基于富集因子法与MLR-APCS模型应用的农田土壤重金属人为来源定量识别

准确定量识别农田土壤重金属的人为污染来源对于后续实施精准防控具有重要意义。采集典型农业区土壤样品,基于富集因子法和多元线性回归-绝对主成分得分(MLR-APCS)模型对农田表层土壤重金属的人为来源进行定量识别研究。结果表明:研究区农田表层土壤中Pb、Cu、Zn、Cr、Ni均受到不同程度的人为污染影响,其平均含量相比当地背景土壤分别提高了112.37%、71.21%、59.38%、69.67%和64.54%。5种重金属富集因子顺序为Pb>Cu>Cr>Ni>Zn。其中,Pb总体已达到中等富集水平,来自人为污染源含量占比超过50%。基于人为源重金属含量,大气沉降和有机肥施用被识别为该研究区2种主要人为重金属污染来源。MLR-APCS模拟进一步表明:大气沉降对Pb、Cr、Ni的污染贡献率分别为42.41%、37.58%和37.26%,而有机肥施用对Cu、Zn的污染贡献率分别为41.67%和39.39%。综上,提出了一种可靠的农田土壤重金属人为来源定量识别方法,可推广应用于其他相似区域。

QUANTITATIVE IDENTIFICATION OF ANTHROPOGENIC HEAVY METAL SOURCES IN FARMLAND SOIL BASED ON ENRICHMENT FACTOR AND MLR-APCS MODEL

An accurate and quantitative identification of anthropogenic heavy metal sources in farmland soil is vital for the subsequent implementation of more precise prevention and control. In this study, soil samples were collected from a typical agricultural area, and the anthropogenic sources of heavy metals in the surface soils were quantitatively identified by using the enrichment factor(EF) and multiple linear regression of absolute principal component scores(MLR-APCS) model.Resultsshowed that heavy metals like Pb, Cu, Zn, Cr and Ni in the surface soil have been affected by anthropogenic sources to different extents. The average increases rates in Pb, Cu, Zn, Cr and Ni were 112.37%, 71.21%, 59.38%, 69.67% and 64.54% respectively, when comparing their total contents in the surface soils with the contents in the local background soils. The EF values of heavy metals decreased with the order of Pb, Cu, Cr, Ni and Zn. Among them, Pb reached a medium enrichment level, and its anthropogenic content was more than 50% of the total content. Based on the anthropogenic heavy metal contents, atmospheric deposition and livestock manure were identified as the two main anthropogenic heavy metal sources. The MLR-APCS simulation results showed that atmospheric deposition could contribute on average 42.41%, 37.58% and 37.26% of total Pb, Cr and Ni contents, respectively, while livestock manure contributed 41.67% of total Cu and 39.39% of total Zn contents. In general, this study provided a reliable method for quantitative identification of anthropogenic heavy metal sources in farmland soil, which can be applied in other similar areas.