five

Effect of aerosol volatility on the sizing accuracy of Differential Mobility Analyzers

收藏
Taylor & Francis Group2016-01-18 更新2026-04-16 收录
下载链接:
https://tandf.figshare.com/articles/dataset/Effect_of_aerosol_volatility_on_the_sizing_accuracy_of_Differential_Mobility_Analyzers/960566/1
下载链接
链接失效反馈
官方服务:
资源简介:
Differential mobility analyzers (DMAs) are widely used for calibrating other instruments and measuring aerosol size distributions. DMAs classify aerosol particles according to their electrical mobility, which is assumed to be constant during the classification process. However, particles containing semi-volatile substances can change their size in the DMA, leading to sizing errors. In this paper, the effect of particle size changes during the classification process on the sizing accuracy of DMAs is discussed. It is shown that DMAs select particles whose time-of-flight-averaged electrical mobility is equal to that of stable particles that are selected under given operating conditions. For evaporating particles, this implies that DMAs select particles that are originally larger than the reported size. At the exit of the DMA, selected particles are smaller than the reported size. Particle evaporation and growth inside DMAs was modeled to study the effect of particle size changes on the sizing accuracy and the transfer function of DMAs in constant- and scanning-voltage modes of operation. Modeling predictions were found to agree well with the results of experiments with ammonium nitrate aerosol. The model was used to estimate sizing errors when measuring hygroscopic and other volatile aerosols. Errors were found to be larger at smaller sizes and low sheath flow rates. Errors, however, are fairly small when saturation concentration is below 10 μg/m<sup>3</sup>, assuming an evaporation coefficient of 0.1. Particles size changes during classification lead to distortion of the DMA transfer function. In voltage scanning mode, errors are generally larger, especially at high scan rates.
创建时间:
2014-05-19
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作