Abstract The Aerodynamic Aerosol Classifier (AAC) and Differential Mobility Analyzer (DMA) are aerosol classifiers commonly used to generate a monodispersed aerosol by selecting particles within a narrow range of relaxation times or electrical mobilities, respectively. However, generating an aerosol of homogeneous particles, which has narrow ranges of particle mass, mobility and relaxation time simultaneously, with either of these methods is challenging. Particles classified by the DMA are often not homogeneous (or monodispersed) due to multiply-charged particles. While the AAC overcomes this challenge for spherical particles, homogeneity is not achieved with non-spherical particles due to their effective density varying with particle size. This study demonstrates using an AAC and DMA in tandem to generate an aerosol of homogeneous, non-spherical particles. This approach is validated using scanning electron microscope (SEM) images and electrical mobility measurements of the tandem-classified particles to highlight their homogeneity. To limit the effects of multiple charging during DMA classification, only a subset of DMA and AAC setpoints are permitted. While this subset is not representative of “average” non-spherical particles from the same aerosol source, this subset of low-density particles deviates the most from spherical morphology, and thus, provide insights into the upper bound of other particle properties, such as charging. Using this approach to select homogeneous particles, the bipolar charge distribution of low-density soot aggregates is then measured using another DMA. This AAC-DMA-DMA approach is demonstrated to measure up to 17 individual charge states (i.e. −8 to +8) after neutralization (with 85Kr) of size-resolved, soot aggregates with mobility diameters between 80 and 433 nm. The low-density soot aggregates obtain higher charges than predicted by theory, which overestimates the uncharged fraction (by 0.042–0.069) and, to a lesser extent, the single charge fractions (by up to 0.037) of the low-density soot aggregates, while underestimating their proportion of multiple charging (by up to 0.135 cumulatively at one particle size or up to 0.039 at one multiple charge state and size). These charging discrepancies represent an upper bound of the bipolar charging of average aggregates from the same source of flame soot.

中文翻译：

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生成均质非球形颗粒的气溶胶并测量其双极电荷分布

摘要 空气动力学气溶胶分类器 (AAC) 和微分迁移率分析仪 (DMA) 是通常用于通过分别在较窄的弛豫时间或电迁移率范围内选择粒子来生成单分散气溶胶的气溶胶分类器。然而，使用这些方法中的任何一种生成均质颗粒的气溶胶，同时具有窄范围的颗粒质量、迁移率和弛豫时间是具有挑战性的。由于多电荷粒子，由 DMA 分类的粒子通常不是均质的（或单分散的）。虽然 AAC 克服了球形颗粒的这一挑战，但由于非球形颗粒的有效密度随颗粒尺寸而变化，因此无法实现均匀性。该研究表明，串联使用 AAC 和 DMA 可产生均匀的气溶胶，非球形颗粒。这种方法使用扫描电子显微镜 (SEM) 图像和串联分类粒子的电迁移率测量进行验证，以突出它们的均匀性。为了限制 DMA 分类期间多次充电的影响，只允许使用 DMA 和 AAC 设置点的子集。虽然这个子集不代表来自同一气溶胶源的“平均”非球形粒子，但这个低密度粒子子集与球形形态的偏差最大，因此，提供了对其他粒子属性上限的洞察，例如收费。使用这种方法来选择均匀颗粒，然后使用另一个 DMA 测量低密度烟灰聚集体的双极电荷分布。这种 AAC-DMA-DMA 方法被证明可以测量多达 17 个单独的电荷状态（即 -8 到 +8) 中和（用 85Kr）大小分辨的、迁移率直径在 80 到 433 nm 之间的烟灰聚集体。低密度煤烟聚集体获得比理论预测更高的电荷，这高估了低密度煤烟聚集体的不带电比例（0.042-0.069），并在较小程度上高估了单电荷比例（高达 0.037），同时低估了它们的多重充电比例（在一种颗粒尺寸下累计高达 0.135 或在一种多重充电状态和尺寸下累计高达 0.039）。这些充电差异代表来自同一火焰烟灰源的平均聚集体双极充电的上限。低密度煤烟聚集体获得比理论预测更高的电荷，这高估了低密度煤烟聚集体的不带电比例（0.042-0.069），并在较小程度上高估了单电荷比例（高达 0.037），同时低估了它们的多重充电比例（在一种颗粒尺寸下累计高达 0.135 或在一种多重充电状态和尺寸下累计高达 0.039）。这些充电差异代表来自同一火焰烟灰源的平均聚集体双极充电的上限。低密度煤烟聚集体获得比理论预测更高的电荷，这高估了低密度煤烟聚集体的不带电比例（0.042-0.069），并在较小程度上高估了单电荷比例（高达 0.037），同时低估了它们的多重充电比例（在一种颗粒尺寸下累计高达 0.135 或在一种多重充电状态和尺寸下累计高达 0.039）。这些充电差异代表来自同一火焰烟灰源的平均聚集体双极充电的上限。039 在一个多电荷状态和大小）。这些充电差异代表来自同一火焰烟灰源的平均聚集体双极充电的上限。039 在一个多电荷状态和大小）。这些充电差异代表来自同一火焰烟灰源的平均聚集体双极充电的上限。