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Quantitative Raman analysis of microplastics in water using peak area ratios for concentration determination

npj Clean Water 2024 24 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 55 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Eun Su Jung, Sung Gyu Pyo Eun Su Jung, Jin Hyun Choe, Jin Hyun Choe, Jin Hyun Choe, Jin Hyun Choe, Eun Su Jung, Jin Hyun Choe, Jin Hyun Choe, JinUk Yoo, Jin Seok Kim, JinUk Yoo, Da Won Ahn, Da Won Ahn, Jin Seok Kim, Da Won Ahn, JinUk Yoo, JinUk Yoo, Da Won Ahn, Tae Min Choi, JinUk Yoo, Tae Min Choi, JinUk Yoo, Tae Min Choi, Tae Min Choi, Sung Gyu Pyo Sung Gyu Pyo

Summary

Researchers developed a new method using Raman spectroscopy to measure microplastic concentrations in water. By analyzing the ratio of plastic-specific signals to the water signal, they created a reliable calibration model for detecting polyethylene and PVC microplastics, even when multiple plastic types are mixed together. This approach could make it faster and easier to monitor microplastic contamination in real-world water sources.

Polymers

This study presents a novel analytical method for the quantitative and qualitative analysis of microplastics (MPs) in deionized (DI) water using Raman spectroscopy. Raman peak area ratios of 1295 cm−1 for polyethylene (PE) and 637 cm−1 for polyvinylchloride (PVC) to the broad H2O peak were utilized to establish a calibration model for the concentration of MPs dispersed in DI water at 0.1 wt% to 1.0 wt%. The calibration model demonstrated R2 values of 0.98537 for PE and 0.99511 for PVC, indicating high linearity between the peak area ratio and concentration. The calibration model was validated using mixed PE and PVC samples to confirm its applicability to real-world water bodies, where multiple types of MPs are present. The calculated standard error of calibration (SEC) and relative standard error of calibration (%RSEC) values further confirmed the accuracy of the predictions, providing a robust approach for detecting and quantifying MPs in aquatic environments.

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