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Source apportionment of potentially toxic elements in soils using APCS/MLR, PMF and geostatistics in a typical industrial and mining city in Eastern China

机译:在中国东部典型工业和矿业城的土壤中潜在有毒元素的潜在有毒元素分配

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Source apportionment of potentially toxic elements in soils is a critical step for devising soil sustainable management strategies. However, misjudgment or imprecision can occur when traditional statistical methods are applied to identify and apportion the sources. The main objective of the study was to develop a robust approach composed of the absolute principal component score/multiple linear regression (APCS/MLR) receptor model, positive matrix factorization (PMF) receptor model and geostatistics to identify and apportion sources of soil potentially toxic elements in typical industrial and mining city, eastern China. APCS/MLR and PMF were applied to provide robust factors with contribution rates. The geostatistics coupled with the variography and kriging methods was used to present factors derived from these two receptor models. The results indicated that mean concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb and Zn exceeded the local background levels. Based on multivariate receptor models and geostatistics, we determined four sources of eight potentially toxic elements including natural source (parent material), agricultural practices, pollutant emissions (industrial, mining and traffic) and the atmospheric deposition of coal combustion, which accounted for 68%, 12%, 12% and 9% of the observed potentially toxic element concentrations, respectively. This study provides a reliable and robust approach for potentially toxic elements source apportionment in this particular industrial and mining city with a clear potential for future application in other regions.
机译:土壤中潜在有毒元素的源分摊是设计土壤可持续管理策略的关键步骤。但是,当应用传统统计方法以识别和分配来源时,可能会发生误判或不精确。该研究的主要目的是开发由绝对主成分评分/多线性回归(APCS / MLR)受体模型,正矩阵分解(PMF)受体模型和地质学,以识别和分摊土壤潜在毒性的稳健方法元素在典型的工业和矿业城,东部。 APCS / MLR和PMF被应用于提供具有贡献率的强大因素。与变型和克里格化方法耦合的地质学,用于呈现衍生自这两个受体模型的因素。结果表明,AS,Cd,Cr,Cu,Hg,Ni,Pb和Zn的平均浓度超过了局部背景水平。基于多变量受体模型和地统计学,我们确定了四种潜在有毒元素的来源,包括自然来源(母体材料),农业习俗,污染物排放(工业,采矿和交通)以及煤炭燃烧的大气沉积,占68%分别观察到的潜在有毒元素浓度的12%,12%和9%。本研究提供了可靠而强大的方法,可实现潜在的有毒元素源分配在这座特殊的工业和矿业城市,在其他地区的未来应用潜力明显。

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