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, we tested a macroscopic dimensioned near-infrared (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., fermenter residue, suggests 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 pretreatment. 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.

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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.

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The adsorption of organic micropollutants onto activated carbon is a favourable solution for the treatment of drinking water and wastewater. However, these adsorption processes are not sufficiently understood to allow for the appropriate prediction of removal processes. In this study, thermogravimetric analysis, alongside evolved gas analysis, is proposed for the characterisation of micropollutants adsorbed on activated carbon. Varying amounts of carbamazepine were adsorbed onto three different activated carbons, which were subsequently dried, and their thermal decomposition mechanisms examined. The discovery of 55 different pyrolysis products allowed differentiations to be made between specific adsorption sites and conditions. However, the same adsorption mechanisms were found for all samples, which were enhanced by inorganic constituents and oxygen containing surface groups. Furthermore, increasing the loadings led to the evolution of more hydrated decomposition products, whilst parts of the carbamazepine molecules were also integrated into the carbon structure. It was also found that the chemical composition, especially the degree of dehydration of the activated carbon, plays an important role in the adsorption of carbamazepine. Hence, it is thought that the adsorption sites may have a higher adsorption energy for specific adsorbates, when the activated carbon can then potentially increase its degree of graphitisation. Increasing amounts of pharmaceuticals enter the water bodies and are detected all over the world 1-3. Many of them are persistent and may accumulate within water cycles 4-6. These organic micropollutants already show adverse effects in aquatic ecosystems despite their comparably low concentrations 7-9. Therefore, technical measures are introduced as advanced wastewater treatment 10. One of the favoured techniques is the removal by adsorption onto activated carbon 11,12. Activated carbon has been used in water purification for more than hundred years. In modern times, we face more ecological and economical challenges that require the accurate prediction of removal efficiencies prior to the upgrade of wastewater treatment plants. Hence, several approaches have been applied to gain fast and efficient predictions through laboratory experiments and the optimization of operating parameters through data driven modeling 13-16. The removal of the target substances has been shown to be strongly influenced by the composition of the waters and that of the activated carbons used in the removal 17,18. The underlying adsorption processes have been extensively described in theory and investigated experimentally 19,20. However, adsorption in the liquid phase has been proven to be much more complicated than adsorption in gas phases, especially in complex water matrices that are governed by the presence of dissolved organic matter, the ionic strength and the pH value 21-23. Hence, both the adsorbate solution and the adsorbent, are mutually influenced. Moreover, activated carbon has a highly heterogeneous pore stru...

We develop a method to detect the diabetes drug metformin in water samples.

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