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首页> 外文期刊>Atmospheric Measurement Techniques >Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: method development for probabilistic modeling of organic carbon and organic matter concentrations
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Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: method development for probabilistic modeling of organic carbon and organic matter concentrations

机译：红外光谱法分析大气气溶胶中的官能团：有机碳和有机物质浓度概率建模的方法开发

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摘要

The Fourier transform infrared (FTIR) spectra of fine particulate matter (PM2.5) contain many important absorption bands relevant for characterizing organic matter (OM) and obtaining organic matter to organic carbon (OM/OC) ratios. However, extracting this information quantitatively - accounting for overlapping absorption bands and relating absorption to molar abundance - and furthermore relating abundances of functional groups to that of carbon atoms poses several challenges. In this work, we define a set of parameters that model these relationships and apply a probabilistic framework to identify values consistent with collocated field measurements of thermal-optical reflectance organic carbon (TOR OC). Parameter values are characterized for various sample types identified by cluster analysis of sample FTIR spectra, which are available for 17 sites in the Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network (7 sites in 2011 and 10 additional sites in 2013). The cluster analysis appears to separate samples according to predominant influence by dust, residential wood burning, wildfire, urban sources, and biogenic aerosols.
机译：细颗粒物质（PM2.5）的傅里叶变换红外（FTIR）光谱含有许多重要的吸收带，其用于表征有机物质（OM）并获得有机物与有机碳（OM / OC）比率。然而，从定量地提取该信息 - 考虑重叠吸收带并将吸收与摩尔丰度相关 - 此外，与碳原子的官能团的丰度与碳原子的丰度相关起作用的若干挑战。在这项工作中，我们定义了一组模型这些关系的参数，并应用概率框架，以识别与热光反射率有机碳（TOR OC）的并置场测量一致的值。参数值的特征在于通过对样本FTIR光谱的集群分析标识的各种样本类型，其可用于受保护的视觉环境（改进）监控网络的间歇监测中的17个站点（2011年的7个站点和2013年的其他10个站点）。聚类分析似乎根据灰尘，住宅木材燃烧，野火，城市来源和生物原料气溶胶的主要影响分离样品。

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