TY - CONF A1 - Bauer, J. A1 - Miclea, P.-T. A1 - Braun, U. A1 - Altmann, Korinna A1 - Turek, M. A1 - Hagendorf, C. T1 - Microplastic detection and analysis in water samples T2 - Sustainable Energy-Water-Environment Nexus in Deserts N2 - 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. T2 - International Conference on Sustainable Energy-Water-Environment Nexus in Desert Climate 2019 CY - Ar-Rayyan, Qatar DA - 02.12.2019 KW - Microplastics KW - Water samples PY - 2022 SP - 111 EP - 113 PB - Springer AN - OPUS4-56240 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hagendorf, C. A1 - Richter, S. A1 - Krause, S. A1 - Bauer, J. A1 - Miclea, P.-T. A1 - Braun, Ulrike A1 - Altmann, Korinna A1 - Turek, M. T1 - Microplastic detection and analysis in water with silicon filter systems N2 - The use of optimized silicon filter systems is presented for the microplastic detection. T2 - International Conference on Sustainable Energy-Water-enviroment Nexus in Desert Climate CY - Doha, Qatar DA - 02.12.2019 KW - Filters KW - Microplastics KW - TED-GC-MS KW - Harmonisation PY - 2019 AN - OPUS4-50006 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Richter, S. A1 - Horstmann, J. A1 - Altmann, Korinna A1 - Braun, U. A1 - Hagendorf, C. T1 - A reference methodology for microplastic particle size distribution analysis: Sampling, filtration, and detection by optical microscopy and image processing JF - Applied research N2 - Microplastic (MP) contamination in natural water circulation is a concern for environmental issues and human health. Various types of polymer materials have been identified and were detected in MP analytic test procedures. Beyond MP polymer type, particle size and form play a major role in water analysis due to possible negative toxicologic effects on flora and fauna. However, the correct quantitative measurement of MP size distribution over several orders of magnitude is strongly influenced by sample preparation, filtration materials and processes, and microanalytical techniques, as well as data acquisition and analysis. In this paper, a reference methodology is presented aiming at an improved quantitative analysis of MP particles. An MP analysis workflow is demonstrated including all steps from reference materials to sample preparation, filtration handling, and MP particle size distribution analysis. Background-corrected particle size distributions (1–1000 µm) have been determined for defined polyethylene (PE) and polyethylene terephthalate (PET) reference samples. Microscopically measured particle numbers and errors have been cross-checked with the total initial mass. In particular, defined reference MP samples (PE, PET) are initially characterized and applied to filtration experiments. Optical microscopy imaging on full-area Si filters with subsequent image analysis algorithms is used for statistical particle size distribution analysis. To quantify the effects of handling and filtration, several blind tests with distilled water are carried out to determine the particle background for data evaluation. Particle size distributions of PE and PET reference samples are qualitatively and quantitatively reproduced with respect to symmetry, and maximum and cut-off diameter of the distribution. It is shown that especially MP particles with a radius of >50 µm can be detected and retrieved with high reliability. For particle sizes <50 µm, a significant interference with background contamination is observed. Data from blank samples allows a correction of background contaminations. Furthermore, for enhanced sampling statistics, the recovery of the initial amount of MP will be qualitatively shown. The results are intended as an initial benchmark for MP analytics quality. This quality is based on statistical MP particle distributions and covers the complete analytic workflow starting from sample preparation to filtration and detection. Microscopic particle analysis provides an important supplement for the evaluation of established spectroscopic methods such as Fourier-transform infrared spectroscopy or Raman spectroscopy. KW - Drinking water KW - Filtration KW - Microplastics detection KW - Quality control KW - Statistical particle distribution PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-567625 DO - https://doi.org/10.1002/appl.202200055 SN - 2702-4288 SP - 1 EP - 10 PB - Wiley-VCH CY - Weinheim AN - OPUS4-56762 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -