首页|Sphalerite as a record of metallogenic information using multivariate statistical analysis: Constraints from trace element geochemistry
Sphalerite as a record of metallogenic information using multivariate statistical analysis: Constraints from trace element geochemistry
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NSTL
Elsevier
? 2021 Elsevier B.V.In this study, the dominant geological factor that influences the element distribution in sphalerite was determined and the behaviors of the elements under a single factor were investigated (e.g., temperature). To this end, two multivariate statistical analysis methods, namely, principal component analysis (PCA) and factor analysis (FA), were performed on a published sphalerite dataset containing 1336 analysis points from 52 deposits. The PCA produced five element clusters, which were each controlled by the five dominant factors identified by the FA (including magmatic-derived materials, temperature, pH, element remobilization, and dynamic recrystallization). Furthermore, the influence of temperature on the trace element composition of sphalerite was quantitatively expressed based on the corresponding homogenization temperature of fluid inclusions from 27 deposits, i.e., TFAS (°C) = (32.22 ± 1.88) × FAS + (245.49 ± 3.79) (Ra2 = 0.918). The above research was then applied to the sphalerite from the Baoshan Cu-Pb-Zn deposit to reveal its metallogenic conditions. The results indicate that from the central-western mining districts to the northern mining districts, the contributions of the magmatic-derived materials, temperature, and fO2 decrease, whereas the contributions of the basement-derived hydrothermal fluid and pH increase.
Factor analysisGeothermometerPrincipal component analysisSphaleriteTrace elements
Zhang J.、Shao Y.、Liu Z.、Chen K.
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Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring Ministry of Education School of Geosciences and Info-Physics Central South University
NSTL
Elsevier
