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Settling velocity,effective density,and mass composition of suspended sediment in a coastal bottom boundary layer,Gulf of Lions,France
Institution:1. Department of Geosciences and Natural Resource Management, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen K, Denmark;2. CENPERM, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen K, Denmark;1. CAS Key Laboratory of Marine Geology and Environment, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China;2. Laboratory for Marine Mineral Resources, Pilot National Laboratory for Marine Science and Technology, Qingdao 266071, China;3. University of Chinese Academy of Sciences, Beijing 100049, China;4. Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao 266071, China;5. Department of Oceanography, Inha University, 100 Inharo, Incheon 22212, Republic of Korea
Abstract:Particle size distribution and size-specific settling velocity are critical parameters for understanding the transport of fine sediment on continental margins. In this study, observed floc size versus settling velocity, volume distributions of particles 2 μm–1 cm in diameter, and calculated effective densities for all particle sizes provided estimates of the mass distribution in suspension, which is used to apportion mass among component particles, microflocs, and macroflocs. Measurements were made during relatively quiescent environmental conditions. Observations of size distributions based on mass demonstrate an increase in the component particle fraction through time. The increase in the percentage of component particles in suspension had implications on water column properties, as small changes in the component particle fraction affected water column optical transmission in a way that was not as easily detected by changes in the volume concentration distribution or total mass concentration. Flocs larger than 133 μm in diameter only comprised one quarter to one third of the mass in suspension. This finding may explain why suspension bulk clearance rates are often an order of magnitude lower than those predicted by other methods.
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