Influence of Ice on Soil Elemental Characterization via Portable X-Ray Fluorescence Spectrometry

D. C. Weindorf, N. Bakr, Y. Zhu, A. Mcwhirt, C. L. Ping, G. Michaelson, C. Nelson, K. Shook, S. Nuss

Research output: Contribution to journalArticlepeer-review

38 Scopus citations


Field portable X-ray fluorescence (PXRF) spectrometry has become an increasingly popular technique for in-situ elemental characterization of soils. The technique is fast, portable, and accurate, requiring minimal sample preparation and no consumables. However, soil moisture > 20% has been known to cause fluorescence denudation and error in elemental reporting and few studies have evaluated the presence of soil moisture in solid form as ice. Gelisols (USDA Soil Taxonomy), permafrost-affected soils, cover a large amount of the land surface in the northern and southern hemispheres. Thus, the applicability of PXRF in those areas requires further investigation. PXRF was used to scan the elemental composition (Ba, Ca, Cr, Fe, K, Mn, Pb, Rb, Sr, Ti, Zn, and Zr) of 13 pedons in central and northern Alaska, USA. Four types of scans were completed: 1) in-situ frozen soil, 2) re-frozen soil in the laboratory, 3) melted soil/water mixture in the laboratory, and 4) moisture-corrected soil. All were then compared to oven dry soil scans. Results showed that the majority of PXRF readings from in-situ, re-frozen, and melted samples were significantly underestimated, compared to the readings on oven dry samples, owing to the interference expected by moisture. However, when the moisture contents were divided into > 40% and < 40% groups, the PXRF readings under different scanning conditions performed better in the group with < 40% moisture contents. Most elements of the scans on the melted samples with < 40% moisture contents acceptably compared to those of the dry samples, with R2 values ranging from 0.446 (Mn) to 0.930 (Sr). However, underestimation of the melted samples was still quite apparent. Moisture-corrected sample PXRF readings provided the best correlation to those of the dry, ground samples as indicated by higher R2 values, lower root mean square errors (RMSEs), and slopes closer to 1 in linear regression equations. However, the in-situ (frozen) sample scans did not differ appreciably from the melted sample scans in their correlations to dry sample scans in terms of R2 values (0.81 vs. 0.88), RMSEs (1.06 vs. 0.85), and slopes (0.88 vs. 0.92). Notably, all of those relationships improved for the group with moisture contents < 40%.

Original languageEnglish
Pages (from-to)1-12
Number of pages12
Issue number1
StatePublished - Feb 2014


  • Gelisols
  • Key Words
  • Moisture
  • Permafrost
  • Proximal sensing
  • Regression


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