Unsupervised pattern-recognition and radiological risk assessment applied to the evaluation of behavior of rare earth elements, Th, and U in monazite sand

Environmental science and pollution research international(2022)

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摘要
The Brazilian coast is rich in monazite which is found in beach sand deposits. In this study, the composition of the monazite sands from beaches of State of Espírito Santo, Brazil, was investigated. The concentrations of rare earth elements (REEs), Th, and U were determined by inductively coupled plasma mass spectrometry (ICP-MS). In the studied region, the mean concentration of investigated elements increased in the following order: Tm < Yb < Ho < Lu < Eu < Er < Tb < Dy < U < Y < Th < Gd < Sm < Pr < Nd < La < Ce. The sampling sites were classified into three clusters and discriminated by the concentrations of REEs, Th, and U found. In general, the radiological risk indices were higher than the established limits, and the risk of developing cancer was estimated to be higher than the world average. Graphical abstract
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关键词
Artificial intelligence,KSOM,Monazite,Radiation,Rare earth elements
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