TY - JOUR A1 - Altmann, Korinna A1 - Goedecke, Caroline A1 - Bannick, C.-G. A1 - Abusafia, A. A1 - Scheid, C. A1 - Steinmetz, H. A1 - Paul, Andrea A1 - Beleites, C. A1 - Braun, U. T1 - Identification of microplastic pathways within a typical European urban wastewater system JF - Applied Research N2 - In recent years, thermoextraction/desorption-gas chromatography/mass spectrometry (TED-GC/MS) has been developed as a rapid detection method for the determination of microplastics (MP) mass contents in numerous environmentally relevant matrices and, in particular, for the measurement of polymers in water samples without time-consuming sample preparation. The TED-GC/MS method was applied to investigate a typical European municipal wastewater system for possible MP masses. Such investigations are important in view of the recent revision of the Urban Wastewater Treatment Directive. Four different representative sampling sites were selected: greywater (domestic wastewater without toilet), combined sewer, and influent and effluent of a wastewater treatment plant (WWTP). All samples were collected by fractional filtration. Filtration was carried out over mesh sizes of 500, 100, 50, and in some cases, 5 µm. Polyethylene (PE), polypropylene (PP), and polystyrene (PS) were detected in all samples, with the PE fraction dominating in all cases. Styrene-butadiene rubber which serves as an indication of tire abrasion, was only found in the influent of the WWTP. The highest MP mass contents were found in the combined sewer, so MP can become a source of pollution during heavy rain events when the capacity limits of the effluent are reached, and the polluted effluent is released uncontrolled into the environment. Based on the studies, MP retention from the WWTP could be estimated to be approximately 96%. Few trends in polymer type or mass contents were detected within the different fractions of the samples or when comparing samples to each other. KW - Microplastics KW - Microplastic analysis KW - TED-GC/MS KW - Microplastic pathways KW - Mass contents PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-568289 DO - https://doi.org/doi.org/10.1002/appl.202200078 SP - 1 EP - 10 PB - Wiley-VCH CY - Weinheim AN - OPUS4-56828 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Haferkamp, Sebastian A1 - Paul, Andrea A1 - Michalchuk, Adam A1 - Emmerling, Franziska T1 - Unexpected polymorphism during a catalyzed mechanochemical Knoevenagel condensation JF - Beilstein Journal of Organic Chemistry N2 - The transformation of a base-catalyzed, mechano-assisted Knoevenagel condensation of mono-fluorinated benzaldehyde derivatives (p-, m-, o-benzaldehyde) with malonodinitrile was investigated in situ and in real time. Upon milling, the para-substituted product was found to crystallize initially into two different polymorphic forms, depending on the quantity of catalyst used. For low catalyst concentrations, a mechanically metastable phase (monoclinic) was initially formed, converting to the mechanically stable phase (triclinic) upon further grinding. Instead, higher catalyst concentrations crystallize directly as the triclinic product. Inclusion of catalyst in the final product, as evidenced by mass spectrometric analysis, suggests this complex polymorphic pathway may be due to seeding effects. Multivariate analysis for the in situ Raman spectra supports this complex formation pathway, and offers a new approach to monitoring multi-phase reactions during ball milling. KW - Ball milling KW - C-C coupling KW - In situ KW - Mechanochemistry KW - Multivariate data analysis PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-481872 DO - https://doi.org/10.3762/bjoc.15.110 SN - 1860-5397 VL - 15 SP - 1141 EP - 1148 PB - Beilstein Insitut CY - Frankfurt am Main AN - OPUS4-48187 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Paul, Andrea A1 - Wander, Lukas A1 - Braun, Ulrike T1 - Multivariate approaches in the evaluation of (hyper)spectral data for microplastics analysis - options and limitations N2 - Die zunehmende Anreicherung von Gewässern und Böden mit Plastikmüll führt zur Anhäufung von mikroskopisch kleinen Plastikpartikeln, sogenannter Mikroplastik (MP). Es werden dringend analytische Methoden benötigt, die helfen MP zu identifizieren und zu quantifizieren. Gegenwärtig kommen dafür hauptsächlich thermoanalytische und mikro¬skopische Verfahren, wie Mikro-Infrarotspektroskopie oder Mikro-Raman zum Einsatz. Letztere sind in der Regel an zeitaufwendige Probenanreicherungen und -aufbereitungen gebunden, es können nur kleine Probenmengen (Mikrogramm) untersucht werden und die Auswertung der erzielten Spektren kann anspruchsvoll sein. Im Rahmen dieser Präsentation werden zwei Ansätze vorgestellt, die über die multi-variate Analyse spektroskopischer Daten i) einen neuen methodischen Ansatz zum Screening von MP in belasteten Böden sowie ii) eine alternative Auswertung großer (Mikro)-spektroskopischer Datensätze ermöglichen. Zunächst wird ein NIR-spektroskopisches Verfahrens vorgestellt, das es gestattet MP bestehend aus Polyethylen, Polyethylenterephthalat, Polypropylen und Polystyrol im Bereich bis zu 0,5 Massenprozent zu detektieren. Aufgrund kurzer Messzeiten und robuster Technik besitzt dieser Ansatz das Potenzial, im Gegensatz zu den thermoanalytischen und mikrospektroskopischen Methoden, größere Probenmengen mit minimaler Vor¬behandlung zu untersuchen. Der zweite Ansatz befasst sich mit der Auswertung großen Datensätze, wie sie typischerweise als Resultat der Mikro-FTIR unter Nutzung moderner FPA-Detektoren erhalten werden. Die Mikro-FTIR-Technik beruht auf der spektralen Aufnahme, Abbildung und an¬schließenden Identifizierung von Schwingungsbanden, die für synthetische Polymere typisch sind. Die Bilddatensätze sind groß und enthalten Spektren von unzähligen Partikeln natürlichen und synthetischen Ursprungs. Zur Ergänzung bestehender Ansätze, die z.B. auf Recherchen von Spektren¬bibliotheken basieren, wurde die explorative multivariate Datenanalyse getestet. Als Kernkonzept wurde hierbei die Dimensionalitäts¬reduktion verwendet. Die Ergebnisse stellen nicht nur eine orthogonale Methode zur Kontrolle der Ergebnisse dar, die auf Grundlage einer automatisierten Bibliothekssuche erzielt wurden, sondern ergaben darüber hinaus eine Gruppe von Spektren, die nicht in den vorhandenen Spektrenbibliotheken erfasst wurden. N2 - The increasing enrichment of water bodies and soils with plastic waste leads to the accumulation of microscopic plastic particles, so-called microplastics (MP). There is an urgent need for analytical methods that help to identify and quantify MP. At present, mainly thermo-analytical and microscopic methods such as micro-infrared spectroscopy or micro-Raman are used for this purpose. The latter are usually tied to time-consuming sample enrichment and preparation, only small sample quantities (micrograms) can be examined and the evaluation of the obtained spectra can be demanding. In the context of this presentation, two approaches are presented which, via the multi-variate analysis of spectroscopic data, allow i) a new methodological approach to screening MP in contaminated soils and ii) an alternative evaluation of large (micro)-spectroscopic data sets. First, a NIR spectroscopic method is presented which allows MP consisting of polyethylene, polyethylene terephthalate, polypropylene and polystyrene to be detected in the range of up to 0.5 mass percent. Due to short measurement times and robust technology, this approach has the potential, in contrast to thermo-analytical and micro-spectroscopic methods, to examine larger sample quantities with minimal pre-treatment. The second approach deals with the evaluation of large data sets, as typically obtained as a result of micro-FTIR using modern FPA detectors. The micro-FTIR technique is based on the spectral recording, imaging and subsequent identification of vibration bands typical of synthetic polymers. The image data sets are large and contain spectra of numerous particles of natural and synthetic origin. Exploratory multivariate data analysis has been tested to complement existing approaches based on e.g. spectrum library searches. The core concept used was dimensionality reduction. The results not only represent an orthogonal method for checking the results obtained by an automated library search, but also revealed a group of spectra that were not recorded in the existing spectrum libraries. T2 - analytica conference 2020 CY - Online meeting DA - 19.10.2020 KW - Microplastics KW - Multivariate Datenanalyse KW - NIR KW - Hyperspectral data PY - 2020 AN - OPUS4-51516 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Wander, Lukas A1 - Vianello, A. A1 - Vollertsen, J. A1 - Westad, F. A1 - Braun, Ulrike A1 - Paul, Andrea T1 - Exploratory analysis of hyperspectral FTIR data obtained from environmental microplastics samples JF - Analytical Methods N2 - 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. KW - Microplastics KW - FTIR KW - Exploratory analysis PY - 2020 DO - https://doi.org/10.1039/c9ay02483b VL - 12 IS - 6 SP - 781 EP - 791 PB - Royal Society of Chemistry AN - OPUS4-50396 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -