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Modeling to Measure the Diffusion Distance of Particulate Matter 2.5 from Combustion of Agricultural Areas |
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| รหัสดีโอไอ | |
| Creator | Ekkawit Sittiwa |
| Title | Modeling to Measure the Diffusion Distance of Particulate Matter 2.5 from Combustion of Agricultural Areas |
| Contributor | Warachanan Choothong, Thiraphat Meesumrarn, Withoon Sontipak, Krisda Khankasikam, Khaninnat chotphornseema |
| Publisher | Faculty of Informatics, Mahasarakham University |
| Publication Year | 2569 |
| Journal Title | Journal of Applied Informatics and Technology |
| Journal Vol. | 8 |
| Journal No. | 2 |
| Page no. | 260470 |
| Keyword | Agricultural Burning, Air Pollution, Environmental Modeling, Gaussian Plume Model, PM2.5, Pollution Dispersion |
| URL Website | https://ph01.tci-thaijo.org/index.php/jait |
| Website title | Journal of Applied Informatics and Technology |
| ISSN | 3088-1803 |
| Abstract | Air pollution caused by fine particulate matter (PM2.5) is a major envi-ronmental and public health concern, particularly in Northern Thailand.Agricultural residue burning is a primary contributor to PM2.5 pollutionin Nakhon Sawan Province, Thailand, where rice and sugarcane cultiva-tion generate substantial biomass waste. This study develops a dispersionmodel based on the Gaussian Plume Model to analyze PM2.5 spread fromburning sites, aiding pollution forecasting and management. The method-ology comprises three steps: (1) calculating PM2.5 emission rates, (2)predicting dispersion using meteorological data, and (3) visualizing re-sults through concentration graphs and geospatial mapping. The modelevaluates PM2.5 dispersion under different wind speeds (light, moderate,and strong) and atmospheric stability conditions. Simulated results indi-cate that PM2.5 concentrations peak near the source and decrease alongthe x-axis. Under light breeze conditions, the PM2.5 concentration at125 meters is 0.00245μg/m3, decreasing to nearly zero at 1,000 meters.Stronger winds enhance dispersion, reducing concentrations more rapidly.The findings confirm the model’s effectiveness in estimating PM2.5 dis-persion and emphasize the influence of meteorological factors on pollutantdistribution. Future improvements should incorporate geographical fac-tors, additional emission sources, and regional accumulation effects forimproved accuracy. The model provides a foundation for policymakersto develop air pollution mitigation strategies that promote public healthand environmental sustainability.1. IntroductionPM2.5 is a particulate matter that significantly con-tributes to air pollution and currently has the mostsubstantial impact on human health. PM2.5 can beproduced from various sources, such as emissions fromvehicle engines, forest fires, and the burning of agricul-tural waste. According to air quality monitoring by thePollution Control Department in Northern Thailand,six provinces have recorded pollution levels exceedingthe standard: Chiang Rai, Chiang Mai, Lampang, Lam-phun, Phrae, and Nan (Pollution Control Department,2019). In Nakhon Sawan province, pollution levels ex-ceeded the standard by 11–20% throughout the year(Air Quality and Noise Management Bureau, PollutionControl Department, 2020).The predominant factor contributing to elevatedpollution levels in Nakhon Sawan province is the openburning of agricultural residues following harvest. Ap-proximately 49% of the province’s agricultural landis allocated to rice and sugarcane cultivation, bothof which generate significant residual biomass. Post-harvest residue management practices primarily involveeither plowing the biomass into the soil or burning it toprepare for the subsequent planting season. When farm-ers opt for burning, particularly during periods of stag-nant atmospheric conditions with minimal wind, the ac-cumulation of fine particulate matter (PM2.5) in the airsignificantly increases. This practice is a major contrib-utor to pollution levels that frequently exceed estab-lished air quality standards (Wongwaitayakool, 2018).Due to the issue of air pollution accumulation ex-ISSN 3088-1803 | Copyright© 2026. Published by the Faculty of Informatics, Mahasarakham University. All rights reserved.This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). |
