Using FTIRS as pre-screening method for detection of microplastic in bulk sediment samples

Area of Science:

• Environmental Science
• Analytical Chemistry
• Materials Science

Background:

• Microplastic pollution is a growing concern in marine and freshwater ecosystems.
• Accurate detection and quantification of microplastics in environmental matrices like sediment are crucial.
• Existing methods for microplastic analysis can be time-consuming and expensive.

Purpose of the Study:

• To develop and validate calibration models for detecting low-density polyethylene (LDPE) and polyethylene terephthalate (PET) in sediments.
• To assess the feasibility of using Fourier transform infrared spectroscopy (FTIRS) coupled with partial least squares regression (PLSR) for microplastic analysis.
• To provide a time- and cost-efficient pre-screening tool for microplastic identification in sediment samples.

Main Methods:

• Preparation of synthetic sediment mixtures with known concentrations of ground LDPE and PET particles (0–5 wt%).
• Analysis of spectral data using Fourier transform infrared spectroscopy (FTIRS).
• Development of calibration models using partial least squares regression (PLSR) to correlate spectral information with plastic content.

Main Results:

• Strong cross-validated correlations (R²CV = 0.73 for LDPE, 0.72 for PET) were achieved.
• Low root-mean-square errors of cross-validation (RMSECV = 0.72% for LDPE, 0.61% for PET) were obtained.
• The method successfully detected microplastics in natural sediment samples, proving effective for high concentrations (>1%).

Conclusions:

• The developed FTIRS-PLSR method offers a semi-quantitative and semi-qualitative approach for microplastic detection in sediments.
• This technique is particularly advantageous as a time- and cost-efficient pre-screening tool for large-scale monitoring studies.
• Further analysis is recommended for samples identified with potential plastic content using this pre-screening method.