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现代地质 ›› 2023, Vol. 37 ›› Issue (03): 790-800.DOI: 10.19657/j.geoscience.1000-8527.2023.041

• 实验、应用与环境地球化学 • 上一篇    下一篇

新疆戈壁荒漠区典型露天煤矿土壤重金属来源解析及空间分布

杜古尔·卫卫(), 石海涛(), 邢浩, 娄雪聪, 胡宏利, 布龙巴特   

  1. 中国地质调查局乌鲁木齐自然资源综合调查中心,新疆 乌鲁木齐 830026
  • 收稿日期:2022-09-15 修回日期:2023-04-19 出版日期:2023-06-10 发布日期:2023-07-20
  • 通讯作者: 石海涛,男,工程师,1991年出生,资源勘查工程专业,从事生态地质调查和综合地质调查研究。Email:shihaitao@mail.cgs.gov.cn
  • 作者简介:杜古尔·卫卫,男,工程师,1989年出生,地球化学专业,从事环境地球化学和生态地球化学研究。 Email:dgeww@mail.cgs.gov.cn
  • 基金资助:
    中国地质调查局项目“新疆哈密市南湖一带矿山集中区生态修复支撑调查”(DD20208081);中国地质调查局项目“环塔里木盆地绿洲区土壤盐渍化现状调查评价”(DD20220872)

Source Analysis and Spatial Distribution of Heavy Metals in Soil from Typical Open-pit Coal Mines in the Gobi Desert, Xinjiang

DUGUER Weiwei(), SHI Haitao(), XING Hao, LOU Xuecong, HU Hongli, BULONG Bate   

  1. Urumqi Comprehensive Survey Center on Natural Resources, China Geological Survey, Urumqi,Xinjiang 830026, China
  • Received:2022-09-15 Revised:2023-04-19 Online:2023-06-10 Published:2023-07-20

摘要:

查明戈壁荒漠区典型露天煤矿土壤重金属来源及其空间分布特征是准确判断和制定土壤污染治理方案的前提,然而系统的研究工作依然薄弱。本文以新疆戈壁荒漠区典型煤矿周边土壤为研究对象,系统的布设和采集了266件土壤样品,测试分析了As、Cd、Co、Cu、Cr、Hg、Ni、Pb、Zn共9种元素含量及土壤pH值。通过利用描述性统计分析、相关性分析、聚类分析以及主成分分析等多元地学统计分析方法分析研究了土壤重金属含量特征并初步识别了土壤重金属来源,使用绝对主成分-多元线性回归受体模型(APCS-MLR)和反距离加权法定量分析各污染源贡献率和重金属元素空间分布特征。结果表明:(1)研究区土壤pH平均值为8.31,9种元素含量低于土壤环境质量农业用地、建设用地筛选值,同时也低于新疆土壤重金属背景值;从各功能分区来看,仅废污水排放区As、Cd、Cu、Ni和Pb元素含量高于新疆背景值;(2)Cr、Ni、Zn、Co、Cu、As、Cd元素两两之间具有中等以上相关性,Cd与Pb具有中等程度相关性,Hg与其他8种元素相关性较弱;(3)聚类分析结果将研究区土壤重金属分为Cr-Ni-Zn-Co-Cu-As、Cd-Pb和Hg三类;(4)源解析结果表明研究区土壤重金属主要来源为成土母质源(50.902%)、废污水与煤尘源(31.507%)。

关键词: 土壤重金属, 受体模型, 源解析, 空间分布, 戈壁荒漠区

Abstract:

Identifying the sources and spatial distribution characteristics of heavy metals in soil of typical opencast coal mines in Gobi desert is crucial in accurately judging and formulating soil pollution control programs. However, systematic research is still weak inadequate. In this study, 266 soil samples were systematically collected around typical coal mines in the Xinjiang Gobi Desert. Soil As, Cd, Co, Cu, Cr, Hg, Ni, Pb, Zn contents and pH values were measured. By using descriptive statistical, correlation, cluster and principal component analyses and other multivariate geostatistical analysis methods,the soil heavy metal compositions were analyzed and the heavy metal source preliminarily identified. We used the absolute principal components-multiple linear regression receptor model(APCS-MLR) and inverse distance weighting method to quantify the contribution rate of each pollution source and the heavy metal spatial distribution patterns. The results show that:(1) The average soil pH is 8.31 in the study area, the contents of nine elements were lower than the threshold for agricultural and construction land, and also below the soil heavy metal background in Xinjiang. From the functional partitions, only the As, Cd, Cu, Ni and Pb contents in the waste sewage discharge area are higher than the Xinjiang background; Cr,Ni, Zn, Co, Cu, As and Cd have moderate or high correlations, Cd and Pb have moderate correlations, and Hg has weak correlations with the other eight elements. (2)Cr, Ni, Zn, Co, Cu, As and Cd have moderate or high correlations, Cd and Pb have moderate correlations, and Hg has weak correlations with the other eight elements.(3)The cluster analysis results divide the soil heavy metals into three categories: Cr-Ni-Zn-Co-Cu-As, Cd-Pb, and Hg. (4) Source analysis results show that the main heavy metal sources of local soil are parent material (50.902%), waste water and coal dust (31.507%).

Key words: heavy metals in soil, receptor-oriented model, source analysis, spatial distribution, Gobi Desert

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