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Estimating Uncertainties for IMPROVE_A Carbon Fraction Measurements in PM2.5 Across Analyzer Brands

机译:估算分析仪品牌PM2.5中提高碳分数测量的不确定性

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Carbon fractions measured during organic carbon/elemental carbon (OC/EC) analysis of PM2.5 quartz filter samples are not independent analytes but rather are defined by the specific conditions (primarily temperature and trace oxygen contamination level) under which they are evolved from the sample during analysis. In OC/EC analysis, none of the carbon fractions except for total carbon (TC) is independent of the other fractions. For example, TC is calculated as the sum of the seven carbon peaks, and TC is always equal to the sum of OC and EC. Because of this, all carbon fractions except for TC are not independent analytes in the same sense that an ion or an element can be measured independent of all other ions or elements present in the sample. In previous work (Peterson and Richards, A&WMA Annual Meeting, Portland, OR, 2008), the authors demonstrated an empirical technique for estimating uncertainties for non-independent carbon fractions measured by the EPA’s Chemical Speciation Network/Thermal-Optical Transmittance (CSN/TOT) method using multiple analyzers from the same manufacturer. This paper will apply the technique to estimate uncertainties for IMPROVE_A carbon fractions across two different thermal-optical carbon aerosol analyzers from different manufacturers. The procedure allows for estimating extended uncertainties that are desirable when human health or safety is a concern and for estimating more typical uncertainties that could be used for samples collected where health and safety are not a concern.
机译:在有机碳/元素碳(OC / EC)分析期间测得的碳级分数PM2.5石英过滤样品的分析不是独立的分析物,而是由它们被从中演变的特定条件(主要温度和痕量氧气污染水平)定义分析过程中的样品。在OC / EC分析中,除了总碳(TC)之外的碳级分都没有与其他级分无关。例如,TC计算为七个碳峰的总和,并且TC总是等于OC和EC的总和。因此,除了TC之外的所有碳级分不是相同的义的分析物,即离子或元素可以独立于样品中存在的所有其他离子或元素。在以前的工作(Peterson和Richards,A&WMA年会,波特兰或2008年)中,作者展示了一种估算通过EPA化学品质网络/热光学透射率测量的非独立碳分数的不确定性的实证技术(CSN / TOT )使用来自同一制造商的多个分析仪的方法。本文将应用该技术来估算来自不同厂商的两种不同热光碳气溶胶分析仪的改进_碳分数的不确定性。该程序允许估计当人类健康或安全是一个问题并且估计可以用于恢复健康和安全不是一个问题的样本的更典型的不确定性时所需的延长的不确定性。

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