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Vertical Distribution of Microplastics in the Water Column and Surficial Sediment from the Milwaukee River Basin to Lake Michigan.

Peter L LenakerAustin K BaldwinSteven R CorsiSherri A MasonPaul C ReneauJohn W Scott
Published in: Environmental science & technology (2019)
Microplastic contamination was studied along a freshwater continuum from inland streams to the Milwaukee River estuary to Lake Michigan and vertically from the water surface, water subsurface, and sediment. Microplastics were detected in all 96 water samples and 9 sediment samples collected. Results indicated a gradient of polymer presence with depth: low-density particles decreased from the water surface to the subsurface to sediment, and high-density particles had the opposite result. Polymer identification results indicated that water surface and subsurface samples were dominated by low-density polypropylene particles, and sediment samples were dominated by more dense polyethylene terephthalate particles. Of the five particle-type categories (fragments, films, foams, pellets/beads, and fibers/lines), fibers/lines were the most common particle-type and were present in every water and sediment sample collected. Fibers represented 45% of all particles in water samples and were distributed vertically throughout the water column regardless of density. Sediment samples were dominated by black foams (66%, identified as styrene-butadiene rubber) and to a lesser extent fibers/lines (29%) with approximately 89% of all of the sediment particles coming from polymers with densities greater than 1.1 g cm-3. Results demonstrated that polymer density influenced partitioning between the water surface and subsurface and the underlying surficial sediment and the common practice of sampling only the water surface can result in substantial bias, especially in estuarine, harbor, and lake locations where water surface concentrations tend to overestimate mean water column concentrations.
Keyphrases
  • heavy metals
  • polycyclic aromatic hydrocarbons
  • healthcare
  • high density
  • organic matter
  • climate change
  • optical coherence tomography
  • neural network