基于APCS-MLR受体模型的农田土壤重金属源解析

定性、定量分析湘潭县农田土壤重金属的污染来源及源贡献率。以湘潭县农田土壤为研究对象,结合地统计学分析,利用数理统计方法相关性分析、因子分析和绝对因子分析/多元线性回归(APCS-MLR)受体模型],解析了研究区域内镉(Cd)、汞(Hg)、砷(As)、铅(Pb)、铬(Cr)、铜(Cu)、锌(Zn)和镍(Ni)8种重金属元素的来源及源贡献率。结果表明:研究区域内8种重金属元素中仅有Cd含量平均值超出了农用地土壤污染风险筛选值(0.3 mg·kg~(-1),pH≤5.5),且Cd的空间变异性较强,其次是Hg,两者均受人为活动影响较大。综合数理统计分析和地统计学分析,将土壤中8种重金属元素的主要来源归结为3个:工业源主要分布于湘潭县工矿企业密集的东北部,其对Cd、Pb、Zn、Hg具有较大贡献率,分别为65.36%、49.21%、43.43%和22.12%;农业源对As、Hg、Pb具有较大贡献率,分别为59.20%、24.97%和17.82%;自然源对Ni、Cu、Cr具有较大贡献率,分别为86.73%、87.87%和89.67%。研究区域内土壤重金属含量主要受工业活动和自然成土母质影响较大,应重点加强Cd的来源控制,并加强管理和修复治理进度,降低其风险水平。受体模型和地统计学的结合使用能有效地定性、定量解析农田土壤重金属的来源与源贡献率。

Source apportionment of heavy metals in farmland soil based on the APCS-MLR model

To analyze the source and contribution of heavy metals in the farmland soil of Xiangtan County, eight heavy metal elements consisting of cadmium(Cd), mercury(Hg), arsenic(As), lead(Pb), chromium(Cr), copper(Cu), zinc(Zn), and nickel(Ni) in Xiangtan County'' s farmland soil, were qualitatively and quantitatively analyzed using geostatistics and mathematical statistics including correlation analysis, factor analysis, and the absolute principal component scores/multiple linear regression(APCS-MLR) receptor model. The results showed that:among the eight heavy metals, only the average value of Cd exceeded the screening value for soil pollution risk control in agricultural land(GB 15618-2018), and the spatial variability of Cd was very strong, followed by Hg, both of which were significantly affected by human activities. Geostatistics and mathematical statistics analyses indicated that the eight heavy metal elements were primarily from three sources, with industrial sources predominant in the northeast of Xiangtan County, where most industrial and mining enterprises are located. The contribution of industrial sources to Cd, Pb, Zn, and Hg was 65.36%, 49.21%, 43.43% and 22.12%, respectively; agricultural sources''contribution to As, Hg, and Pb was 59.20%, 24.97%, and 17.82%, respectively; and natural sources contributed 86.73%, 87.87%, and 89.67% to Ni, Cu, and Cr, respectively. The heavy metal content in the study area was mainly affected by industrial activities and natural parent materials. Therefore, it is necessary to strengthen the source control of Cd, as well as the management and remediation processes, and reduce the risk level. The combination of the acceptor model and geostatistics can effectively analyze the source and contribution rate of heavy metals in farmland soil qualitatively and quantitatively.