基于APCS-MLR和PMF模型的赤泥堆场周边耕地土壤重金属污染源解析

为探究重庆某赤泥堆场周边耕地土壤重金属污染特征和来源，分析土壤中8种重金属元素（Cd、Cr、Hg、Ni、Pb、As、Cu和Zn）含量和空间分布特征，利用单因子污染指数法和内梅罗综合污染指数法对土壤重金属污染特征进行评价，并在相关性分析的基础上采用APCS-MLR和PMF模型定量解析重金属来源.结果表明，除土壤Cr外，其他7种重金属元素含量均值均高于重庆市土壤背景值.土壤重金属整体处于中度污染水平，其中Cd、Hg和As为中度污染，Pb、Cu、Ni和Zn为轻度污染.土壤Cr、Ni、Pb、Cu和Zn空间分布格局相似，相互间呈极显著正相关（P < 0.01）；Cd、Hg和As空间分布特征有较大差异，且相互间相关性不显著（P > 0.05）.源解析表明，研究区土壤重金属来源较为复杂，APCS-MLR和PMF模型均能解析出4种相同的污染源，分别为赤泥堆场渗滤排放和自然来源、火力发电排放源、农业活动与自然来源和有色金属冶炼排放源.两种模型源解析结果差异较小，APCS-MLR模型中4种污染源贡献率分别为51.8%、18.0%、15.9%和14.3%，而在PMF模型中分别为45.9%、12.8%、21.5%和19.8%.

Pollution Source Apportionment of Heavy Metals in Cultivated Soil Around a Red Mud Yard Based on APCS-MLR and PMF Models

In order to explore the characteristics and sources of heavy metal pollution in cultivated soil around a red mud yard in Chongqing， the content and spatial distribution characteristics of eight heavy metal elements （Cd， Cr， Hg， Ni， Pb， As， Cu， and Zn） in the soil were analyzed， and the single factor pollution index method and Nemerow comprehensive pollution index method were used to evaluate the characteristics of heavy metal pollution in soil. On the basis of correlation analysis， the APCS-MLR and PMF models were used to quantitatively analyze the sources of heavy metals. The results showed that the average contents of the other seven heavy metal elements were higher than the background values of Chongqing soil， except for that of Cr. The heavy metals Cd， Hg， and As were moderately polluted， and Pb， Cu， Ni， and Zn were mildly polluted. The spatial distribution pattern of Cr， Ni， Pb， Cu， and Zn in the soil was similar， and there was a very significant positive correlation between them （P < 0.01）. The spatial distribution characteristics of Cd， Hg， and As were significantly different， and there was no significant correlation between them （P > 0.05）. The source apportionment showed that the sources of heavy metals in the soil in the study area were relatively complex， and the APCS-MLR and PMF models could identify the same four pollution sources， namely red mud yard percolation emission and natural sources， thermal power generation emission sources， agricultural activities and natural sources， and non-ferrous metal smelting emission sources. There was little difference in the results of source apportionment between the two models. The contribution rates of the four pollution sources in the APCS-MLR model were 51.8%， 18.0%， 15.9%， and 14.3%， respectively， whereas those in the PMF model were 45.9%， 12.8%， 21.5%， and 19.8%， respectively.