Improvement of GPS-attached Pocket PM2.5 Measuring Device for Personal Exposure Assessment

Assessment of personal exposure to particulate matter with an aerodynamic diameter less than or 2.5 µm (PM2.5) is necessary to study the association between PM exposure and health risk. Development of a personal PM2.5 sensor or device is required for the evaluation of individual exposure level. In t...

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Bibliographic Details
Published inJournal of UOEH Vol. 42; no. 4; pp. 307 - 315
Main Authors WIN-SHWE, Tin-Tin, THEIN, Zaw Lin, AUNG, Win Yu, Ei Ei Pan Nu YI, MAUNG, Cherry, NWAY, Nay Chi, THANT, Zarli, SUZUKI, Takehiro, MAR, Ohn, ISHIGAKI, Yang, NAKAJIMA, Daisuke
Format Journal Article
LanguageEnglish
Japanese
Published Japan The University of Occupational and Environmental Health, Japan 01.12.2020
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Summary:Assessment of personal exposure to particulate matter with an aerodynamic diameter less than or 2.5 µm (PM2.5) is necessary to study the association between PM exposure and health risk. Development of a personal PM2.5 sensor or device is required for the evaluation of individual exposure level. In this study, we aimed to develop a small-sized, lightweight sensor with a global positioning system (GPS) attached that can measure PM2.5 and PM10 every second to assess continuous personal exposure levels. The participants in this study were apparently healthy housewives (n = 15) and university female teaching staff (n = 15) who live in a high PM2.5 area, Yangon, Myanmar. The average PM2.5 exposure levels during 24 h were 16.1 ± 10.0 µg/m3 in the housewives and 15.8 ± 4.0 µg/m3 in the university female teaching staff. The university female teaching staff showed high exposure concentrations during commuting hours, and had stable, relatively low concentrations at work, whereas the housewives showed short-term high exposure peaks due to differences in their lifestyles. This is the first study to show that a GPS-attached standalone PM2.5 and PM10 Sensor [PRO] can be successfully used for mobile sensing, easy use, continuous measurement, and rapid data analysis.
ISSN:0387-821X
2187-2864
DOI:10.7888/juoeh.42.307