Gong Cang, Tan Jun, Yang Weiqing, Tan Changhai, Wen Lang, Liu Jiufen, Gan Liming
Research Center of Applied Geology of China Geological Survey, Chengdu, 610039, China.
Key Laboratory of Natural Resource Coupling Process and Effects, Beijing, 100055, China.
Sci Rep. 2024 Nov 24;14(1):29108. doi: 10.1038/s41598-024-75161-2.
The identification and quantification of soil heavy metal (HM) pollution sources and the identification of driving factors is a prerequisite of soil pollution control. In this paper, the Sabaochaqu Basin of the Tuotuo River, located in the Tibetan Plateau and the headwater of the Yangtze River, was selected as the study area. The soil pollution was evaluated using geochemical baseline, and the source apportionment of soil HMs was performed using absolute principal component score-multiple linear regression (APCS-MLR), edge analysis (UNMIX) and positive matrix decomposition (PMF). The driver of the source factor was identified with the geodetector method (GDM). The results of pollution evaluation showed that the HM pollution of soil in the study area was relatively light. By comparison, UNMIX model was considered to be the preferred model for soil HMs quantitative distribution in this study area, followed by PMF model. The UNMIX model results show that source 1 (U-S1) was dominated by As, with a contribution rate of 53.31%; source 2 (U-S2) was dominated by Cd and Zn, whose contribution rates are 50.35% and 46.60% respectively; source 3 (U-S3) was dominated by Pb, with a contribution rate of 45.58%; source 4 (U-S4) was dominated by Cr, Cu, Hg and Ni, with contribution rates of 60.58%, 60.07%, 51.58% and 56.45%, respectively. The GDM results showed that the main driving factors of U-S1 were distance from lake (explanatory power q = 0.328) and distance from wind channel (q = 0.168), which were defined as long-distance migration sources. The main driving factors of U-S2 were parent material type (q = 0.269) and distance from Tuotuo river (q = 0.213), which were defined as freeze-thaw sources. The main driving factors of U-S3 were distance from town (q = 0.255) and distance from county road (Yanya Line) (q = 0.221), which were defined as human activity sources. The main drivers of U-S4 were V (q = 0.346) and Sc (q = 0.323), which were defined as natural sources. The GDM results of the 3 models were generally consistent with the analytical results of similar types of sources, especially the results of PMF model and Unmix model can basically verify each other. The research results can provide important theoretical reference for the analysis of HM sources in the soil of high-cold and high-altitude regions.
土壤重金属(HM)污染源的识别与量化以及驱动因素的确定是土壤污染控制的前提。本文选取位于青藏高原长江源头的沱沱河萨保岔区流域作为研究区域。采用地球化学基线对土壤污染进行评价,运用绝对主成分得分-多元线性回归(APCS-MLR)、边缘分析(UNMIX)和正定矩阵分解(PMF)对土壤重金属进行源解析。利用地理探测器法(GDM)确定源因子的驱动因素。污染评价结果表明,研究区域土壤重金属污染较轻。相比之下,UNMIX模型被认为是该研究区域土壤重金属定量分布的首选模型,其次是PMF模型。UNMIX模型结果显示,源1(U-S1)以As为主,贡献率为53.31%;源2(U-S2)以Cd和Zn为主,贡献率分别为50.35%和46.60%;源3(U-S3)以Pb为主,贡献率为45.58%;源4(U-S4)以Cr、Cu、Hg和Ni为主,贡献率分别为60.58%、60.07%、51.58%和56.45%。GDM结果表明,U-S1的主要驱动因素是距湖泊距离(解释力q = 0.328)和距风道距离(q = 0.168),定义为长距离迁移源。U-S2的主要驱动因素是母质类型(q = 0.269)和距沱沱河距离(q = 0.213),定义为冻融源。U-S3的主要驱动因素是距城镇距离(q = 0.255)和距县道(雁崖线)距离(q = 0.221),定义为人类活动源。U-S4的主要驱动因素是V(q = 0.346)和Sc(q = 0.323),定义为自然源。3种模型的GDM结果与同类源的分析结果总体一致,尤其是PMF模型和Unmix模型的结果基本可以相互验证。研究结果可为高寒高海拔地区土壤重金属来源分析提供重要的理论参考。