Novel Concepts for the Detection of Microplastics

Microplastics are small pieces of plastic (smaller than 5 mm), which can be found in the environment and can be dangerous to living beings. It is expected that the abundance of microplastics will rise in the future. However, there are still no standard protocols for monitoring the microplastic abundance, which should include spectroscopic methods for an automated discrimination in order to produce reliable data. In this work we examined a new approach for microplastic detection based on the photoluminescence (PL) spectroscopy. To test the applicability of the proposed method a low-cost setup was built and characterized. The PL spectra from 27 different materials were collected and compared. The comparison of the spectra shows that the differentiation between samples is possible, especially between the plastic and non-plastic materials. Furthermore, the measured PL spectra also differ for different plastic types and other materials. However, the presence of dyes in plastic samples and incrustation of plastic samples by organic materials can affect the PL spectra and make the recognition troublesome. Disregarding organic materials and dyed plastic, the material differentiation based on the acquired PL spectra using neural networks resulted in 99.3 % accuracy when categorizing samples into plastic and non-plastic materials and 63.1 % accuracy when categorizing samples among different plastic and non-plastic materials. The promising results show that the PL spectroscopy of microplastics could outperform the spectroscopic methods used so far, by means of measurement speed and lateral resolution.