| 基于受体模型与地统计的耕地土壤重金属污染源解析 |
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| 引用本文： | 吕柏楠,王超,师华定,李明秋.基于受体模型与地统计的耕地土壤重金属污染源解析[J].环境科学研究,2021,34(12):2962-2969. |
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| 作者姓名： | 吕柏楠 王超 师华定 李明秋 |
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| 作者单位： | 1.河南理工大学, 河南 焦作 454003 |
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| 基金项目： | 国家重点研发计划项目2018YFC1800203国家重点研发计划项目2018YFF0213401 |
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| 摘 要： | 为探明云南金子河流域耕地土壤重金属污染现状与主要来源，有效开展土壤污染防治, 通过土壤采样与数据统计分析评价了金子河流域典型耕地的重金属污染风险，采用指示克里格方法阐明了研究区重金属元素的空间分布，使用主成分分析-多元线性回归(PCA-MLR)模型进行土壤重金属源解析，并量化其贡献率. 内梅罗综合污染指数法评价结果表明，本研究区中90.79%的土壤点位为重度污染，土壤整体处于重度污染水平. 指示克里格插值结果显示，元素Cd、As、Pb污染的高概率区域主要分布在研究区西部与西南部，Cd、Pb污染的高概率区域主要分布在研究区北部，而Cd、As、Pb污染的低概率区域主要分布在研究区东部及东南部. PCA-MLR模型解析重金属污染来源包括:研究区整体自然源贡献率为12.79%，工业源贡献率为87.21%；东岸自然源、工业源贡献率分别为92.46%、7.54%，西岸自然源、工业源贡献率分别为8.98%、91.02%. 研究显示，金子河流域西岸区域的重金属污染风险明显高于东岸区域，分区域进行源解析可以有效揭示局部污染特性，更为准确地识别污染来源.
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| 关 键 词： | 土壤重金属 源解析 指示克里格插值 主成分分析-多元线性回归(PCA-MLR)模型 金子河流域 |
| 收稿时间： | 2021-05-31 |
Analysis of Heavy Metal Pollution Sources in Cultivated Land Soil Based on Receptor Model and Geostatistics |
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| Affiliation: | 1.Henan Polytechnic University, Jiaozuo 454003, China2.Technical Centre for Soil, Agricultural and Rural Ecology and Environment, Ministry of Ecology and Environment, Beijing 100012, China |
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| Abstract: | In order to ascertain the current status and main sources of heavy metal pollution in cultivated soils in the Jinzi River Basin of Yunnan, and effectively carry out soil pollution prevention and control, the risk of heavy metal pollution in typical cultivated land in the Jinzi River Basin was evaluated through soil sampling and statistical analysis of data. The indicator kriging method was used to clarify the spatial distribution of heavy metals in the study area, and the principal component analysis-multiple linear regression (PCA-MLR) model was used to analyze the sources of soil heavy metals and quantify their contribution rate. The Nemerow integrated pollution index method evaluation results showed that 90.79% of the soil in the study area was heavily polluted, and the soil as a whole was at a heavy pollution level. The indicator kriging results showed that the areas with high probability of Cd, As and Pb pollution were mainly distributed in the west and southwest of the study area, and the areas with high probability of Cd and Pb pollution were mainly distributed in the northern of the study area, while the areas with low probability of Cd, As and Pb pollution were mainly distributed in the east and southeast of the study area. The PCA-MLR model indicated that the contribution rate of natural sources was 12.79%, and the contribution rate of industrial sources was 87.21%. The contribution rates of natural sources and industrial sources in the east coast were 92.46% and 7.54%, respectively. The contribution rates of natural sources and industrial sources on the west coast were 8.98% and 91.02%, respectively. The research has shown that the risk of heavy metal pollution on the west bank of the study area is significantly higher than that on the east bank. Source analysis in different regions can effectively reveal the characteristics of local pollution and more accurately identify the source of pollution. |
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