Development of Particle Distribution Estimation (PDE) Model Based on Particulate Mass Concentration for Indoor Ambient Air Monitoring

Angelo Sean Franci, and Chee, Fuei Pien and Justin Sentian, and Jackson Hian Wui Chang, (2020) Development of Particle Distribution Estimation (PDE) Model Based on Particulate Mass Concentration for Indoor Ambient Air Monitoring. ASM Sc. J. pp. 1-6.

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Abstract

Particulate Matter (PM) mass concentration is one of the key elements in determining Air Quality Index (AQI). Conventionally, PM mass concentration is measured using Federal Reference Method (FRM) which apply the filter based gravimetric method. While the mass concentration may be used as a threshold limit on particulate matter exposure, recent studies had shown that particles distribution may provide better insight on the adverse effect of particulate matter exposure. In this study a Particle Distribution Estimation Model (PDE) was developed for determination of particle distribution based on particulate mass concentration. The model was developed using correlation between Particle distribution and particulate mass concentration from purple Air-II (PA-II) an optical based research grade instrument. The Particle Distribution Estimation (PDE) Model was evaluated at an outdoor environment. The estimated particle distribution from the PDE shows excellent correlation with the actual particle distribution from the reference instrument with R2is higher than 0.8.

Item Type: Article
Uncontrolled Keywords: PM2.5, Particle Distribution, Particulate Matter, Air Quality
Subjects: Q Science > Q Science (General)
Divisions: FACULTY > Faculty of Science and Natural Resources
Depositing User: SITI AZIZAH BINTI IDRIS -
Date Deposited: 26 Nov 2020 07:24
Last Modified: 15 Jan 2021 08:28
URI: http://eprints.ums.edu.my/id/eprint/26378

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