Identification of Saharan dust particles in Pleistocene dune sand-paleosol sequences of fuerteventura (Canary Islands)
Publikation: Beitrag in Fachzeitschrift › Forschungsartikel › Beigetragen › Begutachtung
Beitragende
Abstract
Automated static image analysis and newly introduced evaluation techniques were applied in this paper to identify Saharan dust material in the unique sand-paleosol sequence of Fuerteventura (Canary Islands). Measurements of ~50,000 individual mineral particles per samples provided huge amount of granulometric data on the investigated sedimentary units. In contrast to simple grain size and shape parameters of bulk samples, (1) parametric curve-fitting allowed the separation of different sedimentary populations suggesting the presence of more than one key depositional mechanisms. Additional (2) Raman-spectroscopy of manually targeted individual particles revealed a general relationship among grain size, grayscale intensity and mineralogy. This observation was used to introduce the (3) intensity based assessment technique for identification of large number of quartz particles. The (4) cluster and (5) network analyses showed that only joint analysis of size, shape and grayscale intensity properties provided suitable results, there is no specific granulometric parameter to distinguish Saharan dust due to their irregular shape characteristics. The presented methods allowed the separation of Saharan dust-related quartz grains from local sedimentary deposits, but due to the lack of robust granulometric characterization of coarsest fractions and due to the diverse geochemical properties of North African sources, exact volumetric amount of deposited dust material and sedimentation rates could not be determined from these data.
Details
Originalsprache | Englisch |
---|---|
Seiten (von - bis) | 121-141 |
Seitenumfang | 21 |
Fachzeitschrift | Hungarian Geographical Bulletin |
Jahrgang | 67 |
Ausgabenummer | 2 |
Publikationsstatus | Veröffentlicht - 2018 |
Peer-Review-Status | Ja |
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- Automated image analysis, Canary Islands, Grain shape, Grain size, Saharan dust