ngocdangytcc@gmail.com
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Abstract
Asian countries often exhibit complex sources of PM2.5 particulate pollution within community living environments, primarily influenced by their distinctive cultural practices and lifestyles. Despite this complexity, current assessments of PM2.5 exposure are primarily based on data from fixed monitoring stations. This reliance on static measurements poses a risk of underestimating actual personal exposure levels, as individual activities and interactions with pollution sources vary considerably throughout the day. Technological advancements have enabled the adoption of low-cost air pollution sensors that offer several advantages over traditional monitoring systems, including affordability, portability, and the ability to measure multiple pollutants simultaneously. In this study, a longitudinal monitoring approach was employed using low-cost sensors to assess PM2.5 exposure among 36 volunteers, alongside measurements from seven fixed emission sources in Ho Chi Minh City. The average daily PM2.5 concentrations at fixed monitoring sites generally complied with the permissible limits set by the Vietnamese National Technical Regulation on Ambient Air Quality (QCVN05:2023). However, personal exposure during specific activities—namely commuting, shopping, cooking/eating, and housework—was found to significantly exceed levels associated with sedentary behaviors. The odds ratios (OR) for these activities were 4.51, 6.19, 5.58, and 2.63, respectively (p<0.01). These findings underscore the importance of expanding research efforts with larger populations and extended monitoring periods to better identify the key determinants of PM2.5 exposure in urban environments such as Ho Chi Minh City.
Article Details
Keywords
PM2.5, exposure, fixed sources, mobile sources, low-cost sensors
References
2. IQAir. World Air Quality Report 2021. IQAir website. 2021. https://www.iqair.com/blog/press-releases/WAQR_2021_PR
3. Li T, Hu R, Chen Z, et al. Fine particulate matter (PM2.5): The culprit for chronic lung diseases in China. Chronic Dis Transl Med. 2018;4(3):176-186. doi:10.1016/j.cdtm.2018.07.002
4. Li YC, Qiu JQ, Shu M, et al. Characteristics of polycyclic aromatic hydrocarbons in PM2.5 emitted from different cooking activities in China. Environ Sci Pollut Res Int. 2018;25(5):4750-4760. doi:10.1007/s11356-017-0603-0
5. Lung SCC, Chen N, Hwang JS, et al. Panel study using novel sensing devices to assess associations of PM2.5 with heart rate variability and exposure sources. J Expo Sci Environ Epidemiol. 2020;30(6):937-948. doi:10.1038/s41370-020-0254-y
6. Lung SCC, Hsiao PK, Wen TY, et al. Variability of intra-urban exposure to particulate matter and CO from Asian-type community pollution sources. Atmospheric Environment. 2014;83:6-13. doi:10.1016/j.atmosenv.2013.10.046
7. Michael Heimbinder, Chris Lim. AirBeam3 Technical Specifications, Operation & Performance. https://www.habitatmap.org/blog/airbeam3-technical-specifications-operation-performance