A daily and complete PM_2.5 dataset derived from space observations for Vietnam from 2012 to 2020

PM_2.5 pollution is a serious problem in Vietnam and around the world, having bad impacts on human health, animals and environment. Regular monitoring at a large scale is important to assess the status of air pollution, develop solutions and evaluate the effectiveness of policy implementation. However, air quality monitoring stations in Vietnam are limited. In this article, we propose an approach to estimate daily PM_2.5 concentration from 2012 to 2020 over the Vietnamese territory, which is strongly affected by cloudy conditions, using a modern statistical model named Mixed Effect Model (MEM) on a dataset consisting of ground PM_2.5 measurements, integrated satellite Aerosol Optical Depth (AOD), meteorological and land use maps. The result of this approach is the first long-term, full coverage and high quality PM_2.5 dataset of Vietnam. The daily mean PM_2.5 maps have high validation results in comparison with ground PM_2.5 measurement (Pearson r of 0.87, R² of 0.75, RMSE of 11.76 μg/m³, and MRE of 36.57 % on a total of 13,886 data samples). The aggregated monthly and annual average maps from 2012 to 2020 in Vietnam have outstanding quality when compared with another global PM_2.5 product. The PM_2.5 concentration maps has shown spatial distribution and seasonal variations of PM_2.5 concentration in Vietnam in a long period from 2012 to 2020 and has been used in other studies and applications in the environment and public health at the national scale, which has not been possible before because of the lack of monitoring stations and an appropriate PM_2.5 modeling approach.