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淮南塌陷塘重金属空间分布特征研究
引用本文:任永乐, 董少春, 姚素平. 淮南塌陷塘重金属空间分布特征研究[J]. 煤田地质与勘探, 2018, 46(1): 125-134. DOI: 10.3969/j.issn.1001-1986.2018.01.022
作者姓名:任永乐  董少春  姚素平
作者单位:1.南京大学地球科学与工程学院,江苏 南京 210023
基金项目:国家自然科学基金项目(41372127,41372353)
摘    要:长期地下煤炭开采在地表产生了大面积的塌陷塘,并造成了不同程度的水域污染。为研究塌陷塘重金属的分布特征及成因,选择了8种对环境影响较大的重金属元素(Fe,Mn,Zn,Cu,Cr,Cd,Pb,Ni)为研究对象,以淮南潘集一矿塌陷塘为研究区域,利用ArcGIS地统计模块中的协同克里格算法,通过水体实测光谱反射率作为协变量来估算水体中的重金属含量空间分布特征。结果表明:水体实测光谱与重金属含量有较好的关系,以水体光谱为协变量的协同克里格插值与单变量的普通克里格插值相比,8种重金属元素的预测值与实际值之间的均方根误差明显减少,证明水体实测光谱适合作为协变量来估计水体重金属的空间分布情况。综合分析发现,水体中的Cd,Pb,Cu,Ni主要来自水域西北部的煤矸石堆山,且Cd,Cu,Pb含量均超过了当地的背景值,对环境影响较大;Cr主要来自农业肥料、成土母质和周边道路旁的煤泥灰厂及煤矸石堆;Zn的来源主要是煤矸石、上游生活污水、农业肥料、土壤母质,由于其含量较低,对水环境质量的影响不大。

关 键 词:塌陷塘  重金属  水体光谱  协同克里格  ArcGIS
收稿时间:2017-04-15

Spatial distribution characteristics of heavy metals in Huainan subsidence pond
REN Yongle, DONG Shaochun, YAO Suping. Spatial distribution characteristics of heavy metals in Huainan subsidence pond[J]. COAL GEOLOGY & EXPLORATION, 2018, 46(1): 125-134. DOI: 10.3969/j.issn.1001-1986.2018.01.022
Authors:REN Yongle  DONG Shaochun  YAO Suping
Affiliation:1.School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China
Abstract:Long-term underground coal mining activities cause severe land subsidence and form large amount of subsidence ponds, and causing water pollution in different degrees. To study the distribution of heavy metals in subsidence pond and cause of formation, this paper chooses subsidence pond in Panji-1 coal mine in Huaihuan as research area and focused on eight kinds of heavy mental elements(Fe, Mn, Zn, Cu, Cr, Cd, Pb, Ni) impacting significantly environmental quality. We took water reflectance spectrum as covariate to estimate the spatial distribution characteristics of heavy metals in water bodies on the basis of collaborative kriging method. The results indicate that measured water spectra and heavy metal content have good relations. And collaborative kriging interpolation method which chooses water spectrum as covariate is much better than single variable ordinary kriging interpolation, the root mean square error of eight heavy metal elements between the predicted values and actual values decreased obviously, proving that the reflectance spectra of water as covariate is suitable for estimation of the spatial distribution of heavy metals in water. Furthermore, the comprehensive analysis results found that Cd, Pb, Cu, Ni in water-looged area mainly come from gangue dump in the northwest of the water body. And Cd, Cu and Pb concentrations exceeded local background value and had the highest pollution risk. Cr mainly comes from agricultural fertilizer, soil parent material and coal ash deposition of the surrounding road and coal gangue. Zn mainly comes from coal gangue, sewage, agricultural fertilizer and soil parent material. Because of its concentrations is low, it has a little effect on the water environment quality. 
Keywords:subsidence pond  heavy metals  reflectance spectra of water  Co-kriging  ArcGIS
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