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POLARSENSE: Polar Online Airborne Nano and Microplastic Sensing and Environmental Monitoring

2025 Score: 48 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Dušan Materić Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Dušan Materić Dušan Materić Dušan Materić Dušan Materić Dušan Materić Dušan Materić Dušan Materić Dušan Materić Dušan Materić Dušan Materić Dušan Materić Dušan Materić Dušan Materić Dušan Materić Dušan Materić Liam Kelleher, Liam Kelleher, Liam Kelleher, Liam Kelleher, Stefan Krause, Stefan Krause, Stefan Krause, Dušan Materić Dušan Materić Dušan Materić Dušan Materić Dušan Materić Dušan Materić Dušan Materić Liam Kelleher, Dušan Materić Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Dušan Materić Stefan Krause, S. W. Allen, S. W. Allen, Dušan Materić Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Liam Kelleher, Liam Kelleher, Liam Kelleher, Dušan Materić Dušan Materić Dušan Materić Gijs D. Breedveld, Liam Kelleher, Dušan Materić Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Liam Kelleher, Dušan Materić Liam Kelleher, Gijs D. Breedveld, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Liam Kelleher, Liam Kelleher, Stefan Krause, Stefan Krause, Dušan Materić Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Liam Kelleher, Stefan Krause, Liam Kelleher, Liam Kelleher, Dušan Materić Stefan Krause, Liam Kelleher, Dušan Materić Dušan Materić Dušan Materić Dušan Materić Stefan Krause, Dušan Materić Dušan Materić Stefan Krause, Liam Kelleher, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Liam Kelleher, Liam Kelleher, S. W. Allen, Stefan Krause, Stefan Krause, Liam Kelleher, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Liam Kelleher, Dušan Materić Dušan Materić Stefan Krause, Stefan Krause, Stefan Krause, Dušan Materić Dušan Materić Stefan Krause, Stefan Krause, Dušan Materić Dušan Materić Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Stefan Krause, Liam Kelleher, Stefan Krause, Dušan Materić

Summary

Researchers deployed an automated long-term nano- and microplastic sampling instrument at an Arctic research station in Ny-Ålesund, Norway to continuously monitor airborne plastic concentrations. The device enabled high-temporal-resolution data collection over months with minimal personnel intervention, filling a critical gap in polar atmospheric microplastic monitoring.

 We present an automated tool for long-term sampling of nano and microplastics (NMP) and associated chemicals in remote areas, addressing a critical need for cost-effective, high-temporal-resolution data collection. A major challenge in NMP research is overcoming the financial and time constraints of intensive sampling campaigns.To address this, we deployed two devices in the Arctic at the Ny-Ålesund research base, focusing on enhancing understanding of polar NMP distribution and transport mechanisms. The auto-sampling system utilises active air sample containers, NanoTank’s, to collect airborne particles through percolation in a liquid trap. Stepper motors, linear actuators, and controllers enable the movement of NanoTanks for automated collection of time-series samples at set intervals.The first systems were deployed in October 2024, and the collected samples will be analysed by pyrolysis gas chromatography mass spectrometry (pyGC/MS) for nanoplastics, Raman spectroscopy for microplastics, and Liquid Chromatography/Tandem Mass Spectrometry (LC/MS/MS) for persistent organic pollutant analysis (PFAS focus).This setup alleviates the need for porous filters that can clog given varied exposure levels. Our system will help to expand the capabilities of atmospheric research and allow us to increase our datasets and understanding of temporal and spatial distributions of NMP.

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