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 sa...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 （St）. 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%.展开更多
Frozen soils or those with permafrost cover large areas of the earth's surface and support unique vegetative ecosystems. Plants growing in such harsh conditions have adapted to small niches, which allow them to su...Frozen soils or those with permafrost cover large areas of the earth's surface and support unique vegetative ecosystems. Plants growing in such harsh conditions have adapted to small niches, which allow them to survive. In northern Alaska, USA, both moist acidic and non-acidic tundra occur, yet determination of frozen soil p Hs currently requires thawing of the soil so that electrometric pH methods can be utilized. Contrariwise, a portable X-ray fluorescence(PXRF) spectrometer was used in this study to assess elemental abundances and relate those characteristics to soil pH through predictive multiple linear regressions. Two operational modes, Soil Mode and Geochem Mode, were utilized to scan frozen soils in-situ and under laboratory conditions, respectively, after soil samples were dried and ground. Results showed that lab scanning produced optimal results with adjusted coefficient of determination(R^2) of 0.88 and 0.33 and root mean squared errors(RMSEs) of 0.87 and 0.34 between elemental data and lab-determined pH for Soil Mode and Geochem Mode, respectively. Even though the presence of ice attenuated fluoresced radiation under field conditions, adjusted R^2 and RMSEs between the datasets still provided reasonable model generalization(e.g., 0.73 and 0.49 for field Geochem Mode). Principal component analysis qualitatively separated multiple sampling sites based on elemental data provided by PXRF, reflecting differences in the chemical composition of the soils studied. Summarily, PXRF can be used for in-situ determination of soil pH in arctic environments without the need for sample modification and thawing. Furthermore, use of PXRF for determination of soil pH may provide higher sample throughput than traditional eletrometric-based methods, while generating elemental data useful for the prediction of multiple soil parameters.展开更多
文摘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 （St）. 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%.
文摘Frozen soils or those with permafrost cover large areas of the earth's surface and support unique vegetative ecosystems. Plants growing in such harsh conditions have adapted to small niches, which allow them to survive. In northern Alaska, USA, both moist acidic and non-acidic tundra occur, yet determination of frozen soil p Hs currently requires thawing of the soil so that electrometric pH methods can be utilized. Contrariwise, a portable X-ray fluorescence(PXRF) spectrometer was used in this study to assess elemental abundances and relate those characteristics to soil pH through predictive multiple linear regressions. Two operational modes, Soil Mode and Geochem Mode, were utilized to scan frozen soils in-situ and under laboratory conditions, respectively, after soil samples were dried and ground. Results showed that lab scanning produced optimal results with adjusted coefficient of determination(R^2) of 0.88 and 0.33 and root mean squared errors(RMSEs) of 0.87 and 0.34 between elemental data and lab-determined pH for Soil Mode and Geochem Mode, respectively. Even though the presence of ice attenuated fluoresced radiation under field conditions, adjusted R^2 and RMSEs between the datasets still provided reasonable model generalization(e.g., 0.73 and 0.49 for field Geochem Mode). Principal component analysis qualitatively separated multiple sampling sites based on elemental data provided by PXRF, reflecting differences in the chemical composition of the soils studied. Summarily, PXRF can be used for in-situ determination of soil pH in arctic environments without the need for sample modification and thawing. Furthermore, use of PXRF for determination of soil pH may provide higher sample throughput than traditional eletrometric-based methods, while generating elemental data useful for the prediction of multiple soil parameters.
