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An evaluation of methodologies for calibrating...
Journal article

An evaluation of methodologies for calibrating Itrax X-ray fluorescence counts with ICP-MS concentration data for discrete sediment samples

Abstract

Core-scanning X-ray Fluorescence (XRF-CS) is a well-established technique for rapid (<30 s/interval) analysis of sediment core geochemistry at sub-mm resolution with substantially less analytical cost compared to methods that rely on physical sub-sampling. Due to issues inherent in analyzing wet sediment of heterogeneous particle size and composition with irregular surface topography using XRF, XRF-CS results are generally considered semi-quantitative. The result of early efforts to calibrate XRF-CS data with conventional geochemical results (e.g. WD- or ED-XRF, ICP-AES, ICP-MS) showed weak correlations for less abundant or poorly detectable elements, however, more recent methods have been proposed to improve accuracy. These methods include: 1) converting XRF-CS results to dry mass concentration; 2) normalizing XRF-CS data to conservative elements (Si, Ca), total counts/second, or X-ray scatter (CIR); and 3) calibration of data using multivariate analysis of elemental log-ratios (MLC). These approaches are not yet widely employed, and require additional testing on a variety of sediment compositions. Recently developed equipment enables analysis of discrete sediment samples, providing >30 replicate analyses for up to 180 samples in a single XRF-CS run. These replicate measurements allow for rigorous testing of precision and accuracy of XRF-CS data. To determine the ideal method of data transformation to improve XRF-CS calibration to quantitative geochemical concentration, 100 lake sediment-surface samples collected from Harvey Lake, New …

Authors

Gregory BRB; Patterson RT; Reinhardt EG; Galloway JM; Roe HM

Journal

Chemical Geology, Vol. 521, , pp. 12–27

Publisher

Elsevier

Publication Date

September 2019

DOI

10.1016/j.chemgeo.2019.05.008

ISSN

0009-2541

Labels

McMaster Research Centers and Institutes (RCI)