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Near-infrared (NIR) spectroscopy is a promising candidate for low-cost, nondestructive, and high-throughput mass quantification of micro¬plastics in environmental samples. Widespread application of the technique is currently hampered mainly by the low sensitivity of NIR spectroscopy compared to thermo-analytical approaches commonly used for this type of analysis. This study shows how the application of NIR spectroscopy for mass quantification of microplastics can be extended to smaller analyte levels by combining it with a simple and rapid microplastic enrichment protocol. For this purpose, the widely used flotation of microplastics in a NaCl solution, accelerated by centrifugation, was chosen which allowed to remove up to 99 % of the matrix at recovery rates of 83–104 %. The spectroscopic measurements took place directly on the stainless-steel filters used to collect the extracted particles to reduce sample handling to a minimum. Partial least squares regression (PLSR) models were used to identify and quantify the extracted microplastics in the mass range of 1–10 mg. The simple and fast extraction procedure was systematically optimized to meet the requirements for the quantification of microplastics from common PE-, PP-, and PS-based packaging materials with a particle size < 1 mm found in compost or soils with high natural organic matter content (> 10 % determined by loss on ignition). Microplastics could be detected in model samples at a mass fraction of 1 mg g-1. The detectable microplastic mass fraction is about an order of magnitude lower compared to previous studies using NIR spectroscopy without additional enrichment. To emphasize the cost-effectiveness of the method, it was implemented using some of the cheapest and most compact NIR spectrometers available.
Microplastic particles are currently detected in almost all environmental compartments. The results of detection vary widely, as a multitude of very different methods are used with very different requirements for analytical validity.
In this work four thermoanalytical methods are compared and their advantages and limitations are discussed. One of them is thermal extraction-desorption gas chromatography mass spectrometry (TED-GC/MS), an analysis method for microplastic detection that has become established in recent years. In addition, thermogravimetric analysis coupled with Fourier-transform infrared spectroscopy (TGA-FTIR) and mass spectrometry (TGA-MS) were applied, two methods that are less common in this field but are still used in other research areas. Finally, microscale combustion calorimeter (MCC) was applied, a method not yet used for microplastic detection.
The presented results are taken from a recently published interlaboratory comparison test by Becker et al. (2020). Here a reference material consisting of suspended matter and specified added polymer masses was examined, and only the results of the recoveries were presented. In the present paper, however, the results for the individual polymers are discussed in detail and individual perspectives for all instruments are shown.
It was found that TED-GC/MS is the most suitable method for samples with unknown matrix and unknown, variable kinds and contents of microplastic. TGA-FTIR is a robust method for samples with known matrix and with defined kinds of microplastic. TGA-MS may offer a solution for the detection of PVC particles in the future. MCC can be used as a very fast and simple screening method for the identification of a potential microplastic load of standard polymers in unknown samples.
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.
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.
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 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.
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.
Microplastics are increasingly entering marine, limnic and terrestrial ecosystems worldwide, where they sorb hydrophobic organic contaminants. Here, the sorption behavior of the fuel-related water contaminants benzene, toluene, ethyl benzene and xylene (BTEX) and four tertiary butyl ethers to virgin and via UV radiation aged polypropylene (PP) and polystyrene (PS) pellets was investigated. Changes in material properties due to aging were recorded using appropriate polymer characterization methods, such as differential scanning calorimetry, Fourier transform infrared spectroscopy, gel permeation chromatography, X-ray photoelectron spectroscopy, and microscopy.
Pellets were exposed to water containing BTEX and the ethers at 130-190 mg/L for up to two weeks.
Aqueous sorbate concentrations were determined by headspace gas chromatography. Sorption to the polymers was correlated with the sorbate's Kow and was significant for BTEX and marginal for the ethers.
Due to substantially lower glass transition temperatures, PP showed higher sorption than PS. Aging had no effect on the sorption behavior of PP. PS sorbed less BTEX after aging due to an oxidized surface layer.
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.
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
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.
Monitoring the ingestion of microplastics is challenging and suitable detection techniques are insufficiently used. Thus, misidentifying natural for synthetic microfibres cannot be avoided. As part of a framework to monitor the ingestion of microplastics in eelpout, this short report addresses the accurate identification of microfibres. We show that, following visual inspections, putatively synthetic microfibres are indeed of natural origin, as ascertained by spectrometric analyses. Consequently, we call for an inclusion of spectroscopic techniques in standardized microplastic monitoring schemes.