Are We Speaking the Same Language? Recommendations for a Definition and Categorization Framework for Plastic Debris

Embargo until 04 Jan 2020The accumulation of plastic litter in natural environments is a global issue. Concerns over potential negative impacts on the economy, wildlife, and human health provide strong incentives for improving the sustainable use of plastics. Despite the many voices raised on the issue, we lack a consensus on how to define and categorize plastic debris. This is evident for microplastics, where inconsistent size classes are used and where the materials to be included are under debate. While this is inherent in an emerging research field, an ambiguous terminology results in confusion and miscommunication that may compromise progress in research and mitigation measures. Therefore, we need to be explicit on what exactly we consider plastic debris. Thus, we critically discuss the advantages and disadvantages of a unified terminology, propose a definition and categorization framework, and highlight areas of uncertainty. Going beyond size classes, our framework includes physicochemical properties (polymer composition, solid state, solubility) as defining criteria and size, shape, color, and origin as classifiers for categorization. Acknowledging the rapid evolution of our knowledge on plastic pollution, our framework will promote consensus building within the scientific and regulatory community based on a solid scientific foundation.acceptedVersio

Identification and characterization of individual airborne volcanic ash particles by Raman microspectroscopy

We present for the first time the Raman microspectroscopic identification and characterization of individual airborne volcanic ash (VA) particles. The particles were collected in April/May 2010 during research aircraft flights, which were performed by Deutsches Zentrum für Luft- und Raumfahrt in the airspace near the Eyjafjallajökull volcano eruption and over Europe (between Iceland and Southern Germany). In addition, aerosol particles were sampled by an Electrical Low Pressure Impactor in Munich, Germany. As references for the Raman analysis, we used the spectra of VA collected at the ground near the place of eruption, of mineral basaltic rock, and of different minerals from a database. We found significant differences in the spectra of VA and other aerosol particles (e.g., soot, nitrates, sulfates, and clay minerals), which allowed us to identify VA among other atmospheric particulate matter. Furthermore, while the airborne VA shows a characteristic Raman pattern (with broad band from ca. 200 to ca. 700 cm−1 typical for SiO2 glasses and additional bands of ferric minerals), the differences between the spectra of aged and fresh particles were observed, suggesting differences in their chemical composition and/or structure. We also analyzed similarities between Eyjafjallajökull VA particles collected at different sampling sites and compared the particles with a large variety of glassy and crystalline minerals. This was done by applying cluster analysis, in order to get information on the composition and structure of volcanic ash

Know What You Don’t Know: Assessment of Overlooked Microplastic Particles in FTIR Images

Assessing data analysis routines (DARs) for microplastics (MP) identification in Fourier-transform infrared (FTIR) images left the question ‘Do we overlook any MP particles in our sample?’ widely unanswered. Here, a reference image of microplastics, RefIMP, is presented to answer this question. RefIMP contains over 1200 MP and non-MP particles that serve as a ground truth that a DAR’s result can be compared to. Together with our MatLab® script for MP validation, MPVal, DARs can be evaluated on a particle level instead of isolated spectra. This prevents over-optimistic performance expectations, as testing of three hypotheses illustrates: (I) excessive background masking can cause overlooking of particles, (II) random decision forest models benefit from high-diversity training data, (III) among the model hyperparameters, the classification threshold influences the performance most. A minimum of 7.99% overlooked particles was achieved, most of which were polyethylene and varnish-like. Cellulose was the class most susceptible to over-segmentation. Most false assignments were attributed to confusion of polylactic acid for polymethyl methacrylate and of polypropylene for polyethylene. Moreover, a set of over 9000 transmission FTIR spectra is provided with this work, that can be used to set up DARs or as standard test set

Extreme differences in oxidation states : Synthesis and structural analysis of the germanide oxometallates A 10[Ge 9] 2[WO 4] as well as A 10+x[Ge 9] 2[W 1-xNb xO 4] with A = K and Rb containing [Ge 9] 4- polyanions

Semitransparent dark-red or ruby-red moisture- and air-sensitive single crystals of A 10+x[Ge 9] 2[W 1-xNb xO 4] (A = K, Rb; x = 0, 0.35) were obtained by high-temperature solid-state reactions. The crystal structure of the compounds was determined by single-crystal X-ray diffraction experiments. They crystallize in a new structure type (P2 1/c, Z = 4) with a = 13.908(1) Å, b = 15.909(1) Å, c = 17.383(1) Å, and α = 90.050(6)° for K 10.35(1)[Ge 9] 2[W 0.65(1)Nb 0.35(1)O 4]; a = 14.361(3) Å, b = 16.356(3) Å, c = 17.839(4) Å, and α = 90.01(3)° for Rb 10.35(1)[Ge 9] 2[W 0.65(1)Nb 0.35(1)O 4]; a = 13.8979(2) Å, b = 15.5390(3) Å, c = 17.4007(3) Å, and α = 90.188(1)° for K 10[Ge 9] 2WO 4; and a = 14.3230(7) Å, b = 15.9060(9) Å, c = 17.8634(9) Å, and α = 90.078(4)° for Rb 10[Ge 9] 2WO 4. The compounds contain discrete Ge 9 4- Wades nido clusters and WO 4 2- (or NbO 4 3-) anions, which are packed according to a hierarchical atom-to-cluster replacement of the Al 2Cu prototype and are separated by K and Rb cations, respectively. The alkali metal atoms occupy the corresponding tetrahedral sites of the Al 2Cu prototype. The amount of the alkali metal atoms on these diamagnetic compounds corresponds directly to the amount of W substituted by Nb. Thus, the transition metals W and Nb appear with oxidation numbers +6 and +5, respectively, in the vicinity of a [Ge 9] 4- polyanion. The crystals of the mixed salts were further characterized by Raman spectroscopy. The Raman data are in good agreement with the results from the X-ray structural analyses

Conductivity for Soot Sensing: Possibilities and Limitations

In this study we summarize the possibilities and limitations of a conductometric measurement principle for soot sensing. The electrical conductivity of different carbon blacks (FW 200, lamp black 101, Printex 30, Printex U, Printex XE2, special black 4, and special black 6), spark discharge soot (GfG), and graphite powder was measured by a van der Pauw arrangement. Additionally the influence of inorganic admixtures on the conductivity of carbonaceous materials was proven to follow the percolation theory. Structural and oxidation characteristics obtained with Raman microspectroscopy and temperature programmed oxidation, respectively, were correlated with the electrical conductivity data. Moreover, a thermophoretic precipitator has been applied to deposit soot particles from the exhaust stream between interdigital electrodes. This combines a controlled and size independent particle collection method with the conductivity measurement principle. A test vehicle was equipped with the AVL Micro Soot Sensor (photoacoustic soot sensor) to prove the conductometric sensor principle with an independent and reliable technique. Our results demonstrate promising potential of the conductometric sensor for on-board particle diagnostic. Furthermore this sensor can be applied as a simple, rapid, and cheap analytical tool for characterization of soot structure

From the Well to the Bottle: Identifying Sources of Microplastics in Mineral Water

Microplastics (MP) have been detected in bottled mineral water across the world. Because only few MP particles have been reported in ground water-sourced drinking water, it is suspected that MP enter the water during bottle cleaning and filling. However, until today, MP entry paths were not revealed. For the first time, this study provides findings of MP from the well to the bottle including the bottle washing process. At four mineral water bottlers, five sample types were taken along the process: raw and deferrized water samples were filtered in situ; clean bottles were sampled right after they left the bottle washer and after filling and capping. Caustic cleaning solutions were sampled from bottle washers and MP particles isolated through enzymatic and chemical treatments. The samples were analyzed for eleven synthetic and natural polymer particles ≥11 µm with Fourier-transform infrared imaging and random decision forests. MP were present in all steps of mineral water bottling, with a sharp increase from <1 MP L−1 to 317 ± 257 MP L−1 attributed to bottle capping. As 81% of MP resembled the PE-based cap sealing material, abrasion from the sealings was identified as the main entry path for MP into bottled mineral water

Comment on "exposure to microplastics (<10 μm) associated to plastic bottles mineral water consumption: The first quantitative study by Zuccarello et al. [Water Research 157 (2019) 365-371]"

Microplastics in food is a relatively new research field with only few studies available so far. Scientists have been pointing out that some of these studies apply questionable analytical methods. Nevertheless, media often use such results to gain attention of the readers. It is therefore of particular significance, that only those scientific studies are published, clearly presenting valid data on the content of microplastics in food. Unfortunately, the study by Zuccarello et al. shows very critical aspects regarding analytical methods used and conclusions made. The applied procedure is not described and, therefore, does not allow any assessment by other groups, which is indispensable prerequisite of any scientific publication. Moreover, the analytical method used for the identification and quantification of microplastic particles – SEM-EDX – is not sound and not validated. Therefore, in our opinion the results on the contamination of bottled mineral water with microplastics published by Zuccarello et al. are more than questionable

TUM-ParticleTyper: A detection and quantification tool for automated analysis of (Microplastic) particles and fibers.

TUM-ParticleTyper is a novel program for the automated detection, quantification and morphological characterization of fragments, including particles and fibers, in images from optical, fluorescence and electron microscopy (SEM). It can be used to automatically select targets for subsequent chemical analysis, e.g., Raman microscopy, or any other single particle identification method. The program was specifically developed and validated for the analysis of microplastic particles on gold coated polycarbonate filters. Our method development was supported by the design of a filter holder that minimizes filter roughness and facilitates enhanced focusing for better images and Raman measurements. The TUM-ParticleTyper software is tunable to the user's specific sample demands and can extract the morphological characteristics of detected objects (coordinates, Feret's diameter min / max, area and shape). Results are saved in csv-format and contours of detected objects are displayed as an overlay on the original image. Additionally, the program can stitch a set of images to create a full image out of several smaller ones. An additional useful feature is the inclusion of a statistical process to calculate the minimum number of particles that must be chemically identified to be representative of all particles localized on the substrate. The program performance was evaluated on genuine microplastic samples. The TUM-ParticleTyper software localizes particles using an adaptive threshold with results comparable to the "gold standard" method (manual localization by an expert) and surpasses the commonly used Otsu thresholding by doubling the rate of true positive localizations. This enables the analysis of a statistically significant number of particles on the filter selected by random sampling, measured via single point approach. This extreme reduction in measurement points was validated by comparison to chemical imaging, applying both procedures to the same area at comparable processing times. The single point approach was both faster and more accurate proving the applicability of the presented program