Abstract
X‐ray fluorescence (XRF) scanning of marine sediment has the potential to yield near‐continuous and high‐resolution records of elemental abundances, which are often interpreted as proxies for paleoceanographic processes over different time scales. However, many other variables also affect scanning XRF measurements and convolute the quantitative calibrations of element abundances and comparisons of data from different labs. Extensive interlab comparisons of XRF scanning results and calibrations are essential to resolve ambiguities and to understand the best way to interpret the data produced. For this study, we sent a set of seven marine sediment sections (1.5 m each) to be scanned by seven XRF facilities around the world to compare the outcomes amidst a myriad of factors influencing the results. Results of raw element counts per second (cps) were different between labs, but element ratios were more comparable. Four of the labs also scanned a set of homogenized sediment pellets with compositions determined by inductively coupled plasma‐optical emission spectrometry (ICP‐OES) and ICP‐mass spectrometry (MS) to convert the raw XRF element cps to concentrations in two ways: a linear calibration and a log‐ratio calibration. Although both calibration curves are well fit, the results show that the log‐ratio calibrated data are significantly more comparable between labs than the linearly calibrated data. Smaller‐scale (higher‐resolution) features are often not reproducible between the different scans and should be interpreted with caution. Along with guidance on practical calibrations, our study recommends best practices to increase the quality of information that can be derived from scanning XRF to benefit the field of paleoceanography.
Key Points
Seven international labs X‐ray fluorescence (XRF) scanned the same seven sections from Integrated Ocean Drilling Program sediment cores
XRF scans are compared as element counts per second and ratios and calibrated with ICP
Log‐ratio calibrations are recommended to achieve the most quantitative outcomes
