Patipat Vongruang1,2, Kansak Suppoung1, Sukrit Kirtsaeng3, Kritana Prueksakorn4, Pham Thi Bich Thao5, Sittichai Pimonsree  This email address is being protected from spambots. You need JavaScript enabled to view it.1

1 Atmospheric Pollution and Climate Change Research Unit (APCC), School of Energy and Environment (SEEN), University of Phayao (UP), 56000, Thailand
2 Environmental Health, School of public health, University of Phayao, 56000, Thailand
3 Thai Meteorological Department, Bangkok, 10260, Thailand
4 Faculty of Environment and Resource Studies, Mahidol University, Nakhon Phathom, 73170, Thailand
5 Joint Graduate School of Energy and Environment (JGSEE), Centre of Excellence on Energy Technology and Environment (CEE), King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, 10140, Thailand


Received: January 10, 2024
Revised: May 28, 2024
Accepted: May 28, 2024

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.4209/aaqr.230321  


Cite this article:

Vongruang, P., Suppoung, K., Kirtsaeng, S., Prueksakorn, K., Thao, P.T.B., Pimonsree, S. (2024). Development of Meteorological Criteria for Classifying PM2.5 Risk in a Coastal Industrial Province in Thailand. Aerosol Air Qual. Res. https://doi.org/10.4209/aaqr.230321


 

ABSTRACT


The meteorological criteria for classifying the risk of PM2.5 problems were developed through a comprehensive approach in Samut Prakan, an industrial province located on the coast in a tropical climate zone. The relationship between meteorological criteria and PM2.5 risk level was conducted by analyzing the dataset of observed PM2.5 and meteorological parameters from 2018 to 2021. The results indicate that PM2.5 issues primarily arise during winter, with January recording the highest monthly concentration, exceeding the annual average by 83%. The high concentration in winter is related to low temperatures, wind speeds, and PBL heights that lead to low ventilation, which is 28% lower than the annual average in January. In the dry season, the mean daily ventilation index (VI) is the most sensitive meteorological parameter for PM2.5 variation and is used to classify PM2.5 risk levels: low risk (0–37 mg m-3) when VI > 2,369 m2 s-1; moderate risk (38–50 mg m-3) when VI = 1,606–2,369 m2 s-1; high risk (51–91 mg m-3) when VI = 886–1,605 m2 s-1; and very high risk (> 91 mg m-3) when VI < 886 m2 s-1. Meteorological criteria should be developed for each region based on climate, emission characteristics, methods, and data used for calculating these criteria, along with other local factors.


Keywords: Air quality management, Meteorological condition, PM2.5, Air quality risk, Ventilation index




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