A Study on Determining the Potential Source Area of PM2.5 Using Bivariate Polar Plot Technique on Short-Term Monitoring Data in Bhan Phi District, Khonkhen Province, Thailand
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Abstract
The issue of particulate matter less than 2.5 microns (PM2.5) has been concerning and important for many countries and Thailand. Many studies in Thailand have focused on the contribution of source types determined by a receptor model, the relationship between PM2.5 and meteorological factors, and the impacts of PM2.5 on human health. In terms of enforcement and management, it is important to know where the pollution comes from. A statistical technique, Bivariate Polar Plot (BVP), has been used to determine the potential source areas affecting air quality and PM2.5 levels at the monitoring location. However, fewer studies are using the BVP in Thailand, especially in rural areas with many air pollution sources surrounding the monitoring station. Moreover, most studies used long-term monitoring data in the analysis. This study was conducted in Ban Phai District, Khon Kaen Province. The results show that 6 days of the 13 days monitoring period with the concentration of PM2.5 particulate matter exceeds 50 µg/m3, the 24-hour average standard of Thailand, and is the interim target 2 (IT-2) of the World Health Organization (WHO). In addition, the results showed that the analysis of short-term hourly monitoring data of PM2.5 could reveal changes in concentrations related to meteorological factors and atmospheric stability. The BVP technique identified the potential source areas of PM2.5 over each period, and their locations changed depending on emission and meteorological factors of the corresponding period. The potential source areas are on the north side of the highway, Ban Phai District's urban area, and the open burning area on the east side. The pollution sources on the southern side of the air quality monitoring station do not exhibit as a potential source.
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References
World Health Organization. WHO global air quality guidelines: particulate matter (PM2.5 and PM10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide [Internet]. Geneva: World Health Organization; 2021 [cited 2021 Oct 1]. Available from: https://
apps.who.int/iris/handle/10665/345329
World Health Organization, editor. WHO Air quality guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide Global update 2005 Summary of risk assessment. Switzerland: World Health Organization; 2006. p. 21.
Cheng Z, Luo L, Wang S, Wang Y, Sharma S, Shimadera H, et al. Status and characteristics of ambient PM2.5 pollution in global megacities. Environ Int. 2016;89–90:212–21.
Kanchanasuta S, Sooktawee S, Patpai A, Vatanasomboon P. Temporal variations and potential source areas of fine particulate matter in Bangkok, Thailand. Air Soil Water Res. 2020;13:1–10.
Kanchanasuta S, Sooktawee S, Bunplod N, Patpai A, Piemyai N, Ketwang R. Analysis of short-term air quality monitoring data in a coastal area. AIMS Environ Sci. 2021;8(6):517–31.
Sooktawee S, Kanabkaew T, Boonyapitak S, Patpai A, Piemyai N. Characterising particulate matter source contributions in the pollution control zone of mining and related industries using bivariate statistical techniques. Sci Rep. 2020;10(1):21372.
Khamkaew C, Chantara S, Wiriya W. Atmospheric PM2.5 and its elemental composition from near source and receptor sites during open burning season in Chiang Mai, Thailand. Int J Environ Sci Dev. 2016;7(6):436–40.
Sooktawee S, Kongsong R, Boonyapitak S, Patpai A, Piemyai N. Identify the Plausible Potential Source Areas Related to Haze Episode in the Upper Northern Thailand. In: The 2nd Environment and Natural Resources International Conference (ENRIC 2016). Phra Nakhon Si Ayutthaya Province, Thailand; 2016. p. 18–25.
Kanabkaew T, Kim Oanh NT. Development of spatial and temporal emission inventory for crop residue field burning. Environ Model Assess. 2011;16(5):453–64.
Sooktawee S, Kanchanasuta S, Boonyapitak S, Patpai A, Piemyai N. Distinguish potential source areas of PM2.5 and PM10 by statistical data analysis. IOP Conf Ser Earth Environ Sci. 2020;489:012024.
Punya L, Thepanondh S, Kwonpongsagoon S, Laowagul W, Sukjit N, Hanma P. Formation potentiality and source apportionment analysis of secondary organic aerosol in urban and suburban area, Thailand. Songklanakarin J Sci Technol. 2022;44(1):191–200.
Sooktawee S, Humphries U, Patpai A, Kongsong R, Boonyapitak S, Piemyai N. Visualization and interpretation of PM10 monitoring data related to causes of haze episodes in Northern Thailand. Appl Environ Res. 2015;37(2):33–48.
Aman N, Manomaiphiboon K, Pala-En N, Kokkaew E, Boonyoo T, Pattaramunikul S, et al. Evolution of urban haze in greater Bangkok and association with local meteorological and synoptic characteristics during two recent haze episodes. Int J Environ Res Public Health. 2020;17(24):9499.
Narita D, Oanh NTK, Sato K, Huo M, Permadi DA, Chi NNH, et al. Pollution characteristics and policy actions on fine particulate matter in a growing Asian economy: The case of Bangkok metropolitan region. Atmosphere. 2019;10(5):227.
Oanh N, Pongkiatkul P, Cruz M, Dung N, Phillip L, Zhuang G, et al. Monitoring and source apportionment for particulate matter pollution in six Asian cities. In: Integrated Air Quality Management. CRC Press; 2012. p. 97–124.
Jinsart W, Tamura K, Loetkamonwit S, Thepanondh S, Karita K, Yano E. Roadside particulate air pollution in Bangkok. J Air Waste Manag Assoc. 2002;52(9):1102–10.
Amnuaylojaroen T, Parasin N, Limsakul A. Health risk assessment of exposure near-future PM2.5 in Northern Thailand. Air Qual Atmosphere Health. Forthcoming 2022.
Pimonsree S, Wongwises P, Pan-Aram R, Zhang M. Model analysis of PM10 concentration variations over a mineral products industrial area in Saraburi, Thailand. Water Air Soil Pollut. 2009;201(1–4):239–51.
Phetrawech T, Thepanondh S. Source contributions of PM10 concentrations in the Na Phra Lan pollution control zone, Saraburi, Thailand. Sci Technol Asia. 2017;22(4):60–70.
Sakunkoo P, Thonglua T, Sangkham S, Jirapornkul C, Limmongkon Y, Daduang S, et al. Human health risk assessment of PM2.5-bound heavy metal of anthropogenic sources in the Khon Kaen Province of Northeast Thailand. Heliyon. 2022;8(6):e09572.
Amnuaylojaroen T, Inkom J, Janta R, Surapipith V. Long Range transport of Southeast Asian PM2.5 pollution to Northern Thailand during high biomass burning episodes. Sustainability. 2020;12(23):10049.
Nguyen GTH, Shimadera H, Uranishi K, Matsuo T, Kondo A, Thepanondh S. Numerical assessment of PM2.5 and O3 air quality in continental Southeast Asia: Baseline simulation and aerosol direct effects investigation. Atmos Environ. 2019;219:117054.
Uria-Tellaetxe I, Carslaw DC. Conditional bivariate probability function for source identification. Environ Model Softw. 2014;59:1–9.
Killick R, Eckley IA. Changepoint: An R package for changepoint analysis. J Stat Softw. 2014;58(3). DOI 10.18637/jss.v058.i03.
Ropkins K, Carslaw DC. Openair - data analysis tools for the air quality community. R J. 2012;4(1):20.
Pikulyam W. [Development of data visualization for particulate matter 2.5 micrometers analysis in Bangkok]. J Appl Res Sci Tech. 2021;20(1):157–64. Thai.