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Identification of antifouling paint particles among colored paint chips in coastal sediments of Phuket, Thailand, using Py-GC/MS.
Summary
Scientists developed a new method to identify toxic paint chips from ship hulls (called antifouling paint) hiding among ordinary microplastic debris on the seafloor near Phuket, Thailand. Using this technique, they found that over half of the paint chips tested contained pesticide-like chemicals or high levels of copper meant to kill barnacles and algae—pollutants that can harm marine life and potentially work their way up the food chain to humans who eat seafood. This tool gives researchers a better way to track this hidden source of ocean pollution going forward.
Marine paint particles are recognized as one source of microplastic pollution in aquatic environments, and antifouling paint particles (APP) are of particular concern because they also contain biocides. In this study, we investigated colored paint chips collected from sediments around ship mooring areas and repair yards along the coast of Phuket, Thailand, to determine whether they originated from APP. A standard APP was prepared by spiking a commercial antifouling paint with five organic biocides, and pyrolysis-gas chromatography/mass spectrometry conditions were developed to quantify five biocides and identify nine resin components in a single run. Elemental compositions were analyzed using X-ray fluorescence, and copper, a major component of antifouling paints, was quantified by atomic absorption spectrometry. The method was applied to 41 paint chips collected from coastal sediments along the coast of Phuket, Thailand. Diuron (up to 6.21 mg/g) and Sea-Nine 211 (up to 8.77 mg/g) were detected in eight dried paint chips, and six resin types (polymethyl methacrylate, nylon 6,6, polypropylene, polyvinyl chloride, polycarbonate, and polystyrene) were also identified. Twenty samples exceeded the Cu reference value of 100 mg/kg. In total, 24 samples either contained organic biocides or exceeded 100 mg/kg Cu and were therefore identified as APP. These findings demonstrate that the developed analytical approach provides a reliable tool for identifying APP in environmental samples and will facilitate future monitoring of APP contamination in marine environments.