A high-throughput, automated technique for microplastics detection, quantification, and characterization in surface...

Area of Science:

• Environmental Science
• Analytical Chemistry
• Spectroscopy

Background:

• Microplastic pollution is a growing environmental concern.
• Accurate detection and characterization of microplastics are crucial for understanding their impact.
• Existing methods for microplastic analysis can be time-consuming and labor-intensive.

Purpose of the Study:

• To demonstrate a high-throughput approach for detecting, quantifying, and characterizing microplastics in surface water.
• To evaluate the effectiveness of laser direct infrared (LDIR) spectroscopy for microplastic analysis.
• To develop and apply a shape-classifying algorithm for microplastic categorization.

Main Methods:

• Utilized laser direct infrared (LDIR) spectroscopy for microplastic analysis in surface water samples from urban creeks.
• Employed a Fenton reaction for sample oxidation and filtration onto a gold-coated polyester membrane.
• Developed a shape-classifying algorithm based on aspect ratio and used a hit quality index (HQI) for spectral matching.

Main Results:

• Achieved microplastic recoveries of 88.3% ± 1.2% with LDIR spectroscopy.
• Quantified microplastics down to a diameter of 20 µm, comparable to FTIR and Raman spectroscopy.
• Identified approximately 50% of environmental microplastics as fragments, with other shapes comprising the remainder.
• LDIR analysis showed comparable polymer identification results to Fourier transform infrared spectroscopy (FTIR) using HQI values.

Conclusions:

• Laser direct infrared (LDIR) spectroscopy provides a simple, automated, and rapid method for high-throughput microplastic analysis.
• The developed method is effective for quantifying and characterizing microplastics by shape, size, and polymer type.
• LDIR spectroscopy is an attractive alternative to traditional methods for environmental microplastic monitoring.