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Data and Code for the publication 'Floodplain vegetation filters microplastics during a major Rhine flood event'
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This paper is a research data and code release accompanying a published study on how floodplain vegetation in Cologne, Germany acts as a natural filter for microplastics during major flood events on the Rhine River. The dataset includes meteorological measurements, plant biomass data, and microplastic counts from vegetation deposits after the 2021 flood. The underlying finding — that plants along riverbanks can trap significant quantities of microplastics during floods — has implications for understanding how natural landscapes slow the spread of plastic pollution into aquatic ecosystems.
The dataset contains data on meteological data, above ground biomass, deposit masses and microplastic abundances from deposits on floodplain vegetation in the floodplain Langel-Merkenich (Cologne, Germany) after the flood event 2021. They were analysed in the paper by M. Rolf, H. Laermanns, C. Laforsch, M. G. J. Löder, C. Bogner "Floodplain vegetation filters microplastics during a major Rhine flood event" (https://link.springer.com/article/10.1186/s43591-026-00181-w) published in Microplastics and Nanoplastics. The ZIP-file contains: 5x R-Markdown files: Start with Data_read_in, Analysis_plots_sqm, Analysis_plots_g, Correlation_plots and precip_data. 1x folder: MP_datasome folders are empty, but they will be used once you run the R-Code. The R-Code is running on R4.5.2 and RStudio 2026.01.0 Build 392. If you face any issue with dataset, please let me know.
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Data and Code for the publication 'Floodplain vegetation filters microplastics during a major Rhine flood event'
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Scientists found that plants along riverbanks act like natural filters, trapping tiny pieces of plastic (called microplastics) from floodwater during a major flood in Germany. This shows that wetland plants help remove plastic pollution from water before it can travel further downstream to drinking water sources or the ocean. Protecting and restoring these natural riverside plant areas could be an important way to reduce the amount of microplastics that end up in our water supply and food chain.
Data and code for the publication "Flooding frequency and floodplain topography determine abundance of microplastics in an alluvial Rhine soil"
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This is a supporting dataset for a study on microplastic abundance in alluvial soil from floodplains along the Rhine River near Cologne, Germany. The data show that flooding frequency and floodplain topography are key factors controlling microplastic accumulation in soil. It is a dataset entry accompanying the published research paper.
Filter effect of Rhine floodplain vegetation on microplastic deposition during a single flood event in Germany
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Researchers studied how Rhine floodplain vegetation filtered microplastic deposition during a single flood event in Germany, documenting that plant cover created distinct spatial deposition patterns and acted as a significant physical barrier concentrating particles compared to unvegetated floodplain surfaces.
The role of floodplain vegetation in filtering microplastics during a major Rhine flood event
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Researchers investigated microplastic deposition on Rhine floodplain vegetation during a major flood event, finding that floodplain vegetation significantly increases hydraulic roughness and reduces flow velocities, enhancing MP capture and acting as an important filter for microplastics remobilized from the riverbed during high-discharge events.
Filter effect of Rhine floodplain vegetation on microplastic deposition during a single flood event in Germany
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Researchers examined the role of floodplain vegetation in controlling microplastic deposition during a single Rhine River flood event in Germany, finding that vegetation cover acts as a physical filter affecting spatial distribution of deposited microplastics beyond the topographic and flood-frequency controls identified in previous studies.
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When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.