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Towards continuous mass and size distributions for beach plastic litter: Spatiotemporal analyses of abundance and composition
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This study investigated microplastic ingestion by deep-sea benthic invertebrates collected from the continental slope, finding particles in all examined species including holothurians, polychaetes, and crustaceans. The study extends the known range of microplastic ingestion to the deep benthos and highlights the pathway by which benthic fauna access surface-derived plastic contamination.
Beaches are known as hotspots for the accumulation of plastic debris and are widely used for monitoring marine litter on a global scale. However, there is a significant knowledge gap regarding temporal trends in marine plastic pollution. Moreover, existing studies on beach plastics and popular monitoring protocols only provide count data. Consequently, it is not possible to monitor marine litter based on weights, which hampers the further application of beach plastic data. To address these gaps, we conducted an analysis of spatial and temporal trends in plastic abundance and composition using OSPAR beach litter monitoring data from 2001 to 2020. We established size and weight ranges for 75 (macro-)plastic categories to estimate the total plastic weight, enabling us to investigate plastic compositions. While the amount of plastic litter exhibits significant spatial variation, most individual beaches displayed notable temporal trends. The spatial variation in composition is primarily attributed to differences in total plastic abundance. We describe the compositions of beach plastics using generic probability density functions (PDFs) for item size and weight. Our trend analysis, method for estimating plastic weight from count data, and PDFs for beached plastic debris represent novel contributions to the field of plastic pollution science.
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A monitoring and data analysis method for microplastics in marine sediments
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Researchers developed and validated a standardized monitoring and data analysis method for microplastics in marine sediments, identifying 13 polymer types across four Dutch coastal sites and finding that particle size distributions follow a power law, providing a replicable framework for MSFD and OSPAR regulatory monitoring programs.
Modelling size and shape distributions of micro- and macroplastics emitted to the natural environment
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This study developed models to describe the size and shape distributions of plastic particles emitted into the environment, combining data from multiple sources for the first time. Accurate physical characterization of emitted particles is essential for meaningful ecological risk assessment.
Effects of spatial and seasonal factors on the characteristics and carbonyl index of (micro)plastics in a sandy beach in Aveiro, Portugal
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Researchers investigated microplastic contamination on a Portuguese sandy beach across wet and dry seasons, finding that surface concentrations were dominated by polyethylene pellets in the wet season (3-6 items/m) and that density separation revealed fibers at 23 times higher concentrations. Seasonal and spatial factors significantly influenced particle type, size, and carbonyl index, highlighting how sampling method choice affects pollution estimates.
Spatio-temporal variability in the abundance and composition of beach litter and microplastics along the Baltic Sea coast of Schleswig-Holstein, Germany
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Beach litter and microplastics (20-5000 microns) were co-assessed along the Baltic Sea coast of Schleswig-Holstein in spring and autumn 2018, finding no correlation between macro and microplastic abundances, with a median of 2 microplastic particles per 500 g dry sediment and six polymer types identified.
An Accurate Size-Probability Distribution Method for Converting Microplastic Counts to Mass
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Researchers developed a size-probability distribution method to convert microplastic particle counts into mass estimates without requiring detailed morphological measurements for every particle, addressing a key gap in environmental monitoring where mass-based reporting is needed but count-based data is more commonly generated.
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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.