Purpose: This study aims to quantitatively determine the impact on nearby risidents by selecting the amount of chemicals emitted from the workplace among the substances subject to the chemical emission plan and predicting the concentration with the atmospheric diffusion program. Method: The selection of research materials considered half-life, toxicity, and the presence or absence of available monitoring station data. The areas discharged from the materials to be studied were selected as the areas to be studied, and four areas with floating populations were selected to evaluate health risks. Result: AERMOD was executed after conducting terrain and meteorological processing to obtain predicted concentrations. The health hazard assessment results indicated that only dichloromethane exceeded the threshold for children, while tetrachloroethylene and chloroform appeared at levels that cannot be ignored for both children and adults. Conclusion: Currently, in the domestic context, health hazard assessments are conducted based on the regulations outlined in the "Environmental Health Act" where if the hazard index exceeds a certain threshold, it is considered to pose a health risk. The anticipated expansion of the list of substances subject to the chemical discharge plan to 415 types by 2030 suggests the need for efficient management within workplaces. In instances where the hazard index surpasses the threshold in health hazard assessments, it is judged that effective chemical management can be achieved by prioritizing based on considerations of background concentration and predicted concentration through atmospheric dispersion modeling.
A statistical downscaling method was adopted in order to establish the high-resolution wave prediction system in the East Sea coastal area. This system used forecast data from the Global Wave Watch (GWW) model, and the East Sea and Busan Coastal Wave Watch (CWW) model operated by the Korea Meteorological Administration (KMA). We used the CWW forecast data until three days and the GWW forecast data from three to seven days to implement the statistical downscaling method (inverse distance weight interpolation and conditional merge). The two-dimensional and station wave heights as well as sea surface wind speed from the high-resolution coastal prediction system were verified with statistical analysis, using an initial analysis field and oceanic observation with buoys carried out by the KMA and the Korea Hydrographic and Oceanographic Agency (KHOA). Similar to the predictive performance of the GWW and the CWW data, the system has a high predictive performance at the initial stages that decreased gradually with forecast time. As a result, during the entire prediction period, the correlation coefficient and root mean square error of the predicted wave heights improved from 0.46 and 0.34 m to 0.6 and 0.28 m before and after applying the statistical downscaling method.
Six land use data for a total of twenty five years were reviewed from 1975 to 2000 by dividing the period by 5-year unit; the land use variation was schematized; the watershed hydrological parameters were extracted by the representative rainfall years(maximum, average, driest year) by analyzing the recent thirty years'(from 1980 to 2010) climate data of the study region with SWAT model to investigate the effect of the precipitation change on the characteristics of groundwater recharge. In addition Markov Chain model was used to estimate the future land use; the predicted land use was applied to study the effect of the land use variation on the characteristics of groundwater recharge. For the research of this, long-term characteristics of groundwater recharge were estimated for the study region; the obtained results can be described as follows. The study region was divided into typical three area using SWAT model; yearly land use conditions were applied to the meteorological data of 1975 to 2010 and analyzed, producing the average rate of groundwater recharge of 30% for the applied period. This number is way lower than that of the earlier studies on the groundwater recharge for Jeju Island, which is 40-50%. Thirty percent (30%) is low considering the geological characteristics of Jeju, water-permeable vesicular strata, the reason of which must be the type of development is non-permeable paving.
Korean Journal of Agricultural and Forest Meteorology
/
v.19
no.3
/
pp.130-139
/
2017
The crop damage caused by strong wind was predicted using the wind speed data available from Korean Meteorological Administration (KMA). Wind speed data measured at 19 automatic weather stations in 2012 were compared with wind data available from the KMA's digital forecast. Linear regression equations were derived using the maximum value of wind speed measurements for the three-hour period prior to a given hour and the digital forecasts at the three-hour interval. Estimates of daily maximum wind speed were obtained from the regression equation finding the greatest value among the maximum wind speed at the three-hour interval. The estimation error for the daily maximum wind speed was expressed using normal distribution and Weibull distribution probability density function. The daily maximum wind speed was compared with the critical wind speed that could cause crop damage to determine the level of stages for wind damage, e.g., "watch" or "warning." Spatial interpolation of the regression coefficient for the maximum wind speed, the standard deviation of the estimation error at the automated weather stations, the parameters of Weibull distribution was performed. These interpolated values at the four synoptic weather stations including Suncheon, Namwon, Imsil, and Jangsu were used to estimate the daily maximum wind speed in 2012. The wind damage risk was determined using the critical wind speed of 10m/s under the assumption that the fruit of a pear variety Mansamgil would begin to drop at 10 m/s. The results indicated that the Weibull distribution was more effective than the normal distribution for the estimation error probability distribution for assessing wind damage risk.
The Journal of The Korea Institute of Intelligent Transport Systems
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v.14
no.2
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pp.30-38
/
2015
In this study, to improve effectiveness of road management services and the safety of the road in winter, road surface temperature prediction model was developed. We have utilized the existing input data of meteorological data and additional traffic data. This Road surface temperature prediction model was utilizing a Heat-Balance Method additionally considering amount of traffic that produce heat radiation by vehicle-tire friction. This improved model was compared to the based model to check into influence of traffic affecting the road surface temperature. There were verified by comparing the real observed road surface temperature of the third Gyeong-In highway and road surface temperature from the two models. As a result, the error of real observed and the predicted value (RMSE) was found to average $1.97^{\circ}C$. Observed road surface temperature was dramatically affected by the sunlight from 6 a.m. to 2 p.m. and degree of influence decreases after that. The predictive value of the model is lower than the observed value in the afternoon, and higher at night. These results appear due to the shielding of solar radiation caused by the vehicle in the afternoon and at night, the vehicle appeared to cause thermal heat supply.
This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. Fuzzy neuron, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an adaptive learning method by which a membership function and fuzzy rules were adapted for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water supplied to the city of Kwangju. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supplied (b) the mean temperature, and (c)the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.35% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.
Kim, Boo-Il;Jeon, Sung-Il;Lee, Moon-Sup;Lim, Kwang-Su
International Journal of Highway Engineering
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v.11
no.4
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pp.143-152
/
2009
The purpose of this study is to evaluate the freezing index and frost penetration depth. The freezing index and frost penetration depth were analyzed using air temperature and temperature profile of pavement system in Korea LTPP-SPS(Long Term Pavement Performance-Specific Pavement Study) site. The predicted frost penetration depth were then compared with the measured one from the LTPP sites. And the trend of annual freezing index was analyzed using the temperature data of meteorological stations located in the vicinity of Korea LTPP-SPS site. The result showed that the freezing index was rapidly decreased since 1987, and it was known that the use of freezing index determined from the past 30 years temperature data could cause the over estimates in the pavement thickness design. The temperature profile measured at 3 sections of LTPP-SPS sites showed that the temperature of subbase layer was above $0^{\circ}C$, even though anti-frost layers were found in these sections. Comparing the measured and calculated frost depth, the frost depth calculated from the subgrade frost penetration permissible method showed a similar trend with the measured frost depth.
Localized heavy storm is one of the major causes of flood damage in urban regions. According to the recent disaster statistics in South Korea, the frequency of urban flood is increasing more frequently, and the scale is also increasing. However, localized heavy storm is difficult to predict, making it difficult for local government officials to deal with floods. This study aims to construct a Flood risk matrix (FRM) using ensemble weather prediction data and to assess its applicability as a means of reducing damage by securing time for such urban flood response. The FRM is a two-dimensional matrix of potential impacts (X-axis) representing flood risk and likelihood (Y-axis) representing the occurrence probability of dangerous weather events. To this end, a regional FRM was constructed using historical flood damage records and probability precipitation data for basic municipality in Busan and Daegu. Applicability of the regional FRMs was assessed by applying the LENS data of the Korea Meteorological Administration on past heavy rain events. As a result, it was analyzed that the flood risk could be predicted up to 3 days ago, and it would be helpful to reduce the damage by securing the flood response time in practice.
The comparison of climate's character of Yunqi(運氣) with the data of meterological observation were made in the research of climate. 1. The comparison of the average velocity of wind, temperature, rainfall, humidity of Seoul, by late 1954 to 1983, with Yunqi(運氣) was made. Fire-Chi(火氣) and moisture-qi(濕氣) were matched with the attribute of Taiyun(大運). Cold-qi(寒氣) was had some relationship. Dry-qi(燥 氣) and Wind-qi(風氣) were not matched. About the relationship of Spirit-of-official-sky(司天之氣) with climate, when the Moisture-soil(濕土) was added, they were matched and when the King-fire(君火) was added, they have some relationship. But Wind-tree(風木), Dry-metal(燥金), Buble-fire(相火), Cold-water(寒水) was added they were not matched. 2. According to the observation data of rainfall by late 180 years of Seoul; about Taiyun(大運), when the Water-Yun(水運) was greatly exceeded and Fire-Yun(火運) was shorted, in the case of Official-sky(司天), when Wind-Tree(風木) was added, the frequency was highly. So when the Soil-Yun(土運) was greatly exceeded and when Official-sky(司天)was added to the Moisture-soil(濕土), the rainfall was not matched. 3. The relationship of the frequency of the abnormal climate occurrences between Yunqi-promotion-weak(運氣盛衰)and Yunqi-Harmony(運氣同化) and Yunqi-soft-attacking(運氣順逆) in the weather of Korean Peninsula was compared by 1564 to 1863. They were not matched except the case of Yunqi-Harmony(運氣同化). 4. There were some cases which were not matched exactly between the climate predicted by the theory and real climate in 1984, the year of Kap-ga(甲子年). But many correspondence between the observation by the office of meteorology and the prediction by the analysis from Yun-qi-sang-hab(運氣相合) theory. 5. Because meterological phenomena of real world and analysis from the hypothesis of Yunqi(運氣) have no relationship with each other, some of Doctor denied Yunqi(運氣) in the way of matching mechanically. But the thought of Doctor who denied Fortune-spirit(運氣) made promotion for the theory of divination by bringing deeper insight. And it was not only the negative side. 6. In the point of geographical difference, the climate of China, the origination Yunqi theory, is different from the Korea's. Thus some observation errors should be considered. From the basis of this thesis, I hope that the deeper advance would be made into the Korean Yunqi theory.
Journal of the Korean Association of Geographic Information Studies
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v.14
no.3
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pp.36-51
/
2011
Global climate change is disturbing the water circulation balance by changing rates of precipitation, recharge and discharge, and evapotranspiration. Groundwater, which occupies a considerable portion of the world's water resources, is related to climate change via surface water such as rivers, lakes, and marshes. In this study, the authors selected a relevant climate change scenario, A1B from the Special Report on Emission Scenario (SRES) which is distributed at Korea Meteorological Administration. By using data on temperature, rainfall, soil, and land use, the groundwater recharge rate for the research area was estimated by periodically and embodied as geographic information system (GIS). In order to calculate the groundwater recharge quantity, Visual HELP3 was used as main model, and the physical properties of weather, temperature, and soil layers were used as main input data. General changes to water circulation due to climate change have already been predicted. In order to systematically solve problems of ground circulation system, it may be urgent to recalculate the groundwater recharge quantity and consequent change under future climate change. The space-time calculation of changes of the groundwater recharge quantity in the study area may serve as a foundation to present additional measures to improve domestic groundwater resource management.
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