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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.
Despite the increasing concern about the harmful effects of micro- and
nanoplastics (MNPs), there are no harmonized guidelines or protocols yet available for MNP ecotoxicity testing. Current ecotoxicity studies often use commercial spherical particles as models for MNPs, but in nature, MNPs occur in variable shapes, sizes and chemical compositions. Moreover, protocols developed for chemicals that dissolve or form stable dispersions are currently used for assessing the ecotoxicity of MNPs. Plastic particles, however, do not dissolve and also show dynamic behavior in the exposure medium, depending on, for example, MNP physicochemical properties and the medium’s conditions such as pH and ionic strength. Here we describe an exposure protocol that considers the particle-specific properties of MNPs and their dynamic behavior in exposure systems. Procedure 1 describes the top-down production of more realistic MNPs as representative of MNPs in nature and particle characterization (e.g., using thermal extraction desorption-gas chromatography/mass spectrometry). Then, we describe exposure system development for short- and long-term toxicity tests for soil (Procedure 2) and aquatic (Procedure 3) organisms. Procedures 2 and 3 explain how to modify existing ecotoxicity guidelines for chemicals to target testing MNPs in selected exposure systems. We show some examples that were used to develop the protocol to test, for example, MNP toxicity in marine rotifers, freshwater mussels, daphnids and earthworms. The present protocol takes between 24 h and 2 months, depending on the test of interest and can be applied by students, academics, environmental risk assessors and industries.
Microplastics are small plastic fragments that are widely distributed in marine and terrestrial environments. While the soil ecosystem represents a large reservoir for plastic, research so far has focused mainly on the impact on aquatic ecosystems and there is a lack of information on the potentially adverse effects of microplastics on soil biota. Earthworms are key organisms of the soil ecosystem and are due to their crucial role in soil quality and fertility a suitable and popular model organism in soil ecotoxicology.
Therefore, the aim of this study was to gain insight into the effects of environmentally relevant concentrations of microplastics on the earthworm Eisenia andrei on multiple levels of biological organization after different exposure periods. Earthworms were exposed to two types of microplastics: (1) polystyrene-HBCD and (2) car tire abrasion in natural soil for 2, 7, 14 and 28 d. Acute and chronic toxicity and all subcellular investigations were conducted for all exposure times, avoidance behavior assessed after 48 h and reproduction after 28 d. Subcellular endpoints included enzymatic biomarker responses, namely, carboxylesterase, glutathione peroxidase, acetylcholinesterase, glutathione reductase, glutathione S-transferase and catalase activities, as well as fluorescence-based measurements of oxidative stress-related markers and multixenobiotic resistance activity. Multiple biomarkers showed significant changes in activity, but a recovery of most enzymatic activities could be observed after 28 d. Overall, only minor effects could be observed on a subcellular level, showing that in this exposure scenario with environmentally relevant concentrations based on German pollution levels the threat to soil biota is minimal. However, in areas with higher concentrations of microplastics in the environment, these results can be interpreted as an early warning signal for more adverse effects. In conclusion, these findings provide new insights regarding the ecotoxicological effects of environmentally relevant concentrations of microplastics on soil organisms.
The TED-GC-MS analysis is a two-step method. A sample is first decomposed in a thermogravimetric analyzer (TGA) and the gaseous decomposition products are then trapped on a solid-phase adsorber. Subsequently, the solid-phase adsorber is analyzed with thermal desorption gas chromatography mass spectrometry (TDU-GC-MS). This method is ideally suited for the analysis of polymers and their degradation processes. Here, a new entirely automated System is introduced which enables high sample throughput and reproducible automated fractioned collection of decomposition products. Strengths and limitations of the system configuration are elaborated via three examples focused on practical challenges in materials analysis and identification: i) separate analysis of the components of a wood-plastic-composite material, ii) quantitative determination of weight concentration of the constituents of a polymer blend and iii) quantitative analysis of model samples of microplastics in suspended particulate matter.
There is only sparse empirical data on the settling velocity of small, non-buoyant microplastics thus far, although it is an important parameter governing their vertical transport within aquatic environments. This study reports the settling velocities of 4031 exemplary microplastic particles. Focusing on the environmentally most prevalent particle shapes, irregular microplastic fragments of four different polymer types (9–289 µm) as well as five discrete length fractions (50–600 µm) of common nylon and polyester fibers were investigated, respectively. All settling experiments were carried out in quiescent water using a specialized optical imaging setup. The method has been previously validated in order to minimize disruptive factors, e.g. thermal convection or particle interactions, and thus enable the precise measurements of the velocities of individual microplastic particles (0.003–9.094 mm/s). Based on the obtained data, ten existing models for predicting a particle’s terminal settling velocity were assessed. It is concluded that models, which were specifically deduced from empirical data on larger microplastics, fail to provide accurate predictions for small microplastics. Instead, a different approach is highlighted as a viable option for computing settling velocities across the microplastics continuum in terms of size, density and shape.
Microplastic detection in water samples becomes important for tracing microplastic sources. Microplastic may harm desalination facilities by blocking filters and disturbing the marine food chain. Thermo analytical methods such as pyrolysis gas chromatography mass spectroscopy, and spectroscopic methods like (micro) Raman spectroscopy or (micro) Fouriertransform infrared spectroscopy in combination with appropriate filters and sample preparation are suitable for analyzing microplastics on a scale from 1 µm to 1000 µm fast and unambiguous. While the thermo analytical methods are suitable for larger sample volumes, Raman spectroscopy and Fouriertransform infrared spectroscopy are able to detect and analyze single microplastic particles for instance in bottled water. Machine learning algorithms ensure a reliable classification of different plastic materials.