Youn-Seo Koo

A Development of PM10 Forecasting System

The forecasting system for Today`s and Tomorrow`s PM10 was developed based on the statistical model and the forecasting was performed at 9 AM to predict Today`s 24 hour average PM10 concentration and at 5 PM to predict Tomorrow`s 24 hour average PM10. The Today`s forecasting model was operated based on measured air quality and meteorological data while Tomorrow`s model was run by monitored data as well as the meteorological data calculated from the weather forecasting model such as MM5 (Mesoscale Meteorological Model version 5). The observed air quality data at ambient air quality monitoring stations as well as measured and forecasted meteorological data were reviewed to find the relationship with target PM10 concentrations by the regression analysis. The PM concentration, wind speed, precipitation rate, mixing height and dew-point deficit temperature were major variables to determine the level of PM10 and the wind direction at 500 hpa height was also a good indicator to identify the influence of long-range transport from other countries. The neural network, regression model, and decision tree method were used as the forecasting models to predict the class of a comprehensive air quality index and the final forecasting index was determined by the most frequent index among the three model`s predicted indexes. The accuracy, false alarm rate, and probability of detection in Tomorrow`s model were 72.4%, 0.0%, and 42.9% while those in Today`s model were 80.8%, 12.5%, and 77.8%, respectively. The statistical model had the limitation to predict the rapid changing PM10 concentration by long-range transport from the outside of Korea and in this case the chemical transport model would be an alternative method.

Analysis of Domestic and Foreign Contributions using DDM in CMAQ during Particulate Matter Episode Period of February 2014 in Seoul

This study was carried out to understand the regional contribution of Particulate Matter (PM) emissions from East Asia (82°~149°E, 18°~53°N) to Seoul during high concentration period in February 2014. The Community Multi-scale Air Quality (CMAQ) version 5.0.2 with Decoupled Direct Method (DDM) was used to analyze levels of contributions over Seoul. In order to validate model performance of the CMAQ, predicted PM and its chemical species concentrations were compared to observations in China and Seoul. Model predictions could depict the daily and hourly variations of observed PM. The calculated PM concentrations, however, had a tendency of underestimation. The discrepancies are due to uncertainties of meteorological data, emission inventories and CMAQ model itself. The high PM concentration in Seoul was induced by stationary anticyclone over the West Coast of Korea during 24 to 27 February. The DDM in CMAQ was used to analyze the contributions of emissions from East Asia on Seoul during this PM episode. PM10 concentration in Seoul is contributed by 39.77%~53.19% from China industrial and urban region, 15.37%~37.10% from South Korea, and 9.03%~18.05% North Korea. These indicate that PM10 concentrations in Seoul during the episode period are dominated by long-range transport from China region as well as domestic sources. It was also found that the largest contribution region in China were Shandong peninsula during the PM event period.

Evaluations of WRF-CMAQ/CAMx Performance in East Asia Focusing on the Seoul Metropolitan Area

Comparative study of two chemical transport models of CMAQ and CAMx with WRF (Weather Research and Forecasting) model under the identical conditions of meteorological field as well as emission inventory was carried out to evaluate their performances to predict atmospheric aerosols in East Asia focusing on the Seoul Metropolitan Area. Predicted concentrations of PM10, PMC (particulate matter with less than 10 μm and larger than 2.5 μm), PM2.5, sulfate, nitrate, organic carbon, elemental carbon and soil component were compared with those measured in Korea especially with intensive measurements in the SMA. CMAQ and CAMx generally depicted the variation of temporal trend and spatial distribution of the aerosols components but the PM10 and PMC were intrinsically underestimated by both models due to inherent uncertainty and lack of information for emission data of fugitive soil dusts. CAMx has a tendency to predict higher PM species concentrations than those of CMAQ. According to soccer plots of fractional bias vs. fractional gross error in annual PM chemical species, both CMAQ and CAMx, however, are acceptable in the range of between good performance and average performance. It is inferred from this study that the main reasons to induce differences between CMAQ and CAMx in predicting PM species are due to dry deposition mechanism and nesting method.

A Status of Atmospheric Environmental Impact Assessment and Future Prospects

The current status of atmospheric environmental impact assessment (EIA) has been summerized and future prospective for effective and accurate atmospheric EIA has been proposed by reviewing available papers and reports for the atmospheric EIA. The number of reports for the EIA in the EIA support system which is operated by the Korean Environmental Institute have been dramatically decreased from 282 reports in 2008 to 113 reports in 2012 during recent five years. This is partially due to simplification of the EIA procedure, the contraction of the public development and economic recession. We analyzed details of the EIA report to review how actual atmospheric EIA has preformed according to the EIA guidelines from the Korean Ministry of Environment. The 264 reports of EIA published in 2011 and 2012 had been reviewed especially focusing on the atmospheric evaluation items such as meteorology, air quality measurement and modeling, odor measurement and modeling, wind corridor in urban planning, and climate change. In overall sense, the atmospheric EIA has been performed quite well by abiding the guidelines except for local meteorological data measurement, permit standard for air quality and wind corridor. The new approaches to improve the procedure of atmospheric EIA and to reflect future of national air quality standard of have been proposed. The guidelines on how to evaluate the wind corridor, to implement atmospheric EIA for permit, and how to acquire local meteorological data by combining local measurement and model prediction are required for the effective and future oriented atmospheric EIA.

The Simulation of Aerosol Transport over East Asia Region Using CMAQ

The modeling system using MM5, SMOKE, and CMAQ was developed to investigate the aerosol transport from China to Korea. The model prediction was validated with measurements in Korea during the high PM 10 episode days. The simulation showed that the significant amount of PM 10 in Korea was transported from China, especially from Beijing Area