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Capabilities of simultaneous 193 nm - LIBS/LA-ICP-MS imaging for microplastics characterization

Talanta 2023 23 citations

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This study developed a simultaneous 193 nm LIBS/LA-ICP-MS imaging method for comprehensive characterization of microplastics, enabling co-localized elemental and molecular analysis of plastic particles in a single measurement. The dual-technique approach provided richer characterization data than either method alone.

Microplastics (MPs) are currently one of the major environmental challenges within our society. With the awareness of the impact of MPs on the environment increasing over the last years, the need for increased monitoring as well as comprehensive analysis to better understand the fate and impact of MPs has become more and more important. A major aspect of MP characterization is the assignment of the polymer type of individual particles. Here, per- and poly-fluoroalkyl substances (PFAS), originating from fluor-containing polymers, have gained a lot of attention due to the severe environmental impact. Additionally, quantitative analysis of the metal content is of great interest in the field, since MPs are prone to either leaching (in)organic additives into the environment or taking up and accumulating hazardous components (e.g., heavy metals). In this work we demonstrate the capabilities of a simultaneous LIBS/LA-ICP-MS setup for the analysis of MPs. In the first part, we demonstrate the potential of targeted LIBS analysis for the imaging of fluor-containing polymers. Using a laser spot size of 5 μm combined with highly sensitive ICCD detection enables analysis of particles in the low μm range. In the second part we combine the polymer-identification capabilities of LIBS with the high sensitivity of ICP-MS to perform matrix-matched quantification of the metal content of individual MPs. In this case we use a spot size of 50 μm facilitating polymer classification with a broadband spectrometer, resulting in detection limits of 0.72 μg/g for Pb and 9.5 μg/g for Sn simultaneously measured using ICP-MS.

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