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.

In order to validate the applicability of pXRF for rapid in situ detection of heavy metals in urban soils and to accurately obtain an assessment of soil quality in Changchun, a city in northeast China, 164 soil samples from within the main urban area of Changchun were collected for pXRF analysis. The main stable elements Si and Ti were used to establish a matrix effect correction model, and the values of Cr (64.2 mg⋅kg⁻¹), Cu (43.8 mg⋅kg⁻¹), Zn (96.2 mg⋅kg⁻¹), As (20.9 mg⋅kg⁻¹), and Pb (57.4 mg⋅kg⁻¹) were predicted. The empirical findings indicate that the quality of soil data from the pXRF was improved to different degrees under the correction model, and it became a relatively reliable dataset; the order of improvement was Cu > Pb > Cr > Zn > As. A comprehensive assessment indicated that Changchun City is primarily contaminated by the heavy metals As, Pb, and Cu, with the main sources being automobile manufacturing and pharmaceutical chemical production. These findings align with previous studies and have produced favorable outcomes in practical applications. This rapid, non-destructive and economical detection method is very applicable and economical for the sustainable monitoring and control of heavy metals in large cities. This study provides a basis for rapid large-scale prediction of urban soil safety and protection of local human health.