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Airborne Microplastic in the Atmospheric Deposition, How to Identify and Quantify the Threat? Novel Semi-quantitative Approach based on Kraków Case Study

Preprints.org 2022 7 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Kinga Jarosz, Rafał Janus, Mariusz Wądrzyk, Wanda Wilczyńska-Michalik, Piotr Natkański, Marek Michalík

Summary

Researchers developed a semi-quantitative method for identifying and measuring airborne microplastic pollution in atmospheric deposition, using Krakow as a case study to address the lack of standardized monitoring approaches for this emerging pollutant.

Airborne microplastic (MP) is an emerging pollutant, still under-characterised and insufficiently understood. Detailed description of MP air pollution is crucial as it has been identified in human lungs and remote locations, highlighting atmosphere as medium of MP dispersion and transportation. The lack of standardization of methods for measuring and further monitoring of the MP pollution is an obstacle towards the assessment of health risks. Since the first recognition of MP presence in the atmosphere of Krakow in 2019, this research was conducted to further characterise and develop the methods for qualitative and quantitative analysis of airborne MP (ATR-FTIR, Pyr-GC-MS, SEM-EDS) and pre-treatment of samples.The data was gathered in seven cycles, from June 2019 to February 2020. Methods used in the study allowed the identification and analysis of the changing ratio of the different types of synthetic polymers identified in the atmospheric fallout (LDPE, Nyl-66, PE, PET, PP, PUR). Observations of interactions between MP particles and environment were made with analyses of surface changes due to the degradation. Mineral phases attached to the MPs’ surfaces, with some of the inorganic contaminants transported on these surfaces, determined to also be of anthropogenic origin.Methodology proposed in this study, allows further characterisation of MP from multiple locations to provide highly comparable data, leading to the identification of the sources of this phenomenon, as well as seasonal changes.

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