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In this study a modeling system consisting of Weather Research and Forecasting (WRF), Sparse Matrix Operator Kernel Emissions (SMOKE), the Community Multiscale Air Quality (CMAQ) model, and the CMAQ-Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) model has been applied to estimate enhancements of PM10 during Asian dust events in Korea. In particular, 5 experimental formulas were applied to the WRF-SMOKE-CMAQ (MADRID) model to estimate Asian dust emissions from source locations for major Asian dust events in China and Mongolia: the US Environmental Protection Agency (EPA) model, the Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model, and the Dust Entrainment and Deposition (DEAD) model, as well as formulas by Wang et al. (2000). According to the weather map, backward trajectory and satellite image analyses, Asian dust is generated by a strong downwind associated with the upper trough from a stagnation wave due to development of the upper jet stream, and transport of Asian dust to Korea shows up behind a surface front related to the cut-off low (known as comma type cloud) in satellite images. In the WRF-SMOKE-CMAQ modeling to estimate the PM10 concentration, Wang et al.'s experimental formula was depicted well in the temporal and spatial distribution of Asian dusts, and the GOCART model was low in mean bias errors and root mean square errors. Also, in the vertical profile analysis of Asian dusts using Wang et al's experimental formula, strong Asian dust with a concentration of more than 800

We investigate the amount of potential electricity energy generated by wind power in Busan metropolitan area, using the mesoscale meteorological model WRF (Weather Research & Forecasting), combined with small wind power generators. The WRF modeling has successfully simulated meteorological characteristics over the urban areas, and showed statistical significant to predict the amount of wind energy generation. The highest amount of wind power energy has been predicted at the coastal area, followed by at riverbank and upland, depending on predicted spatial distributions of wind speed. The electricity energy prediction method in this study is expected to be used for plans of wind farm constructions or the power supplies.

In order to clarify the contribution rate of PM concentration due to regional emission distribution, Brute force analysis were carried out using numerical estimated PM data from WRF-CMAQ. The emission from Kyeongki region including Seoul metropolitan is the largest contribution of PM concentration than that from other regions except for emission of trans-country and source itself. Contribution rate of self emission is also the largest at Kyeongki region and its rate reach on over 95 %. And the rate at Gangwon region also higher than any region due to synoptic wind pattern. Due to synoptic wind direction at high PM episode, pollutants at downwind area along from west to east and from north to south tends to mix intensively and its composition is also complicated. Although the uncertainty of initial concentration of PM, the contribution of regional PM concentration tend to depend on the meteorological condition including intensity of synoptic and mesoscale wind and PM emission pattern over upwind region.

To estimate the benefit of high-resolution meteorological data for building energy estimation, a building energy analysis has been conducted over Busan metropolitan areas. The heating and cooling load has been calculated at seven observational sites by using temperature, wind and relative humidity data provided by WRF model combined with the inner building data produced by American Society of Heating Refrigeration and Air-conditioning Engineers (ASHRAE). The building energy shows differences 2-3% in winter and 10-30% in summer depending on locations. This result implicates that high spatiotemporal resolution of meteorological model data is significantly important for building energy analysis.