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Automated Identification and Quantification of Microplastics by FTIR Imaging and Image Analysis
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This research developed an automated system using FTIR imaging and chemometric analysis to identify and count microplastic particles smaller than 500 micrometers. Automating this step addresses a major bottleneck in microplastic research, allowing for faster and more consistent analysis of environmental samples.
In the last decades the pollution of the oceans with plastic particles smaller than 5 mm, called microplastics has moved into the focus of science and governments. The analysis of particles especially <500 µm in size is a challenging field. These particles cannot be handled well manually and are therefore often concentrated on filters or meshes. By common FTIR microscopy the filter will be inspected visually and particles of interest marked for the following analysis. The manual selection process is prone to human bias, which can be overcome by FTIR imaging. Here, the complete filter area is mapped by FTIR using focal-plane-array (FPA) detectors, which collect several hundred spectra within one measurement for a large area. Each particle on the filter is therefore examined by FTIR spectroscopy. The results of this imaging can be either analyzed manually by the application of integrals for certain regions of the spectrum or automated. While the manual process is time consuming and prone to human bias we present an automated approach, which is totally impartial. With this process it is possible to analyze measurement files containing up to 1.8 million single spectra by library searches against an optimized database of different synthetic and natural polymers. The high quality data generated allowed image analysis, giving information for the particle size distribution for each polymer type as well as their distribution on the filter. All data was collected with relative ease even for complex sample matrices like (deep sea) sediments, waste water treatment plants, plankton samples and arctic ice cores. This approach has significantly decreased the expenditure of time for the interpretation of FTIR-imaging data and increased the quality of the generated data. The approach allows the standardization of microplastic analysis.
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