Copyright © 2018 Mohammadali Sarparandeh, Ardeshir Hezarkhani. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. International Journal of Advanced Geosciences, 6 (2) (2018) 205-208 International Journal of Advanced Geosciences Website: www.sciencepubco.com/index.php/IJAG doi: 10.14419/ijag.v6i2.13151 Research paper Principal component analysis of rare earth elements in Sechahun iron deposit, central Iran Mohammadali Sarparandeh 1 , Ardeshir Hezarkhani 1 * 1 Department of mining and metallurgical engineering, Amirkabir university of technology *Corresponding author E-mail: ardehez@aut.ac.ir Abstract Principal component analysis (PCA) is a sufficient way for finding the groups of correlated features. In geochemical exploration of precious metals, it helps to cluster the elements. Especially for rare earth elements (REEs), because of multiplicity of parameters, the proposed method helps to have a better interpretation. Geochemical exploration programs aim to find the hidden information about specific ele- ment(s), its abundance, its behavior and its relation with minerals and some other elements. REEs are a group of elements with same chemical behavior. However, some chemical characteristics of light rare earth elements (LREEs) and heavy rare earth elements (HREEs) are different. In this study, relationship between these elements was investigated by applying PC analysis method in Kiruna-type iron ore deposit of Se-Chahun in Central Iran. The four first PCs covered the most variances of the REEs. All the elements showed a correlation together with exception of La, Ce, Nd, Yb and Y. Results of PC analysis are related to the anomaly of Rare earth elements. It can be concluded that in anomalous areas, loadings of the principal components are affected by variance and anomalous content of the elements. Keywords: Central Iran; Geochemical Exploration; Principal Component Analysis (PCA); Rare Earth Elements (Rees); Se-Chahun Deposit 1. Introduction The rare earth elements, lanthanum to lutetium (atomic numbers 57—71), are members of group IIIA in the periodic table and all have very similar chemical and physical properties (Henderson 1984). The REEs are often broken into two groups: light rare earth elements (LREEs)—lanthanum through europium (atomic numbers 57-63) and the heavier rare earth elements (HREEs)—gadolinium through lutetium (atomic numbers 64-71) (Humphries 2013). Yt- trium is often grouped with the HREEs because of its similar chem- ical properties (Samson and Wood 2004). In Kiruna type iron de- posit of Se-Chahun, Ce, Nd and La are more abundant among all REEs and almost all the analyzed samples are depleted from Eu and enriched in Yb and Y. It should be noted that principally, all depos- its contain much more LREE than HREE. Most of the deposits have a content of yttrium and other HREE of only a few percentages (Schuler et al. 2011). Different geological processes and thermodynamic conditions specify the distribution of REEs in various environments, each with its unique pattern. Therefore, the REEs are known as important ge- ochemical tracers for a wide range of geological processes and their abundances, ratios, isotope compositions, and normalized patterns are the important criteria for geochemical exploration studies (Ber- ger et al. 2014, Cole et al. 2014, Tsay et al. 2014). The REEs are mainly concentrated in specific types of rocks and deposits. In ad- dition, they are potentially known as an important by-product of iron oxide-apatite (IOA) deposits (Simandl 2014). The relationships in a geochemical dataset can be assessed using two approaches: in term of samples (clustering analysis) and in term of variables (i.e. elements). For example, in this regard, Levitan et al. (2015) applied multivariate statistical treatment consisted of hi- erarchical cluster analysis and principal component analysis (PCA) for analysis of soil geochemical data collected from the Coles Hill uranium deposit, Virginia, USA. PCA is a classic multivariate anal- ysis technique which has been commonly used to examine relation- ships among variables. Since only the first few PCs possess most of variances of input data sets which are retained for further interpre- tation, PCA is an efficient tool in reducing dimension of multi-var- iable data sets (Wang et al. 2014). Sadeghi et al. (2013) used PCA for spatial interpretations of distributions of rare earth elements (REEs) in Sweden using the Forum of European Geological Sur- veys (FOREGS) geochemical database of topsoil, subsoil and stream sediment compositions. They showed that the light rare earth elements (LREEs) La, Ce, Nd and Sm have good correlations among each other but not with Eu, and the heavy rare earth elements (HREEs) including Tb, Dy, Ho, Er, Tm, Yb and Lu also show good correlations among each other but not necessarily with the LREEs. Successful results of this study lead us to use PCA for evaluation of REEs relationships in Se-Chahun iron deposit which is prone to REEs. 2. General settings of study area There are significant concentrations of iron ore in central and north east of Iran. Magnetite is the main mineral in most of important iron ore bodies. Obtrusive elements are often phosphorus and sulfur in the form of apatite, pyrite and seldom chalcopyrite. Iron deposits of Iran can be divided into two main groups: magmatogene and vol- cano sediments. In most iron ore deposits of Iran, metasomatism is the main reason of concentrating (NISCO 1975). Systematic explo- ration work during the 1960s and 1970s outlined 34 zones of aero- magnetic anomalies between Bafq in the south to Saghand in the north with a total reserve of more than 1500 Mt iron ore (Torab 2008). Moore and Modabberi (2003) suggested that the separation of an iron oxide melt and the ensuing hydrothermal processes dom-