Underestimating microplastics? Quantification of the recovery rate of microplastic particles including sampling, sample preparation, subsampling, and detection using µ-Ramanspectroscopy

Abstract

This study is one of the first to investigate the recovery rate of high- and low-density microplastic particles (polyvinyl chloride and polypropylene) from wastewater treatment plant effluents or comparable technical facilities under nearly realistic experimental conditions. For this purpose, a method of continuous dosing of microplastic particles into an experimental flume for open-channel flow was developed. Subsequently, 12 samples were taken using volume-reduced sampling and the entire sample purification process including oxidative treatment (with hydrogen peroxide and sodium hypochlorite), density separation (with sodium polytungstate), and subsampling was carried out. Detection was conducted using automatic particle recognition and µ-Ramanspectroscopy. An average recovery rate of 27 ± 10% was determined for polypropylene microplastic particles (d = 53 ± 29 µm), decreasing with the particle size, and 78 ± 14% for polyvinyl chloride microplastic particles (d = 151 ± 37 µm). The results suggest that microplastic emissions from wastewater treatment plants are underestimated, particularly because the recovery rate of small microplastic particles < 50 µm is only 9%.

Development of a machine learning-based method for the analysis of microplastics in environmental samples using µ-Raman spectroscopy

“…Especially the single model approach seems to be acceptable, as recall and precision are around 90%. However, we decided to increase precision and recall by using the human-machine teaming approach for several reasons: In spectroscopic microplastic analysis, recovery rates are low [11,29]. Therefore, any possibility to increase accuracy should be taken.…”

“…The data set used in this study was generated in the research projects EmiStop [20], Eintrag MiPa (2022-2025), and an investigation of microplastics in two German rivers [21]. The set includes data from 47 analysis filters.…”

“…Sampling was conducted from January 2021 to April 2022. Sampling, sample preparation, and analysis by µ-Raman spectroscopy were conducted according to the methods used in Weber and Kerpen B [21], Weber and Kerpen A [11], and Barkmann-Metaj et al [22]: After volume-reduced sampling, the samples were prepared for analysis. Biological-organic matrix components were digested by hydrogen peroxide (323.15 K, 24 h) and sodium hypochlorite (room temperature, 6 d).…”

“…However, this is because this value was defined as the lower limit of quantification in the projects from which the data were obtained. Although the detection of microplastic particles ≥ 1 µm using µ-Raman spectroscopy is not a problem, there are still no methods for reliable sample preparation of environmental or wastewater samples with sufficiently high recovery rates for microplastics < 10 µm [11]. As soon as such methods are available, the spectra identification will probably have to be adapted to smaller microplastics.…”

“…It is necessary to analyze several thousand particles per sample to achieve a representative result [8,9]. Although automatic particle recognition is now available from open-source programs [10] or is incorporated into the instrument software [11], detection is still time-consuming, so the measurement settings are chosen as a compromise between spectra quality and the time required for measurement. This leads to weak spectra quality (including a lower signal-to-noise ratio) [12].…”