Publication:
Distinguish Potential Source Areas of PM<inf>2.5</inf> and PM<inf>10</inf> by Statistical Data Analysis

dc.contributor.authorS. Sooktaweeen_US
dc.contributor.authorS. Kanchanasutaen_US
dc.contributor.authorS. Boonyapitaken_US
dc.contributor.authorA. Patpaien_US
dc.contributor.authorN. Piemyaien_US
dc.contributor.otherMahidol Universityen_US
dc.contributor.otherCenter of Excellence on Environmental Health and Toxicologyen_US
dc.contributor.otherMinistry of Natural Resources and Environmenten_US
dc.date.accessioned2020-08-25T09:42:25Z
dc.date.available2020-08-25T09:42:25Z
dc.date.issued2020-05-27en_US
dc.description.abstract© Published under licence by IOP Publishing Ltd. Power plant from biomass in community area has been complained as emission source of many pollutants such as wastewater, noise, odor and polluted air. For air pollution, total suspended particulate (TSP) and particulate matter less than 10 micron (PM10) from rice husk energy process is quite large. Roi Et is a province located in Northeast of Thailand which obtains power plants using rice husk as fuel in the process. According to the land-use pattern of the community area of Roi Et, it revealed that there are many sources of air pollution. This study selected the statistical techniques to distinguish the potential source area influencing the high concentrations of particulate matter less than 2.5 micron (PM2.5), particulate matter 2.5 to 10 micron (PMcoarse), and PM10 which caused the health effects of people around the rice husk power plants. Hourly observed PM10 and PM2.5 data were analysed by time series and bivariate polar plot. Results showed that increasing the concentration of PM10 and PM2.5 were observed in the duration of low wind speed. However, daily average of PM10 was not more than National Ambient Air Quality Standard (NAAQS) which is 120 μg/m3. In contrast, results showed that daily average of PM2.5 performed over NAAQS of 50 μg/m3 in the 20th -22nd December 2018 that high pressure cover Thailand. While sources of these particulate matters could be distinguished into 3 potential areas based on the mobile air quality monitoring station location which were 1) east side and 2) north-west side which regarded as sub-urban and traffic areas, respectively and 3) north-east side which regarded as power plants area. Results revealed that PMcoarse was the major pollutant dispersed from the Northeast direction that the power plants were the major source. Whereas traffic and community were the main sources of PM2.5 coming from the East and the Northwest direction of the mobile air quality monitoring station point. Therefore, discrimination of each point source could be done first before implementing to control and manage the air pollution effectively.en_US
dc.identifier.citationIOP Conference Series: Earth and Environmental Science. Vol.489, No.1 (2020)en_US
dc.identifier.doi10.1088/1755-1315/489/1/012024en_US
dc.identifier.issn17551315en_US
dc.identifier.issn17551307en_US
dc.identifier.other2-s2.0-85086269880en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/57863
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85086269880&origin=inwarden_US
dc.subjectEarth and Planetary Sciencesen_US
dc.subjectEnvironmental Scienceen_US
dc.titleDistinguish Potential Source Areas of PM<inf>2.5</inf> and PM<inf>10</inf> by Statistical Data Analysisen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85086269880&origin=inwarden_US

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