10.30495/ijes.2021.685399

Identification of Geochemical Distribution of REEs Using Factor Analysis and Concentration-Number (C-N) Fractal Modeling in Granitoids, South of Varcheh 1:100000 Sheet, Central Iran

  1. Department of Geology, North Tehran Branch, Islamic Azad University, Tehran, Iran
  2. Soil Conservation and Watershed Management Research Department, Lorestan Agricultural and Natural Resources Research and Education Center, AREEO, Khoramabad, Iran

Revised: 2019-11-29

Accepted: 2020-12-04

Published in Issue 2021-10-01

How to Cite

Pirdadeh Beyranvand, D., Arian, M. A., Farhadinejad, T., & Ashja Ardalan, A. (2021). Identification of Geochemical Distribution of REEs Using Factor Analysis and Concentration-Number (C-N) Fractal Modeling in Granitoids, South of Varcheh 1:100000 Sheet, Central Iran. Iranian Journal of Earth Sciences, 13(4), 288-289. https://doi.org/10.30495/ijes.2021.685399

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Abstract

The purpose of the present research is delineating geochemical anomaly of REEs in granitoids in south of Varcheh 1:100,000 sheet by the use of C-N fractal model and classical statistical methods. We gathered and studied 59 rock samples for REEs by ICP-MS method in the laboratory of Iran Mineral Processing Research Center (IMPRC). The Concentration–Number (C-N) fractal model was used to delineate elemental thresholds. According to the results, the distribution of elemental concentration for Pr and Sm were divided to three classifications and Ce, La, Nd and Y had five geochemical populations in the area. The classical statistics methods were able to separate three geochemical populations. The results obtained by this study showed that the separation of geochemical anomalies for REEs using C-N fractal model and classical statistics methods yielded to the same results. Meanwhile, the high ratio of LREE to HREE in rock samples as well as high P content, assigns monazite, apatite, and sphene as a possible source of REEs in the study area.

Keywords

  • REEs,
  • Varcheh,
  • Concentration-Number (C-N) fractal modeling,
  • factor analysis