基于APCS-MLR和PMF的铅锌矿流域土壤重金属来源解析

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摘要以广西阳朔铅锌矿为研究对象，分析了表土中的Cr、Mn、Ni、Cu、Zn、As、Cd、Sb、Hg和Pb共10种重金属元素含量，并利用绝对主成分-多元线性回归模型（APCS-MLR）和正定矩阵因子分解法（PMF）等方法，识别和定量解析污染源及其贡献率.研究区内Pb、Zn、Hg、Cd、Mn和Cu的含量超过了广西当地土壤背景值3.29~13.08倍，Cr、Ni、As和Sb在局部地区超过背景值，表明研究区存在重金属污染现象；10种重金属在各深度上呈现条带状和点状分布，其中Mn、Cu、Zn、As、Cd、Sb和Pb含量高值条带状分布于思的河左岸和思的河山前区域，Cr、Ni和Hg含量高值主要分布于中西部高冈处；APCS-MLR模型和PMF模型源解析结果表明表层土壤重金属来源主要为工矿活动源、自然因素（成土母质、降雨冲刷等）和工矿及农业活动复合源，但在贡献率上存在差异，APCS-MLR模型提取的污染源贡献率依次为工矿及农业混合源（30.95%）、工矿活动（22.39%）、自然因素（15.79%）和未识别源（8.35%），PMF模型提取污染源贡献率依次为工矿活动（35.16%）、尾矿和废渣（28.21%）、工矿活动及农业活动的复合源（20.89%）和自然因素（15.74%）.两种模型不同的因子提取方式、APCS-MLR模型的正交性约束、PMF模型的不确定度考虑和非负约束性等可能是引起解析差异的原因.

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	刘楠
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关键词 ：铅锌矿, 土壤重金属, 来源解析, APCS-MLR模型, PMF模型

Abstract：This study took a typical lead-zinc mining area in Yangshuo county, Guangxi as the research object, and analyzed the contents of 10 heavy metal elements (Cr, Mn, Ni, Cu, Zn, As, Cd, Sb, Hg, and Pb) in the surface soil. The absolute principal component scores-multiple linear regression (APCS-MLR) model and positive definite matrix factorization (PMF) model were comprehensively used to identify and quantitatively analyze pollution sources and their contribution. The results showed that the means content of Pb, Zn, Hg, Cd, Mn, and Cu were higher than their corresponding local background values by approximately 3.29~13.08 times, Cr, Ni, As, and Sb also exceeded the background value in some areas, indicated that heavy metal pollution existed in the study area. The 10 heavy metals were mainly distributed in strips and spots at various depths, and the high content of Mn, Cu, Zn, As, Cd, Sb, and Pb were mainly distributed in the left bank of the Side river and southeast of the study area. The high contents of Cr, Ni, and Hg were mainly distributed in strip highlands of the central and western of study area. The source apportionment results of the APCS-MLR model and the PMF model were relatively consistent in terms of pollution sources. The metal pollution sources in the surface soil were jointly affected by mining activities, natural sources (such as, soil parent materials, rainfall erosion, etc), and mixed source of mining activities and agricultural activities. There were differences in the contribution rate of the APCS-MLR model and the PMF model. For the APCS-MLR model, the contribution rate of pollution sources in the order of mixed sources of mining activities and agricultural activities (30.95%), mining activities (22.39%), natural sources (15.79%), and unidentified sources (8.35%). The PMF model extracted the contribution of pollution sources in the order of mining activities (35.16%), tailings and waste (28.21%), mixed sources of mining activities and agricultural activities (20.89%), and natural sources (15.74%). The reasons for the difference in the pollution sources apportionment of the APCS-MLR model and PMF model may be attributed to different factor extraction methods, orthogonality constraint of the APCS-MLR model, and the uncertainty consideration and the non-negative constraint of the PMF model.

Key words： lead-zinc mine heavy metal in soil source apportionment APCS-MLR model PMF model

收稿日期: 2022-07-25

PACS:

X131.3

基金资助:广西自然科学基金资助项目（2020GXNSFBA297050）；广西科技基地和人才专项（桂科AD19110046）

通讯作者: 陈盟,副教授,cattlepen@163.com E-mail: cattlepen@163.com

作者简介: 刘楠(1998-),女,陕西咸阳人,桂林理工大学环境科学与工程学院硕士研究生,主要研究方向为区域环境污染调查与评价.发表论文1篇.

引用本文:

刘楠, 唐莹影, 陈盟, 潘泳兴. 基于APCS-MLR和PMF的铅锌矿流域土壤重金属来源解析[J]. 中国环境科学, 2023, 43(3): 1267-1276. LIU Nan, TANG Ying-ying, CHEN Meng, PAN Yong-xing. Source apportionment of soil heavy metals in lead-zinc area based on APCS-MLR and PMF. CHINA ENVIRONMENTAL SCIENCECE, 2023, 43(3): 1267-1276.

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http://www.zghjkx.com.cn/CN/ 或 http://www.zghjkx.com.cn/CN/Y2023/V43/I3/1267

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