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To understand the dynamics of aerosols and their associated influence on regional and global climatic conditions requires the knowledge of spatial and temporal distributions of aerosols on regional and global scales. In this study, the satellite-based MODIS AODs retrievals level 2 products from Terra (MOD04-10 km) and Aqua (MYD04-10 km) satellites were inter-compared with the ground-based AERONET AODs (level 2) over Nghia Do station located in an urban area of Hanoi city, Vietnam for the period of 2010-2016. The Terra AODs showed good-match with the ground-based AODs measurements (slope = 0.830, intercept = 0.099, RMSE = 0.260, R 2 = 0.673, and RMB = 0.970). However, the Aqua AODs expressed systematically the underestimation of AERONET AODs (slope = 0.556, intercept = 0.184, RMSE = 0.390, R 2 = 0.408, and RMB = 0.810). All MODIS AODs indicated the moderate correlation with AERONET AODs (slope = 0.683, intercept = 0.147, RMSE = 0.330, R 2 = 0.520, and RMB = 0.890). Although MODIS AODs followed well the monthly variations of AERONET AODs, the relatively high discrepancy between MODIS and AERONET AODs could be observed during the winter months.

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This study aimed to assess PM_2.5 concentration and the potential impacts of biomass burning sources on PM_2.5 measured at the sampling sites in Hanoi, Vietnam and Chiang Rai, Thailand during the high season (from January to April) in 2021 in which intensive biomass burning activities occur in Southeast Asia (SEA) region. For this purpose, an integrated approach of PM_2.5 in-situ measurement, receptor and trajectory modelling techniques and satellite remote sensing was employed. Results showed that the average value of PM_2.5 daily concentrations measured at the sampling site in Hanoi was higher than that at the sampling site in Chiang Rai during January–February (winter) periods. In contrast, the average value of PM_2.5 daily concentrations measured at the sampling site in Hanoi was slightly lower than the counterpart at the sampling site in Chiang Rai during March–April (spring) periods. Elevated concentrations of PM_2.5 measured in Chiang Rai during March–April periods were largely associated with intensive biomass burning activities in the SEA region. Positive Matrix Factorisation (PMF) receptor model-based source apportionment results indicated a larger contribution of biomass burning sources to the PM_2.5 measured at the sampling site in Chiang Rai compared to that at the sampling site in Hanoi. Analysis of MODIS cumulative fire radiative power maps in the SEA region and three-day air masses backward trajectories arrived at the sampling sites in Hanoi and Chiang Rai further suggested the potential impacts of biomass burning sources on the PM_2.5 measured at the sampling sites in Hanoi during the winter periods and in Chiang Rai during the spring periods.