Li Yuru, Wang Zihua, Liu Leiyu, Geng Yani, Zhang Jun
Shaanxi Provincial Key Laboratory of Disaster Monitoring and Mechanism Simulation, Baoji College of Arts and Science, Baoji, 721013, China.
Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang'an University, Xi'an, 710064, China.
Sci Rep. 2025 Apr 23;15(1):14040. doi: 10.1038/s41598-025-98881-5.
The issue of soil heavy metal contamination has garnered significant global attention, with the identification of heavy metal sources and their driving factors being crucial for the prevention and management of soil heavy metal pollution. This study introduces a comprehensive source-driver model integrating the Positive Matrix Factorization (PMF) model, Geographically Weighted Regression (GWR), and Geo-detector Model (GDM). Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was employed to quantify the concentrations of eight heavy metals in the soils of the lower reaches of the Qian River. The findings revealed that: (1) The average concentrations of the 8 heavy metals did not exceed the risk screening thresholds for soil environmental quality. Specifically, the mean concentrations of Ni, Zn, As, and Cd were 42.16, 102.07, 18.23, and 0.32 mg kg, respectively, which are 1.46, 1.47, 3.7, and 6.17 times higher than the background values for soil in Shaanxi Province, with Cd exhibiting a coefficient of variation of 0.58. This high degree of variation is attributed to anthropogenic activities. Spatially, each heavy metal was more heavily concentrated in the southeastern and northwestern regions of the study area. (2) The results of PMF model showed that soil heavy metals in the study area mainly came from nature, industry, agriculture, and traffic, and the contribution of each source was 19.12%, 23.42%, 36.85% and 20.61%. Notably, agricultural sources emerged as the predominant contributors to soil pollution in the region. (3) GDM and GWR results showed that distance from village, soil type and elevation were the main drivers of soil heavy metal pollution sources in the study area. This study provides a reference for the analysis of soil heavy metal sources, and the results can provide a theoretical basis for the prevention and control of soil heavy metal pollution in the study area.
土壤重金属污染问题已引起全球广泛关注，识别重金属来源及其驱动因素对于土壤重金属污染的预防和治理至关重要。本研究引入了一种综合源驱动模型，该模型整合了正定矩阵因子分解（PMF）模型、地理加权回归（GWR）和地理探测器模型（GDM）。采用电感耦合等离子体质谱法（ICP-MS）对千河下游土壤中8种重金属的含量进行了定量分析。研究结果表明：（1）8种重金属的平均含量均未超过土壤环境质量风险筛选值。具体而言，Ni、Zn、As和Cd的平均含量分别为42.16、102.07、18.23和0.32mg/kg，分别是陕西省土壤背景值的1.46、1.47、3.7和6.17倍，其中Cd的变异系数为0.58。这种高度的变异性归因于人为活动。在空间上，每种重金属在研究区域的东南部和西北部地区更为集中。（2）PMF模型结果表明，研究区域土壤重金属主要来源于自然、工业、农业和交通，各来源的贡献率分别为19.12%、23.42%、36.85%和20.61%。值得注意的是，农业源是该地区土壤污染的主要贡献者。（3）GDM和GWR结果表明，距村庄距离、土壤类型和海拔是研究区域土壤重金属污染源的主要驱动因素。本研究为土壤重金属来源分析提供了参考，研究结果可为研究区域土壤重金属污染的防治提供理论依据。
