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.

Black soils are vital agricultural resources, and assessing heavy metal contamination in black soils is of great significance to the sustainable development of agriculture and the environment. In this study, 1246 surface soil samples were collected from the central-eastern part of Changchun, where phaeozems and chernozems are widely distributed, and the As, Hg, Cr, Cd, and Pb concentrations were determined to investigate the pollution status in the black soils by the geoaccumulation index (I_geo). To eliminate the influence of background variation and improve the calculation accuracy of the I_geo values, the local background values of these five elements were estimated after classifying the samples into three clusters with the k-means clustering method. The I_geo calculated with the local background values not only identified the pollution that is difficult to recognize in the low-background areas but also eliminated the easily misidentified pollution in the high-background areas. The I_geo results show that the black soils are mainly contaminated with Hg, followed by Cd and Pb, and are almost free from the pollution of As and Cr. The further the sampling sites are from urban areas, the milder the soil pollution is. A positive matrix factorization (PMF) analysis shows that industrial activities and coal burning contributed the most to the heavy metal pollution in the black soils, followed by agricultural activities, which should be paid more attention to.

The Huolin River is an important water supply source for the wetland located in western Jilin province, especially the river flooding in the lower reaches of the basin. In recent years, the degree of aridity and salinization of the wetlands has increased. To prevent the further deterioration of the ecological system, water conservancy projects and irrigation systems were constructed to ensure water safety. What effects on the ecological system and biological diversity were induced by all the measures and constructions is not clear. The “emergency project” of the water recession of the Huolin River is taken as example. In the analysis, the project is divided into two stages, five indicators for criteria tier were selected, and for index tier, 21 indicators during the implementation stage and 15 indicators during the operation stage were selected for constructing the analytic hierarchy process (AHP) model. By using expert scoring to determine the weight of each indicator, the impact index and degree of water conservancy of projects on biodiversity are calculated. The results show that at the level of the impact categories, ecological landscape is identified as a key influence factor. At the index level, the occupied area of the landscape type, the changes in patch number, the water conservation function, and the water purification quality are identified as corresponding key impact indicators. The biodiversity overall impact index is −23.45, which means the negative impact and the degree is medium to low. Meanwhile, for the implementation stage, the index is −51.58, which indicates a medium to low negative impact, while for the operation stage, the index is 33.66, which indicates a medium to low positive impact. These results are analyzed and scientifically evaluated and corresponding protection suggestions for the local area are proposed.

Eighteen organochlorine pesticides (OCPs) in soil samples from the Changchun central urban area, Northeast China were analyzed using accelerated solvent extraction combined with gas chromatography/mass spectrometry (ASE-GC/MS) for the purpose of elucidating their contamination status, distribution characteristics, influencing factors, and feasible dangers in this city region. The complete concentrations of OCPs ranged from 15.63 to 92.79 ng/g, with a geomean of 36.46 ng/g. Hexachlorocyclohexane(HCHs), dichlorodiphenyltrichoroethane (DDTs), and chlordanes were the most dominant OCPs, with γ-HCH and p,p′-DDT being the predominant isomers. Higher concentrations of OCPs often centered to the northeast and southwest of the Changchun metropolis, and these artificial influences contributed to the destiny of OCPs in the soils. The residues of OCPs were derived from the historic utility of the technological DDT, dicofol, and lindane. A Pearson’s correlation evaluation indicated that TOC was once a key factor controlling OCP accumulation. The ecological risk evaluation based on the soil quality guidelines (SQGs) advises that the presence of DDTs, lindane, and heptachlor may additionally pose a poisonous ecological danger to soil organisms. The contrast outcomes of the incremental lifetime cancer risk (ILCR) confirmed that the highest cancer risk of OCPs to the posed populace was once low, whilst some unique areas with excessive OCP residues ought to be given attention. The research results provide basic information for evaluating the extent of OCP pollution in the soil of major cities in Northeast China and can help authorities establish environmental protection regulations and soil remediation techniques.

Owing to the strong control bedrock geology may exert on the chemical composition of stream sediments, the determination of stream sediment geochemical anomalies is always affected by the lithology background in areas with variable lithologies. In this study, the expectation–maximization (EM) algorithm was used to separate lithologies of different chemical compositions in a 1: 200 000 scale regional geochemical data set of stream sediments in a lithologically complex region in Hunan province, SE China. The data set included 1024 minerogenic stream sediment samples which were analysed for Cu, La, Li, Be, Cr, Ni, Sr, V, Th, Ti and Zr. A comparison between Cu anomalies determined with and without taking into account the separation of lithologies was carried out. The result shows that stream sediment geochemical anomalies in lithologically complex regions can be determined in a more reasonable way by application of the EM clustering method. Strong but false or meaningless anomalies can be eliminated, and weak but important or meaningful anomalies are more clearly revealed.