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测量不确定性的估计和有用性从不同空间尺度的抽样:微米到公里
1School of Life Sciences, University of Sussex, Brighton, BN1 9QG, UK. m.h.ramsey@sussex.ac.uk.
Environmental geochemistry and health
|March 13, 2024
概括
重复方法估计了地质化学数据中的测量不确定性 (MU). 这种在各种尺度上应用的方法揭示了采样和测量程序的问题,确保了数据可靠性.
科学领域:
- 地质化学 地质化学
- 环境科学 环境科学
- 分析化学 分析化学
背景情况:
- 测量不确定性 (MU) 对于准确地质化学解释至关重要.
- 重复方法提供了一个可扩展的方法,通过分析重复样本来估计MU.
- 了解MU对于验证测量程序和评估其适合目的至关重要.
研究的目的:
- 展示重复方法在不同空间尺度上估计MU的应用.
- 为了说明MU估计如何增强地质化学解释.
- 通过评估它们的适用性来验证包括采样在内的测量程序.
主要方法:
- 重复方法涉及对重复样本的子集进行分析.
- 样本重复距离被优化,以反映在调查规模上的分析物异质性.
- 在公里,微米和特定地点的尺度上使用案例研究来应用和验证该方法.
主要成果:
- 欧洲农业土壤中53种元素的MU估计 (GEMAS调查) 从1.01的不确定因素到10以上的不确定因素不等.
- 在53个元素中的8个元素中,MU超过了总方差的20%,表明不合适的测量程序.
- 对石英中氧气同位素的微量分析显示,采样异质性主导着MU.
- 英国土壤中的Pb显示异质性,用重复方法量化 (因子1.03到2.4),表明元素来源.
结论:
- 复制方法是有效的估计MU和量化各种规模的异质性.
- 使用重复方法的MU评估可以识别不适合目的的测量程序.
- 这种方法改善了地质化学数据的解释,并验证了分析方法.
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