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Large Sample Volumes Improve Detection Reliability of Sparse Particles in Water: A Poisson Sampling Perspective
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This study examined microplastic accumulation in deep-sea holothurians (sea cucumbers), analyzing plastic particle types and loads in digestive tissues from abyssal specimens. The findings demonstrate that microplastic contamination has reached some of the deepest ocean environments through ingestion by benthic organisms.
Abstract: Detection of dispersed particles in water systems, including microplastics and nanoplastics, is strongly influenced by stochastic sampling effects at low concentrations. When particle concentrations are sparse, the probability of detection in small sample volumes follows Poisson statistics, resulting in high variability and frequent false-negative results. This paper examines the implications of Poisson sampling variance for environmental monitoring and demonstrates how larger sample volumes substantially improve detection reliability. We advocate for volume-aware sampling strategies and provide quantitative guidance to support more robust monitoring of microplastics, nanoplastics, and other low-concentration particulates.
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Large Sample Volumes Improve Detection Reliability of Sparse Particles in Water: A Poisson Sampling Perspective
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