American Association for Aerosol Research - Abstract Submission

AAAR 35th Annual Conference
October 17 - October 21, 2016
Oregon Convention Center
Portland, Oregon, USA

Abstract View


Quantitative Analysis of Nanoparticle Size Distribution with Scanning Electron Microscope for Personal Exposure Measurement

MAROMU YAMADA, Sheng-Chieh Chen, David Y. H. Pui, University of Minnesota

     Abstract Number: 656
     Working Group: Aerosol Exposure

Abstract
Personal exposure assessment to nanomaterial particles is strongly needed in occupational health field. In workplaces handling nanomaterials, direct-reading instruments and gravimetric/chemical analyses are generally applied to quantitative analyses of the nanomaterial particles. However, there are some problems in these measurements, e.g. the direct-reading instruments are not able to distinguish nanomaterials from ambient nanoparticles, gravimetric/chemical analyses require large volume of aerosol samples, and only limited morphological information can be obtained. Therefore, in this study, a new approach for quantitative analysis of nanomaterial particle concentration and their number size distribution with a scanning electron microscope (SEM) is investigated for accurate personal exposure measurements. An active personal nanoparticle sampler (PENS) composed of a micro-orifice impactor (MOI) and a subsequent 25-mm Nuclepore filter is applied for the nanoparticle samplings. Potassium chloride and silver particles are used for evaluating cutoff size of the MOI and collection efficiency of the Nuclepore filters. Cutoff size of the impactor can be varied from 400 to 100 nm depending on the operation flow rate from 0.5 to 2.0 LPM. Surface-collection efficiency of the Nuclepore filter for nanoparticles was confirmed and compared with previously suggested surface-collection efficiency models. These results obtained provide information for a method of personal exposure measurements by using the PENS as well as for considering further methodology of exposure assessment with SEM.