@article{fdi:010075270,
  title = {{A} {SEM}-based method to determine the mineralogical composition and the particle size distribution of suspended sediment},
  author = {{P}inet, {S}. and {L}artiges, {B}. and {M}artinez, {J}ean-{M}ichel and {O}uillon, {S}ylvain},
  editor = {},
  language = {{ENG}},
  abstract = {{A} robust method for characterizing the mineralogy of suspended sediment in continental rivers is introduced. {I}t encompasses 3 steps: the filtration of a few milliliters of water, measurements of {X}-ray energy dispersive spectra using {S}canning {E}lectron {M}icroscopy ({SEM}), and robust machine learning tools of classification. {T}he method is applied to suspended particles collected from various {A}mazonian rivers. {A} total of more than 204,000 particles were analyzed by {SEM}-{EDXS} ({E}nergy {D}ispersive {X}-ray {S}pectroscopy), i.e. about 15,700 particles per sampling station, which lead to the identification of 15 distinct groups of mineralogical phases. {T}he size distribution of particles collected on the filters was derived from the {SEM} micrographs taken in the backscattered electron imaging mode and analyzed with {I}mage{J} freeware. {T}he determination of the main mineralogical groups composing the bulk sediment associated with physical parameters such as particle size distribution or aspect ratio allows a precise characterization of the load of the terrigenous particles in rivers or lakes. {I}n the case of the {A}mazonian rivers investigated, the results show that the identified mineralogies are consistent with previous studies as well as between the different samples collected. {T}he method enabled the evolution of grain size distribution from fine to coarse material to be described in the water column. {I}mplications about hydrodynamic sorting of mineral particles in the water column are also briefly discussed. {T}he proposed method appears well suited for intensive routine monitoring of suspended sediment in river systems.},
  keywords = {{M}ineralogy ; {S}canning {E}lectron {M}icroscopy ; {S}uspended sediment ; {M}achine learning ; {P}article size distribution ; {BRESIL} ; {AMAZONIE} ; {SOLIMOES} {COURS} {D}'{EAU} ; {MADEIRA} {COURS} {D}'{EAU} ; {AMAZONE} {COURS} {D}'{EAU}},
  booktitle = {},
  journal = {{I}nternational {J}ournal of {S}ediment {R}esearch},
  volume = {34},
  numero = {2},
  pages = {85--94},
  ISSN = {1001-6279},
  year = {2019},
  DOI = {10.1016/j.ijsrc.2018.10.005},
  URL = {https://www.documentation.ird.fr/hor/fdi:010075270},
}