Filtern
Dokumenttyp
- Zeitschriftenartikel (10)
Sprache
- Englisch (10)
Referierte Publikation
- ja (10) (entfernen)
Schlagworte
- Microplastics (10) (entfernen)
Organisationseinheit der BAM
Paper des Monats
- ja (2)
Inputs of plastic impurities into the environment via the application of fertilizers are regulated in Germany and the EU by means of ordinances. Robust and fast analytical methods are the basis of legal regulations. Currently, only macro- and large microplastic contents (>1 mm) are measured. Microplastics (1–1,000 µm), are not yet monitored. Thermal analytical methods are suitable for this purpose, which can determine the mass content and can also be operated fully automatically in routine mode. Thermal extraction desorption-gas chromatography/mass spectrometry (TED-GC/MS) allows the identification of polymers and the determination of mass contents in solid samples from natural environments. In accordance with the German or European Commission (EC) Fertiliser Ordinance, composting plants should be monitored for microplastic particles with this method in the future. In this context a compost plant was sampled. At the end of the rotting process, the compost was sieved and separated in a coarse (>1 mm) and a fine fraction (<1 mm). The fine fraction was processed using density separation comparing NaCl and NaI as possible salt alternative and screened for microplastic masses by TED-GC/MS with additional validation and quality assurance experiments. With TED-GC/MS total microplastics mass contents of 1.1–3.0 μg/mg in finished compost could be detected with polyethylene mainly. What differs much to the total mass of plastics in the coarse fraction with up to 60 μg/mg, which were visually searched, identified via ATR-FTIR and gravimetrically weighted.
Avoiding aerial microfibre contamination of environmental samples is essential for reliable analyses when it comes to the detection of ubiquitous microplastics. Almost all laboratories have contamination problems which are largely unavoidable without investments in clean-air devices. Therefore, our study supplies an approach to assess background microfibre contamination of samples in the laboratory under particle-free air conditions. We tested aerial contamination of samples indoor, in a mobile laboratory, within a laboratory fume hood and on a clean bench with particles filtration during the examining process of a fish. The used clean bench reduced aerial microfibre contamination in our laboratory by 96.5%. This highlights the value of suitable clean-air devices for valid microplastic pollution data. Our results indicate, that pollution levels by microfibres have been overestimated and actual pollution levels may be many times lower. Accordingly, such clean-air devices are recommended for microplastic laboratory applications in future research work to significantly lower error rate
Exploratory analysis of hyperspectral FTIR data obtained from environmental microplastics samples
(2020)
Hyperspectral imaging of environmental samples with infrared microscopes is one of the preferred methods to find and characterize microplastics. Particles can be quantified in terms of number, size and size distribution. Their shape can be studied and the substances can be identified. Interpretation of the collected spectra is a typical problem encountered during the analysis. The image datasets are large and contain spectra of countless particles of natural and synthetic origin. To supplement existing Analysis pipelines, exploratory multivariate data analysis was tested on two independent datasets. Dimensionality reduction with principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) was used as a core concept. It allowed for improved visual accessibility of the data and created a chemical two-dimensional image of the sample. Spectra belonging to particles could be separated from blank spectra, reducing the amount of data significantly. Selected spectra were further studied, also applying PCA and UMAP. Groups of similar spectra were identified by cluster analysis using k-means, density based, and interactive manual clustering. Most clusters could be assigned to chemical species based on reference spectra. While the results support findings obtained with a ‘targeted analysis’ based on automated library search, exploratory analysis points the attention towards the group of unidientified spectra that remained and are otherwise easily overlooked.
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.
In this study, a method for the determination of tire and road wear particle (TRWP) contents in particulate samples from road Environment was developed. Zn was identified as the most suitable elemental marker for TRWP, due to its high concentration in tire tread and the possibility of separation from other Zn sources. The mean concentration of 21 tire samples was 8.7 ± 2.0 mg Zn/g. Before quantification in samples from road environment, TRWP were separated from the particulate matrix by density separation. Method development was conducted using shredded tread particles (TP) as a surrogate for TRWP.
Recovery of TP from spiked sediment was 95 ± 17% in a concentration range of 2 - 200 mg TP/g. TP determination was not affected by other Zn containing solids or spiked Zn-salts. By adjusting the density of the separation solution to 1.9 g/cm3, more than 90% of total TRWP were separated from the sample matrix. TRWP concentrations in particulate matter collected in two road runoff treatment Systems ranged from 0.38 to 150 mg TRWP/g. Differences in quantified TRWP contents of the two Systems indicate changes in particle dynamics due to ageing and aggregation processes. The developed method allows TRWP determination in road runoff and in environments that are influenced by road traffic. The validated separation procedure can also be applied for TRWP characterization in future studies.
In recent years, an increasing trend towards investigating and monitoring the contamination of the environment by microplastics (MP) (plastic pieces < 5 mm) has been observed worldwide. Nonetheless, a reliable methodology that would facilitate and automate the monitoring of MP is still lacking. With the goal of selecting practical and standardized methods, and considering the challenges in microplastics detection, we present here a critical evaluation of two vibrational spectroscopies, Raman and Fourier transform infrared (FTIR) spectroscopy, and two extraction methods: thermal extraction desorption gas chromatography mass spectrometry (TED-GC-MS) and liquid extraction with subsequent size exclusion chromatography (SEC) using a soil with known contents of PE, PP, PS and PET as reference material. The obtained results were compared in terms of measurement time, technique handling, detection limits and requirements for sample preparation. The results showed that in designing and selecting the right methodology, the scientific question that determines what needs to be understood is significant, and should be considered carefully prior to analysis. Depending on whether the object of interest is quantification of the MP particles in the sample, or merely a quick estimate of sample contamination with plastics, the appropriate method must be selected. To obtain overall information about MP in environmental samples, the combination of several parallel approaches should be considered.
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.
In order to determine the relevance of microplastic particles in various environmental media, comprehensive investigations are needed. However, no analytical method exists for fast identification and quantification. At present, optical spectroscopy methods like IR and RAMAN imaging are used. Due to their time consuming procedures and uncertain extrapolation, reliable monitoring is difficult. For analyzing polymers Py-GC-MS is a standard method. However, due to a limited sample amount of about 0.5 mg it is not suited for analysis of complex sample mixtures like environmental samples. Therefore, we developed a new thermoanalytical method as a first step for identifying microplastics in environmental samples. A sample amount of about 20 mg, which assures the homogeneity of the sample, is subjected to complete thermal decomposition. The specific degradation products of the respective polymer are adsorbed on a solid-Phase adsorber and subsequently analyzed by thermal Desorption gas chromatography mass spectrometry. For certain identification, the specific degradation products for the respective polymer were selected first. Afterwards real environmental samples from the aquatic (three different rivers) and the terrestrial (bio gas plant) systems were screened for microplastics. Mainly polypropylene (PP), polyethylene (PE) and polystyrene (PS) were identified for the samples from the bio gas plant and PE and PS from the rivers. However, this was only the first step and quantification measurements will follow.
A harmonization of sampling, sample preparation and detection is pivotal in order to obtain comparable data on microplastics (MP) in the environment. This paper develops and proposes a suitable sampling concept for waterbodies that considers different plastic specific properties and influencing factors in the environment.
Both artificial water including defined MP fractions and the discharge of a wastewater treatment plant were used to verify the derived sampling procedure, sample preparation and the subsequent analysis of MP using thermal extraction-desorption gas chromatography - mass spectrometry (TED-GC-MS).
A major finding of this paper is that an application of various particle size classes greatly improves the practical handling of the sampling equipment. Size classes also enable the TED-GC-MS to provide any data on the MP size distribution, a substantial sampling property affecting both the necessary sampling volume and the optimal sampling depth.
In the artificial water with defined MP fractions, the recovery rates ranged from 80 to 110%, depending on the different MP types and MP size classes. In the treated wastewater, we found both Polyethylene and polystyrene in different size classes and quantities.
A sedimented freshwater suspended organic matter fortified with particles of polyethylene (PE), polypropylene (PP), polystyrene (PS), and polyethylene terephthalate (PET) was employed in an interlaboratory comparison of thermoanalytical methods for microplastics identification and quantification. Three laboratories performed pyrolysis gas chromatography-mass spectrometry (Py-GC-MS), three others provided results using thermal extraction desorption followed by gas chromatography coupled to mass spectrometry (TED-GC-MS). One participant performed thermogravimetry-infrared spectroscopy (TGA-FTIR) and two participants used thermogravimetry coupled to mass spectrometry (TGA-MS). Further participants used differential scanning microscopy (DSC), a procedure based on micro combustion calorimetry (MCC) and a procedure based on elemental analysis.
Each participant employed a different combination of sample treatment, calibration and instrumental Settings for polymer identification and quantification. Though there is obviously room for improvements regarding the between-laboratory reproducibility and the harmonization of procedures it was seen that the participants Performing Py-GC-MS, TED-GC-MS, and TGA-FTIR were able to correctly identify all polymers and to report reasonable quantification results in the investigated concentration range (PE: 20.0 μg/mg, PP: 5.70 μg/mg; PS: 2.20 μg/mg, PET: 18.0 μg/mg). Although for the other methods limitations exists regarding the detection of specific polymers, they showed potential as alternative approaches for polymer quantification in solid environmental matrices.