• 한국환경과학회지
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• 제22권8호
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• pp.1043-1052
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• 2013

This study was conducted to investigate the correlations between the $PM_{10}$ concentration trend and meteorological elements in the Gimhae region and analyze the transportation routes of air pollutants through back-trajectory analysis. Among the air quality measuring stations in the Gimhae regions, the $PM_{10}$ concentration of the Sambangdong station was higher than that of the Dongsangdong station. Also, an examination of the relationships between $PM_{10}$ concentration and meteorological elements showed that the greater the number of yellow dust occurrence days was and the lower the temperature and precipitation were, the higher the $PM_{10}$ concentration appeared. Furthermore, a cluster analysis through the HYSPLIT model showed that there were 4 clusters of trajectories that flowed into the Gimhae region and most of them originated in China. The meteorological characteristics of the four clusters were analyzed and they were similar to those of the air masses that influence South Korea. These analyses found that meteorological conditions affect the $PM_{10}$ concentration.

• 분석과학
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• 제35권1호
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• pp.32-40
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• 2022

The concentrations of radon in the atmosphere were measured at the Gosan site of Jeju Island during 2017-2018, in order to investigate the time-series variation characteristics and the dependency of airflow transport pathways. The mean ²²²Rn concentration was 2,480 mBq m^-3, and its monthly concentration in November was 3,262 mBq m^-3, more than twice as that in July (1,459 mBq m^-3). The diurnal radon concentrations increased throughout the nighttime to the maximum (2,862 mBq m^-3) at around 7 a.m., then gradually decreased throughout the daytime by the minimum (1,997 mBq m^-3) at around 3 p.m. The seasonal and monthly variations of CO, NO₂, O₃ showed a roughly similar pattern to that of radon for the same period, as high in winter and low in summer. The cluster back trajectory analysis described that about 60 % of overall airflow pathways was influenced by the airflow from China. The concentrations of radon and gaseous pollutants were relatively high as the airflow was influenced by China continent, but comparatively much lower as influenced by the northern Pacific Ocean.

• 한국대기환경학회지
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• 제33권2호
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• pp.174-183
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• 2017

The background level and timely variation characteristics of atmospheric $^{222}Rn$ concentrations have been evaluated by the real time monitoring at Gosan site of Jeju Island, Korea, during 2008~2015. The average concentration of atmospheric radon was $2,480mBq\;m^{-3}$ for the study period. The cyclic seasonality of radon was characterized such as winter maximum and summer minimum, consistent with the reduction in terrestrial fetch going to summer. On monthly variations of radon, the mean concentration in October was the highest as $3,041mBq\;m^{-3}$, almost twice as that in July ($1,481mBq\;m^{-3}$). The diurnal radon concentrations increased throughout the nighttime approaching to the maximum ($2,819mBq\;m^{-3}$) at around 7 a.m., and then gradually decreased throughout the daytime by the minimum ($2,069mBq\;m^{-3}$) at around 3 p.m. The diurnal radon cycle in winter showed comparatively small amplitude due to little variability in atmospheric mixing depth, conversely, large amplitude was observed in summer due to relatively a big change in atmospheric mixing depth. The cluster back-trajectories of air masses showed that the high radon events occurred by the predominant continental fetch over through Asia continent, and the radon concentrations from China continent were about 1.9 times higher on the whole than those from the North Pacific Ocean. The concentrations of $PM_{10}$ also increased in proportion to the high radon concentrations, showing a good linear correlation between $PM_{10}$ and radon concentrations.

• 한국대기환경학회지
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• 제34권2호
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• pp.321-330
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• 2018

Concentrations of the atmospheric radon and gaseous pollutants were measured at the Gosan site on Jeju Island from 2010 to 2015, in order to observe their time-series variation characteristics and examine the concentration change related to the airflow transport pathways. Based on the realtime monitoring of the atmospheric radon and gaseous pollutants, the daily mean concentrations of radon ($^{222}Rn$) and gaseous pollutants($SO_2$, CO, $O_3$, $NO_x$) were $2,400mBq\;m^{-3}$ and 1.3, 377.6, 41.1, 3.9 ppb, respectively. On monthly variations of radon, the mean concentration in October was the highest as $3,033mBq\;m^{-3}$, almost twice as that in July ($1,452mBq\;m^{-3}$). The diurnal variation of radon concentration shows bimodal curves at early morning (around 7 a.m.) and near midnight, whereas its lowest concentration was recorded at around 3 p.m. Several gaseous pollutants($SO_2$, CO, $NO_x$) showed a similar seasonal variation with radon concentration as high in winter and low in summer, whereas the $O_3$ concentrations had a bit different seasonal trend. According to the cluster back trajectory analysis, the frequencies of airflow pathways moving from continental North China, East China, Japan and the East Sea, the Korean Peninsula, and North Pacific Ocean routes were 36, 37, 10, 13, and 4%, respectively. When the airflow were moved to Jeju Island from continental China, the concentrations of radon and gaseous pollutants were relatively high. On the other hand, when the airflows were moved from North Pacific Ocean and East Sea, their concentrations were much lower than those from continental China.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권3호
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• pp.1204-1227
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• 2020

The tradeoff between energy conservation and traffic balancing is a dilemma problem in Wireless Sensor Networks (WSNs). By analyzing the intrinsic relationship between cluster properties and long distance transmission energy consumption, we characterize three node sets of the cluster as a theoretical foundation to enhance high performance of WSNs, and propose optimal solutions by introducing rendezvous and Mobile Elements (MEs) to optimize energy consumption for prolonging the lifetime of WSNs. First, we exploit an approximate method based on the transmission distance from the different node to an ME to select suboptimal Rendezvous Point (RP) on the trajectory for ME to collect data. Then, we define data transmission routing sequence and model rendezvous planning for the cluster. In order to achieve optimization of energy consumption, we specifically apply the economic theory called Diminishing Marginal Utility Rule (DMUR) and create the utility function with regard to energy to develop an adaptive energy consumption optimization framework to achieve energy efficiency for data collection. At last, Rendezvous Transmission Algorithm (RTA) is proposed to better tradeoff between energy conservation and traffic balancing. Furthermore, via collaborations among multiple MEs, we design Two-Orbit Back-Propagation Algorithm (TOBPA) which concurrently handles load imbalance phenomenon to improve the efficiency of data collection. The simulation results show that our solutions can improve energy efficiency of the whole network and reduce the energy consumption of sensor nodes, which in turn prolong the lifetime of WSNs.

• 한국대기환경학회지
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• 제24권5호
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• pp.584-593
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• 2008

The surface $O_3,\;CO,\;NO_x,\;and\;SO_2$ were measured at Gosan in Jeju Island from May 2004 to April 2005. Over this period, the mean concentrations $({\pm}s.d.)$ of each gas was 40.06 $({\pm}16.01)$ ppbv for $O_3,\;264.92({\pm}115.73)ppbv\;for\;CO,\;1.98({\pm}2.73)ppbv\;for\;SO)_2,\;and\;4.64 ({\pm}3.24) ppbv\;for\;NO_x$. The monthly variations and the diurnal variations of these gases show that the Gosan site is situated in a relatively clean region. However, there were episodic simultaneous peaks in CO and $SO_2$, especially in winter and early spring. Using cluster analysis with air mass back- ward trajectory analysis, we suggest that these episodes are due to the influence of transportation of polluted air mass from polluted regions. In the cluster, which was under the dominant influence of clean maritime air mass, low levels of $O_3,\;CO,\;and\;SO_2$ were observed. The levels of these species were elevated in the other two clusters which had the air mass influenced by polluted continental regions. In addition, ratios of the chemical species such as $CO/NO_x,\;SO_2/NO_x,\;and\;CO/SO_2$ revealed the somewhat different characteristics of emission sources influencing each cluster. The differences in concentration of trace gases among clusters with different origin and transport pathways imply that Gosan is under the effect of pollution transported from other regions.

• Asian Journal of Atmospheric Environment
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• 제11권2호
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• pp.114-121
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• 2017

Real-time monitoring of hourly concentrations of atmospheric Radon-222 ($^{222}Rn$, radon) and some gaseous pollutants ($SO_2$, CO, $O_3$) was performed throughout 2013-2014 at Gosan station of Jeju Island, one of the cleanest regions in Korea, in order to characterize their background levels and temporal variation trend. The hourly mean concentrations of radon and three gaseous pollutants ($SO_2$, CO, $O_3$) over the study period were $2216{\pm}1100mBq/m^3$, $0.6{\pm}0.7ppb$, $211.6{\pm}102.0ppb$, and $43.0{\pm}17.0ppb$, respectively. The seasonal order of radon concentrations was as fall ($2644mBq/m^3$)$${\sim_\sim}$$winter ($2612mBq/m^3$)>spring ($2022mBq/m^3$)>summer ($1666mBq/m^3$). The concentrations of $SO_2$ and CO showed similar patterns with those of radon as high in winter and low in summer, whereas the $O_3$ concentrations had a bit different trend. Based on cluster analyses of air mass back trajectories, the air mass frequencies originating from Chinese continent, North Pacific Ocean, and the Korean Peninsula routes were 30, 18, and 52%, respectively. When the air masses were moved from Chinese continent to Jeju Island, the concentrations of radon and gaseous pollutants ($SO_2$, CO, $O_3$) were relatively high: $2584mBq/m^3$, 0.76 ppb, 225.8 ppb, and 46.4 ppb. On the other hand, when the air masses were moved from North Pacific Ocean, their concentrations were much low as $1282mBq/m^3$, 0.24 ppb, 166.1 ppb, and 32.5 ppb, respectively.