• Journal of Korean Society for Atmospheric Environment
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• v.5 no.2
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• pp.55-71
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• 1989

This study was carried out to determine the ozone concentration to behaviour and the factors to be influenced the variation of its concentration in the ambient air in Seoul. Measurements of ozone concentrations were made at 10 monitoring station to take care of SIHE (Seoul Institute of Health & Environment) during December 1987 to November 1988, also measured the hourly average concentration of sulfur dioxide, total suspended particulate, nitrogen oxide $(NO & NO_2)$, carbon monoxide, hydro carbon $(n-CH_4 & THC)$ and meteorological factors, that is, temperature, humidity, wind velocity wind direction and ultraviolet intensity etc, for the same period at same place. The basis of the data obtained were analyzed statistically along with the various data. The results were as follows; 1. The annually arithmetic mean concentration of ozone for the 10 sites during one years was 10.0 ppb and ranged from 3.1 $\pm$ 4.5ppb at the Kuro industrial complex to 17.2 $\pm$ 18.7 ppb at the Ssangmun site. 2. The frequency of hours on which oxidant concentrations exceeded the present short term standard of ozone (100 ppb) were 78 times. 3. The diurnal patterns of hourly ozone concentrations in Seoul area was a typical bi-modal variation which have 4 to 5 a.m. peak and 3. to 4 p.m peak. 4. The time ozone of highest ozone concentration in a whole day and hight was 1 to 5 p.m and 90.9 percent of appearence rate. 5. The diurnal patterns of hourly ozone concentrations in Seoul were on the whole the order of daytime from 5.8ppb to 28.7 ppb evening from 1.7 to 18.7 ppb night time from 1.9 to 9.3 ppb daybreak from 1.4ppb according to measuring sites, and the highest that observed at the Ssangmun area while the lowest was the Kuro industrial complex monitor sites. 6. The weekly variation of ozone concentration was the higher level ozone concentration in the day of the week occured sunday-monday and weekend but the decrease were observed from wednesday to thursday.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.2
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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.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1293-1300
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• 2014

The temperature data influences on various policies of the country. In this article, the autoregressive error (ARE) model has been considered for analyzing the monthly and seasonal temperature data at the northern part of the Chungcheong Namdo, Seosan monitoring site in Korea. In the ARE model, five meteorological variables, four greenhouse gas variables and five pollution variables are used as the explanatory variables for the temperature data set. The five meteorological variables are wind speed, rainfall, radiation, amount of cloud, and relative humidity. The four greenhouse gas variables are carbon dioxide ($CO_2$), methane ($CH_4$), nitrous oxide ($N_2O$), and chlorofluorocarbon ($CFC_{11}$). And the five air pollution explanatory variables are particulate matter ($PM_{10}$), sulfur dioxide ($SO_2$), nitrogen dioxide ($NO_2$), ozone ($O_3$), and carbon monoxide (CO). The result showed that the monthly ARE model explained about 39-63% for describing the temperature. However, the ARE model will be expected better when we add the more explanatory variables in the model.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4554-4560
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• 2023

Continuous monitoring of radioactive substances over a prolonged duration can yield crucial insights into the levels of radiation exposure through inhalation, both in the vicinity of nuclear facilities and/or general environments. In this study, we evaluated long-term measurements (2012-2022) of gross alpha-beta activities in the air in the vicinity of nuclear facilities and reference site, distribution characteristics of temporal trends and spatial fluctuations, and factors affecting radioactivity levels. The average airborne gross-α (in mBq m^-3) for onsite and off-site were 0.124 and 0.117, respectively, and the average airborne gross-β (in mBq m^-3) measurements were 1.10 and 1.04, respectively. The activity ratio (AR) of gross-α and gross-β were calculated as a ratio of 0.12. The distribution characteristics of gross-α and gross-β activities in this study area are likely influenced by the meteorological factors and variations in airborne PM concentrations rather than the operation of the nuclear facility.

• Journal of Environmental Science International
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• v.15 no.8
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• pp.701-718
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• 2006

The average ratio of the daily UV-B to total solar (75) irradiance at Busan (35.23$^{\circ}$N, 129.07$^{\circ}$E) in Korea is found as 0.11%. There is also a high exponential relationship between hourly UV-B and total solar irradiance: UV-B=exp (a$\times$(75-b))(R$^2$=0.93). The daily variation of total ozone is compared with the UV-B irradiance at Pohang (36.03$^{\circ}$N, 129.40$^{\circ}$E) in Korea using the Total Ozone Mapping Spectrometer (TOMS) data during the period of May to July in 2005. The total ozone (TO) has been maintained to a decreasing trend since 1979, which leading to a negative correlation with the ground-level UV-B irradiance doting the given period of cloudless day: UV-B=239.23-0.056 TO (R$^2$=0.52). The statistical predictions of daily total ozone are analyzed by using the data of the Brewer spectrophotometer and TOMS in East Asia including the Korean peninsula. The long-term monthly averages of total ozone using the multiplicative seasonal AutoRegressive Integrated Moving Average (ARIMA) model are used to predict the hourly mean UV-B irradiance by interpolating the daily mean total ozone far the predicting period. We also can predict the next day's total ozone by using regression models based on the present day's total ozone by TOMS and the next day's predicted maximum air temperature by the Meteorological Mesoscale Model 5 (MM5). These predicted and observed total ozone amounts are used to input data of the parameterization model (PM) of hourly UV-B irradiance. The PM of UV-B irradiance is based on the main parameters such as cloudiness, solar zenith angle, total ozone, opacity of aerosols, altitude, and surface albedo. The input data for the model requires daily total ozone, hourly amount and type of cloud, visibility and air pressure. To simplify cloud effects in the model, the constant cloud transmittance are used. For example, the correlation coefficient of the PM using these cloud transmissivities is shown high in more than 0.91 for cloudy days in Busan, and the relative mean bias error (RMBE) and the relative root mean square error (RRMSE) are less than 21% and 27%, respectively. In this study, the daily variations of calculated and predicted UV-B irradiance are presented in high correlation coefficients of more than 0.86 at each monitoring site of the Korean peninsula as well as East Asia. The RMBE is within 10% of the mean measured hourly irradiance, and the RRMSE is within 15% for hourly irradiance, respectively. Although errors are present in cloud amounts and total ozone, the results are still acceptable.

• Environmental and Resource Economics Review
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• v.27 no.3
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• pp.569-611
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• 2018

Rapid economic growth, urbanization, and industrialization of China have tremendously degraded the overall quality of living environments, especially the air quality, not only negatively affecting Chinese people but also impacting citizens of neighboring countries, namely Korea. The Chinese government has invested much effort to regulate the air pollution due to burning coal through introducing strict environmental monitoring policies and aggressive implementation. This paper presents an overview of Chinese air pollution prevention policy due to burning coal, and the associated trends and specifics of institutional arrangements regarding air pollutant emission regulations. It turns out that the policies have become stricter than before; some polices are geared towards enforcing extra regulation at the regional level. It is expected that the regulation will become stricter in the future. However, the actual contribution and feasibility of such policies must be analyzed based on sound science. The policies seem to care little about influencing the air quality of Korea, and this has to be improved. In order to do so, it is important to strengthen environmental cooperation between Korea and China, and better yet to research on not only the air quality but also the associated fields, such as energy, industrial technology, and global environmental governance.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.2
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• pp.143-152
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• 2008

This study investigates the variation and spatial distribution of nitrogen dioxide($NO_2$) concentrations measured with passive diffusive samplers at 40 curbside points in Daejeon. Average $NO_2$ concentration was $39.8{\pm}18.0\;ppb$ (n=1,127) and the significant difference in concentrations by regional groups (Dong-gu, Jung-gu, Seo-gu, Daedeok-gu, Yuseong-gu) was not observed. The frequency distribution of $NO_2$ concentration was found to be a normal distribution with the high frequency in the concentration range of 30 to 40 ppb (20 to 25%). Average $NO_2$ concentration measured during the rainy periods was lower than that measured during the non-rainy periods and the decrease of concentration by rainfall was about 16% (7 ppb). The variation of $NO_2$ concentrations measured by passive diffusive samplers during the sampling period was similar to that continuously measured at the air quality monitoring station.

• Journal of the Korean earth science society
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• v.38 no.4
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• pp.283-292
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• 2017

In this study, the empirical models were established to estimate the concentrations of surface-level $PM_{2.5}$ over Seoul, Korea from 1 January 2012 to 31 December 2013. We used six different multiple linear regression models with aerosol optical thickness (AOT), ${\AA}ngstr{\ddot{o}}m$ exponents (AE) data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites, meteorological data, and planetary boundary layer depth (PBLD) data. The results showed that $M_6$ was the best empirical model and AOT, AE, relative humidity (RH), wind speed, wind direction, PBLD, and air temperature data were used as input data. Statistical analysis showed that the result between the observed $PM_{2.5}$ and the estimated $PM_{2.5}$ concentrations using $M_6$ model were correlations (R=0.62) and root square mean error ($RMSE=10.70{\mu}gm^{-3}$). In addition, our study show that the relation strongly depends on the seasons due to seasonal observation characteristics of AOT, with a relatively better correlation in spring (R=0.66) and autumntime (R=0.75) than summer and wintertime (R was about 0.38 and 0.56). These results were due to cloud contamination of summertime and the influence of snow/ice surface of wintertime, compared with those of other seasons. Therefore, the empirical multiple linear regression model used in this study showed that the AOT data retrieved from the satellite was important a dominant variable and we will need to use additional weather variables to improve the results of $PM_{2.5}$. Also, the result calculated for $PM_{2.5}$ using empirical multi linear regression model will be useful as a method to enable monitoring of atmospheric environment from satellite and ground meteorological data.

• Journal of IKEEE
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• v.22 no.2
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• pp.495-498
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• 2018

In this paper, we propose an DAP system for dose evaluation of medical and industrial X-ray generator. Based on the DAP measurement technique using the Ion-Chamber, the proposed system can clearly measure the exposure radiation dose generated by the diagnostic X-ray apparatus. The hardware part of the DAP measures the amount of charge in the air that is captured by an X-ray. The high-speed processing algorithm part for cumulative radiation dose measurement through microcurrent measures the amount of charge captured by X-ray at a low implementation cost (power) with no input loss. The wired/wireless transmission/reception protocol part synchronized with the operation of the X-ray generator improves communication speed. The PC-based control program part for interlocking and aging measures the amount of X-ray generated in real time and enables measurement graphs and numerical value monitoring through PC GUI. As a result of evaluating the performance of the proposed system in an accredited testing laboratory, the measured values using DAP increased linearly in each energy band (30, 60, 100, 150 kV). In addition, since the standard deviation of the measured value at the point of 4 division was ${\pm}1.25%$, it was confirmed that the DAP showed uniform measurements regardless of location. It was confirmed that the normal operation was not less than ${\pm}4.2%$ of the international standard.

• Asian Journal of Atmospheric Environment
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• v.12 no.1
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• pp.59-66
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• 2018

This study aims to evaluate the performance of the Air Quality Model (AQM) for the seasonal and spatial distribution of the $NH_3$ concentration in the atmosphere. To obtain observational data for the model validation, observations based on biweekly sampling have been conducted using passive samplers since April 2015 at multiple monitoring sites in the Tokyo metropolitan area. AQM, built based on WRF/CMAQ, was applied to predict the $NH_3$ concentration observed from April 2015 to March 2016. The simulation domain includes the Kanto region, which is the most densely populated area in Japan. Because the area also contains large amount of livestock, especially in its northern part, the density of the $NH_3$ emissions derived from human activities and agriculture there are estimated to be the highest in Japan. In the model validation, the model overestimated the observed $NH_3$ concentration in the summer season and underestimated it in the winter season. In particular, the overestimation in the summer was remarkable at a rural site (Komae) in Tokyo. It was found that the overestimation at Komae was caused by the transportation of $NH_3$ emitted in the northern part of the Kanto region during the night. It is suggested that the emission input used in this study overestimated the $NH_3$ emission from human sources around the Tokyo suburbs and agricultural sources in the northern part of the Kanto region in the summer season. In addition, the current emission inventories might overestimate the difference of the agricultural $NH_3$ emissions among seasons. Because the overestimation of $NH_3$ in the summer causes an overestimation of $NO_3{^-}$ in $PM_{2.5}$ in the AQM simulation, further investigation is necessary for the seasonal variation in the $NH_3$ emissions.