Aerosols affect climate by scattering and absorbing radiation and by altering cloud microphysics known as direct and indirect effect, respectively. Since these impacts occur from local- to global-scale with high spatio-temporal variation, satellite sensors which can observe extensive area with high temporal resolution, have been valuable to monitor their distribution and investigate relevant problems. In our laboratory, retrieval algorithms for aerosols have been developed, and impacts of aerosols on climate and air quality have been investigated by using various satellite sensors including GOCI, MODIS, MISR, TROPOMI, CALIOP, etc.  Machine learning algorithms are also developed to convert the satellite retrievals to surface PM2.5 concentrations. Data fusion has been conducted among different satellite instruments and algorithms for better accuracy and coverage based on big data science.

Air quality has become one of the key environmental issues with its wider impact on our society, economy, industry, diplomacy,

Thus, it is crucial to monitor concentration of relevant gases and aerosols over Asia in high temporal and spatial resolution. A geostationary Earth orbit(GEO) satellite, Geostationary Environmental Monitoring Spectrometer (GEMS) was launched successfully in Feb 19th, 2020. GEMS is the first instrument to observe air pollutants concentrations from GEO. The objectives of the GEMS are: (1) To provide atmospheric chemistry measurements in high temporal and spatial resolution over Asia, (2) To monitor regional transport events: transboundary pollution and Asia dust, (3) To enhance our understanding on interactions between atmospheric chemistry and meteorology, (4) To better understand the globalization of tropospheric pollution, (5) To improve air quality forecast by: constraining emission rates / data assimilation of chemical observations.

This group has been in charge of its data processing algorithm for GEMS, based on radiative transfer and inversion theory including optimal estimation, differential optical absorption spectroscopy(DOAS), machine learning etc. GEMS is to be followed by NASA's TEMPO in 2023 and ESA's Sentinel-4 in 2024 to form a geostationary air quality constellation to cover major continents in Northern Hemisphere