Ulsan National Institute of Science and Technology · Environmental Science
Professor Chang-Keun Song's research lab specializes in atmospheric aerosol modeling, satellite remote sensing, and air quality simulation with a focus on East Asia and the continental United States. The lab develops advanced algorithms for retrieving aerosol optical depth and particulate matter concentrations from geostationary and polar-orbiting satellite instruments, integrating multi-sensor data with chemical transport models. Key research directions include improving air quality forecasting through downscaling of global chemistry models and investigating the formation and impacts of secondary organic aerosols. The lab also emphasizes the application of satellite-derived aerosol data to assess public health risks and support environmental policy.
Figures are computed from collected data and may differ slightly.
Abstract. The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm together with validation results during the Distributed Regional Aerosol Gr
Abstract. Long-term exposure to particulate matter (PM) with aerodynamic diameters < 10 (PM10) and 2.5 µm (PM2.5) has negative effects on human health. Although station-based PM monitoring has been conducted around the world, it is still challenging to provide spatially continuous PM information for vast areas at high spatial resolution. Satellite-derived aerosol information such as aerosol optical depth (AOD) has been frequently used to investigate ground-level PM concentrations. In this stu
Abstract. An aerosol model optimized for northeast Asia is updated with the inversion data from the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-northeast (NE) Asia campaign which was conducted during spring from March to May 2012. This updated aerosol model was then applied to a single visible channel algorithm to retrieve aerosol optical depth (AOD) from a Meteorological Imager (MI) on-board the geostationary meteorological satellite, Communication, Ocean, and Meteorologi
The goal of this study is to assess the impact of the downscale linkage of global chemistry model output on the simulated regional scale O 3 concentration and its vertical and horizontal structure over the continental US. For the global chemistry model, the NASA LaRC‐University of Wisconsin Real‐time Air Quality Modeling System (RAQMS) with a global ozone assimilation framework was used. RAQMS simulation results were downscaled with a RAQMS‐CMAQ linkage tool (RAQ2CMAQ) to provide dynamic lateral
The growing utilization of the air quality forecast induced the public strongly to demand that the accuracy of the national forecasting be improved. In this study, we investigated the problems in the current forecasting as well as various alternatives to solve the problems. Such efforts to improve the accuracy of the forecast are expected to contribute to the protection of public health by increasing the availability of the forecast system.
A numerical sensitivity study on secondary organic aerosol formation has been carried out by employing the WRF-Chem (Weather Research and Forecasting model coupled with Chemistry). Two secondary organic aerosol formation modules, the Modal Aerosol Dynamics model for Europe/Volatility Basis Set (MADE/VBS) and the Modal Aerosol Dynamics model for Europe/Secondary Organic Aerosol Model (MADE/SORGAM) were employed in the WRF-Chem model, and surface PM2.5 (particulate matter less than 2.5 μm in size)
We examine the spatial and temporal variabilities of ground-observed concentrations of particulate matter with diameters <= 10 mu m (PM10) over China and compare them with satellite-retrieved data on the aerosol optical depth (AOD) collected over the period 2003-2005 using a moderate resolution imaging spectroradiometer ( MODIS). Annual mean values of the PM10 concentrations and AOD show a strong spatial correlation, indicating the consistent presence of aerosol concentrations. However, the t
This study used observational data and a chemical transport model to investigate the contributions of several factors to the recent change in air quality in China and South Korea from 2016 to 2020. We focused on observational data analysis, which could reflect the annual trend of emission reduction and adjust existing emission amounts to apply it into a chemical transport model. The observation data showed that the particulate matter (PM<sub>2.5</sub>) concentrations during winter 2020 decreased
Abstract An urban heat island (UHI) is a well‐known urban climatic feature; however, an opposite effect, i.e., an urban cool island (UCI), was recently observed at locations where high‐rises were concentrated. Here, we analyzed the impact of two urbanization factors (anthropogenic heat flux (AH) and building height (ZR)), which could affect the formation of UHIs and UCIs, on urban precipitation over the Seoul Metropolitan area. AH caused an increasing precipitation in urban and downwind areas, e
Abstract. This study suggests a new modeling framework using a hybrid Eulerian–Lagrangian-based modeling tool (the Screening Trajectory Ozone Prediction System, STOPS) for a prediction of an Asian dust event in Korea. The new version of STOPS (v1.5) has been implemented into the Community Multi-scale Air Quality (CMAQ) model version 5.0.2. The STOPS modeling system is a moving nest (Lagrangian approach) between the source and the receptor inside the host Eulerian CMAQ model. The proposed model g
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