We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Rapid Identification of Beached Marine Plastics Pellets Using Laser-Induced Breakdown Spectroscopy: A Promising Tool for the Quantification of Coastal Pollution
AI summary Read the abstract
Researchers applied laser-induced breakdown spectroscopy combined with chemometric analysis to rapidly identify and classify beached plastic pellets by polymer type, achieving over 80% accuracy and demonstrating its potential as a fast, field-deployable tool for coastal pollution monitoring.
The rapid identification of beached marine micro-plastics is essential for the determination of the source of pollution and for planning the most effective strategies for remediation. In this paper, we present the results obtained by applying the laser-induced breakdown spectroscopy (LIBS) technique on a large sample of different kinds of plastics that can be found in a marine environment. The use of chemometric analytical tools allowed a rapid classification of the pellets with an accuracy greater than 80%. The LIBS spectrum and statistical tests proved their worth to quickly identify polymers, and in particular, to distinguish C-O from C-C backbone pellets, and PE from PP ones. In addition, the PCA analysis revealed a correlation between appearance (surface pellets roughness) and color (yellowing), as reported by other recent studies. The preliminary results on the analysis of metals accumulated on the surface of the pellets are also reported. The implication of these results is discussed in view of the possibility of frequent monitoring of the marine plastic pollution on the seacoast.
More Papers Like This
Identifying microplastic litter with Laser Induced Breakdown Spectroscopy: A first approach
AI summary Read the abstract
Researchers demonstrated that Laser Induced Breakdown Spectroscopy (LIBS) can identify microplastic particles by their spectral fingerprints, offering a first approach to a rapid analytical technique for distinguishing plastic litter types.
Laser-Induced Breakdown Spectroscopy for the Identification of Microplastics Collected from Arabian Sea of Pakistan
AI summary Read the abstract
Researchers applied laser-induced breakdown spectroscopy (LIBS) combined with FTIR to identify and characterize microplastic samples collected from the Arabian Sea coast of Pakistan, demonstrating that calibration-free LIBS can reliably distinguish polymer types through elemental analysis of carbon and oxygen content.
Chemometric analysis of polymer spectra for degradation assessment and enhanced identification of macro, meso and microplastics
AI summary Read the abstract
Scientists tested ways to identify weathered plastic fragments and pellets, focusing on two common ocean plastics, polyethylene and polypropylene. They developed tools to measure plastic breakdown and used computer classification methods to better distinguish plastic types from spectroscopy data, aiming to improve identification when plastic samples are heavily degraded.
Identification and Quantification of Microplastics in the Marine Environment Using the Laser Direct Infrared (LDIR) Technique
AI summary Read the abstract
Researchers evaluated the laser direct infrared (LDIR) technique for identifying and quantifying marine microplastics, demonstrating it as a faster and more automated alternative to conventional FTIR methods with comparable accuracy.
Development of new spectroscopic and multivariate chemometric methods for the characterization of microplastics in the marine environment
AI summary Read the abstract
New spectroscopic and multivariate chemometric methods were developed to characterize and identify microplastics in environmental samples, addressing the lack of standardized analytical protocols. The approach improves the accuracy and reproducibility of microplastic detection across different environmental compartments.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.