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黄河下游典型滩区土壤重金属污染特征及来源解析
引用本文:徐祖奔,伍艳,赵越,乔奥克,冯帅滔,刘振延. 黄河下游典型滩区土壤重金属污染特征及来源解析[J]. 农业工程学报, 2023, 39(15): 200-207
作者姓名:徐祖奔  伍艳  赵越  乔奥克  冯帅滔  刘振延
作者单位:黄河水利委员会黄河水利科学研究院, 郑州 450003;水利部堤防安全与病害防治工程技术研究中心, 郑州 450003;河南黄科工程技术检测有限公司, 郑州 450003
基金项目:中央级公益性科研院所基本科研业务费专项项目(HKY-JBYW-2021-03)
摘    要:针对黄河滩区土壤重金属污染、来源复杂的问题,该研究以原阳滩区复合污染土壤为例,结合土壤重金属含量空间分布和正定矩阵因子分解(positive matrix factorization, PMF)模型,探讨滩区土壤重金属富集特征及来源。源解析结果表明,原阳滩区土壤重金属污染受工业源、交通源、自然来源、燃煤污染源和农业源影响,农业源占主导,相对贡献率达23.5%,其次为工业源、自然来源、交通源、和燃煤污染源。该研究能够准确解析多金属复合土壤复杂成因,可为黄河滩区多金属复合污染土壤的污染源识别提供参考。

关 键 词:重金属  风险评价  正定矩阵因子分解法  源解析  黄河滩区
收稿时间:2023-02-11
修稿时间:2023-07-11

Source apportionment and pollution of soil heavy metals in typical floodplain in the Lower Reaches of the Yellow River
XU Zuben,WU Yan,ZHAO Yue,QIAO Aoke,FENG Shuaitao,LIU Zhenyan. Source apportionment and pollution of soil heavy metals in typical floodplain in the Lower Reaches of the Yellow River[J]. Transactions of the Chinese Society of Agricultural Engineering, 2023, 39(15): 200-207
Authors:XU Zuben  WU Yan  ZHAO Yue  QIAO Aoke  FENG Shuaitao  LIU Zhenyan
Affiliation:Yellow River Conservancy Commission, Yellow River Institute of Hydraulic Research, Zhengzhou 450003, China;Research Center on Embankment safety and disease control engineering technology of the Ministry of Water Resources, Zhengzhou 450003, China;Henan Huangke Engineering Technology Testing Co., Ltd, Zhengzhou 450003, China
Abstract:Soil heavy metal pollution and complex sources have posed the serious risks on the ecological system in recent years. In this study, the positive matrix factorization (PMF) model was established to explore the spatial distribution and sources of heavy metals in soil. The composite polluted soil was taken from the Yuanyang floodplain of the lower Yellow River. 81 surface soil (0-20 cm) samples were collected to identify the soil heavy metal, such as Pb, Cu, Cd, Hg Cr, Ni, Zn and As. A systematic analysis was then made to determine the pollution content and spatial distribution of heavy metals. The geographical accumulation index and potential ecological risk index were used to assess the pollution degree of heavy metals and their ecology risk. The contents of Pb, Cu, Cd, Hg, Cr, Ni, Zn, and As in the soil of the study area were 27.77, 27.05, 0.31, 0.24, 73.55, 25.38, 88.25, and 29.00 mg/kg, respectively. Among them, Hg pollution was the most severe with an average content nearly 7 times of the soil background value, indicating a strong ecological risk, followed by Cd pollution with a strong ecological risk. An island -like pattern was observed in the spatial distribution of heavy metal concentration in the Yuanyang Beach District. The Cu, Ni, Pb, and Cd pollution were widely polluted with the high value in the central Jiangzhuang Township of the study area. An overlapping space was found on the high value distribution of Zn, Cr, As, and Hg in the surface soil, indicating the point source pollution. The geographical accumulation index also showed that the Hg pollution was the most serious, followed by As and Cd. The intensity of potential ecological risk was ranked in the descending order of Hg>Cd>As>Pb>Cu>Ni>Cr>Zn. The heavy metal of Hg presented the very strong ecological hazards, while Cd was the strong ecological hazards, and the rest were belonged to the slight ecological hazards. The potential ecological risk index (RI) was 459.31 on average among the eight heavy metals, indicating the level of strong ecological hazards. The contribution rates of Hg and Cd were 61.66% and 27.71%, respectively. The spatial interpolation was performed on the comprehensive potential ecological risk index of heavy metals. The most severe pollution of heavy metals was distributed in Xibianqiao North Township and middle Jiangzhuang Township, indicating a strong ecological risk level. The Hg and Cd pollution were relatively sereve and posed the greatest ecological harm to the environment. The cluster and source analysis showed that the heavy metal pollution was attributed to the industrial, transportation, natural, coal-burning, and agricultural sources. Agricultural sources were dominated in the soil heavy metal pollution, with the relative contribution rate of 23.5%. By contrast, the relative contribution rate of industrial, transportation, natural and coal-burning sources were 16.2%, 22.1%, 19.4% and 18.9%, respectively. The finding can provide a strong reference to identify the pollution sources of polymetallic composite polluted soil. The scientific basis and data support can greatly contribute to the "scientific pollution control" and "precise pollution control" of the soil for the better Ecological protection and high-quality development in the Yellow River Basin.
Keywords:heavy metals  risk assessment  positive matrix factorization method  source apportionment  Yellow River floodplain
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