An Approach of Statistical Analysis and Interpretation on PM2.5 Concentration with Meteorological Factors and Temperature effects in Bangkok Area.

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chalisa veesommai


Currently, Bangkok is facing with air pollution as continuously problem. In particular, the fine particulate matter (PM2.5, diameter> 2.5µm) and meteorological changes, have effect problem of PM2.5 and more severe situation. It causes affects to public health and environment. Therefore, the objective of this research is to study the meteorological factors influencing the changing of PM2.5 concentration in Bangkok area. In the methodology, the relationship between meteorological factors was analyzed such as relative humidity, wind direction, wind speed, temperature, and air pressure by using statistically significant relationship with the PM2.5 concentration. The correlation coefficients were-0.270, -0.127, -0.013, –0.130 and 0.084, respectively. Especially relative humidity can be referred to the variation in PM2.5 (approximately 64.20%) at high PM2.5 concentrations in winter and in the rush hour of every year. In addition, the occurrence of the Temperature Inversion (TI) affects to the concentration of PM2.5 during the 4 years of study period (2016 and 2018-2020). The trend of TI is the increasing of occurrences changes and longer period of TI. The highest to lowest of TI is on 2020, 2016, 2019, and 2018, respectively. 


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Chakrit C. and Duangnapha L. (2018). Meteorological Factors Related to Air Pollution in Chiang Mai Province. Journal of Research Unit on Science, Technology and Environment for Learning 9(2), 237-249

Lou, C., Liu, H., Li, Y., Peng, Y., Wang, J. and Dai, L. (2017). Relationships of relative humidity with PM 2.5 and PM 10 in the Yangtze River Delta, China. Environmental monitoring and assessment, 189(11), 1-16.

Kwanma, P., Pukngam, S. and Arunpraparu, W. (2019). Meteorological factors Affecting Concentration of PM10 At Na Phra Lan Sub-district, Chaloem Phra Kiat, Saraburi. PSRU Journal of Science and Technology, 4(2), 85-94.

Patcharasak Alai. (2019). PM 2.5 dust phenomenon and sustainable solutions. Academic seminar on "PM 2.5 dust catastrophe and sustainable management ". Nakhon Pathom Rajabhat University.

Pollution Control Department (PCD). Pollution Prevention and Mitigation Policy 1997–2016. Available online: (March 1, 2021)

Sam F. Iacobellis, Joel R. Norris, Masao Kanamitsu, Mary Tyree, and Daniel C. Cayan. (2009). Weather variability, and California low-level Temperature infiltration. California Climate Change Center.

Sivarin D, Wongpun L. and Panwadee S. (2013). Carbon composition of PM10 and PM2.5 in Bangkok ambient air from a city center sampling site. Rangsit Journal of Arts and Sciences, 3(1), 17-23.

Thuy T. T. Tham T. T. Trinh T. L. Nguyen T. D. H. and Binh M. T. (2019). Temperature inversion and air pollution relationship and its effects on human health in Hanoi City, Vietnam. Environ Geochem Health. 41, 929–937.

Veesommai C. and Kiyoki Y. 2019. An analytical relationship retrieval scenario with temporal information data approaching to plastic waste-leaks into marine environments. The 21th International Electronics Symposium (IES). IEEE. 19, 320-324.

Veesommai C. and Kiyoki Y. 2018. Spatial Dynamics of The Global Water Quality Analysis System with Semantic-ordering functions. Information Modelling and Knowledge Base XXIX, 301, 149 – 163.

Xu, Y., Zhu, B., Shi, S. and Huang, Y. (2019). Two inversion layers and their impacts on PM2. 5 concentration over the Yangtze River Delta, China. Journal of Applied Meteorology and Climatology, 58(11), 2349-2362.

Zang, Z., Wang, W., You, W., Li, Y., Ye, F. and Wang, C. (2017). Estimating ground-level PM2.5 concentrations in Beijing, China using aerosol optical depth and parameters of the temperature inversion layer. Science of the Total Environment, 575, 1219-1227.