• Journal of Environmental Health Sciences
• /
• v.26 no.2
• /
• pp.34-40
• /
• 2000

The purpose of this study was to investigate the seasonal variation of PAHs and to estimate their source characteristics in Taegu area. To do this, four sampling sites were selected to represent an industrial, a traffic, a traffic & residential, and a residential area in Taegu. Total of 72 samples had been collected from January, 1999 to September, 1999 on glass micro fiber filters by high volume air sampler. The PAHs in the total suspended particulate were extracted by a soxhlet process with dichloromethane and analyzed by GC/MSD, GC/FID. A statistical analysis was performed for the PAHs data set using a principal component analysis to derive important factor inherent in the interactions among the variables. The specific conclusions of this research are: 1) There was a significant seasonal and local variation in the atmospheric concentration of PAHs. The seasonal variation is winter>spring>Fall>summer, and the local variation is industrial>traffic>graffic & residential>residential area. 2) To evaluate the correlation between a measured PAHs and other affecting factors such as air pollutant concentration and meterological data, statistical analysis was performed. PAHs and other affecting factors such as air pollutant concentration and meterological data, statistical analysis was performed. PAHs have negative correlation with temperature (r=-0.593, p<0.05), radiation(r=-0.535, p<0.05), and O3(r=-0.719, p<0.05), but have positive correlation with NO(r=0.615, p<0.05) 3)Finally, multivariate analysis was performed for the PAHs dat set to identify and to estimate the source contributions of PAHs. According to results of statistical analysis, it could be identifies as three factors such as vehicular/gasoline, vehicular/diesel, and combustion in Taegu area.

• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.1751_1752
• /
• 2009

The accurate measurement of soil resistivity and earthing system resistance is fundamental to electrical safety. However, geological and meterological factors can have a considerable effect on the accuracy of conventional measurements and the validity of the measurement methods. This paper presents optimization method of dc resistivity data acquisition system using ERT.

• Proceedings of the KIEE Conference
• /
• 2006.07d
• /
• pp.1795-1796
• /
• 2006

The accurate measurement of soil resistivity and earthing system resistance is fundamental to electrical safety. However, geological and meterological factors can have a considerable effect on the accuracy of conventional measurements and the validity of the measurement methods. This paper presents optimization method of dc resistivity data acquisition system using multi-electrode arrays.

• Journal of Korean Society of Forest Science
• /
• v.83 no.3
• /
• pp.380-390
• /
• 1994

This study was conducted to investigate the effects of the topographical factors (16 items), physico-chemical properties of soil (13 items) and meteorological factors(9 items) on the height growth of Pinus thunbergii stands along the coastal area in Korea. According to the coefficients by partial correlation analysis in total area, it was found that tree height growth was considerably affected by local topography, soil hardness, soil B-horizental depth, effective soil depth, soil moisture, parent rock, soil texture, and etc.. And the soil factors were available $P_2O_5$, total nitrogen, base saturation, exchangeable $Ca^{{+}+}$, and etc.. In partial correlation analysis, annual relative humidity, annual precipitation, index of aridity, and etc. were found to be the most important factors influencing on tree height growth of Pinus thunbergii stands. In conlusion, the topographical, soil and meteorological factors have multiplex influence on the tree height growth in the Pinus thunbergii stands. They promise to provide the basis of improving not only the selection of suitable sites and the management of soil fertilizer but also the estimation of growth and yield. Hence these results would be used successfully for the design in the scientific forest working plan.

• Journal of Korea Water Resources Association
• /
• v.33 no.5
• /
• pp.603-610
• /
• 2000

Climate factors such as rainfall, temperature, wind, humidity, and solar radiant heat affect soil erosion. Among those factors, rainfall influences soil erosion to the most extent. The kinetic energy of rainfall breaks away soil particles and the water flow caused by the rainfall entrains and transport them downstream. In order to estimate soil erosion, therefore, it is important to determine the rainfall erosivity. In this study, the annual average Rainfall Erosivity(R) in Korea, an important factor of the Universal Soil Loss Equation(USLE) and Revised Equation(RUSLE), has been estimated using the nationwide rainfall data from 1973 to 1996. For this estimation, hourly rainfall data at 53 meterological stations managed by the Meterological Agency was used. It has been found from this study that the newly computed values for R are slightly larger than the existing ones. It would be because this study is based on the range of rainfall data that is longer in period and denser in the number of gauging stations than what the existing result used. The final result of this study is shown in the form the isoerodent map of Korea.

• Journal of Environmental Science International
• /
• v.8 no.4
• /
• pp.465-471
• /
• 1999

The concentration of air pollution in a large city such as Pusan has been increased every years due to the increase on fuel consumption at factories and by vehicles as well as the gravitation of the population. In this study, we have analyzed $NO_2$ concentration data and various data of meteorological factors during 1994-1997 to investigate the characteristics of $NO_2$ concentration and how the high $NO_2$ concentration is generated under the meterological condition. According to the study, $NO_2$ peak concentration at most sites occured about 1h later after the rush hour. In the characteristics of emissions in sites, sinpyeong-dong was highly contributed to point source while the other sites were highly contributed to line source. The high $NO_2$ concentration had high generation probability when temperature contained typical seasonal characteristics and wind speed was low. Using the relationship between meteorological factors and the daily average $NO_2$ concentration, correlation analysis was practiced. the seasonal variation of the daily average $NO_2$ concentration was correlated with air temperature, solar radiation and wind speed, but the correlation coefficient between meteorological factors and the daily average $NO_2$ concentration was not so much high. Thus we have known that the daily average $NO_2$ concentration is partially explained by meteorological factors.

• Journal of Environmental Science International
• /
• v.24 no.3
• /
• pp.281-290
• /
• 2015

Recent climate change has led to fluctuations in agricultural production, and as a result national food supply has become an important strategic factor in economic policy. As such, in this study, panel data was collected to analyze the effects of seven meteorological elements on the production of five types of grain with error component panel data regression method following the test results of LM tests, Hausman test. The key factors affecting the production of rice were average temperature, average relative humidity and average ground surface temperature. The fluctuations in the other four grains types are not well explained by meterological elements. For other grains and beans, only average temperature and time (year) affect the production of other grains while average temperature, ground surface temperature, and time (year) influence the production of beans. For barley and millet, only average temperature positively affects the production of barley while ground surface temperature and time (year) negatively influence the production of millet. The implications of this study are as follow. First, it was confirmed that the meteorological elements have profound effects on the rice production. Second, when compared to existing studies, this study was not limited to rice but encompassed all five types of grains and went beyond other studies that were limited to temperature and rainfall to include various meteorological elements.

• Journal of Climate Change Research
• /
• v.7 no.2
• /
• pp.193-203
• /
• 2016

The importance of forecasting agricultural production is receiving attention while climate change is accelerating. This study suggested three types of crop yield forecasting model for major vegetable crops by using downscaled meteorological information of main production area on farmland level, which identified as limitation from previous studies. First, this study conducted correlation analysis with seven types of farm level downscaled meteorological informations and reported crop yield of main production area. After, we selected three types of meteorological factors which showed the highest relation with each crop species and regions. Parameters were deducted from meterological factor with high correlation but crop species number was neglected. After, crop yield of each crops was estimated by using the three suggested types of models. Chinese cabbage showed high accuracy in overall, while the accuracy of daikon and onion was quiet revised by neglecting the outlier. Chili and garlic showed differences by region, but Kyungbuk chili and Chungnam, Kyungsang garlic appeared significant accuracy. We also selected key meteorological factor of each crops which has the highest relation with crop yield. If the factor had significant relation with the quantity, it explains better about the variations of key meteorological factor. This study will contribute to establishing the methodology of future studies by estimating the crop yield of different species by using farmland meterological information and relatively simplify multiple linear regression models.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.1 no.1
• /
• pp.20-28
• /
• 1999

This study was conducted to reveal the effect of some meterological factors on the weight of cone and seed per cone in Korean white pine (Pinus koraiensis SIEB. et ZUCC.). The weight of cone and seed per cone for 7 years from 1992 to 1998 on 45(1992) year-old trees and some meterological factors for 9 years from 1990 to 1998 were surveyed in Hongcheon-Gun region, Gangweon-Do. Simple correlations and multiple regression between weight of cone and seed per cone and some meterological factors were analyzed. The results obtained from the above experiments were as follows: 1. Positive correlations were found between weight of cone and monthly mean temperature of February in flower bud differentiation year. number of annual hoarfrost days of the cone production year monthly mean temperature of may in the cone production year, as July respectively. There were negative correlations between weight of cone and monthly mean temperature of august in the flowering year, wind speed of April in the flower bud differentiation year, number of clear days of december in the flowering year, number of annual cloudy days of the flowering year, number of precipitation days of june in the flowering year, number of annual precipitation days of the flowering year, number of annual cloudy days of March in the cone production year. number of annual cloudy days from march to October in the flowering year as well as number of precipitation from march to october in the flowering year. 2. Positive correlation between weight of seed per cone and number of hours with sunshine duration of June in the flowering year, the percentage of sunshine duration of June in the flowering year, number of clear days of June in the flowering year. monthly mean temperature of may in the cone production year. as well as monthly mean temperature of July in the cone production year were found. Negative correlations were recognized between weight of seed per cone and monthly mean temperature of January in the flowering year, monthly mean temperature of august in the flowering year, wind speed of april in the flower bud differentiation year, number of annual cloudy days of the flowering year, number of precipitation days of June in the flowering year, number of annual cloudy days from March to October in the flowering year as well as number of precipitation from march to October in the flowering year.