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The increasing pollution of terrestrial and aquatic ecosystems with plastic debris leads to the accumulation of microscopic plastic particles of still unknown amount. To monitor the degree of contamination analytical methods are urgently needed, which help to quantify microplastics (MP). Currently, time-costly purified materials enriched on filters are investigated both by micro-infrared spectroscopy and/or micro-Raman. Although yielding precise results, these techniques are time consuming, and are restricted to the analysis of a small part of the sample in the order of few micrograms. To overcome these problems, here we tested a macroscopic dimensioned NIR process-spectroscopic method in combination with chemometrics. For calibration, artificial MP/soil mixtures containing defined ratios of polyethylene, polyethylene terephthalate, polypropylene, and polystyrene with diameters < 125 µm were prepared and measured by a process FT-NIR spectrometer equipped with a fiber optic reflection probe. The resulting spectra were processed by chemometric models including support vector machine regression (SVR), and partial least squares discriminant analysis (PLS-DA). Validation of models by MP mixtures, MP-free soils and real-world samples, e.g. and fermenter residue, suggest a reliable detection and a possible classification of MP at levels above 0.5 to 1.0 mass% depending on the polymer. The benefit of the combined NIRS chemometric approach lies in the rapid assessment whether soil contains MP, without any chemical pre-treatment. The method can be used with larger sample volumes and even allows for an online prediction and thus meets the demand of a high-throughput method.
Background: The ubiquitous occurrence of microplastic particles in marine and aquatic ecosystems was intensively investigated in the past decade. However, we know less about the presence, fate, and input paths of microplastic in terrestrial ecosystems. A possible entry path for microplastic into terrestrial ecosystems is the agricultural application of sewage sludge and solid bio-waste as fertilizers. Microplastic contained in sewage sludge also includes Polyethylene terephthalate (PET), which could originate as fiber from textile products or as a fragment from packaging products (foils, bottles, etc.). Information about microplastic content in such environmental samples is limited yet, as most of the used analytical methods are very time-consuming, regarding sample preparation and detection, require sophisticated analytical tools and eventually need high user knowledge.
Results: Here, we present a simple, specific tool for the analysis of PET microplastic particles based on alkaline extraction of PET from the environmental matrix and subsequent determination of the monomers, terephthalic acid, using liquid chromatography with UV detection (LC-UV). The applicability of the method is shown for different types of PET in several soil-related, terrestrial environmental samples, e.g., soil, sediment, compost, fermentation residues, but also sewage sludge, suspended particles from urban water management systems, and indoor dust. Recoveries for model samples are between 94.5 and 107.1%. Limit of determination and limit of quantification are absolute masses of 0.031 and 0.121 mg PET, respectively. In order to verify the measured mass contents of the environmental samples, a method comparison with thermal extraction-desorption-gas chromatography–mass spectrometry (TED-GC/MS) was conducted. Both methods deliver similar results and corroborated each other. PET mass contents in environmental samples range from values below LOQ in agriculture soil up to 57,000 mg kg−1 in dust samples.
Conclusions: We demonstrate the potential of an integral method based on chemical extraction for the Determination of PET mass contents in solid environmental samples. The method was successfully applied to various matrices and may serve as an analytical tool for further investigations of PET-based microplastic in terrestrial ecosystems.