Identification and quantification of macro- and microplastics on an agricultural farmland

Abstract Microplastic contamination of aquatic ecosystems is a high priority research topic, whereas the issue on terrestrial ecosystems has been widely neglected. At the same time, terrestrial ecosystems under human influence, such as agroecosystems, are likely to be contaminated by plastic debris. However, the extent of this contamination has not been determined at present. Via Fourier transform infrared (FTIR) analysis, we quantified for the first time the macro- and microplastic contamination on an agricultural farmland in southeast Germany. We found 206 macroplastic pieces per hectare and 0.34 ± 0.36 microplastic particles per kilogram dry weight of soil. In general, polyethylene was the most common polymer type, followed by polystyrene and polypropylene. Films and fragments were the dominating categories found for microplastics, whereas predominantly films were found for macroplastics. Since we intentionally chose a study site where microplastic-containing fertilizers and agricultural plastic applications were never used, our findings report on plastic contamination on a site which only receives conventional agricultural treatment. However, the contamination is probably higher in areas where agricultural plastic applications, like greenhouses, mulch, or silage films, or plastic-containing fertilizers (sewage sludge, biowaste composts) are applied. Hence, further research on the extent of this contamination is needed with special regard to different cultivation practices

Effects of high CO2 and warming on a Baltic Sea microzooplankton community

Global warming and ocean acidification are among the most important stressors for aquatic ecosystems in the future. To investigate their direct and indirect effects on a near-natural plankton community, a multiple-stressor approach is needed. Hence, we set up mesocosms in a full-factorial design to study the effects of both warming and high CO2 on a Baltic Sea autumn plankton community, concentrating on the impacts on microzooplankton (MZP). MZP abundance, biomass, and species composition were analysed over the course of the experiment. We observed that warming led to a reduced time-lag between the phytoplankton bloom and an MZP biomass maximum. MZP showed a significantly higher growth rate and an earlier biomass peak in the warm treatments while the biomass maximum was not affected. Increased pCO2 did not result in any significant effects on MZP biomass, growth rate, or species composition irrespective of the temperature, nor did we observe any significant interactions between CO2 and temperature. We attribute this to the high tolerance of this estuarine plankton community to fluctuations in pCO2, often resulting in CO2 concentrations higher than the predicted end-of-century concentration for open oceans. In contrast, warming can be expected to directly affect MZP and strengthen its coupling with phytoplankton by enhancing its grazing pressure

Classification of target tissues of Eisenia fetida using sequential multimodal chemical analysis and machine learning

Acquiring comprehensive knowledge about the uptake of pollutants, impact on tissue integrity and the effects at the molecular level in organisms is of increasing interest due to the environmental exposure to numerous contaminants. The analysis of tissues can be performed by histological examination, which is still time-consuming and restricted to target-specific staining methods. The histological approaches can be complemented with chemical imaging analysis. Chemical imaging of tissue sections is typically performed using a single imaging approach. However, for toxicological testing of environmental pollutants, a multimodal approach combined with improved data acquisition and evaluation is desirable, since it may allow for more rapid tissue characterization and give further information on ecotoxicological effects at the tissue level. Therefore, using the soil model organism Eisenia fetida as a model, we developed a sequential workflow combining Fourier transform infrared spectroscopy (FTIR) and matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) for chemical analysis of the same tissue sections. Data analysis of the FTIR spectra via random decision forest (RDF) classification enabled the rapid identification of target tissues (e.g., digestive tissue), which are relevant from an ecotoxicological point of view. MALDI imaging analysis provided specific lipid species which are sensitive to metabolic changes and environmental stressors. Taken together, our approach provides a fast and reproducible workflow for label-free histochemical tissue analyses in E. fetida, which can be applied to other model organisms as well. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00418-021-02037-1

Comparison of two rapid automated analysis tools for large FTIR microplastic datasets

AbstractOne of the biggest issues in microplastic (MP, plastic items  &lt;5 mm) research is the lack of standardisation and harmonisation in all fields, reaching from sampling methodology to sample purification, analytical methods and data analysis. This hampers comparability as well as reproducibility among studies. Concerning chemical analysis of MPs, Fourier-transform infrared (FTIR) spectroscocopy is one of the most powerful tools. Here, focal plane array (FPA) based micro-FTIR (µFTIR) imaging allows for rapid measurement and identification without manual preselection of putative MP and therefore enables large sample throughputs with high spatial resolution. The resulting huge datasets necessitate automated algorithms for data analysis in a reasonable time frame. Although solutions are available, little is known about the comparability or the level of reliability of their output. For the first time, within our study, we compare two well-established and frequently applied data analysis algorithms in regard to results in abundance, polymer composition and size distributions of MP (11–500 µm) derived from selected environmental water samples: (a) the siMPle analysis tool (systematic identification of MicroPlastics in the environment) in combination with MPAPP (MicroPlastic Automated Particle/fibre analysis Pipeline) and (b) the BPF (Bayreuth Particle Finder). The results of our comparison show an overall good accordance but also indicate discrepancies concerning certain polymer types/clusters as well as the smallest MP size classes. Our study further demonstrates that a detailed comparison of MP algorithms is an essential prerequisite for a better comparability of MP data.</jats:p

Municipal biowaste treatment plants contribute to the contamination of the environment with residues of biodegradable plastics with putative higher persistence potential

Biodegradable plastics (BDP) are expected to mineralize easily, in particular under conditions of technical composting. However, the complexity of the sample matrix has largely prevented degradation studies under realistic conditions. Here composts and fertilizers from state-of-the-art municipal combined anaerobic/aerobic biowaste treatment plants were investigated for residues of BDP. We found BDP fragments > 1 mm in significant numbers in the final composts intended as fertilizer for agriculture and gardening. Compared to pristine compostable bags, the recovered BDP fragments showed differences in their material properties, which potentially renders them less prone to further biodegradation. BDP fragments < 1 mm were extracted in bulk and came up to 0.43 wt% of compost dry weight. Finally, the liquid fertilizer produced during the anaerobic treatment contained several thousand BDP fragments < 500 µm per liter. Hence, our study questions, if currently available BDP are compatible with applications in areas of environmental relevance, such as fertilizer production

Structural Diversity in Early-Stage Biofilm Formation on Microplastics Depends on Environmental Medium and Polymer Properties

Plastics entering the environment can not only undergo physical degradation and fragmentation processes, but they also tend to be colonized by microorganisms. Microbial colonization and the subsequent biofilm formation on plastics can alter their palatability to organisms and result in a higher ingestion as compared to pristine plastics. To date, the early stage of biofilm formation on plastic materials has not been investigated in context of the environmental medium and polymer properties. We explored the early-stage biofilm formation on polyamide (PA), polyethylene terephthalate (PET), and polyvinyl chloride (PVC) after incubation in freshwater and artificial seawater and categorized the structural diversity on images obtained via scanning electron microscopy. Furthermore, by the measurement of the initial &zeta;-potential of the plastic materials, we found that PA with the highest negative &zeta;-potential tended to have the highest structural diversity, followed by PET and PVC after incubation in freshwater. However, PVC with the lowest negative &zeta;-potential showed the highest structural diversity after incubation in seawater, indicating that the structural diversity is additionally dependent on the incubation medium. Our results give insights into how the incubation medium and polymer properties can influence the early-stage biofilm formation of just recently environmentally exposed microplastics. These differences are responsible for whether organisms may ingest microplastic particles with their food or not