Publications by authors named "Merel Kooi"

Microplastics pose numerous threats to aquatic environments, yet understanding their transport mechanisms remains limited. Drawing from natural sediment research provides valuable insights to address this knowledge gap. One key dimensionless number used to describe sediment transport is the transport stage, referring to the ratio between the flow shear velocity and the particle settling velocity.

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The influence of algae presence in surface water on the settling velocities of microplastics is unknown, and determining it is challenging due to the turbidity of algal suspensions. Measuring the settling velocity of microplastics has traditionally relied on either manual measurement techniques or 2D Particle Tracking Velocimetry (PTV). This study introduces a 3D-PTV method tailored to determine the effects of algae (Synechoccocussp.

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The effects and risks of microplastics correlate with three-dimensional (3D) properties, such as the volume and surface area of the biologically accessible fraction of the diverse particle mixtures as they occur in nature. However, these 3D parameters are difficult to estimate because measurement methods for spectroscopic and visible light image analysis yield data in only two dimensions (2D). The best-existing 2D to 3D conversion models require calibration for each new set of particles, which is labor-intensive.

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Current methods of characterizing plastic debris use arbitrary, predetermined categorizations and assume that the properties of particles are independent. Here we introduce Gaussian mixture models (GMM), a technique suitable for describing non-normal multivariate distributions, as a method to identify mutually exclusive subsets of floating macroplastic and microplastic particles (latent class analysis) based on statistically defensible categories. Length, width, height and polymer type of 6,942 particles and items from the Atlantic Ocean were measured using infrared spectroscopy and image analysis.

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Plastic accumulates in the environment because of insufficient waste handling and its high durability. Better understanding of plastic behavior in the aquatic environment is needed to estimate transport and accumulation, which can be used for monitoring, prevention, and reduction strategies. Plastic transport models benefit from accurate description of particle characteristics, such as rising and settling velocities.

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Understanding the multidimensionality of microplastics is essential for a realistic assessment of the risks these particles pose to the environment and human health. Here, we capture size, shape, area, polymer, volume and mass characteristics of >60,000 individual microplastic particles as continuous distributions. Particles originate from samples taken from different aquatic compartments, including surface water and sediments from the marine and freshwater environment, waste water effluents, and freshwater organisms.

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Microplastic debris ending up at the sea surface has become a known major environmental issue. However, how microplastic particles move and when they sink in the ocean remains largely unknown. Here, we model microplastic subject to biofouling (algal growth on a substrate) to estimate sinking timescales and the time to reach the depth where particles stop sinking.

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Human exposure to microplastic is recognized as a global problem, but the uncertainty, variability, and lifetime accumulation are unresolved. We provide a probabilistic lifetime exposure model for children and adults, which accounts for intake via eight food types and inhalation, intestinal absorption, biliary excretion, and plastic-associated chemical exposure via a physiologically based pharmacokinetic submodel. The model probabilistically simulates microplastic concentrations in the gut, body tissue, and stool, the latter allowing validation against empirical data.

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The lack of standard approaches in microplastic research limits progress in the abatement of plastic pollution. Here, we propose and test rescaling methods that are able to improve the alignment of methods used in microplastic research. We describe a method to correct for the differences in size ranges as used by studies reporting microplastic concentrations and demonstrate how this reduces the variation in aqueous-phase concentrations caused by method differences.

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Microplastics have recently been detected in drinking water as well as in drinking water sources. This presence has triggered discussions on possible implications for human health. However, there have been questions regarding the quality of these occurrence studies since there are no standard sampling, extraction and identification methods for microplastics.

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Researcher and media alarms have caused plastic debris to be perceived as a major threat to humans and animals. However, although the waste of plastic in the environment is clearly undesirable for aesthetic and economic reasons, the actual environmental risks of different plastics and their associated chemicals remain largely unknown. Here we show how a systematic assessment of adverse outcome pathways based on ecologically relevant metrics for exposure and effect can bring risk assessment within reach.

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Recent studies suggest size-selective removal of small plastic particles from the ocean surface, an observation that remains unexplained. We studied one of the hypotheses regarding this size-selective removal: the formation of a biofilm on the microplastics (biofouling). We developed the first theoretical model that is capable of simulating the effect of biofouling on the fate of microplastic.

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Most studies on buoyant microplastics in the marine environment rely on sea surface sampling. Consequently, microplastic amounts can be underestimated, as turbulence leads to vertical mixing. Models that correct for vertical mixing are based on limited data.

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