A spectral-decomposition aging index for microplastics in aquatic environments

Area of Science:

• Environmental Science
• Analytical Chemistry
• Polymer Science

Background:

• Microplastics (MPs) age in natural waters via photodegradation and microbial colonization, altering their properties and ecological risks.
• Traditional infrared indices struggle to quantify aging in oxygen-containing MPs and are confounded by biofilms.
• A need exists for a universal method to assess microplastic aging across diverse polymer types and environmental conditions.

Purpose of the Study:

• To develop and validate a novel Spectral Decomposition Aging Index (SDAI) for quantifying microplastic aging.
• To overcome limitations of traditional infrared indices, especially for oxygen-containing polymers and complex environmental samples.
• To establish a robust and transferable framework for comparative microplastic aging assessment.

Main Methods:

• Developed SDAI using multivariate curve resolution-alternating least squares (MCR-ALS) decomposition of infrared spectra.
• Determined optimal component numbers for photoaging (two) and microbial aging (three) using core consistency diagnostics.
• Validated SDAI on six aquatic polymers (PVC, PET, PCL, PE, PP, PLA) using laboratory and public spectral data.

Main Results:

• SDAI demonstrated high model robustness (>99.7% explained variance) and reproducibility (SD ≤ 0.19).
• SDAI accurately tracked aging in conventional MPs and captured monotonic aging in oxygen-containing polymers where traditional indices failed.
• SDAI successfully resolved aging and biofilm signals simultaneously in microbially aged samples.

Conclusions:

• SDAI offers a robust and transferable method for comparative microplastic aging assessment, especially under complex spectral conditions.
• The index overcomes limitations of traditional methods for oxygen-containing polymers and mixed environmental signals.
• Further validation on field-weathered samples is recommended to broaden SDAI's application.