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Data and code for the publication "Evaluating the effectiveness of the MicroPlastic Sediment Separator (MPSS)"
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This is a data and code repository deposit accompanying a published research paper on the MicroPlastic Sediment Separator (MPSS), a tool for extracting microplastics from sediment samples. The deposit contains the raw datasets, R analysis code, and figures used in the evaluation of the MPSS's extraction effectiveness. While not a standalone research paper, this resource supports reproducibility in microplastic analytical method development.
Authors Prume, Julia A.; Laermanns, Hannes; Löder, Martin G. J.; Laforsch, Christian; Bogner, Christina; Koch, Martin Background The data set contains all data analysed in the paper with the title "Evaluating the effectiveness of the MicroPlastic Sediment Separator (MPSS)", published in the journal Microplastics & Nanoplastics (https://doi.org/10.1186/s43591-023-00073-3). Description The spreadsheet MPSS_data.xlsx contains all data analysed in this work, organised in 11 sheets. The R notebook 2023-11-09_MPSS_data_analysis.Rmd contains the code to read, process, analyse, and plot the data for both the main text and the Supplementary Information. The zipped folder Figures contains all plots for the main text and the Supplementary Information. The file EXTRACT_2023-06-05_Q9-Blank-2-1000.0_000001.0.dpt contains data for the spectrum plotted in Supplementary Figure S1, the file EXTRACT_2023-05-12-MPSS-Testpartikel.0_000000.0.dpt contains data for the spectrum plotted in Supplementary Figure S17. Disclaimer The data and code are provided as is without any warranty. Funding J.A.P. gratefully acknowledges the support of the German Federal Ministry for Education and Research (BMBF) for the Citizen Lab for Microplastics (project 01BF1705) and the Hessian Ministry of Higher Education, Research and the Arts (HMWK) for the project Entwicklung eines Modells zur Simulation von Stoffströmen im Bereich Mikroplastik, LOEWE-Exploration. H.L., M.G.J.L., C.L., and C.B. acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), Project Number 391977956 SFB 1357. Open access funding provided by the Open Access Publishing Fund of Philipps-Universität Marburg with support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation).
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