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Statistical analysis code and analysis-ready data for: Discharge-Dependent Variations in Microplastic and Microfiber Concentrations in the Danube River during a Flood Event
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Scientists tracked microplastic pollution in the Danube River during a major flood in Budapest, using two different sampling methods to see how plastic particle levels changed as water flow surged and receded. This matters because floods are becoming more common with climate change, and understanding how they stir up and transport microplastics can help us predict when rivers, and the drinking water or fish that come from them, might carry higher plastic contamination. Note: this particular repository shares the data and statistical code behind the study, rather than presenting new health findings itself.
This repository contains the Python code and analysis-ready dataset used for the statistical analyses associated with the manuscript “Discharge-Dependent Variations in Microplastic and Microfiber Concentrations in the Danube River during a Flood Event.” The study investigates temporal variability in microplastic (MP) concentrations during the September 2024 flood event in the Danube River at Budapest, Hungary, using complementary manta-net and pump-based sampling approaches representing different operational particle fractions. The deposited Python script reproduces the formal statistical analyses reported in the revised manuscript, including Shapiro–Wilk normality tests, Spearman and Pearson correlations, simple linear regression, Shapiro–Wilk tests of regression residuals, Breusch–Pagan tests for homoscedasticity, Kruskal–Wallis tests, and pairwise Mann–Whitney U tests with Holm correction. Analyses are performed at replicate and daily scales to evaluate concentration–discharge relationships and differences among hydrological phases. Concentration–discharge hysteresis is interpreted qualitatively in the manuscript and no numerical hysteresis index is calculated by the deposited script. The repository includes the analysis-ready Excel workbook required to reproduce the statistical analyses, together with documentation describing the statistical rationale, software requirements, input structure, and generated outputs.
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Statistical analysis code and analysis-ready data for: Discharge-Dependent Variations in Microplastic and Microfiber Concentrations in the Danube River during a Flood Event
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Scientists tracked how microplastic pollution levels in the Danube River changed during a major flood in 2024, using two different sampling methods to measure tiny plastic particles and fibers in the water. Floods can stir up and transport large amounts of plastic waste, and understanding this pattern matters because rivers like the Danube feed into water systems people rely on for drinking water and food sources like fish. This particular paper shares the data and statistical methods used, laying groundwork for future research into how extreme weather events may worsen microplastic exposure.
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Researchers tracked microplastic concentrations along 750 kilometers of the Tisza River over three years, finding that floods flush stored sediments — and the microplastics trapped in them — downstream in distinct "clouds" of pollution. Average microplastic concentrations more than doubled from 2021 to 2023, underscoring that flood events dramatically accelerate microplastic transport in river systems.
Data and Code for the publication 'Floodplain vegetation filters microplastics during a major Rhine flood event'
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