The Application of Google Earth Engine on PM2.5 Estimation and its Distribution Pattern in Saraburi Province, Thailand

In 2019, air pollution in Thailand caused 41,000 deaths, with Saraburi province identified as an area of concern for air pollution monitoring. From 2020 to 2022, there were consistently reported cases of respiratory diseases caused by prolonged exposure to air pollution in this province. Moreover, the number of air quality monitoring stations in Saraburi is insufficient for accurate future predictions of particulate matter levels. Therefore, this research aims to estimate PM2.5 concentrations from Aerosol Optical Depth (AOD) and meteorological data and study the spatial distribution patterns of PM2.5 in Saraburi Province. The estimation of PM2.5 levels is conducted using AOD data combined with meteorological data through a Multiple Linear Regression (MLR) method. The estimated values are then used to analyze the distribution patterns of PM2.5. The study found that in 2018, the average monthly PM2.5 concentration ranged from 0 to 74.1 μg/m³, with high-value clustering (hot spots) covering approximately 421.43 km², or 12.04% of the provincial area. In 2019, the average monthly PM2.5 concentration ranged from 0 to 41.4 μg/m³, with hot spots covering approximately 509.29 km², or 14.55% of the provincial area. In 2020, the average monthly PM2.5 concentration ranged from 0 to 50.0 μg/m³, with hot spots covering approximately 648.37 km², or 18.53% of the provincial area. In 2021, the average monthly PM2.5 concentration ranged from 0 to 55.3 μg/m³, with hot spots covering approximately 562.93 km², or 16.09% of the provincial area. In 2022, the average monthly PM2.5 concentration ranged from 0 to 57.3 μg/m³, with hot spots covering approximately 615.97 km², or 18% of the provincial area. The most of high-value clusters were in the western part of the province, where agricultural activities are prevalent, contributing to higher PM2.5 levels. In contrast, low-value clusters (cold spots) were primarily found in the eastern part of the province, which is largely forested.