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Mixing state of carbonaceous aerosol in an urban environment: single particle characterization using the soot particle aerosol mass spectrometer (SP-AMS)

机译:城市环境中碳质气溶胶的混合状态:使用烟尘颗粒气溶胶质谱仪(SP-AMS)进行单颗粒表征

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摘要

Understanding the impact of atmospheric black carbon (BC)-containingparticles on human health and radiative forcing requires knowledge of themixing state of BC, including the characteristics of the materials withwhich it is internally mixed. In this study, we examine the mixing state ofrefractory BC (rBC) and other aerosol components in an urban environment(downtown Toronto) utilizing the Aerodyne soot particle aerosol massspectrometer equipped with a light scattering module (LS-SP-AMS). -meanscluster analysis was used to classify single particle mass spectra intochemically distinct groups. One resultant particle class is dominated by rBCmass spectral signals (C to C) while the organicsignals fall into a few major particle classes identified ashydrocarbon-like organic aerosol (HOA), oxygenated organic aerosol (OOA),and cooking emission organic aerosol (COA). A gradual mixing is observedwith small rBC particles only thinly coated by HOA (~ 28%by mass on average), while over 90% of the HOA-rich particles did notcontain detectable amounts of rBC. Most of the particles classified intoother inorganic and organic particle classes were not significantlyassociated with rBC. The single particle results also suggest that HOA andCOA emitted from anthropogenic sources were likely major contributors toorganic-rich particles with vacuum aerodynamic diameter () rangingfrom ~ 200 to 400 nm. The similar temporal profiles and massspectral features of the organic classes identified by cluster analysis andthe factors from a positive matrix factorization (PMF) analysis of theensemble aerosol data set validate the interpretation of the PMF results.
机译:要了解含大气黑碳(BC)的颗粒对人体健康和辐射强迫的影响,需要了解BC的混合状态,包括内部混合材料的特性。在这项研究中,我们使用装有光散射模块(LS-SP-AMS)的Aerodyne烟灰颗粒气溶胶质谱仪,研究了城市环境(多伦多市中心)中难治性BC(rBC)和其他气溶胶成分的混合状态。 -均值聚类分析用于将单颗粒质谱分为化学上不同的组。一种最终的颗粒类别由rBCmass光谱信号(C到C)控制,而有机信号则分为几个主要的颗粒类别,分别被识别为类烃类有机气溶胶(HOA),氧化有机气溶胶(OOA)和蒸煮排放有机气溶胶(COA)。 。观察到仅用HOA薄涂的小rBC颗粒逐渐混合(平均约占质量的28%),而超过90%的富含HOA的颗粒不包含可检测量的rBC。归类为其他无机和有机颗粒类别的大多数颗粒与rBC没有显着关联。单个粒子的结果还表明,人为来源发出的HOA和COA可能是真空有机空气直径(〜)为200至400 nm的富含有机物的粒子的主要贡献者。通过聚类分析和有机气溶胶数据集的正矩阵因式分解(PMF)分析得出的因素,有机物类别的相似时间分布和质谱特征验证了对PMF结果的解释。

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