Exploiting the results of running the GEOS-CF model to evaluate PM₂.₅ concentration in near real-time in Vietnam

Abstract

Near real-time information about global atmospheric composition, including PM₂.₅ fine dust, is valuable because it helps forecast air quality and manage environmental disasters. Recently, NASA’s Global Modeling and Assimilation Office has released a set of near real-time Goddard Earth Observing System models that help analyze and forecast global air quality, named GEOS-CF (GEOS Composition Forecast). In particular, GEOS-CF can simulate the transport from the stratosphere to the troposphere (the stratosphere to troposphere transport) which is technically very difficult. In Vietnam’s challenging conditions, research and application of GEOS-CF output results must be made. In this study, the authors developed a tool named ENAR (Envim Nasa Analysis Result) to help interpret GEOS-CF results provided free of charge by NASA to form PM₂.₅ pollution maps for each area hourly across the entire territory of Vietnam. ENAR was applied to build pollution maps for the first three months 2024. The results were analyzed to clarify the range of pollution levels for each area, including the Hoang Sa and Truong Sa archipelagos, Vietnam. These results allow scientific agencies to obtain reliable information for studies predicting this type of pollution.