A high-throughput, automated technique for microplastics detection, quantification, and characterization in surface waters using laser direct infrared spectroscopy.

Abstract

A high-throughput approach to detecting, quantifying, and characterizing microplastics (MPs) by shape, size, and polymer type using laser direct infrared (LDIR) spectroscopy in surface water samples is demonstrated. Three urban creeks were sampled for their MP content near Cincinnati, OH. A simple Fenton reaction was used to oxidize the surface water samples, and the water samples were filtered onto a gold-coated polyester membrane. Infrared (IR) analysis for polymer identification was conducted, with recoveries of 88.3% ± 1.2%. This method was able to quantify MPs down to a diameter of 20µm, a size comparable to that of MPs quantified by other techniques such as Fourier transform infrared spectroscopy (FTIR) and Raman spectroscopy. A shape-classifying algorithm was designed using the aspect ratio values of particles to categorize MPs as fibers, fibrous fragments, fragments, spherical fragments, or spheres. Cut-off values were identified from measurements of known sphere, fragment, and fibrous particles. About half of all environmental samples were classified as fragments while the other shapes accounted for the other half. A cut-off hit quality index (HQI) value of 0.7 was used to classify known and unidentified particles based on spectral matches to a reference library. Center for Marine Debris Research Polymer Kit 1.0 standards were analyzed by LDIR and compared to the given FTIR spectra by HQI, showing that LDIR obtains similar identifications as FTIR analysis. The simplicity and automation of the LDIR allows for quick, reproducible particle analysis, making LDIR attractive for high-throughput analysis of MPs.