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应用Rietveld方法评估铬铁矿加工残渣中的六价铬形态。

Application of the Rietveld method to assess chromium(VI) speciation in chromite ore processing residue.

作者信息

Chrysochoou Maria, Dermatas Dimitris

机构信息

W.M. Keck Geoenvironmental Laboratory, Stevens Institute of Technology, Castle Point on Hudson, Hoboken NJ 07030, USA.

出版信息

J Hazard Mater. 2007 Mar 15;141(2):370-7. doi: 10.1016/j.jhazmat.2006.05.081. Epub 2006 Jun 2.

Abstract

The Rietveld method allows the quantification of crystalline phases and amorphous material identified by X-ray powder diffraction (XRPD) and other diffraction methods. The method assists in determining the speciation of contaminants in solid matrices both qualitatively and quantitatively in a statistically defensible approach, as it does not focus on a microscale. Rietveld was applied to chromite ore processing residue (COPR), a cementitious waste containing hexavalent chromium. Calcium aluminum chromium oxide hydrates (CACs) were the crystalline phases identified by XRPD that bind Cr(6+) in COPR according to their chemical formula. Rietveld quantification, combined with mass balances on Cr(6+), showed that CACs may bind Cr(6+) in variable percentages, ranging from 25% to 85%. Analysis of duplicate samples showed that material variability is the predominant factor of uncertainty in evaluating the role of CACs in Cr(6+) speciation, provided that a consistent quantification strategy is pursued. The choice of strategy was performed on the basis of the pertinent literature, preliminary analyses of the equipment and the software settings, and mass balances. The correlation between the average CAC-bound Cr(6+) concentration and the total Cr(6+) for five samples (R(2)=0.94), extracted from different zones and soil borings, suggests that CACs are a primary sink for Cr(6+) in COPR.

摘要

里特韦尔德方法可对通过X射线粉末衍射(XRPD)及其他衍射方法识别出的晶相和非晶质材料进行定量分析。该方法有助于以一种统计学上合理的方式,定性和定量地确定固体基质中污染物的形态,因为它并不聚焦于微观尺度。里特韦尔德方法被应用于铬铁矿加工残渣(COPR),这是一种含有六价铬的胶凝废物。通过XRPD识别出的钙铝铬氧化物水合物(CACs)是COPR中根据其化学式结合Cr(6+)的晶相。里特韦尔德定量分析与Cr(6+)的质量平衡相结合,结果表明,CACs结合Cr(6+)的百分比可能有所不同,范围在25%至85%之间。对重复样品的分析表明,如果采用一致的定量策略,材料变异性是评估CACs在Cr(6+)形态中的作用时不确定性的主要因素。策略的选择是基于相关文献、对设备和软件设置的初步分析以及质量平衡来进行的。从不同区域和土壤钻孔中提取的五个样品的平均CAC结合Cr(6+)浓度与总Cr(6+)之间的相关性(R(2)=0.94)表明,CACs是COPR中Cr(6+)的主要汇。

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