Harmonization of Uncertainties of X-Ray Fluorescence Data for PM2.5 Air Filter Analysis
Harmonization of Uncertainties of X-Ray Fluorescence Data for PM2.5 Air Filter Analysis
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DOI：
10.3155/1047-3289.60.2.184
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发表时间：
2010-02-01
影响因子：
2.7
通讯作者：
Sarver, Richard H.
中科院分区：
文献类型：
--
作者：
Gutknecht, William;Flanagan, James;Sarver, Richard H.
美国环境保护署（EPA）的PM2.5化学形态网络（CSN）和受保护视觉环境的机构间监测（IMPROVE）网络使用X射线荧光（XRF）分析来量化空气动力学直径小于2.5微米的细颗粒物（PM2.5）样品中的微量元素。计算XRF结果不确定度值的方法因实验室和仪器品牌和型号而异。为了支持某些类型的建模和数据分析，不确定性估计需要在监测程序内和监测程序之间保持一致，并且独立于进行分析的实验室和使用的分析仪器。这项工作的目标是为与PM2.5过滤器样品的XRF分析相关的不确定性开发一个共识模型。本文描述的模型中包括以下重要的不确定性分量：峰面积的可变性、校准、现场采样和轻元素的X射线强度衰减。本文详细分析了如何推导出轻元素的衰减不确定度。对于模型中包含的其余不确定性分量，提出了一种方法和建议，以确保进行此类分析的实验室可以使用类似的方程和参数化。通过应用这种统一的方法，它说明了如何由CSN和IMPROVE网络实验室报告的不确定性可以带入非常好的协议。所提出的方法最好在数据生成时应用，但也可以对现有数据集的不确定性进行回顾性估计。本文旨在记录用于计算PM2.5 CSN项目中目前公布在EPA空气质量系统数据库中的PM2.5数据的不确定性的方程。
The U.S. Environmental Protection Agency (EPA)'s PM2.5 Chemical Speciation Network (CSN) and the Interagency Monitoring of Protected Visual Environments (IMPROVE) network use X-ray fluorescence (XRF) analysis to quantify trace elements in samples of fine particles less than 2.5 microns in aerodynamic diameter (PM2.5). Methods for calculating uncertainty values for XRF results vary considerably among laboratories and instrument makes and models. To support certain types of modeling and data analysis, uncertainty estimates are required that are consistent within and between monitoring programs, and that are independent of the laboratories that performed the analyses and the analytical instrumentation used. The goal of this work was to develop a consensus model for uncertainties associated with XRF analysis of PM2.5 filter samples. The following important components of uncertainty are included in the model described herein: variability in peak area, calibration, field sampling, and attenuation of X-ray intensity for light elements. This paper includes a detailed analysis of how attenuation uncertainties for light elements are derived. For the remaining uncertainty components included in the model, an approach and recommendations are presented to ensure that laboratories performing this type of analysis can use similar equations and parameterizations. By applying this uniform approach, it is illustrated how the uncertainties reported by the CSN and IMPROVE network laboratories can be brought into very good agreement. The proposed method is best applied at the time of data generation, but retrospective estimation of uncertainties in existing data-sets is also possible. This paper serves to document the equations used for calculating the uncertainties in speciated PM2.5 data currently being posted on EPA's Air Quality System database for the PM2.5 CSN program.