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μ-FTIR Reflectance Spectroscopy Coupled with Multivariate Analysis: A Rapid and Robust Method for Identifying the
Eleonora Conterosito1, Maddalena Roncoli1, Chiara Ivaldi1
1Department of Sustainable Development and Ecological Transition, Università del Piemonte Orientale, Piazza Sant'Eusebio 5, Vercelli 13100, Italy.
Analytical Chemistry
|February 6, 2025
Summary
This study introduces a new method using micro-Fourier-transform infrared (μ-FTIR) spectroscopy and principal component analysis (PCA) to identify microplastics and assess their photodegradation. The technique offers increased sensitivity and a faster workflow for analyzing plastic pollution.
Area of Science:
- Environmental Science
- Analytical Chemistry
- Materials Science
Background:
- Microplastic (MP) pollution poses environmental risks, necessitating accurate chemical identification and understanding of degradation.
- Photoaging alters MP chemical structures, influencing their environmental impact and biological effects.
- Micro-Fourier-transform infrared (μ-FTIR) spectroscopy is crucial for MP analysis, but reflectance methods face challenges with particle thickness and photodegradation.
Purpose of the Study:
- To develop a robust method for identifying microplastics, including photodegraded ones, using μ-FTIR spectroscopy.
- To compare different μ-FTIR acquisition methods and data analysis strategies for MP identification and degradation assessment.
- To validate the proposed method against existing techniques like the carboxyl index (CI).
Main Methods:
- Investigated micro-transflectance-infrared (μ-TR-IR) and attenuated total reflectance-infrared (ATR-IR) spectroscopy for MP analysis.
- Employed multivariate analysis, specifically principal component analysis (PCA), for spectral data processing.
- Examined various data pretreatments and dataset analysis procedures, including validation with a test set.
Main Results:
- The μ-TR-IR method coupled with PCA effectively classified microplastics and analyzed their degradation.
- μ-TR-IR demonstrated higher sensitivity to degradation changes compared to ATR-IR.
- PCA proved more robust than the carboxyl index (CI) method for assessing polymer degradation, considering the entire spectrum and multiple degradation mechanisms.
Conclusions:
- The developed μ-TR-IR and PCA method provides a sensitive and efficient approach for microplastic identification and photodegradation analysis.
- This technique overcomes limitations of manual spectral matching and offers advantages over traditional methods like CI.
- The findings contribute to a better understanding of plastic pollution and its environmental consequences.
