4.7 Article

Comparison of two rapid automated analysis tools for large FTIR microplastic datasets

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ANALYTICAL AND BIOANALYTICAL CHEMISTRY
卷 415, 期 15, 页码 2975-2987

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SPRINGER HEIDELBERG
DOI: 10.1007/s00216-023-04630-w

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Automated microplastic analysis; FTIR; siMPle; Bayreuth Particle Finder (BPF); Freshwater samples; Seawater samples

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One of the biggest challenges in microplastic research is the lack of standardization and harmonization across various fields, which leads to discrepancies in sampling, analysis methods, and data interpretation. In this study, two commonly used algorithms for data analysis were compared, and while they showed overall agreement in abundance, polymer composition, and size distribution of microplastics, discrepancies were observed in certain polymer types/categories and the smallest particle sizes.
One of the biggest issues in microplastic (MP, plastic items <5 mm) research is the lack of standardisation and harmonisation in all fields, reaching from sampling methodology to sample purification, analytical methods and data analysis. This hampers comparability as well as reproducibility among studies. Concerning chemical analysis of MPs, Fourier-transform infrared (FTIR) spectroscocopy is one of the most powerful tools. Here, focal plane array (FPA) based micro-FTIR (mu FTIR) imaging allows for rapid measurement and identification without manual preselection of putative MP and therefore enables large sample throughputs with high spatial resolution. The resulting huge datasets necessitate automated algorithms for data analysis in a reasonable time frame. Although solutions are available, little is known about the comparability or the level of reliability of their output. For the first time, within our study, we compare two well-established and frequently applied data analysis algorithms in regard to results in abundance, polymer composition and size distributions of MP (11-500 mu m) derived from selected environmental water samples: (a) the siMPle analysis tool (systematic identification of MicroPlastics in the environment) in combination with MPAPP (MicroPlastic Automated Particle/fibre analysis Pipeline) and (b) the BPF (Bayreuth Particle Finder). The results of our comparison show an overall good accordance but also indicate discrepancies concerning certain polymer types/clusters as well as the smallest MP size classes. Our study further demonstrates that a detailed comparison of MP algorithms is an essential prerequisite for a better comparability of MP data.

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