4.5 Article

Application of a diffusion charger for the measurement of particle surface concentration in different environments

期刊

AEROSOL SCIENCE AND TECHNOLOGY
卷 41, 期 6, 页码 571-580

出版社

TAYLOR & FRANCIS INC
DOI: 10.1080/02786820701272020

关键词

-

向作者/读者索取更多资源

Particle surface area has recently been considered as a possible metric in an attempt to correlate particle characteristics with health effects. In order to provide input to such studies, two Nanoparticle Surface Area Monitors (NSAMs, TSI, Inc.) were deployed in different urban sites within Los Angeles to measure the concentration levels and the diurnal profiles of the surface area of ambient particles. The NSAM's principle of operation is based on the unipolar diffusion charging of particles. Results show that the particle surface concentration decreases from similar to 150 mu m(2) cm(-3) next to a freeway to similar to 100 mu m(2) cm(-3) at 100 m downwind of the freeway, and levels decline to 50 - 70 mu m(2) cm(-3) at urban background sites. Up to 51% and 30% of the total surface area corresponded to particles < 40 nm next to the freeway and at an urban background site, respectively. The NSAM signal was well correlated with a reconstructed surface concentration based on the particle number size distribution measured with collocated Scanning Mobility Particle Sizers (SMPSs, TSI, Inc.). In addition, the mean surface diameter calculated by combination of the NSAM and the total particle number concentration measured by a Condensation Particle Counter (CPC, TSI, Inc.) was in reasonable agreement with the arithmetic mean SMPS diameter, especially at the urban site. This study corroborates earlier findings on the application of diffusion chargers for ambient particle monitoring by demonstrating that they can be effectively used to monitor the particle surface concentration, or combined with a CPC to derive the mean surface diameter with high temporal resolution.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据