From April 29 to 30, 2011, under the influence of Asian dust originated from Mongolia, a high concentration of Asian dust was observed nationwide for 4 days in Korea. This study investigated the causes and characteristics of and weather conditions associated with Asian dust at high concentrations at its source in Mongolia. For analysis, Asian dust weather data, Asian dust monitoring tower data, satellite data, backward trajectory data, observation data (PM10 and OPC data), and ECMWF reanalysis data were used. In the synoptic analysis, it was observed that the intervals of isobars were densely distributed in the central region of Mongolia and the pressure gradient force was strong. It could be inferenced that Asian dust occurred due to strong winds. The temperature was relatively high, above 10℃, just before the occurrence of Asian dust, and it decreased sharply at the onset of the dust. The relative humidity had a low value of less than approximately 40%. After the occurrence of Asian dust, it increased sharply to over 50% and then showed a tendency to decrease. In the aerosol index shown by the COMS satellite, a high concentration value of over 25 was detected in Inner Mongolia, and it was consistent with the observations made with naked eyes. In the 72-hour backward trajectory, the northwest airflow streamed into Korea, and on May 2, Heuksando showed the highest PM10 concentration of 1,025 ㎍ m-3(times the average). Especially, in kinematic vertical analysis, it was observed that low pressure on the ground was strengthened by cyclonic relative vorticity developed in the upper layer. Also, the vertical velocity development is considered to have played a major role in the occurrence of high concentration Asian dust.
Impacts of global warming have been identified in many areas including natural ecosystem. A good number of studies based on climate models forecasting future climate have been conducted in many countries worldwide. Due to its global coverage, GCM, which is a most frequently used climate model, has limits to apply to Korea with such a narrower and complicated terrain. Therefore, it is necessary to perform a study impact assessment of climate changes with a climate model fully reflecting characteristics of Korean climate. In this respect, this study was designed to compare and analyze the GCM and RCM in order to determine a suitable climate model for Korea. In this study, spatial scope was Korea for 10 years from 1981 to 1990. As a research method, current climate was estimated on the basis of the data obtained from observation at the GHCN. Future climate was forecast using 4 GCMs furnished by the IPCC among SRES A2 Scenario as well as the RCM received from the NIES of Japan. Pearson correlation analysis was conducted for the purpose of comparing data obtained from observation with GCM and RCM. As a result of this study, average annual temperature of Korea between 1981 and 1990 was found to be around $12.03^{\circ}C$, with average daily rainfall being 2.72mm. Under the GCM, average annual temperature was between 10.22 and $16.86^{\circ}C$, with average daily rainfall between 2.13 and 3.35mm. Average annual temperature in the RCM was identified $12.56^{\circ}C$, with average daily rainfall of 5.01mm. In the comparison of the data obtained from observation with GCM and RCM, RCMs of both temperature and rainfall were found to well reflect characteristics of Korea's climate. This study is important mainly in that as a preliminary study to examine impact of climate changes such as global warming it chose appropriate climate model for our country. These results of the study showed that future climate produced under similar conditions with actual ones may be applied for various areas in many ways.
We investigate two abnormal CME-Storm pairs that occurred on 2014 September 10 - 12 and 2015 March 15 - 17, respectively. The first one was a moderate geomagnetic storm ($Dst_{min}{\sim}-75nT$) driven by the X1.6 high speed flare-associated CME ($1267km\;s^{-1}$) in AR 12158 (N14E02) near solar disk center. The other was a very intense geomagnetic storm ($Dst_{min}{\sim}-223nT$) caused by a CME with moderate speed ($719km\;s^{-1}$) and associated with a filament eruption accompanied by a weak flare (C9.1) in AR 12297 (S17W38). Both CMEs have large direction parameters facing the Earth and southward magnetic field orientation in their solar source region. In this study, we inspect the structure of Interplanetary Flux Ropes (IFRs) at the Earth estimated by using the torus fitting technique assuming self-similar expansion. As results, we find that the moderate storm on 2014 September 12 was caused by small-scale southward magnetic fields in the sheath region ahead of the IFR. The Earth traversed the portion of the IFR where only the northward fields are observed. Meanwhile, in case of the 2015 March 17 storm, our IFR analysis revealed that the Earth passed the very portion where only the southward magnetic fields are observed throughout the passage. The resultant southward magnetic field with long-duration is the main cause of the intense storm. We suggest that 3D magnetic field geometry of an IFR at the IFR-Earth encounter is important and the strength of a geomagnetic storm is strongly affected by the relative location of the Earth with respect to the IFR structure.
The spatial mapping of risk is very useful data in planning for disaster preparedness. This research presents a methodology for making the landslide life risk map in the Boeun area which had considerable landslide damage following heavy rain in August, 1998. We have developed a three-stage procedure in spatial data analysis not only to estimate the probability of the occurrence of the natural hazardous events but also to evaluate the uncertainty of the estimators of that probability. The three-stage procedure consists of: (i)construction of a hazard prediction map of "future" hazardous events; (ii) validation of prediction results and estimation of the probability of occurrence for each predicted hazard level; and (iii) generation of risk maps with the introduction of human life factors representing assumed or established vulnerability levels by combining the prediction map in the first stage and the estimated probabilities in the second stage with human life data. The significance of the landslide susceptibility map was evaluated by computing a prediction rate curve. It is used that the Bayesian prediction model and the case study results (the landslide susceptibility map and prediction rate curve) can be prepared for prevention of future landslide life risk map. Data from the Bayesian model-based landslide susceptibility map and prediction ratio curves were used together with human rife data to draft future landslide life risk maps. Results reveal that individual pixels had low risks, but the total risk death toll was estimated at 3.14 people. In particular, the dangerous areas involving an estimated 1/100 people were shown to have the highest risk among all research-target areas. Three people were killed in this area when landslides occurred in 1998. Thus, this risk map can deliver factual damage situation prediction to policy decision-makers, and subsequently can be used as useful data in preventing disasters. In particular, drafting of maps on landslide risk in various steps will enable one to forecast the occurrence of disasters.
Journal of Korean Society for Atmospheric Environment
/
v.34
no.5
/
pp.687-696
/
2018
In order to develop effective emission abatement strategies for coal-fired power plants, we analyzed the shutdown effects of coal-fired power plants on $PM_{2.5}$ concentration in June by employing air quality model for the period from 2013 to 2016. WRF (Weather Research and Forecast) and CMAQ(Community Multiscale Air Quality) models were used to quantify the impact of emission reductions on the averaged $PM_{2.5}$ concentrations in June over Chungcheongnam-do area in Korea. The resultant shutdown effects showed that the averaged $PM_{2.5}$ concentration in June decreased by 1.2% in Chungcheongnam-do area and decreased by 2.3% in the area where the surface air pollution measuring stations were located. As a result of this study, it was confirmed that it is possible to analyze policy effects considering the change of meteorology and emission and it is possible to quantitatively estimate the influence at the maximum impact region by utilizing the air quality model. The results of this study are expected to be useful as a basic data for analyzing the effect of $PM_{2.5}$ concentration change according to future emission changes.
International concern over the environmental pollution is ever increasing, and diversified countermeasures must be devised in Korea also. Global trend, damages, problems and countermeasures with respect to issues mentioned in the Rio Declaration, such as prevention of ozone layer destruction, reduction of migratory atmospheric pollution between neighboring countries, and prevention of global greenhouse effect, were discussed in this report. Conclusion of the report is summarized as follows : A. Measurement, Planning and Monitoring (1) Development and implementation of a global network for measurement and monitoring from the global aspects such factors as related to acid rain(Pioneer substances, pH, sulfate, nitrate), effect of global temperature(Air temperature, $CO_2$, $CH_4$, CFC, $N_2O$) and destruction of ozone layer($CFC_S$). (2) Establishment of network system via satellite monitoring movement of regional air mass, damage on the ozone layer and ground temperature distribution. B. Elucidation of Present State (1) Improvement and development of devices for carbon circulation capable of accurately forecasting input and output of carbon. (2) Developmental research on chemical reactions of greenhouse gas in the air. (3) Improvement and development of global circulation model(GCM) C. Impact Assessment Impact assessment on ecosystem, human body, agriculture, floodgate, land use, coastal ecology, industries, etc. D. Preventive Measures and Technology Development (1) Development and consumption of new energy (2) Development of new technology for removal of pioneer substances (3) Development of substitute matter for $CFC_S$ (4) Improvement of agriculture and forestry means to prevent the destruction of ozone layer and the greenhouse effect of the globe (5) Improvement of housing to prevent the destruction of ozone layer and the greenhouse effect of the globe (6) Development of new technology for probing underground water (7) Preservation of forest (8) Biomass 5. Policy Development (1) Development of strategy model (2) Development of long term forecast model (3) Development of penalty charge effect and expense evaluation methods (4) Feasibility study on regulations By establishing the above mentioned measures for environmentally sound and sustainable development to establish the right to live for humankind and to preserve the one and only earth.
In this study, we investigated the impact of different initial data on atmospheric modeling results using the Weather Research and Forecast (WRF) model. Four WRF simulations were conducted with different initialization in March 2015, which showed the highest monthly mean $PM_{10}$ concentration in the recent ten years (2006-2015). The results of WRF simulations using NCEP-FNL and ERA-Interim were compared with observed surface temperature and wind speed data, and the difference of grid nudging effect on WRF simulation between the two data were also analyzed. The FNL simulation showed better accuracy in the simulated temperature and wind speed than the Interim simulation, and the difference was clear in the coastal area. The grid nudging effect on the Interim simulation was larger than that of the FNL simulation. Despite of the higher spatial resolution of ERA-Interim data compared to NCEP-FNL data, the Interim simulation showed slightly worse accuracy than those of the FNL simulation. It was due to uncertainties associated with the Sea Surface Temperature (SST) field in the ERA-Interim data. The results from the Interim simulation with different SST data showed significantly improved accuracy than the standard Interim simulation. It means that the SST field in the ERA-Interim data need to be optimized for the better WRF simulation. In conclusion, although the WRF simulation with ERA-Interim data does not show reasonable accuracy compared to those with NCEP-FNL data, it would be able to be Improved by optimizing the SST variable.
The impact of horizontal resolution on a regional climate model was investigated by simulating precipitation over the Korean Peninsula. As a regional climate model, the SNURCM(Seoul National University Regional Climate Model) has 21 sigma layers and includes the NCAR CLM(National Center for Atmospheric Research Community Land Model) for land-surface model, the Grell scheme for cumulus convection, the Simple Ice scheme for explicit moisture, and the MRF(Medium-Range Forecast) scheme for PBL(Planetary Boundary Layer) processing. The SNURCM was performed with 20 km resolution for Korea and 60 km resolution for East Asia during a 20-year period (1980-1999). Although the SNURCM systematically underestimated precipitation over the Korean Peninsula, the increase of model resolution simulated more precipitation in the southern region of the Korean Peninsula, and a more accurate distribution of precipitation by reflecting the effect of topography. The increase of precipitation was produced by more detailed terrain data which has a 10 minute terrain in the 20 km resolution model compared to the 30 minute terrain in the 60 km resolution model. The increase in model resolution and more detailed terrain data played an important role in generating more precipitation over the Korean Peninsula. While the high resolution model with the same terrain data resulted in increasing of precipitation over the Korean Peninsula including the adjoining sea, the difference of the terrain data resolution only influenced the precipitation distribution of the mountainous area by increasing the amount of non-convective rain. In conclusion, the regional climate model (SNURCM) with higher resolution simulated more precipitation over the Korean Peninsula by reducing the systematic underestimation of precipitation over the Korean Peninsula.
Yu, Jae Jeong;Shin, Suk Ho;Yoon, Young Sam;Kang, Doo Kee
Journal of Environmental Impact Assessment
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v.21
no.4
/
pp.543-552
/
2012
Namgang mid-watershed is located in downstream of Nakdong river basin. There are many pollution sources arround this area and it's control is important to manage a water quality of Nakdong river. A target year of Namgang mid-watershed water environment management plan is 2013. To predict a water quality at downstream of Namgang, we have investigated and forecasted the pollutant source and it's loading. There are some plan to construction the sewage treatment plants to improve the water quality of Nam river. Those are considered on predicting water quality. As results, it is shown that the population is 343,326 and sewerage supply rate is 79.2% and the livestock is 1,662,000 in Namgang mid-watershed. It is estimated that the population is 333,980, the sewerage supply rate is 86.9% in 2013. The milk cow and cattle were estimated upward and the pigs were downward by 2013. The generated loading of BOD and TP is 75,957 kg/day and 4,311 kg/day, discharged loading is 18,481 kg/day and 988 kg/day respectively in 2006. It were predicted upward the discharged loading of BOD and TP by 4.08% and 6.3% respectively. The results of water quality prediction of Namgang4 site were 2.5 mg/L of BOD and 0.120 mg/L of TP in 2013. It is over the target water quality at that site in 2015 about 25.0% and 9.1% respectively. Consequently, there need another counterplan to reduce the pollutants in that mid-watershed.
This study applied the Neural Network and Fuzzy theory to show water-purity control and preventive measure in water quality forecasting of the future river. This study picked out NAJU and HAMPYUNG as the subject of investigation and used monthly the water quality and the outflow data of KWANGJU2, NAJU, YOUNGSANNPO and HAMPYUNG from 1995 to 1999 to forecast BOD, COD, T-N, T-P water density. The datum from 1995 to 1999 are used for study and that of 2000 are used for verification. To develop model of water quality forecasting, firstly, this research formed Neural Network model and divided Neural Network model into two case - the case of considering lag and not considering. And this study selected optimal Neural Network model through changing the number of hidden layer based on input layer(n) from n to 3n. Through forecasting result, the case without considering lag showed more precise simulated result. Accordingly, this study intended to compare, analyse that Fuzzy model using the method without considering lag with Neural Network model. As a result, this study found that the model without considering lag in Neural Network Network shows the most excellent outcome. Thus this study examined a forecasting accuracy, analyzed result and verified propriety through appling the method of water quality forecasting using Neural Network and Fuzzy Algorithms to the actual case.
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