Analytische Chemie
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Im Vorhaben „MARKERIA - Bestimmung von anthropogenen Markerkonzentrationen für die SARS-CoV-2 Quantifizierung mittels eines Hochdurchsatzverfahrens (ELISA)“ geht es um die Bestimmung von Carbamazepin, Diclofenac, Koffein und einer endogenen Gallensäure als potentielle Marker für die Kalibrierung der SARS-CoV-2 Quantifizierung im Abwasser. Es ist ein Teilvorhaben des übergeordneten Projektes ESI-CorA und wird von der BAM im Auftrag des Umweltbundesamtes durchgeführt. Der Vortrag wurde gehalten im Rahmen der Abschlussveranstaltung des Projektes ESI-CorA. Er gab den Projektstand wieder, den UBA und BAM bis dahin erzielt hatten, das SARS-CoV-2 Virus und die anthropogenen Marker in 20 Kläranlagenzuläufen zu bestimmen und miteinander zu korrelieren.
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.
In this study, the thermal decomposition of 1,3,5-tris-(2,3-dibromopropyl)-1,3,5-triazine-2,4,6-trione (TDBPTAZTO) and 2,4,6-tris-(2,4,6-tribromo-phenoxy)-1,3,5-triazine (TTBP-TAZ) were investigated for the first time by thermogravimetric analysis. Both compounds were thermal degraded between 225 and 350 °C (TDBP-TAZTO) as well as 300 and 400 °C (TTBP-TAZ).
As a result, mass loss (%) of 98.5% for TTBP-TAZ and 95.4% for TDBP-TAZTO at 600 °C under N2 were observed. The major pyrolytic degradation products of TTBP-TAZ were formed in a single step and identified by FTIR analysis as 2,4,6-tribromophenol and further bromine-substituted aromatic compounds. In comparison, TDBP-TAZTO was pyrolytic degraded in two steps, whereby on the first step the release of hydrogen Bromide and 1,3,5-triallyl-1,3,5-triazine-2,4,6-trione could be detected. In the second minor step, isocyanic acid could be additionally identified.
Subsequently, the obtained products of the TGA-FTIR measurements were used for a targeted search for mass fragments in mass spectrometry measurements. For TTBP-TAZ, only the degradation product 1,3,5-tribromobenzene could be detected by MS/MS analyzes. No comparable thermal degradation products, except hydrogen bromide, were observed in the MS/MS spectra of TDBP-TAZTO. Therefore, the search of further mass fragments was not possible compared to the findings of the TGA-FTIR measurements.
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.
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.
Near-infrared (NIR) spectroscopy is a promising candidate for low-cost, nondestructive, and highthroughput mass quantification of microplastics in environmental samples. Widespread application of the technique is currently hampered mainly by the low sensitivity of NIR spectroscopy compared to thermoanalytical 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.