Portable X-ray fluorescence spectrometry (pXRF) is an analytical technique that can be used for rapid and non-destructive analysis in the field. However, the testing accuracy and precision for trace elements are significantly affected by the matrix effect, which comes mainly from major elements that constitute most of the matrix of a sample. To solve this problem, many methods based on linear regression models have been proposed, but when extreme values or outliers occur, the application of these methods will be greatly affected. In this study, 16 certified reference materials were collected for pXRF analysis, and the major elements most closely related to the elements to be measured were employed as correction indicators to calibrate the analysis results through the application of multiple linear regression analysis. Some statistical parameters were calculated to evaluate the correction results. Compared with the calibration data obtained from simple linear regression analysis without taking major elements into account, those corrected by the new method were of higher quality, especially for elements of Co, Zn, Mo, Ta, Tl, Pb, Cd and Sn. The results show that the new method can effectively suppress the influence of the matrix effect.

Rock weathering is the main source of element geochemical cycle, which has a very important impact on the environment. Three well-developed basalt weathering profiles in Changbai Mountain area are selected in this study, and the samples of parent rock, parent material layer, sedimentary layer, and leaching layer are systematically collected. The systematic study showed that the basalt in the study area experienced moderate chemical weathering under warm and humid climate conditions, with leaching of some major elements such as silicon and aluminum. The distribution of the rare earth elements (REE) in the weathering products recalls that of an alkali-basalt, with an evident fractionation between light- and heavy-REE. Such a feature is therefore referable to the parent volcanic rock, although with some degree of leaching.

This study comprehensively investigated the occurrence, sources, and potential toxicity risks of 16 PAHs in main urban area surface soils of Changchun, northeast China. The 16 total PAHs (Σ16PAHs) concentrations in surface soils decreased significantly along the commercial traffic district, industrial zone, residential zone, park zone, and outskirt farmland, ranging from 46.6 to 8870.8 ng/g, with a mean value of 1480.1ng/g and 4-ring PAHs were always the dominant constituents in all land used area soils. Based on ArcGIS mapping, higher concentrations of PAHs are mainly concentrated in the northeast region and the central historic district soils of Changchun city. Mixed pyrogenic sources and coal combustion were the dominant sources and contributed approximately 45% and 30% of the total soil PAHs, respectively. Toxicity risk assessment based on the toxic equivalent concentrations (BaPeq) of soil PAHs indicated the potential toxicity risks detected in this study were relatively moderate compared with other global cities, while some special attention still should be paid to hotspots with high PAHs concentrations surrounding the commercial traffic area and industrial zone in the northeast pattern of Changchun city. This study could be potentially useful for local governments targeted to control toxicity exposure, promote actions to alleviate PAHs contamination.

Identifying saline soils is of great importance for protecting land resources and for the sustainable development of agriculture. Total soil salinity (TSS) is the most commonly used indicator for determining soil salinization, but the application of soil geochemical data is rarely reported. In general, there is a significant relationship between TSS and the content of soil-soluble Na, which can be estimated by the difference between the bulk-soil Na₂O content and its background value. In this study, the partial least squares regression (PLSR) method was employed to calculate the Na₂O background value via a regression model between Na₂O and SiO₂, Al₂O₃, TFe₂O₃, Cr, Nb, and P in a 1:250,000 scale regional geochemical data set of soils in Jilin Province, NE China. We defined δNa as the difference between the bulk-soil Na₂O value and the regression background value, which can be used as a geochemical indicator to identify saline soils. One hundred and five samples with known TSS contents in the study area were selected to test the capability of the indicator δNa. The result shows that the identification accuracy can be up to 75%, indicating that the indicator can provide a new means for saline soil identification.