PM(2.5) Characterization for Time Series Studies: Pointwise Uncertainty Estimation and Bulk Speciation Methods Applied in Denver.
PM(2.5) Characterization for Time Series Studies: Pointwise Uncertainty Estimation and Bulk Speciation Methods Applied in Denver.
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DOI：
10.1016/j.atmosenv.2008.10.003
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发表时间：
2009-02-01
影响因子：
5
通讯作者：
Hannigan, Michael P.
中科院分区：
文献类型：
--
作者：
Dutton, Steven J.;Schauer, James J.;Vedal, Sverre;Hannigan, Michael P.
许多研究已经确定了不良健康影响与短期暴露于直径小于2.5微米的颗粒物（PM2.5）之间的关联。然而，这些影响在各地理区域并不一致。这可能部分是由于PM2.5的化学组成不同，这是由于不同地区的主要和次要来源的独特组合造成的。丹佛气溶胶来源与健康（DASH）研究是一项为期多年的时间序列研究，旨在描述丹佛PM2.5的日常化学成分，确定主要贡献来源，并调查来源与广泛的不良健康结果之间的关联。测量方法，现场空白校正，逐点不确定性估计和检测限的考虑进行了讨论的背景下，散装形态的DASH研究。结果提出了第一个4.5年的质量，无机离子和散装碳形态。衍生的测量不确定度传播使用平方根和方法，并显示出良好的协议与来自双周重复样品收集的并置采样器的精密度估计。重力质量具有任何测量的最大不确定性，并且从单个物种的总和生成的重建质量显示出比平均测量质量更小的不确定性。讨论的方法提供了一个很好的框架PM2.5形态测量和推广到其他环境措施的分析。
Many studies have identified associations between adverse health effects and short-term exposure to particulate matter less than 2.5 microns in diameter (PM2.5). These effects, however, are not consistent across geographical regions. This may be due in part to variations in the chemical make-up of PM2.5 resulting from unique combinations of sources, both primary and secondary, in different regions. The Denver Aerosol Sources and Health (DASH) study is a multi-year time series study designed to characterize the daily chemical composition of PM2.5 in Denver, identify the major contributing sources, and investigate associations between sources and a broad array of adverse health outcomes. Measurement methodology, field blank correction, pointwise uncertainty estimation and detection limit consideration are discussed in the context of bulk speciation for the DASH study. Results are presented for the first 4.5 years of mass, inorganic ion and bulk carbon speciation. The derived measurement uncertainties were propagated using the root sum of squares method and show good agreement with precision estimates derived from bi-weekly duplicate samples collected on collocated samplers. Gravimetric mass has the most uncertainty of any measurement and reconstructed mass generated from the sum of the individual species shows less uncertainty than measured mass on average. The methods discussed provide a good framework for PM2.5 speciation measurements and are generalizable to analysis of other environmental measures.
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