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Improving Sampling Strategies for Microplastic Detection in Aquatic Environments: Precision, Recovery, and Sample Size Requirements

Microplastics 2026

Summary

Researchers compared grab sampling and large-volume filtration for quantifying microplastics across four water matrices — wastewater, tap water, sewer overflow, and surface water — finding that large-volume sampling required only 21 samples to achieve a ±25% margin of error versus 51 for grab sampling, with fluorescent staining and automated counting enabling reliable quantification across all matrices.

Polymers
Study Type Environmental

The accurate quantification of microplastics (MPs) in aquatic environments remains challenging due to the heterogeneous distribution of MPs in different environments, making representative sampling difficult, as well as methodological variabilities in sampling, sample processing, and detection. This study examined measurement fluctuations for MP analysis across four distinct water matrices: wastewater treatment plant (WWTP) effluent, tap water (TW), combined sewer overflow (CSO), and surface water (SW). Two sampling strategies were compared: grab sampling (0.5 L, n = 5) and large-volume filtration using a particle sampling unit (PSU; 100 L, 10 µm mesh, subsampled). Samples were processed through oxidative digestion, stained with fluorescent dye, and analyzed via fluorescence microscopy with automated particle counting. Recovery experiments using polyamide (PA) reference particles (357 ± 60 µm) were conducted to assess method accuracy. PSU sampling demonstrated higher precision (mean R.S.D. 41 ± 17%) compared to grab sampling (mean R.S.D. 64 ± 19%), despite additional variability introduced by subsampling. Recovery rates reached 93 ± 7% for grab samples and 88 ± 23% for PSU samples with complete filter analysis. Statistical modeling revealed that achieving a ±25% margin of error (95% CI) required 21 PSU samples versus 51 grab samples. The quadratic relationship between the margin of error and required sample size underscores the importance of methodological optimization for cost-effective monitoring. These findings provide practical guidance for designing MP monitoring campaigns and demonstrate that fluorescent labeling combined with large-volume sampling offers a reliable approach for MP quantification in diverse aquatic environments.

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