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Chemical composition of microplastics floating on the surface of the Mediterranean Sea

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This dataset describes the polymer composition of microplastics collected from Mediterranean Sea surface waters during the 2014 Tara Mediterranean expedition. Polyethylene was the dominant polymer at 67.3%, followed by polypropylene at 20.8% and polystyrene at 3.0%, as identified by FTIR spectroscopy.

This dataset describes the types and proportions of the different microplastic types in samples collected from the surface waters during the Tara Mediterranean expedition in 2014. The main polymers identified by Fourier Transform Infra-Red (FTIR) spectroscopy were poly(ethylene) (67.3 ± 2.4%), poly(propylene) (20.8 ± 2.1%) and poly(styrene) (3.0 ± 0.9%). N

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Chemical composition of microplastics floating on the surface of the Mediterranean Sea

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This dataset describes the polymer composition of microplastics collected from Mediterranean Sea surface waters during the 2014 Tara Mediterranean expedition. Polyethylene was the dominant polymer at 67.3%, followed by polypropylene at 20.8% and polystyrene at 3.0%, as identified by FTIR spectroscopy.

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Chemical composition of microplastics floating on the Mediterranean Sea surface

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Surface water samples from the 2014 Tara Mediterranean expedition revealed that the Mediterranean Sea's microplastic composition was relatively homogeneous at large scales, dominated by polyethylene (67%), polypropylene (21%), and polystyrene (3%). Some regional variation was observed, with the North Tyrrhenian Sea showing lower polyethylene proportions.

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This study characterized microplastic contamination in the benthic sediments of a shallow tropical reef lagoon, finding widespread particle distribution influenced by seasonal monsoon-driven circulation patterns. Concentrations were highest in low-energy depositional zones, and polymer types reflected a mixture of locally derived and oceanic transport sources.

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Chemical composition of microplastics floating on the surface of the Mediterranean Sea

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Chemical composition analysis of microplastics floating on the Mediterranean Sea surface showed a relatively homogeneous polymer distribution dominated by polyethylene and polypropylene, with particle size influencing mass and number concentration distributions.

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A machine learning algorithm for high throughput identification of FTIR spectra: Application on microplastics collected in the Mediterranean Sea

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Researchers developed a machine learning method to automatically identify the chemical composition of microplastics from FTIR spectroscopy data collected during the Tara Mediterranean expedition. The algorithm performed well for common polymers like polyethylene and was applied to classify over 4,000 unidentified microplastic spectra. The study demonstrates that automated identification tools can significantly speed up large-scale microplastic pollution surveys while maintaining acceptable accuracy.

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