It is well known that atmospheric environments, including both meteorology and air quality, significantly affect public health, such as chronic lung disease and cancer, and respiratory infections. In this study, we have analyzed correlations between the number of daily respiratory outpatients and the atmospheric environments data for about ten years for the city of Busan, South Korea. The respiratory problem patients data have been categorized into two health-vulnerable groups by age over 65(DayPA_O65) and under 20(DayPA_U20), each of which shows relatively higher correlations with air quality and meteorology, respectively. However, time series analysis with factor separation results in that DayPA_O65 and DayPA_U20 show a higher relation with variance components and daily irregular factors of atmospheric concentrations, respectively.

A model coupling a meteorological predictive model and a vegetation photosynthesis and respiration model was used to simulate CO2 concentrations over coastal basin areas, and modeling results were estimated with aircraft observations during a massive sampling campaign. Along with the flight tracks, the model captured the meteorological variables of potential temperature and wind speed with mean bias results of 0.8℃, and 0.2 m/s, respectively. These results were statistically robust, which allowed for further estimation of the model’s performance for CO2 simulations. Two high-resolution emission data sets were adopted to determine CO2 concentrations, and the results show that the model underestimated by 1.8 ppm and 0.9 ppm at higher altitude over the study areas during daytime and nighttime, respectively, on average. Overall, it was concluded that the model’s CO2 performance was fairly good at higher altitude over the study areas during the study period.

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.

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.

EnergyPlus is a whole building energy simulation program that engineers, architects, and researchers use to model energy and water use in buildings. Modeling the performance of a building with EnergyPlus enables building professionals to optimize the building design to use less energy and water. This program provides energy analysis of building and needs weather data for simulation. Weather data is available for over 2,000 locations in a file format that can be read by EnergyPlus. However, only five locations are avaliable in Korea. This study intends to use AWS data for having high spatial resolution to simulate building energy. The result of this study shows the possibility of using AWS data for energy simulation of building.

PM10 concentration is related to the meteorological variables including to local and synoptic meteorology. In this study the PM10 concentrations of Busan in 2007~2011 were analyzed and the days of yellow sand or rainfall which is more than 5 mm were excluded. The sections of PM10 concentration were divided according to 10-quantiles, quartiles and 90-quantiles. The 90-quantiles of daily PM10 concentration were selected as high concentration dates. In the high concentration dates the daily mean averaged cloudness, mean daily surface wind speed, daily mean surface pressure and PBL height were low and diurnal variation of surface pressure and daily maximum surface temperature were high. When the high PM10 dates occurred, the west and south wind blew on the ground and the west wind blew strongly on the 850 hPa. So it seemed that long range transboundary air pollutants made effects on the high concentration dates. The cluster analysis using Hysplit model which is the backward trajectory was made on the high concentration dates. As a result, 3 clusters were extracted and on the short range transboundary cluster the daily mean relative humidity and cloudness were high and PBL height was low.

In order to clarify the relation between sea breeze penetration and Planetary Boundary Layer development in southeastern part of the Korean Peninsula, several numerical assessments were carried out using atmospheric numerical model WRF(Weather Research and Forecasting). Compared with onset time of sea breeze at eastern coast area(Uljin), the time at southern coast region(Masan) with complex costal line tend to delay for several hours. The penetration patterns of sea breeze between two coastal regions are some different due to the shape of their coastal line and back ground topography. Intensified valley wind due to high topography of lee side of Uljin can help penetration of sea breeze at early time. So penetration of sea breeze at early time often prevent PBL to develop at Uljin and lower PBL height last for a day time. But because of late penetration of sea breeze at Masna, PBL Height dramatically decrease after 1500LST. The distribution of front genesis function based on the heat and momentum variation are explained obviously the sea breeze penetration patterns and agreed well with the PBL height distribution.

In recent years, the urban thermal environment has become worse, such as days on which the temperature goes above 30℃, sultry nights and heat stroke increase, due to the changes in terrestrial cover such as concrete and asphalt and increased anthropogenic heat emission accompanied by artificial structure. The land use type is an important determinant to near-surface air temperature. Due to these reasons we need to understand and improve the urban thermal environment. In this study, the fifth-generation Pennsylvania State University- National Center for Atmospheric Research Mesoscale Model(MM5) was applied to the metropolitan of Daegu area in order to investigate the influence of land cover changes and urban modifications increase of Albedo to the surface energy budget on the simulated near-surface air temperature and wind speed. The single urban category in existing 24-category U.S. Geological survey land cover classification used in MM5 was divided into 6 classes to account for heterogeneity of urban land cover. As a result of the numerical simulation intended for the metropolitan of Daegu assumed the increase of Albedo of roofs, buildings, or roads, the increase of Albedo (Cool scenario)can make decrease radiation effect of surface, so that it caused drops in ambient air temperature from 0.2 to 0.3 on the average during the daylight hours and smaller (or near-zero) decrease during the night. The Sensible heat flux and Wind velocity is decreased. Modeling studies suggest that increased surface albedo in urban area can reduce surface and air temperatures near the ground and affect related meteorological parameters such as winds, surface air temperature and sensible heat flux.

The frequency of tropical nights and tropical days in Busan during summer season (June-August) from 1995 to 2004 were investigated. When air temperature higher than 25 ℃ continuously maintains at night in summer, it is called the occurrence of tropical night. Tropical day is defined that maximum air temperature is higher than 30 ℃. In Jin-Gu and Daeyeon-dong shows a lot of frequency of tropical day and tropical night because there were located in downtown. Relatively, the areas where are located in seaside and riverside show very low frequency. This can be explained the cooling effects of sea and river. The main meteorological characteristics during tropical nights and tropical days is proved pattern of reverse tendency through wind rose. We analyzed heat index and discomfort index during tropical night and tropical day. This study is useful to understand the aspect of urban thermal environment but need some more observation to quantify.

In this study, meteorological characteristics concerning the occurrence of fog are analyzed using 4-years (2000-2003) data at Chuncheon. From the analysis of meteorological characteristics, the fog at Chuncheon occurred before sunrise time and disappeared after that time and lasted for 2-4 hours. When fog occurred, on the whole, wind direction was blew the northerly and wind speed was below 2.1 m/s. Especially, about 42 % of foggy day fell on the calm(0～0.2 m/s) conditions. The difference between air temperature and dew point temperature near the surface were mainly less than 2 ℃. For the lack of water surface temperature, the water surface temperature was calculated by using Water Quality River Reservoir System (WQRRS). In Chuncheon, there is close correlation between the frequency of fog day and outflow from Soyang reservoir and high frequency of occurrence due to the difference between air and cold outlet water temperature.

In this study, climate analysis and wind sector division were conducted for a propriety assessment to determine the location of air quality monitoring sites in the Busan metropolitan area. The results based on the meteorological data(2000～2004) indicated hat air temperature is strongly correlated between 9 atmospheric monitoring sites, while wind speed and direction are not. This is because wind is strongly affected by the surrounding terrain and the obstacles such as building and tree. In the next stage, we performed cluster analysis to divide wind sector over the Busan metropolitan area. The cluster analysis showed that the Busan metropolitan area is divided into 6 wind sectors. However 1 downtown and 2 suburbs an area covering significantly broad region in Busan are not divided into independent sectors, because of the absence of atmospheric monitoring site. As such, the Busan metropolitan area is finally divided into 9 sectors.