„ ATMOSPHERIC CHEMISTRY MODELING GROUP

 Emission and transport are the main processes that determine concentrations of chemical species in the atmosphere. Chemical transport models (CTMs) simulate these processes to calculate concentrations. However, simulated concentrations generally contain errors, indicating the need for improvement. The goal of this project is to optimize emission and transport processes in the CTMs by updating emission inventories and meteorological systems.

 Emissions in the chemical transport model can be provided by bottom-up emission inventories, which are obtained by information from fossil fuel usage, population, traffic volume, etc. The simulated concentrations when bottom-up inventories were used are usually different from the observed concentrations from aircraft, satellite, etc. Inverse modeling can be used to obtain top-down emission inventory by considering both a priori information (bottom-up inventory) and observation. In specific, we aim to optimize volatile organic compound (VOC) emission by formaldehyde (HCHO) observation from DC-8 aircraft and GEMS satellite retrieval.

 Another objective of this project is to improve transport processes in the model by updating the meteorological system. For this purpose, we have been upgrading MCIP, which is a module that reproduces data from the meteorological model into data that could be used as an input for CTMs. Also, we are developing wind speed and PBLH (planetary boundary layer height) algorithms by using adjusted parameters from observations.

  To come up with effective measures to reduce and manage PM in Korea, it is necessary to not only manage the local pollutant but also scientifically identify the effects of inflow from abroad, and research on the pollutants themselves must be conducted.

  In this research, the air quality observations of Korea and China are collected through complementary joint research to identify the pollution characteristics, chemical reaction process and transport characteristics in the atmosphere of PM2.5 in gas and particulate phase. Through this, Korea and China derive measures to improve the performance of air quality forecasting models and identify the causes of air pollution in East Asia. 

  Among them, we are responsible for chemical mechanism sensitivity experiments through multi-model inter-comparison and VOC scheme improvement experiments and applications related to organic aerosol production.

  Organic aerosols (OA) are one of the most important chemical components of PM2.5 in East Asia. To improve the scientific understanding of OA using an air chemistry model, we first focus on the quantitative assessment of both natural and anthropogenic emissions of precursors. We validate precursor emissions by using both ground/airborne in-situ measurements and satellite remote sensing. We also update the gas phase chemical processes of volatile organic compounds (VOCs) in the model, and compare different parameterizations used to simulate the formation and evolution of OA. Implications from this research can contribute to reducing model-observation gaps in current OA simulations, developing an effective parametric approach for OA modeling suitable for East Asia, and finally improving our scientific knowledge on the atmospheric processing of OA.