Plastic Quantification and Polyethylene Overestimation in Agricultural Soil Using Large-Volume Pyrolysis and TD-GC-MS/MS.

Quantification of microplastics in soil is needed to understand their impact and fate in agricultural areas. Often, low sample volume and removal of organic matter (OM) limit representative quantification. We present a method which allows simultaneous quantification of microplastics in homogenized, large environmental samples (>1 g) and tested polyethylene (PE), polyethylene terephthalate (PET), and polystyrene (PS) (200-400 µm) overestimation by fresh and diagenetically altered OM in agricultural soils using a new combination of large-volume pyrolysis adsorption with thermal desorption-gas chromatography-tandem mass spectrometry (TD-GC-MS/MS). Characteristic MS/MS profiles for PE, PET, and PS were derived from plastic pyrolysis and allowed for a new mass separation of PET. Volume-defined standard particles (125 × 125 × 20 µm3) were developed with the respective weight (PE: 0.48 ± 0.12, PET: 0.50 ± 0.10, PS: 0.31 ± 0.08 µg), which can be spiked into solid samples. Diagenetically altered OM contained compounds that could be incorrectly identified as PE and suggest a mathematical correction to account for OM contribution. With a standard addition method, we quantified PS, PET, and PEcorrected in two agricultural soils. This provides a base to simultaneously quantify a variety of microplastics in many environmental matrices and agricultural soil.

Identification of different plastic types and natural materials from terrestrial environments using fluorescence lifetime imaging microscopy.

Environmental pollution by plastics is a global issue of increasing concern. However, microplastic analysis in complex environmental matrices, such as soil samples, remains an analytical challenge. Destructive mass-based methods for microplastic analysis do not determine plastics' shape and size, which are essential parameters for reliable ecological risk assessment. By contrast, nondestructive particle-based methods produce such data but require elaborate, time-consuming sample preparation. Thus, time-efficient and reliable methods for microplastic analysis are needed. The present study explored the potential of frequency-domain fluorescence lifetime imaging microscopy (FD-FLIM) for rapidly and reliably identifying as well as differentiating plastics and natural materials from terrestrial environments. We investigated the fluorescence spectra of ten natural materials from terrestrial environments, tire wear particles, and eleven different transparent plastic granulates <5 mm to determine the optimal excitation wavelength for identification and differentiation via FD-FLIM under laboratory conditions. Our comparison of different excitation wavelengths showed that 445 nm excitation exhibited the highest fluorescence intensities. 445 nm excitation was also superior for identifying plastic types and distinguishing them from natural materials from terrestrial environments with a high probability using FD-FLIM. We could demonstrate that FD-FLIM analysis has the potential to contribute to a streamlined and time-efficient direct analysis of microplastic contamination. However, further investigations on size-, shape-, color-, and material-type detection limitations are necessary to evaluate if the direct identification of terrestrial environmental samples of relatively low complexity, such as a surface inspection soil, is possible.

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

One of the biggest issues in microplastic (MP, plastic items <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.

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.

Reconstructing the Environmental Degradation of Polystyrene by Accelerated Weathering.

The fragmentation of macro- into microplastics (MP) is the main source of MP in the environment. Nevertheless, knowledge about degradation mechanisms, changes in chemical composition, morphology, and residence times is still limited. Here, we present a long-term accelerated weathering study on polystyrene (PS) tensile bars and MP particles using simulated solar radiation and mechanical stress. The degradation process was monitored by gel permeation chromatography (GPC), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX), 13C magic-angle spinning (MAS) NMR spectroscopy, tensile testing, and Monte Carlo simulations. We verified that degradation proceeds in two main stages. Stage I is dominated by photooxidation in a near-surface layer. During stage II, microcrack formation and particle rupturing accelerate the degradation. Depending on the ratio and intensity of the applied stress factors, MP degradation kinetics and lifetimes vary dramatically and an increasing amount of small MP fragments with high proportions of carboxyl, peroxide, and keto groups is continuously released into the environment. The enhanced surface area for adsorbing pollutants and forming biofilms modifies the uptake behavior and interaction with organisms together with potential ecological risks. We expect the proposed two-stage model to be valid for predicting the abiotic degradation of other commodity plastics with a carbon-carbon backbone.

Finding Microplastics in Soils: A Review of Analytical Methods.

Research on microplastics in soils is still uncommon, and the existing publications are often incomparable due to the use of different sampling, processing, and analytical methods. Given the complex nature of soils, a suitable and efficient method for standardized microplastic analysis in the soil matrix has yet to be found. This paper proposes a critical review on the different published methods for sampling, extraction, purification, and identification/quantification of microplastics in complex environmental matrices, with the main focus on their applicability for soil samples. While large microplastic particles can be manually sorted out and verified with chemical analysis, sample preparation for smaller microplastic analysis is usually more difficult. Of the analytical approaches proposed in the literature, some are established, whereas others are a proof of principle and have not yet been applied to environmental samples. For the sake of development, all approaches are discussed and assessed for their potential applicability for soil samples. So far, none of the published methods seems ideally suitable for the analysis of smaller microplastics in soil samples, but slight modifications and combinations of methods may prove promising and need to be explored.

Enzymatic Purification of Microplastics in Environmental Samples.

Micro-Fourier transform infrared (micro-FTIR) spectroscopy and Raman spectroscopy enable the reliable identification and quantification of microplastics (MPs) in the lower micron range. Since concentrations of MPs in the environment are usually low, the large sample volumes required for these techniques lead to an excess of coenriched organic or inorganic materials. While inorganic materials can be separated from MPs using density separation, the organic fraction impedes the ability to conduct reliable analyses. Hence, the purification of MPs from organic materials is crucial prior to conducting an identification via spectroscopic techniques. Strong acidic or alkaline treatments bear the danger of degrading sensitive synthetic polymers. We suggest an alternative method, which uses a series of technical grade enzymes for purifying MPs in environmental samples. A basic enzymatic purification protocol (BEPP) proved to be efficient while reducing 98.3 ± 0.1% of the sample matrix in surface water samples. After showing a high recovery rate (84.5 ± 3.3%), the BEPP was successfully applied to environmental samples from the North Sea where numbers of MPs range from 0.05 to 4.42 items m-3. Experiences with different environmental sample matrices were considered in an improved and universally applicable version of the BEPP, which is suitable for focal plane array detector (FPA)-based micro-FTIR analyses of water, wastewater, sediment, biota, and food samples.

Identification of microplastics by FTIR and Raman microscopy: a novel silicon filter substrate opens the important spectral range below 1300 cm(-1) for FTIR transmission measurements.

The presence of microplastics in aquatic ecosystems is a topical problem and leads to the need of appropriate and reliable analytical methods to distinctly identify and to quantify these particles in environmental samples. As an example transmission, Fourier transform infrared (FTIR) imaging can be used to analyze samples directly on filters without any visual presorting, when the environmental sample was afore extracted, purified, and filtered. However, this analytical approach is strongly restricted by the limited IR transparency of conventional filter materials. Within this study, we describe a novel silicon (Si) filter substrate produced by photolithographic microstructuring, which guarantees sufficient transparency for the broad mid-infrared region of 4000-600 cm(-1). This filter type features holes with a diameter of 10 µm and exhibits adequate mechanical stability. Furthermore, it will be shown that our Si filter substrate allows a distinct identification of the most common microplastics, polyethylene (PE), and polypropylene (PP), in the characteristic fingerprint region (1400-600 cm(-1)). Moreover, using the Si filter substrate, a differentiation of microparticles of polyesters having quite similar chemical structure, like polyethylene terephthalate (PET) and polybutylene terephthalate (PBT), is now possible, which facilitates a visualization of their distribution within a microplastic sample by FTIR imaging. Finally, this Si filter can also be used as substrate for Raman microscopy-a second complementary spectroscopic technique-to identify microplastic samples.

Facilitation of intraguild prey by its intraguild predator in a three-species Lotka-Volterra model.

Explaining the coexistence of multiple species in the competition and predation theatre has proven a great challenge. Traditional intraguild predation (IGP) models have only relatively small regions of stable coexistence of all species. Here, we investigate potential additional mechanisms that extend these regions of stable coexistence. We used a 3-species Lotka-Volterra system to which we added an interaction term to model a unidirectional facilitative relationship between the two predators in the IGP. In this modelling study the IG predator was able to precondition a part of the common resource by an instantaneous manipulation, which resulted in the immobilization of the resource species. This mechanism of immobilization facilitated the resource uptake by the IG prey and thus increased its growth rates even in the presence of the common predator. The facilitative relationship of the IG prey by the IG predator produced a stable coexistence of both predators even though the IG prey was an inferior competitor for a common resource, which cannot be attained with the traditional IGP models. Furthermore, our model predicted a 3-species stable coexistence even at high enrichment where no coexistence was found in the basic IGP model. Thus, we showed that diversity of resource traits could significantly alter emergent community patterns via shifts in exploitative competition of IGP-related predators. The described mechanism could potentially lead to a higher efficiency in exploitation of common resources and thus promote higher diversity in a real community.

A promising method for fast identification of microplastic particles in environmental samples: A pilot study using fluorescence lifetime imaging microscopy.

Microplastic pollution of the environment has been extensively studied, with recent studies focusing on the prevalence of microplastics in the environment and their effects on various organisms. Identification methods that simplify the extraction and analysis process to the point where the extraction can be omitted are being investigated, thus enabling the direct identification of microplastic particles. Currently, microplastic samples from environmental matrices can only be identified using time-consuming extraction, sample processing, and analytical methods. Various spectroscopic methods are currently employed, such as micro Fourier-transform infrared, attenuated total reflectance, and micro Raman spectroscopy. However, microplastics in environmental matrices cannot be directly identified using these spectroscopic methods. Investigations using frequency-domain fluorescence lifetime imaging microscopy (FD-FLIM) to identify and differentiate plastics from environmental materials have yielded promising results for directly identifying microplastics in an environmental matrix. Herein, two artificially prepared environmental matrices that included natural soil, grass, wood, and high-density polyethylene were investigated using FD-FLIM. Our first results showed that we successfully identified one plastic type in the two artificially prepared matrices using FD-FLIM. However, further research must be conducted to improve the FD-FLIM method and explore its limitations for directly identifying microplastics in environmental samples.

Detection and specific chemical identification of submillimeter plastic fragments in complex matrices such as compost.

Research on the plastic contamination of organic fertilizer (compost) has largely concentrated on particles and fragments > 1 mm. Small, submillimeter microplastic particles may be more hazardous to the environment. However, research on their presence in composts has been impeded by the difficulty to univocally identify small plastic particles in such complex matrices. Here a method is proposed for the analysis of particles between 0.01 and 1.0 mm according to number, size, and polymer type in compost. As a first demonstration of its potential, the method is used to determine large and small microplastic in composts from eight municipal compost producing plants: three simple biowaste composters, four plants processing greenery and cuttings and one two-stage biowaste digester-composter. While polyethylene, PE, tends to dominate among fragments > 1 mm, the microplastic fraction contained more polypropylene, PP. Whereas the contamination with PE/PP microplastic was similar over the investigated composts, only composts prepared from biowaste contained microplastic with a signature of biodegradable plastic, namely poly(butylene adipate co-terephthalate), PBAT. Moreover, in these composts PBAT microplastic tended to form the largest fraction. When the bulk of residual PBAT in the composts was analyzed by chloroform extraction, an inverse correlation between the number of particles > 0.01 mm and the total extracted amount was seen, arguing for breakdown into smaller particles, but not necessarily a mass reduction. PBAT oligomers and monomers as possible substrates for subsequent biodegradation were not found. Remaining microplastic will enter the environment with the composts, where its subsequent degradability depends on the local conditions and is to date largely uninvestigated.

Multi-method analysis of microplastic distribution by flood frequency and local topography in Rhine floodplains.

Rivers are important transport pathways for microplastics into the ocean, but they can also be potential sinks due to microplastic deposition in the sediments of the river bed and adjacent floodplains. In particular, floods can (re)mobilise microplastics from sediments and floodplains, (re)deposit and relocate them depending on the floodplain topography. The knowledge about fluvial microplastic input to floodplains, their spatial distribution and their fate in floodplain soils is limited. To investigate this topic, we sampled soil at a depth of 5-20 cm along three transects in three different Rhine floodplains. We analysed the soil samples in tandem with pyrolysis GC/MS and ATR- & µ-FPA-FTIR for their microplastic abundance and mass concentrations. To study the influence of flood frequency on the microplastic abundance in the three floodplains, we fitted a hydrodynamic flood model (MIKE 21, DHI, Hørsholm, Denmark) and related the results to the respective spatial microplastic distribution. We found similar microplastic distribution patterns in each floodplain. The highest microplastic abundance (8516-70,124 microplastics kg-1) and mass concentration (46.2-141.6 mg kg-1) were consistently found in the farthest transects from the Rhine in a topographical depression. This microplastic distribution pattern is detectable with both, pyrolysis GC/MS and FTIR. The strongest correlation between the results of both methods was found for small, abundant microplastic particles. Our results suggest that the spatial distribution of microplastics in floodplains is related to the combination of flood frequency and local topography, that ought to be explicitly considered in future studies conducted in floodplains. Finally, our results indicate that pyrolysis GC/MS and FTIR data are comparable under certain conditions, which may help in the decision for the analytical method and sampling design in future studies.

Seasonal variations of microplastic pollution in the German River Weser.

Rivers play a major role in the distribution of microplastics (MPs) in the environment, however, research on temporal variations in these highly dynamic systems is still in its infancy. To date, most studies dealing with the seasonality of MP contamination in rivers focus on bi-yearly analysis, while temporal fluctuations over the course of the year are rarely studied. To shed more light on seasonal variability of MP abundance and potential driving factors, we have thus sampled the water surface of one location in the Weser River in Germany monthly over one entire year. In our study, we targeted MP in the size range 10-5000 µm, using two different state-of-the-art sampling methods (manta net for large MP (l-MP; 500-5000 µm) and a filtration system for small MP (s-MP; 10-500 µm)) and analysis techniques (ATR-FTIR and FPA-µFTIR) for chemical identification. Our findings show a strong size-dependent positive correlation of the MP concentration with discharge rates (specifically direct runoff) and suspended particulate matter (SPM) for s-MPs, specifically in the size range 10-149 µm. L-MPs, however, show a different environmental behaviour and do not follow these patterns. With our study, we were able to deliver a much higher temporal resolution, covering a broader size range of MPs compared to most studies. Our findings point towards an interplay of two possible mechanisms: a) the riverbeds play an important role in large-scale MP and SPM release via resuspension during high discharge events, and b) precipitation-driven soil erosion and runoff from urban surfaces (e.g. rain sewers) introduce MP and SPM. Hence, our study serves as a basis for more detailed investigations of MP transport in and between ecosystems.

The fate of microplastics from municipal wastewater in a surface flow treatment wetland.

Microplastics (MPs) are an anthropogenic pollutant of emerging concern prominent in both raw and treated municipal wastewater as well as urban and agricultural run-off. There is a critical need for the mitigation of both point- and diffuse sources, with treatment wetlands a possible sustainable nature-based solution. In this study, the possible retention of MPs in treatment wetlands of the widely used surface flow (SF) type was investigated. In- and outflow water, as well as atmospheric deposition, at a full-scale reed-based SF wetland (operating as a polishing phase of municipal wastewater treatment) was analyzed for MPs in a size range of 25-1000 µm. FPA-based µFT-IR spectroscopic imaging was used in combination with automated data analysis software, allowing for an unbiased assessment of MP numbers, polymer types and size distribution. Inflow water samples (secondary treated wastewater) contained 104 MPs m-3 and 56 MPs m-3 in sampling campaigns 1 and 2, respectively. Passage through the SF wetland increased the MP concentration in the water by 92 % during a rain intense period (campaign 1) and by 43 % during a low precipitation period (campaign 2). The MP particle numbers, size and polymer type distribution varied between the two sampling campaigns, making conclusions around the fate of specific types of MPs in SF wetlands difficult. Atmospheric deposition was measured to be 590 MPs m-2 week-1 during the rain-intense period. Our findings point towards atmospheric deposited MPs as an important factor in the fate of MPs in SF wetlands, causing an increase of MP concentrations, and potentially explaining the variations observed in MP concentrations in wetland effluent and removal efficiency. Furthermore, atmospheric deposition might also be a reason for the considerable inter-study variation regarding MPs removal efficiency in SF wetlands found in the available literature.

A novel approach to extract, purify, and fractionate microplastics from environmental matrices by isopycnic ultracentrifugation.

The increasing accumulation of microplastics (MP) in the environment is considered one of the most important environmental challenges of our times. Reliable extraction and detection methods for MP in environmental samples are essential for determining the extent of pollution and assessing ecological risks. However, extraction of MP from complex environmental matrices such as soil remains technically challenging. Today, density-based extractions with saturated salt solutions are widely applied. Nevertheless, current methods do not allow for the fractionation of different MP particle types according to their specific polymer densities. Here, we present a novel isopycnic ultracentrifugation approach for the simultaneous extraction and fractionation of MP mixtures based on the particle-specific buoyant densities. In this proof-of-concept study, diffusion-based density gradients were prepared using caesium chloride media, covering a density range between 1.1 and 1.5 g mL-1, sufficient to resolve many common polymer densities. We selected MP particles with a low (polyamide; PA66), medium (polybutylene adipate terephthalate; PBAT), and high (polyethylene terephthalate; PET) density to validate separation performance. Both pristine and soil-incubated MP mixtures showed clear banding patterns at expected buoyant densities after isopycnic separation. µFTIR imaging of subsamples collected from resolved MP fractions showed a polymer-specific separation of ≥87.6 %. In addition, the quantitative recovery of MP particles from soil was between 86 and 99 %. The potential of isopycnic ultracentrifugation to preserve MP-associated biofilms was also assessed. Soil-incubated MP particles were inspected by confocal laser scanning microscopy before and after isopycnic separation, indicating a preservation of bioorganic structures. Hence, isopycnic ultracentrifugation offers a powerful novel approach for a polymer-specific extraction and resolution of MP particles with a wide potential for applications in MP research.

Nano- and microplastics: a comprehensive review on their exposure routes, translocation, and fate in humans.

Contamination of the environment with nano-and microplastic particles (NMPs) and its putative adverse effects on organisms, ecosystems, and human health is gaining increasing scientific and public attention. Various studies show that NMPs occur abundantly within the environment, leading to a high likelihood of human exposure to NMPs. Here, different exposure scenarios can occur. The most notable exposure routes of NMPs into the human body are via the airways and gastrointestinal tract (GIT) through inhalation or ingestion, but also via the skin due to the use of personal care products (PCPs) containing NMPs. Once NMPs have entered the human body, it is possible that they are translocated from the exposed organ to other body compartments. In our review article, we combine the current knowledge on the (1) exposure routes of NMPs to humans with the basic understanding of the potential (2) translocation mechanisms into human tissues and, consequently, their (3) fate within the human body. Regarding the (1) exposure routes, we reviewed the current knowledge on the occurrence of NMPs in food, beverages, personal care products and the air (focusing on indoors and workplaces) and found that the studies suggest an abundant presence of MPs within the exposure scenarios. The overall abundance of MPs in exposure matrices relevant to humans highlights the importance of understanding whether NMPs have the potential for tissue translocation. Therefore, we describe the current knowledge on the potential (2) translocation pathways of NMPs from the skin, GIT and respiratory systems to other body compartments. Here, particular attention was paid to how likely NMPs can translocate from the primary exposed organs to secondary organs due to naturally occurring defence mechanisms against tissue translocation. Based on the current understanding, we conclude that a dermal translocation of NMPs is rather unlikely. In contrast, small MPs and NPs can generally translocate from the GIT and respiratory system to other tissues. Thus, we reviewed the existing literature on the (3) fate of NMPs within the human body. Based on the current knowledge of the contamination of human exposure routes and the potential translocation mechanisms, we critically discuss the size of the detected particles reported in the fate studies. In some cases, the particles detected in human tissue samples exceed the size of a particle to overcome biological barriers allowing particle translocation into tissues. Therefore, we emphasize the importance of critically reading and discussing the presented results of NMP in human tissue samples.

Beyond microplastics: Water soluble synthetic polymers exert sublethal adverse effects in the freshwater cladoceran Daphnia magna.

Plastic pollution is considered one of the causes of global change. However, water soluble synthetic polymers (WSSPs) have been neglected so far, although they are used in several industrial, dietary, domestic and biomedical products. Moreover, they are applied in wastewater treatment plants (WWTPs) as flocculants and coagulant agents. Hence, their presence in the aquatic environment as well as their uptake by aquatic organisms is probable, whereas no data are available regarding their potential adverse effects. Here we show in the freshwater key species D. magna exposed to five different WSSPs life history changes along with an altered level of reactive oxygen species, although acute mortality was not observed. Since daphnids act as keystone species in lake ecosystems by controlling phytoplankton biomass, even sublethal effects such as WSSPs induced changes in life history may result in cascading effects, from lower to higher trophic levels, which in turn could affect the whole food web.

Flooding frequency and floodplain topography determine abundance of microplastics in an alluvial Rhine soil.

Rivers are major pathways for the transport of microplastics towards the oceans, and many studies focus on microplastic abundance in fluvial ecosystems. Although flooding strongly affects transport of microplastics, knowledge about the potential input via floodwaters, spatial distribution, and fate of microplastics in adjacent floodplains remains very limited. In this study, we suggest that local topography and flood frequency could influence the abundance of microplastics in floodplains. Based on this concept, we took soil samples in a Rhine River floodplain in two different depths (0-5 cm and 5-20 cm) along three transects with increasing distance to the river and analysed the abundance of microplastics via FTIR spectroscopy. Flood frequency of the transects was estimated by a combination of hydrodynamic modelling with MIKE 21 (DHI, Hørsholm Denmark) and analysis of time series of water levels. Microplastic abundance per kg dry soil varied between 25,502 to 51,119 particles in the top 5 cm and 25,616 to 84,824 particles in the deeper soil (5-20 cm). The results of our study indicate that local topography and resulting flooding patterns are responsible for the amount of microplastics found at the respective transect. Differences in soil properties, vegetation cover and signs of earthworm activity in the soil profile seem to be related to microplastic migration and accumulation in the deeper soil. The interdisciplinary approach we used in our work can be applied to other floodplains to elucidate the respective processes. This information is essentially important both for locating potential microplastic sinks for process-informed sampling designs and to identify areas of increased bioavailability of microplastics for proper ecological risk assessment.

Tackling the Challenge of Extracting Microplastics from Soils: A Protocol to Purify Soil Samples for Spectroscopic Analysis.

Microplastic pollution in soils is an emerging topic in the scientific community, with researchers striving to determine the occurrence and the impact of microplastics on soil health, ecology, and functionality. However, information on the microplastic contamination of soils is limited because of a lack of suitable analytical methods. Because micro-Fourier-transform infrared spectroscopy (µ-FTIR), next to Raman spectroscopy, is one of the few methods that allows the determination of the number, polymer type, shape, and size of microplastic particles, the present study addresses the challenge of purifying soil samples sufficiently to allow a subsequent µ-FTIR analysis. A combination of freeze-drying, sieving, density separation, and a sequential enzymatic-oxidative digestion protocol enables removal of the mineral mass (>99.9% dry wt) and an average reduction of 77% dry weight of the remaining organic fraction. In addition to visual integrity, attenuated total reflectance FTIR, gel permeation chromatography, and differential scanning calorimetry showed that polyamide, polyethylene, polyethylene terephthalate, and polyvinyl chloride in the size range of 100 to 400 µm were not affected by the approach. However, biodegradable polylactic acid showed visible signs of degradation and reduced molecular weight distribution after protease treatment. Nevertheless, the presented purification protocol is a reliable and robust method to purify relatively large soil samples of approximately 250 g dry weight for spectroscopic analysis in microplastic research and has been shown to recover various microplastic fibers and fragments down to a size of 10 µm from natural soil samples. Environ Toxicol Chem 2022;41:844-857. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Computer-Assisted Analysis of Microplastics in Environmental Samples Based on µFTIR Imaging in Combination with Machine Learning.

The problem of automating the data analysis of microplastics following a spectroscopic measurement such as focal plane array (FPA)-based micro-Fourier transform infrared (FTIR), Raman, or QCL is gaining ever more attention. Ease of use of the analysis software, reduction of expert time, analysis speed, and accuracy of the result are key for making the overall process scalable and thus allowing nonresearch laboratories to offer microplastics analysis as a service. Over the recent years, the prevailing approach has been to use spectral library search to automatically identify spectra of the sample. Recent studies, however, showed that this approach is rather limited in certain contexts, which led to developments for making library searches more robust but on the other hand also paved the way for introducing more advanced machine learning approaches. This study describes a model-based machine learning approach based on random decision forests for the analysis of large FPA-µFTIR data sets of environmental samples. The model can distinguish between more than 20 different polymer types and is applicable to complex matrices. The performance of the model under these demanding circumstances is shown based on eight different data sets. Further, a Monte Carlo cross validation has been performed to compute error rates such as sensitivity, specificity, and precision.