Applications of pm2.5 concentration from satellite aerosol optical depth for health impact assessment during and after covid-19 lockdown in Bangkok metropolitan region | |
| Author | Wissuta Woothisen |
| Call Number | AIT Thesis no.EV-24-08 |
| Subject(s) | Air--Pollution--Remote sensing--Thailand--Bangkok Air quality--Heath aspects--Thailand--Bangkok Air quality--Environment aspects--Thailand--Bangkok |
| 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 | The COVID-19 pandemic has underscored the critical interplay between respiratory health and environmental factors, notably air pollution. This thesis investigates the dynamics of PM2.5 concentrations in the Bangkok Metropolitan Region (BMR), focusing on during and after the lockdown of pandemic periods. PM2.5, a hazardous pollutant, poses significant health risks, especially in densely populated urban areas like Bangkok. The study utilizes MODIS's Aerosol Optical Depth (AOD) data to estimate PM2.5 levels and assesses their health impacts using the Environmental Benefits Mapping and Analysis Program (BenMAP). By analyzing the correlation between AODs, meteorological variables, and PM2.5 concentrations, the research aims to provide insights into the relationship between air quality and health impact in the BMR. The advantages of the AOD products from the MODIS satellite were utilized in this research to fill temporal data gaps for PM2.5 concentration estimation daily from January to December in BMR for 2019 and 2021. This study chose a statistical model to develop the relationship between daily AOD and PM2.5 concentration. Two models were examined: (1) Model AOD and PM2.5 with meteorological parameters in 2019 and (2) Model AOD and PM2.5 with meteorological parameters in 2021. The results indicated that the coefficient of determination (R2 ) of Model 2019 and 2021 was 0.41 and 0.70, respectively. Subsequently, Model 2019 and 2021, incorporating AOD, Temperature, Sea level pressure, and relative humidity, were employed to estimate PM2.5 concentration in BMR from January to December 2019 and 2021. The evaluation of the model indicated that the estimated daily PM2.5 concentrations closely matched the observed daily PM2.5 levels, with R2 values of 0.44 in 2019 and 0.58 in 2021 for all data spanning from January to December. The root mean square error (RMSE), Mean Absolute Error (MAE), and Index of agreement (d) in 2019 were 13.69 µg/m, 10.49 µg/m3 , and 0.87, respectively. Conversely, in 2021, the RMSE, MAE, and d were 11.26 µg/m3 , 9.54 µg/m3 , and 0.93, respectively. Subsequently, the Model 2019 and 2021 were utilized to generate monthly maps depicting the spatial distribution of PM2.5 from January to December. The relationship between daily AOD and PM2.5 was ultimately leveraged to estimate the annual average PM2.5 concentration in 2019 and 2021. Subsequently, the health impacts associated with PM2.5 concentration were assessed for long-term exposures. The findings revealed that in 2019, reducing PM2.5 concentration to the level recommended by WHO guidelines could potentially lead to a significant reduction in the highest number of deaths across all causes (4.5%), with the most substantial decreases observed in Ischemic Heart Disease (15.6%), followed by Lung Cancer (9.8%). Similarly, in 2021, lowering PM2.5 concentration could result in a notable reduction in the highest number of deaths across all causes (4.1%), with the most significant declines seen in Ischemic Heart Disease (14.3%), followed by Lung Cancer (8.9%). |
| Year | 2024 |
| Type | Thesis |
| School | School of Environment, Resources, and Development |
| 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) | Shipin, Oleg V.;Cruz, Simon Guerrero |
| Scholarship Donor(s) | Royal Thai Government Fellowship |
| Degree | Thesis (M. Sc.) - Asian Institute of Technology, 2024 |