Multi-element analysis of discrete samples via X-Ray fluorescence or inductively coupled plasma spectrometry is commonly used to characterise the composition of solid geo-materials for environmental geochemical characterisation. Conventional geochemical analysis of individual samples is time consuming and costly, which often results in low-resolution sampling with the danger of missing crucial information. X-ray fluorescence Core Scanning (XCS) provides an alternative method to obtain elemental information, which can be potentially used quantitatively when combined with the Multivariate Log-ratio Calibration (MLC) approach. The suitability of the XCS-MLC method was tested for environmental geochemical characterisation on four terrestrial Holocene-Pleistocene sediment cores that have a variable lithology (clay, sand, peat, with variable calcareous content), were stored at ambient room conditions and scanned post sampling. Element contents based on XCS-MLC and conventional geochemical analysis proved to be comparable (R2 > 0.5) for Al, Ca, Cr, Fe, K, Sr, Mn, Ni, Pb, Rb, S, Si, Ti, Zn, Zr, and also for Br as proxy for organicmatter. For As, Cu and Ba the correlations were less satisfactory (R 2 < 0.4) partially due to the low concentration ranges present in these sediments. For some samples aberrant high values for Ca, Fe, S, and Zn were introduced by application of the MLC method due to extrapolation outside the MLC-calibrated range. Similar to the conventional element analyses the XCS-MLC approach has the ability to retrieve quantitative element contents and enable the calculation of mineral phases such as calcium carbonate and reactive iron species. Both conventional and XCS-MLC methods reproduced the average contents per sediment layer and mostly their ranges. Nevertheless, local features such as diagenetic enrichments were not always evident from the discrete samples. Thus, a better understanding of the spatial heterogeneity in geochemical and mineralogical contents within the sediment layers was obtained with the additional XCS-MLC data. Our study shows that also cores stored under unfavourable conditions can be reliably re-analysed with XCS to generate high resolution records.
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