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用于多相冶金后场地的非原位便携式X射线荧光光谱技术的开发与优化

Development and optimisation of ex situ portable X-ray fluorescence spectroscopy for heterogenous post-metallurgical sites.

作者信息

Marsay N H, Wagland S T, Campo P, Alamar M C

机构信息

Faculty of Engineering and Applied Sciences, Cranfield University, Cranfield, Bedfordshire, UK.

出版信息

Environ Geochem Health. 2025 Jul 5;47(8):298. doi: 10.1007/s10653-025-02574-x.

DOI:10.1007/s10653-025-02574-x
PMID:40616668
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12228670/
Abstract

Portable X-ray fluorescence spectroscopy (pXRF) is widely used for rapid measurement of metals in soils, however, thorough evaluation of common pre-processing methods and their effectiveness is limited. This study addresses processing methods using samples collected at a highly heterogeneous post-metallurgical site containing, basic oxygen steelmaking (BOS) slag and soil; the former being an important source of potentially toxic and valuable elements. Impact of pre-treatment processes, (sieving, drying, grinding, sample vessel, and ignition) on the accuracy of pXRF measurements was compared against reference ICP-MS measurements.Of the twelve elements detected, four showed qualitative (Cr and Fe r ≥ 0.60, RSD ≤ 30%) or quantitative (Mn and Ca r ≥ 0.70, RSD ≤ 20%) measurements for raw samples. Improving to six elements after pre-processing (Sr qualitative, and Pb, Cr, Mn, Ca, Fe quantitative). Sieving and grinding improved precision (average RSD fell by 7.17 and 8.37% respectively), while drying and grinding enhanced accuracy (average r increased by 0.03 and 0.10 respectively). This study provides the first evidence that organic matter does not significantly impact pXRF accuracy or precision (average r and RSD changed by zero and - 0.32%, respectively). The two distinct matrices (BOS slag and soil) on-site resulted in a bimodal concentration distribution and a negative correlation for Ti. Importantly, this research proposes that not all common pre-processing steps are necessary to generate high-quality data due to their negligible impact on accuracy or precision (such as incineration to remove organic matter), thereby increasing the speed and reducing the cost of data collection.

摘要

便携式X射线荧光光谱法(pXRF)被广泛用于快速测量土壤中的金属,然而,对常见预处理方法及其有效性的全面评估却很有限。本研究针对在一个高度异质的冶金后场地采集的样品,该场地含有碱性氧气炼钢(BOS)炉渣和土壤;前者是潜在有毒和有价值元素的重要来源。将预处理过程(筛分、干燥、研磨、样品容器和灼烧)对pXRF测量准确性的影响与参考电感耦合等离子体质谱(ICP-MS)测量结果进行了比较。在检测到的12种元素中,有4种元素在原始样品中显示出定性(Cr和Fe,r≥0.60,相对标准偏差≤30%)或定量(Mn和Ca,r≥0.70,相对标准偏差≤20%)测量结果。预处理后提高到6种元素(Sr定性,Pb、Cr、Mn、Ca、Fe定量)。筛分和研磨提高了精度(平均相对标准偏差分别下降了7.17%和8.37%),而干燥和研磨提高了准确性(平均r分别增加了0.03和0.10)。本研究首次证明有机物不会显著影响pXRF的准确性或精度(平均r和相对标准偏差分别变化了零和 -0.32%)。现场的两种不同基质(BOS炉渣和土壤)导致了双峰浓度分布和Ti的负相关。重要的是,本研究提出,并非所有常见的预处理步骤对于生成高质量数据都是必要的,因为它们对准确性或精度的影响可忽略不计(例如焚烧以去除有机物),从而提高了数据收集的速度并降低了成本。

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本文引用的文献

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Identification of Legacy and Active Sources of Metal Contamination in Soils in Brooklyn, NY.识别纽约布鲁克林土壤中金属污染的遗留和活跃来源。
Arch Environ Contam Toxicol. 2022 Jul;83(1):67-76. doi: 10.1007/s00244-022-00942-7. Epub 2022 Jun 27.
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Nutrient and toxic elements in soils and plants across 10 urban community gardens: Comparing pXRF and ICP-based soil measurements.土壤和植物中的营养和有毒元素在 10 个城市社区花园中的分布情况:比较 pXRF 和 ICP 土壤测量方法。
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3
Portable X-ray fluorescence (pXRF) calibration for analysis of nutrient concentrations and trace element contaminants in fertilisers.
便携式 X 射线荧光 (pXRF) 校准分析肥料中的养分浓度和痕量元素污染物。
PLoS One. 2022 Jan 11;17(1):e0262460. doi: 10.1371/journal.pone.0262460. eCollection 2022.
4
Revealing XRF data quality level, comparability with ICP-ES/ICP-MS soil PTE contents and similarities in PTE induced health risk.揭示 XRF 数据质量水平、与 ICP-ES/ICP-MS 土壤 PTE 含量的可比性以及 PTE 引起的健康风险的相似性。
Environ Geochem Health. 2022 Jun;44(6):1739-1750. doi: 10.1007/s10653-021-01079-7. Epub 2021 Sep 5.
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A general framework and practical procedure for improving pxrf measurement accuracy with integrating moisture content and organic matter content parameters.一种利用水分含量和有机质含量参数提高 PXRF 测量精度的通用框架和实用程序。
Sci Rep. 2021 Mar 12;11(1):5843. doi: 10.1038/s41598-021-85045-4.
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Source apportionment of soil heavy metals using robust spatial receptor model with categorical land-use types and RGWR-corrected in-situ FPXRF data.利用稳健空间受体模型,结合分类土地利用类型和 RGWR 校正原位 FPXRF 数据进行土壤重金属源解析。
Environ Pollut. 2021 Feb 1;270:116220. doi: 10.1016/j.envpol.2020.116220. Epub 2020 Dec 6.
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Sci Total Environ. 2020 Jul 15;726:138670. doi: 10.1016/j.scitotenv.2020.138670. Epub 2020 Apr 12.
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