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Analytics of paints and coatings with (reactive) pyrolysis-GC/MS – challenges and perspective
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Researchers examined the application of reactive pyrolysis-GC/MS for analyzing paints and coatings as a source of microplastic particles, addressing challenges in detecting these particles in environmental samples such as sediment and water. The study highlighted that paints and coatings have been estimated as the largest single source of microplastics to oceans yet remain poorly characterized due to analytical limitations.
Paints and coatings have recently become the focus of microplastics research, as a study has estimated high particle emissions of this type of microplastic1. For oceans and waterways, this study even estimates that paints and coatings are by far the largest source of microplastics. However, there is little environmental data on the concentration of paint and coating particles in sediment and water samples to confirm this study. One of the reasons for the lack of environmental data is that these particles are quite difficult to analyze. There are many different types of paints and coatings, each consisting of a complex formulation of different polymers, pigments, additives and fillers. The layered structure of the paint and coating particles, to which rust often still adheres, makes analysis with spectroscopic or visual methods difficult. I. A promising tool for the analysis of paint and coating particles in environmental samples is (reactive) pyrolysis gas chromatography/mass spectrometry (py-GC/MS). Based on this technique we will present: A mass-spectral database and a semi-automated data evaluation to achieve reliable identification of different paint types at the polymer level by py-GC/MS on the basis of the analysis of more than 40 corrosion protection coatings and 10 anti-fouling coatings. II. A proof-of-concept for the identification and quantification of antifouling paint particles (APPs) carried out for samples from underwater cleaning of ship hulls, for which ships with hard coatings, foul-release coatings (FR) and self-polishing coatings (SPC) were selected. III. A method comparison of py-GC/MS with spectroscopic techniques (laser direct infrared, RAMAN- and Fourier-transform infrared spectroscopy) carried out for 28 different single corrosion-protection coating particles. The comparison shows that py-GC/MS (in combination with multivariate statistics) is a well-suited tool for identification of paint and coating particles. 1Paruta, P., Pucino, M., & Boucher, J. (2022). Plastic Paints the Environment. https://www.e-a.earth/_files/ugd/425198_a864877fefd74ade85d85080ae21e029.pdf Also see: https://micro2024.sciencesconf.org/558784/document
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Analytics of paints and coatings with (reactive) pyrolysis-GC/MS – challenges and perspective
AI summary Read the abstract
Researchers examined the application of reactive pyrolysis-GC/MS as an analytical method for detecting and quantifying paint and coating particles in environmental samples, addressing challenges posed by the complex, layered structure of paint particles containing multiple polymers, pigments, and fillers. They found pyrolysis-GC/MS to be a promising approach for this difficult-to-analyze microplastic category, which one major estimate suggests may be the single largest global source of marine microplastics.
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Researchers developed a new method using reactive pyrolysis gas chromatography to analyze the complex chemical composition of anti-corrosion marine coatings, which are estimated to be a major source of microplastics in the ocean. Marine paint particles are difficult to study because they contain many different polymers and additives mixed together. The new analytical approach provides better chemical characterization of paint-derived microplastics, an important step toward understanding this overlooked pollution source.
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Researchers optimized a pyrolysis-GC/MS method for identifying and quantifying microplastics in environmental samples, improving the reliability of polymer identification especially for small particles that are difficult to classify visually. The improved method is particularly valuable for analyzing the smallest microplastic size fractions that dominate by number in marine environments.
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