Estimating hourly full-coverage PM2.5 concentrations model based on MODIS data over the northeast of Thailand

被引：0
作者：
Wilawan Kumharn
Sumridh Sudhibrabha
Kesrin Hanprasert
Serm Janjai
Itsara Masiri
Sumaman Buntoung
Somjet Pattarapanitchai
Rungrat Wattan
Choedtrakool Homchampa
Terathan Srimaha
Oradee Pilahome
Waichaya Nissawan
Yuttapichai Jankondee
机构：
[1] Sakon Nakhon Rajabhat University,Department of Physics, Faculty of Science and Technology
[2] Thai Meteorological Department,Department of Physics, Faculty of Science
[3] Silpakorn University,undefined
来源：
Modeling Earth Systems and Environment | 2024年 / 10卷
关键词：
Particulate matter2.5; Aerosol optical depth; Linear mixed effect; Meteorological factors;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Particulate matter (PM2.5) pollutants are a significant health issue impacting human health. To monitor hourly PM2.5 data, ground-based and satellite data are essential. This work aims to improve the hourly PM2.5 model obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data over Northeastern Thailand in 2020. In addition, an innovative combination of MODIS was developed to fulfill all missing aerosol optical depth (AOD) data before being applied to the model. A Linear mixed-effects (LME) model was utilized, and a 10- fold cross-validation was addressed for validation. It was found that hourly PM2.5 data from the models gave R2 > 0.70. Interestingly, PM2.5 data along the Mekong River area were higher than in the plain area. The finding can infer that the monsoon wind brings polluted air into the region. The results will help analyze air pollution-related health studies.
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页码：1273 / 1280
页数：7
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