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Beyond the net: sub-300 μm microplastics accumulating in Amazonian estuarine waters
Summary
Standard microplastic sampling methods using coarse nets miss the smallest particles — and a study of Amazonian estuary waters confirms that the vast majority of microplastics are smaller than the 300 micrometer threshold those nets can capture. By using finer sampling procedures, researchers found concentrations nearly three times higher in the more sheltered estuarine channel than in open marine water, with plastic fibers making up over 70% of particles. These findings suggest that global microplastic pollution figures are significantly underestimated, and that monitoring programs need to adopt finer-mesh methods to get accurate readings.
Microplastics (MPs) are persistent pollutants increasingly found in estuarine environments. However, particles smaller than 300 µm are often underestimated because coarse-mesh screens (≥ 300 µm) exhibit physical selectivity, despite evidence that smaller size fractions predominate in the distribution of MPs in the environment. This study aims to evaluate the abundance, size distribution, and morphology of MPs in surface waters from two mangrove channels on the Ajuruteua Peninsula: Furo do Taici (estuarine) and Furo Grande (marine). When considering particles < 300 µm under rigorous contamination control procedures, we evaluated how hydrodynamic conditions and the selectivity of conventional nets influence the detection of MPs in estuarine systems rich in organic matter. Concentrations were higher in Furo do Taici (2.6 items/m 3 ) than in Furo Grande (0.9 items/m 3 ), with a notable predominance of particles < 300 µm, likely retained due to local hydrodynamics and organic matter. Fibers predominated in both locations (~70% at the Furo do Taici and ~80% at the Furo Grande), exceeding 90% in the > 300 µm fraction, while blue and transparent particles were the most frequent in all size classes. These findings emphasize the need to include sub-300 µm particles in monitoring programs, as their exclusion can lead to an underestimation of pollution levels. The study provides valuable baseline data to improve sampling strategies in tropical estuarine systems.