The heavy metals (HMs) usually have high natural background levels in lead-zinc mines. Strengthening the ecological risk assessment and accurate identification sources of HMs is an important component of land resource utilization and food security. A total of 795 soil samples (with a depth of 0~20 cm) were collected in Hezhang County, an area of typical high background levels of HMs with more than 18 large lead-zinc deposits. In this study, inductively coupled plasma emission spectrometry (ICP-OES), inductively coupled plasma mass spectrometry (ICP-MS), atomic fluorescence spectrometry (AFS), and the potentiometric method (POT) were used to test the total concentration of HMs and pH values. The geographic information system was used to model the concentration distribution of HMs, and the ecological risk was assessed according to the source analysis results. The results suggest that: (1) the mean concentration of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn were 24.55, 2.25, 176.4, 89.6, 0.19, 64.2, 102, and 257 mg·kg⁻¹, respectively, which exceeded the average background value of soils in Guizhou Province by 1.23, 3.41, 1.84, 2.80, 1.73, 1.64, 2.90, and 2.58 times, respectively, and the average concentrations of Cd, Cr, Cu, Ni, Pb and Zn exceed the screening values specified in soil contamination risk in agricultural land; (2) the results of enrichment factor (EF) showed that 29.73% of Cd are moderately polluted, and other HMs were slightly polluted in a small area or near the baseline value (EF ≈ 1); and (3) PMF analysis showed that there are five main sources, pyrite, lead-zinc ore, basalt, carbonate rock, and agricultural production, with the risk contribution ratios of 5.25%, 27.37%, 28.94%, 17.91%, and 20.53%, respectively.

Resources in deserts and sandy landscapes have potential for development, but existing surveys and sampling have not collected desert soil samples. As such, the geochemical background of these spaces remains unexplored due to the vastness and desolation of deserts. Therefore, researching the geochemical background values and geochemical baseline values of deserts is of long-term significance. Our research indicates that in addition to macrostructural environmental divisions, microelement geochemistry can also be used for geological unit zoning. In this paper, geochemical background and geochemical baseline values of 61 desert elements were calculated using the iterative method, frequency histograms method, and multifractal concentration-area method. It also analyzes the distribution characteristics of major, trace, and rare earth elements, and divides the 12 desert sand regions into different geochemical zones. This paper determines, for the first time, the geochemical background values of elements in Chinese deserts, filling the gap in the study of desert background values. By combining machine learning methods, different deserts have been divided into three geochemical zones. This research will greatly enhance our ability to interpret the geochemical distribution and evolutionary patterns of desert elements in China, and it has important scientific significance and practical value for desert research.

Studying surface geochemical anomalies is important for detecting the presence of mineral deposits. However, distinguishing inconspicuous geochemical anomalies is a challenge for geochemists. This paper studies geochemical quantitative prediction for Pb–Zn metallic mineral deposits by identifying inconspicuous surface geochemical anomalies mainly associated with the Permian and Jurassic strata in the middle-southern Da Hinggan Mountains metallogenic belt. Some new methods are employed to highlight weak surface geochemical anomalies. The weak surface geochemical anomalies of Pb and Zn are effectively highlighted by the average contrast values of Pb–Zn–Ag–Cd. The similarity coefficient with the large typical discovered deposits is used to identify new Pb–Zn mineralized anomalies and delineate new prospecting target areas. The denudation degree of mineral deposit is determined by the ratio of (W × Sn)/(As × Sb). The analogy method and areal productivity method are employed for resource prediction. Thirty-six prediction areas with Pb–Zn resources of 307.73 million tons are delineated. Five prediction areas are verified, and some new mineral deposits are proven by drilling. The verification results show that the predicted resources are very reasonable and credible. This paper is a successful case of quantitative prediction assessment of mineral resource potential, which can be used as a reference for future prospecting activities.

Particle size exerts significant control on the concentration of elements in stream sediments and is therefore critical in stream sediment-based geochemical exploration, which has proved important in China’s National Geochemical Mapping Project. There are various geographical landscapes in China with different distribution characteristics of stream sediments. Therefore, we studied the relationship between particle size and element distribution in stream sediments, which is always a crucial but challenging issue in geochemical surveys. The distributions of minerals and elements in eight size fractions of stream sediments (2–0.84, 0.84–0.42, 0.42–0.25, 0.25–0.177, 0.177–0.125, 0.125–0.096, 0.096–0.074, and <0.074 mm) from the Dongyuan W-Mo deposit in eastern China were studied. The results show that the 2–0.25 mm particle size fraction of stream sediments is composed mainly of rock debris and various minerals from broken bedrock upstream, while the <0.25 mm fraction is composed mainly of clay, individual minerals, and organic matter. The pilot survey results prove that using 2–0.25 mm as the sampling particle size fraction is better than using <0.25 mm, especially in geochemical prospecting and geological body delineation. Sampling the 2–0.25 mm particle size fraction of stream sediments can help to delineate proven ore bodies, ore-related anomalies, and geological bodies more effectively and more credibly. The suggested sampling particle size fraction for a stream sediment geochemical survey in a humid to semi-humid low mountain landscape in eastern China is therefore 2–0.25 mm, rather than the particle size fraction of <0.25 mm that was used for sampling in this area before. This paper depicts a successful example for determining the optimal sampling particle size fraction for stream sediment-based geochemical exploration.