Fine particulate matter (PM2.5) is a major air pollutant that affects population health. Collaborative and coordinated studies on the spatially-resolved health impact of air pollution are limited in SEA, but are much needed as multi-country studies may contribute to public policy decisions on air quality management. This study is aimed at estimating PM2.5 concentration using aerosol and gases pollutants data from various satellite sensors and atmospheric parameters using a deep learning model. Integrating space-based gases pollutants in PM2.5 model is novel and vital for this region that is prone to biomass burning. The sources of PM2.5 will be traced by analysing PM2.5’s chemical composition. Urban land use will be categorised and PM2.5 will be collected from residential areas using portable sensors. These data will be assimilated for health risk assessment using population density data and relative exposure risk model. Respondents from Malaysia, Indonesia, Philippines and Thailand will record ambient PM2.5 levels using portable sensors. These results will be communicated with policy makers to set a unified safe limit PM2.5 value in SEA. Promoting awareness about health impact of PM2.5 is also a significant output. Novelty of this study is integrating PM2.5 from satellite data and low-cost sensors with source apportionment and health assessment for proper PM2.5 management in SEA.