Estimation of fine particulate matter concentrations in urban areas using satellite-derived aerosol optical depth | |
| Author | Bongkotporn Jachernram |
| Call Number | AIT Thesis no.EV-21-22 |
| Subject(s) | Air--Pollution--Estimates Particulate matter--Environmental aspects Air quality--Environmental aspects |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Environmental Engineering and Management |
| Publisher | Asian Institute of Technology |
| Abstract | Air pollution has been recognized as one of the largest health and environmental problems in the world, especially in many developing countries (Kanada et al., 2013). In Bangkok, high Particulate Matter (PM) concentration occurs every year. The level of pollutants in Bangkok Metropolitan Region (BMR) are increasing. Satellite measurement provides monitoring data covering large area on the Earth (Weng, 2013). Prediction of the ground based PM2.5 by AOD retrieval on optical properties of particles. Fine-resolution AOD can reveal more spatial detail on PM2.5 pollution than coarse-resolution AOD, benefitting urban-scale spread of studies. In this study, the high spatial-resolution of SARA-MODIS was developed by Jansakoo (2020) and high temporal resolution of Himawari-8 was used for estimation both high spatial and temporal distribution of PM2.5 concentration in the BMR region. The AOD products with a resolution of 0.5x0.5 km2 provided the relationship between AOD Himawari-8&MODIS and AOD AERONET at the Bangkok station to correlate with R2 equal to 0.36. Additionally, the RMSE and MAE were 0.091 and -0.058 of January, 0.115 and -0.075 of February, 0.226 and -0.166 of March, and 0.187 and -0.114 of April respectively. The overall results illustrated that the observed PM2.5 concentration was agreed well with the AOD products from two satellites correlated with R2 equal to 0.67. In addition, the results represented that the estimated PM2.5 concentration was a better relationship with the observed PM2.5 concentration with a correlation coefficient of 0.67 in the equation train set and a correlation coefficient of 0.73 in the equation test set respectively. However, the prediction model was underestimate, especially for the PM2.5 concentration more than 75 µg/m3 . |
| Year | 2021 |
| Type | Thesis |
| School | School of Environment, Resources, and Development (SERD) |
| Department | Department of Energy and Climate Change (Former title: Department of Energy, Environment, and Climate Change (DEECC)) |
| Academic Program/FoS | Environmental Engineering (EV) |
| Chairperson(s) | Ekbordin Winijkul |
| Examination Committee(s) | Xue, Wenchao;Virdis, Salvatore G.P. |
| Scholarship Donor(s) | Royal Thai Government Fellowship |
| Degree | Thesis (M. Sc.) - Asian Institute of Technology, 2021 |