Gong Cang, Wang Liang, Wang Shun-Xiang, Zhang Zhi-Xiang, Dong Hang, Liu Jiu-Fen, Wang De-Wei, Yan Bu-Qing, Chen Ying
Civil-Military Integrated Geological Survey Center of China Geological Survey, Chengdu 611732, China.
Natural Resources Comprehensive Survey Command Center of China Geological Survey, Beijing 100055, China.
Huan Jing Ke Xue. 2022 Oct 8;43(10):4566-4577. doi: 10.13227/j.hjkx.202112077.
Geographic detectors can quickly detect spatial stratified heterogeneity and quantitatively reveal the intensity of driving factors of heavy metal content, which is of great significance for the prevention, control, and remediation of soil heavy metal pollution. In order to reveal the spatial differentiation and influencing factors of soil heavy metal content on the town-scale, 788 topsoil samples were collected from a town in the hinterland of Chengdu Plain. Soil heavy metal (Cd, Hg, As, Cu, Pb, Cr, Zn, and Ni) pollution risk assessments were carried out by using the geo-accumulation index method. Additionally, based on the geographic detector model, 15 factors such as soil properties, topography, soil forming factors, and distance were taken as independent variables, and the contents of each heavy metal element were taken as dependent variables to explore the spatial differentiation and influencing factors of heavy metal content in soils. The results showed that:the average contents of Hg, As, Pb, Cr, Cu, Ni, and Zn in the study area were 1.06-1.93 times the background value of Chengdu, and the content of Cd was lower than the background value; among them, Hg reached the light pollution level, and the other seven heavy metals were at the non-pollution level. The spatial distribution of eight heavy metals was significantly different, the correlation among the elements was significant, and a significant correlation was found between most heavy meals with soil properties; however, the correlation with distance factor and topographic factor was relatively weak. The factor detection showed that TP, TK, pH, TOC, elevation, and distance from the railway had the most significant explanatory power for the heavy metal contents. Interaction detection showed that the interaction between soil properties and other factors was the dominant factor for the spatial variation in heavy metals, and elevation, distance from residential area, distance from railways, and distance from industrial areas were also important factors. Risk detection showed that Hg had the most significant difference in the subregion of elevation and distance from railway, whereas the other seven heavy metals had the most significant difference in the sub-regions of influencing factors of soil properties. The spatial distribution of heavy metals varied significantly in soil at the town-scale, which was closely related to soil properties, topography, and human activities in the study area.
地理探测器能够快速检测空间分层异质性，并定量揭示重金属含量驱动因素的强度，这对于土壤重金属污染的预防、控制和修复具有重要意义。为了揭示城镇尺度上土壤重金属含量的空间分异及其影响因素，在成都平原腹地某镇采集了788个表层土壤样本。采用地累积指数法对土壤重金属（镉、汞、砷、铜、铅、铬、锌和镍）污染风险进行评估。此外，基于地理探测器模型，选取土壤性质、地形、成土因素和距离等15个因素作为自变量，各重金属元素含量作为因变量，探究土壤中重金属含量的空间分异及其影响因素。结果表明：研究区汞、砷、铅、铬、铜、镍和锌的平均含量是成都背景值的1.06 - 1.93倍，镉含量低于背景值；其中，汞达到轻度污染水平，其他7种重金属处于无污染水平。8种重金属的空间分布差异显著，元素间相关性显著，多数重金属与土壤性质显著相关；但与距离因子和地形因子的相关性相对较弱。因子探测表明，总磷、全钾、pH值、总有机碳、海拔以及距铁路距离对重金属含量的解释力最为显著。交互探测表明，土壤性质与其他因素之间的交互作用是重金属空间变异的主导因素，海拔、距居民区距离、距铁路距离和距工业区距离也是重要因素。风险探测表明，汞在海拔和距铁路距离子区域差异最为显著，而其他7种重金属在土壤性质影响因子子区域差异最为显著。城镇尺度土壤中重金属空间分布差异显著，与研究区土壤性质、地形及人类活动密切相关。
