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  • Microplastics
  • American Chemical Society  (1)
  • Frontiers Media  (1)
  • American Institute of Physics (AIP)
  • MDPI Publishing
  • 1
    Publication Date: 2022-10-21
    Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Colson, B. C., & Michel, A. P. M. Flow-through quantification of microplastics using impedance spectroscopy. ACS Sensors, 6(1), (2021): 238–244, doi:10.1021/acssensors.0c02223.
    Description: Understanding the sources, impacts, and fate of microplastics in the environment is critical for assessing the potential risks of these anthropogenic particles. However, our ability to quantify and identify microplastics in aquatic ecosystems is limited by the lack of rapid techniques that do not require visual sorting or preprocessing. Here, we demonstrate the use of impedance spectroscopy for high-throughput flow-through microplastic quantification, with the goal of rapid measurement of microplastic concentration and size. Impedance spectroscopy characterizes the electrical properties of individual particles directly in the flow of water, allowing for simultaneous sizing and material identification. To demonstrate the technique, spike and recovery experiments were conducted in tap water with 212–1000 μm polyethylene beads in six size ranges and a variety of similarly sized biological materials. Microplastics were reliably detected, sized, and differentiated from biological materials via their electrical properties at an average flow rate of 103 ± 8 mL/min. The recovery rate was ≥90% for microplastics in the 300–1000 μm size range, and the false positive rate for the misidentification of the biological material as plastic was 1%. Impedance spectroscopy allowed for the identification of microplastics directly in water without visual sorting or filtration, demonstrating its use for flow-through sensing.
    Description: The authors thank the Richard Saltonstall Charitable Foundation and the National Academies Keck Futures Initiative (NAKFI DBS13) for their funding support.
    Keywords: Microplastics ; Plastics ; Impedance spectroscopy ; Dielectric properties ; Instrumentation ; Particle detection ; Flow-through ; Environmental sensing
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-10-26
    Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in DiBenedetto, M. H. Non-breaking wave effects on buoyant particle distributions. Frontiers in Marine Science, 7, (2020): 148, doi:10.3389/fmars.2020.00148.
    Description: The dispersal of buoyant particles in the ocean mixed layer is influenced by a variety of physical factors including wind, waves, and turbulence. Microplastics observations are often made at the free surface, which is strongly forced by surface gravity waves. Many studies have used numerical simulations to examine how turbulence and wave effects (e.g., breaking waves, Langmuir circulation) control buoyant particle dispersal at the ocean surface. However these simulations are not wave phase-resolving. Therefore, the effects of an unsteady free surface due to surface gravity waves remain unknown in this context. To address this, we develop an analytical model for the distribution of buoyant particles as a function of wave-phase under wind-wave conditions in deep-water. Using this analytical model and complementary numerical simulations, we quantify the effects of a nonbreaking, monochromatic, progressive wave train on the equilibrium vertical and horizontal distributions of buoyant particles. We find that waves result in non-uniform horizontal distributions of particles with more particles under the wave crests than the troughs. We also find that the waves can stretch or compress the equilibrium vertical distribution. Finally, we consider the effects of waves on the sampling of microplastics with a towed net, and we show that waves have the ability to lower the measured concentrations relative to nets sampling without the influence of waves.
    Description: This work was supported by the Postdoctoral Scholar Program at the Woods Hole Oceanographic Institution, and by the US National Science Foundation under grant no. CBET-1706586.
    Keywords: Ocean waves ; Microplastics ; Particle distributions ; Sampling error ; Particle-laden flows ; Neuston nets
    Repository Name: Woods Hole Open Access Server
    Type: Article
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