Microplastic analysis in sediment samples utilizing quantum cascade laser- infrared spectroscopy and pyrolysis gass chromatography mass spectrometry

Microplastics (MP) are diverse and exist in a broad range of types, sizes, colors, morphologies, and compositions. Therefore, advanced analytical techniques that detect and quantify MP in environmental samples with high accuracy, selectivity, sensitivity, and efficiency are needed. Several studies have published methods and results; however, few have provided accuracy-, recovery tests and method comparison that ensure the correctness of the results. Quantum Cascade Laser- Infrared Spectroscopy (QCL-µIR) is a non-destructive identification of particles based on their unique chemical signatures. Combined with machine learning (ML) algorithms for identification, has led to rapid, accurate and robust classification. Furthermore, using pyrolysis gas chromatography-mass spectrometry (PY-GC-MS) allows for precise characterization and quantification of MP based on their unique chemical compositions. MP in marine sediment samples from Norwegian open-sea areas were isolated using ZnCl2 and CaCl2 solution (density ¿ 1.5 g/ml) in a bauta microplastic-sediment separator, followed by a two-step chemical digestions and further filtration on a 45 µm stainless steel filter. The spectral data obtained from the QCL-µIR (Daylight Solutions SperoQT 340) were re-processed utilizing random forest algorithm. The MP were further analyzed using a PY (Frontier, Laboratories; Fukushima Japan) GC-MS (Thermo Scientific, MA, USA) method optimized for the relevant polymer types and the sample matrix, achieving low limit of quantification (between 0.01 and 0.1 µg) and is controlled for recovery. The integration of ML in QCL-µIR facilitated rapid data analysis and reliable interpretation of the acquired spectra information. Here, we have demonstrated that the number of particles corresponds with the added polymers in the sample. For detection in the PY-GC, a high mass resolution and high mass accuracy (2-5 ppm) mass spectrometer was utilized, confirming the findings from ML-QCL-µIR. Consequently, these methods ensure accurate and sensitive measurements of polymers in marine sediment samples. Also see: https://micro2024.sciencesconf.org/558540/document