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Stormwater microplastic polymer types, particle sizes, and impact of techniques

Zenodo (CERN European Organization for Nuclear Research) 2024
Lilia Ochoa, Swaraj Parmar, Will Boni, Georgia Arbuckle-Keil, Nicole Fahrenfeld

Summary

Researchers characterised microplastic size distribution, morphology, and polymer profiles in urban stormwater runoff across multiple storm events and assessed how different subsampling techniques affect estimated microplastic concentrations and polymer diversity. The study found that subsampling methodology significantly influences results, highlighting the need for standardised approaches to accurately quantify stormwater as a microplastic pathway into aquatic ecosystems.

Stormwater runoff is a pathway of entry for microplastics (MPs) into aquatic ecosystems. Understanding not only microplastic concentrations but also size distribution, morphology, and polymer profiles is desirable. A challenge is that subsampling is often required for analysis of environmental samples and the impact of subsampling on estimated MP concentrations and polymer diversity is poorly characterized. The objectives of this study were to (1) determine MP size, morphology, chemical composition, and loading across urban storm events and (2) the impact of subsampling on these observations for MP. Sampling was performed in two campaigns: the first based on NOAA methods with a wet peroxide oxidation and density separation and the second based on ASTM methods with a wet peroxide oxidation and cellulose digestion. MP analysis was performed via attenuated total reflectance (ATR) FTIR and/or FTIR-microscopy. MP concentrations (MP/L) were 86 ± 107 for 63-250 µm, 0.68 ± 0.36 for 250-500 µm, and 0.4 ± 0.24 for 500-2000µm or 0.99 ± 1.10 MP/L for 500-1000 μm and 0.41±0.30 MP/L for the 1000-5000 μm size ranges. Concentrations were comparable or greater and polymer richness was greater using the ASTM methods and larger sample volume. Varying the number of particles subsampled demonstrated the coefficient of variation for concentration (standard deviation/mean) for most samples was Also see: https://micro2024.sciencesconf.org/559566/document

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