison
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Researchers developed and validated a combined Raman microscopy and pyrolysis GC/MS method for comprehensive analysis of microplastics in PM10 airborne particulate matter, comparing urban and rural samples. Both methods detected microplastics in PM10 from all sites, with higher concentrations in urban air, and the combination provided complementary information on polymer composition and particle morphology.
Microplastics (MP) have emerged as pervasive pollutants, present in environments ranging from urban centers to remote areas worldwide. While research has largely concentrated on aquatic and terrestrial systems, the study of microplastics in airborne particles is a comparatively new and evolving domain. In particular, investigating the risks of inhaling nano- and microplastic particles is critical, as fine particulate matter (PM) with aerodynamic diameters under 10 µm (PM10) is recognized for its substantial potential to impact human health.This study presents the development and optimization of methodologies for identifying and quantifying microplastic content in PM10 samples. Critical aspects of the workflow include the selection of appropriate filter materials in sampling, such as quartz fibre filters (QFF) and steel mesh filters, chosen for their minimal interference with subsequent analytical techniques. Sampling durations were optimized to ensure sufficient microplastic proportion while avoiding filter overloading.Pre-treatment protocols were carefully designed to isolate microplastics from the complex atmospheric particulate matter matrix, enabling compatibility with Raman microscopy. These protocols incorporate chemical digestion steps tailored to reduce organic matter while preserving polymer integrity and use density separation with heavy salt solutions to effectively remove inorganic contaminants like mineral dust.Methodological improvements were validated through controlled experiments, demonstrating reliability in detecting microplastics including particles below 10 microns. The study also addresses the challenges in applying automated Raman microscopy for rapid identification and quantification. Issues such as background interference, polymer-specific spectral variability, and the need for optimized machine learning algorithms to classify microplastic types are explored, highlighting advancements and limitations in automation.In parallel, the study employs a mass-based analytical technique, pyrolysis gas chromatography/mass spectrometry (pyrolysis GC/MS), to complement particle-based findings. Results from this approach underline the importance of selecting appropriate quantification parameters, such as calibration standards and sampling subsets, to ensure accurate mass-specific data.To contextualize findings, a comparative analysis was conducted to evaluate microplastic concentrations and polymer characteristics in PM10 samples collected from urban and rural locations. This comparison of the results raises the opportunity to evaluate the spatial variability of microplastic pollution and the influence of local and regional activities, providing valuable insights into the sources, dispersal mechanisms, and environmental impact of airborne microplastics.
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