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The necessity of whole-water-column monitoring: microplastic vertical and horizontal distribution and ecological risk on the Eastern Coast of the inner Gulf of Thailand

Zenodo (CERN European Organization for Nuclear Research) 2026

Summary

Researchers sampled microplastics at surface, mid-depth, and near-bottom layers across 20 coastal stations in the Gulf of Thailand, finding significant vertical and horizontal heterogeneity that surface-only monitoring would miss, with depth and distance from shore jointly controlling microplastic fate and ecological risk.

This dataset contains the underlying environmental monitoring data for the manuscript: "The necessity of whole-water-column monitoring: microplastic vertical and horizontal distribution and ecological risk on the Eastern Coast of the inner Gulf of Thailand". Data Description The dataset includes microplastic (MP) quantification and characterization data collected from 73 water-column samples across 20 coastal stations in the eastern inner Gulf of Thailand. To assess vertical and horizontal distribution, sampling was conducted across three distinct depth profiles: Surface (0–1 m) Mid-depth (5–10 m) Near-bottom (~1 m above seabed) Variables Included The data details MP concentrations (particles/L), morphological characteristics (shape), size fractions (16–5000 µm), and polymer types identified via μFTIR spectroscopy. Additionally, the dataset supports the spatial interpolation maps, Principal Component Analysis (PCA), and Potential Ecological Risk Index (PERI) calculations presented in the associated study. This dataset contains the underlying environmental monitoring data for the manuscript: "Whole-Water-Column: How Depth and Distance Control Microplastic Fate and Risk in eastern coast of the inner Gulf of Thailand". Data Description The dataset includes microplastic (MP) quantification and characterization data collected from 73 water-column samples across 20 coastal stations in the eastern inner Gulf of Thailand. To assess vertical and horizontal distribution, sampling was conducted across three distinct depth profiles: Surface (0–1 m) Mid-depth (5–10 m) Near-bottom (~1 m above seabed) Variables Included The data details MP concentrations (particles/L), morphological characteristics (shape), size fractions (16–5000 µm), and polymer types identified via μFTIR spectroscopy. Additionally, the dataset supports the spatial interpolation maps, Principal Component Analysis (PCA), and Potential Ecological Risk Index (PERI) calculations presented in the associated study.

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