Nationwide Assessment of Microplastic Contamination and Polymer Risk Indices in Brazilian Coastal Sands (2023–2024)
Description
This dataset compiles georeferenced information on microplastic (MP) contamination in beach sands sampled across the Brazilian coastline between 2020 and 2024, as part of the MicroMar Project. The dataset includes 4,000+ sampling points distributed along 1,000 beaches, representing all coastal states of Brazil. For each sample, metadata include geographic coordinates (longitude and latitude), sample identification code, state, municipality, and beach name. Quantitative data comprise microplastic concentrations normalized by dry sand mass (MPs_kg, particles per kilogram), as well as three synthetic environmental risk indices: the Polymer Load Index (PLI), Polymer Hazard Index (PHI), and Pollution Ecological Risk Index (PERI). These indices were calculated from polymer composition and hazard weighting following established frameworks. This dataset provides a baseline for assessing spatial patterns, polymer-specific risks, and regional drivers of microplastic pollution in Brazilian coastal ecosystems. It supports national and international research efforts on marine litter and coastal contamination.
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Steps to reproduce
This dataset was generated under the MICROMar Project, the largest standardized survey of microplastic contamination ever conducted in the Global South. A total of 4,134 sand samples were collected from 1,024 beaches distributed across 211 municipalities and 17 coastal states of Brazil, covering approximately 7,500 km of coastline. Sampling was conducted between April 2023 and April 2024. At each site, surface sediments (0–5 cm depth) were collected using 50 × 50 cm quadrats positioned along the high tide line. Each composite sample (≈70–80 g) consisted of five subpoints (four corners and one center), ensuring spatial representativeness. Sampling was restricted to low tide conditions and excluded estuarine, inaccessible, or privately restricted areas. All sites were georeferenced using handheld GPS units (±5 m accuracy). Microplastic extraction was performed at the Laboratory of Toxicology Applied to the Environment (IF Goiano – Urutaí Campus, Brazil) under strict anti-contamination protocols. Sediment samples were homogenized and subjected to density separation using zinc chloride (ZnCl₂, 1.7 g/cm³), followed by centrifugation (2,500 rpm, 5 min), filtration (400-mesh, ≈37 µm), and drying at 45 °C for 8 h. Organic matter was removed with 30% hydrogen peroxide (H₂O₂) at room temperature for 2 h. The mean procedural recovery efficiency was 92.3% ± 4.1%, validated with pristine and weathered polymer spikes (PE, PP, PS, PET, PVC). Particles (300 µm – 5 mm) were visually sorted under stereomicroscopy and classified by color, morphotype, and shape. Polymer composition was confirmed via Raman spectroscopy (Anton Paar Cora 5001, λ = 785 nm, 45 mW, 10 s exposure, 3 accumulations) using a 23-polymer reference library and commercial databases. Spectra with ≥70% similarity were accepted. Subsampling of up to 10 MPs per sample was statistically validated to capture ~89% of polymeric diversity. Microplastic concentration (MPs/kg, dry weight) and three risk indices were calculated: (i) Pollution Load Index (PLI) – contamination intensity; (ii) Polymer Hazard Index (PHI) – toxicity-weighted polymer risk; (iii) Potential Ecological Risk Index (PERI) – combined hazard and pollution intensity. Geospatial coordinates and computed indices were compiled in a single xlsx file. Data cleaning, baseline estimation, and statistical modeling were performed using R (v4.3.2), Jamovi, GraphPad Prism, and QGIS (v3.30). All analyses followed standardized, reproducible workflows described in the corresponding publication: Microplastic Pollution Across the Brazilian Coastline: Evidence from the MICROMar Project.
Institutions
- Instituto Federal de Educacao Ciencia e Tecnologia Goiano - Campus Urutai