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The interaction of microcroplastics (MP) with dissolved organic matter, especially humic substances, is of great importance in understanding the behavior of microplastics in aquatic ecosystems. Surface modification by humic substances plays an essential role in transport and interaction of MP with abiotic and biotic components. Previous studies on the interaction between MP and humic substances were largely based on a model compound, humic acid (Sigma-Aldrich). In our work, we therefore investigated the interaction of natural organic matter (NOM) sampled from a German surface water with low-density polyethylene particles (LDPE). Highpressure size exclusion chromatography (HPSEC) and UV/vis absorption and fluorescence spectroscopy were used to characterize the incubation solutions after modifications due to the presence of LDPE, and Raman spectroscopy was used to characterize the incubated microplastics. While the studies of the solutions generally showed only very small effects, Raman spectroscopic studies allowed clear evidence of the binding of humic fractions to MP. The comparison of the incubation of NOM and a lignite fulvic acid which also was tested further showed that specific signatures of the humic substances used could be detected by Raman spectroscopy. This provides an elegant opportunity to conduct broader studies on this issue in the future.
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.
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.
A process spectroscopic approach for the monitoring of microplastics in environmental samples
(2018)
The potential of Raman and NIR process-spectroscopic as a rapid approach for the estimation of microplastics (MP) in soil matrix were tested. For this purpose, artificial MP/soil mixture samples consisting of standard soils or sand with defined ratios of MP (0,5 – 10 mass% polymer) from polyethylene (PE), polypropylene (PP), polystyrene (PS) and polyethylene terephthalate (PET) were prepared. MP particles with diameters < 2 mm and < 125 µm were obtained from industrial polymer pellets after cryo-milling. Spectra of these mixtures were collected by (i) a process FT-NIR spectrometer equipped with a reflection probe, (ii) by a cw-process Raman spectrometer and (iii) by a time-gated Raman spectrometer using fiber-optic probes. The evaluation of process-spectra was performed by chemometric methods. Whereas MP could be detected by Raman spectroscopy in coastal sand at 0.5 mass%, in standard soil detection of MP was limited to 10 – 5 mass% with the large fraction, but samples containing particles of the 125µm mass-fraction yielded no positive result at all. One reason for the lacking sensitivity could be fluorescence by soil organic matter and thus, in a next test time-gated Raman spectroscopy was applied. However, although being indeed more sensitive to the small particles this method failed at MP < 5 mass% indicating that fluorescence was not the major problem. Finally, FT-NIR was tested. Depending on the polymer, MP contents of 0,5 or 1 mass%, respectively, could be detected in standard soils and polymers identified. Furthermore, this approach could be used for the investigation of mixtures of up to four polymers and in real-world samples from bio-waste fermenter residues.
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.