• 한국대기환경학회지
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• 제24권5호
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• pp.604-612
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• 2008

The ozone concentration is one of the important environmental issue for measurement of the atmospheric condition of the country. This study focuses on applying the Autoregressive Error (ARE) model for analyzing the ozone data at middle part of the Gyeonggi-Do, Anyang monitoring site in Korea. In the ARE model, eight meteorological variables and four pollution variables are used as the explanatory variables. The eight meteorological variables are daily maximum temperature, wind speed, amount of cloud, global radiation, relative humidity, rainfall, dew point temperature, and water vapor pressure. The four air pollution variables are sulfur dioxide $(SO_2)$, nitrogen dioxide $(NO_2)$, carbon monoxide (CO), and particulate matter 10 (PM10). The result shows that ARE models both overall and monthly data are suited for describing the oBone concentration. In the ARE model for overall ozone data, ozone concentration can be explained about 71% to by the PM10, global radiation and wind speed. Also the four types of ARE models for high level of ozone data (over 80 ppb) have been analyzed. In the best ARE model for high level of ozone data, ozone can be explained about 96% by the PM10, daliy maximum temperature, and cloud amount.

• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1153-1164
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• 2008

The ozone data is one of the important environmental data for measurement of the atmospheric condition of the country. In this article, the Autoregressive Error (ARE) model have been considered for analyzing the ozone data at the northern part of the Gyeonggi-Do, Uijeongbu monitoring site in Korea. The result showed that both overall and monthly ARE models are suited for describing the ozone concentration. In the ARE model, seven meteorological variables and four pollution variables are used as the as the explanatory variables for the ozone data set. The seven meteorological variables are daily maximum temperature, wind speed, relative humidity, rainfall, dew point temperature, steam pressure, and amount of cloud. The four air pollution explanatory variables are Sulfur dioxide(SO2), Nitrogen dioxide(NO2), Cobalt(CO), and Promethium 10(PM10). Also, the high level ozone data (over 80ppb) have been analyzed four ARE models, General ARE, HL ARE, PM10 add ARE, Temperature add ARE model. The result shows that the General ARE, HL ARE, and PM10 add ARE models are suited for describing the high level of ozone data.

• 응용통계연구
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• 제22권4호
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• pp.687-695
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• 2009

The Bayesian multiple change-point estimation has been applied to the daily means of ozone and PM10 data in Seoul for the period 1999. We focus on the detection of multiple change-points in the ozone and PM10 bivariate vectors by evaluating the posterior probabilities and Bayesian information criterion(BIC) using the stochastic approximation Monte Carlo(SAMC) algorithm. The result gives 5 change-points of mean vectors of ozone and PM10, which are related with the seasonal characteristics.

• Journal of Periodontal and Implant Science
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• 제48권3호
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• pp.136-151
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• 2018

Purpose: The decontamination procedure is a challenging aspect of surgical regenerative therapy (SRT) of peri-implantitis that affects its success. The purpose of the present study was to determine the impact of additional topical gaseous ozone therapy on the decontamination of implant surfaces in SRT of peri-implantitis. Methods: A total of 41 patients (22 males, 19 females; mean age, $53.55{\pm}8.98years$) with moderate or advanced peri-implantitis were randomly allocated to the test group (ozone group) with the use of sterile saline with additional ozone therapy or the control group with sterile saline alone for decontamination of the implant surfaces in SRT of peri-implantitis. Clinical and radiographic outcomes were evaluated over a period of 12 months. Results: At the 12-month follow-up, the plaque and gingival index values were significantly better in the ozone group (P<0.05). Probing depth decreased from $6.27{\pm}1.42mm$ and $5.73{\pm}1.11mm$ at baseline to $2.75{\pm}0.7mm$ and $3.34{\pm}0.85mm$ at the end of the 12-month observation period in the ozone and control groups, respectively. Similarly, the clinical attachment level values changed from $6.39{\pm}1.23mm$ and $5.89{\pm}1.23mm$ at baseline to $3.23{\pm}1.24mm$ and $3.91{\pm}1.36mm$ at the 12-month follow-up in the ozone and control groups, respectively. According to the radiographic evidence, the defect fill between baseline and 12 months postoperatively was $2.32{\pm}1.28mm$ in the ozone group and $1.17{\pm}0.77mm$ in the control group, which was a statistically significant between-group difference (P<0.05). Conclusions: Implant surface decontamination with the additional use of ozone therapy in SRT of peri-implantitis showed clinically and radiographically significant. Trial registry at ClinicalTrials.gov, NCT03018795.

• 한국방사선학회논문지
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• 제10권3호
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• pp.171-180
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• 2016

본 연구는 고 에너지 방사선 조사에 기인된 방사선치료실 내 오존 농도의 변화를 비교 분석하고자 하였다. 이를 위하여 치료실 주변 대기 중 오존 농도와 치료실 내 배경 오존 농도를 분석하여 고 에너지 방사선 조사에 기인된 치료실 내 평균 오존 농도를 비교하였다. 치료실 내 배경 오존 농도는 평균 $17.4{\pm}7.9ppb$로 방사선치료실 주변의 대기 중 오존 농도(평균 $36.8{\pm}22.3ppb$)보다 약 50% 정도 통계적으로 유의하게 낮게 나타났다(p<0.05). 고 에너지 방사선 조사에 기인된 치료실 내 오존 농도는 방사선이 조사됨과 동시에 배경 오존 농도의 약 2배 수준으로 급격하게 증가되었으며 조사시간이 증가함에 따라 기울기가 일정한 증가 추이를 보이다가 약 130초에서 180초 부근에서 최대 오존 농도를 이루고 점차 포화되는 경향을 보였으며 배경 오존 농도로 감소하는데 소요되는 시간은 약 10분 이상이었다. 본 연구 결과를 토대로 고 에너지 방사선 조사에 기인된 방사선치료실 내 오존 농도는 후각을 자극하는 오존의 특이한 냄새를 맡거나 순간적인 호흡 곤란과 마른기침으로 가슴 통증 등의 신체적 증상이 나타날 수 있는 수준으로 밀폐된 방사선치료실에서 고농도 오존에 장시간 노출될 경우 폐 질환을 악화시킬 수 있기 때문에 각별한 주의가 요구된다.

• 한국환경과학회지
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• 제26권8호
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• pp.927-938
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• 2017

This study was conducted to determine correlations and similarity between the ozone and $PM_{10}$ data of 19 air quality monitoring stations in Busan from 2013 to 2016, using correlation and cluster analyses. Ozone concentrations ranged from $0.0278{\pm}0.0148ppm$ at Gwangbok to $0.0378{\pm}0.017ppm$ at Taejongdae and were high in suburban areas, such as Yongsuri and Gijang, as well as in coastal areas, such as Jaw, Gwangan, Taejongdae and Noksan. $PM_{10}$ concentrations ranged from $37.2{\pm}25.0ug/m^3$ at Gijang to $58.3{\pm}32.2ug/m^3$ at and Jangrim. $PM_{10}$ concentrations were high in the west, exceeding the annual ambient air quality standard of $50ug/m^3$. Positive correlations were observed for ozone at most stations, ranging from 0.61 between Taejongdae and Sujeong to 0.92 between Bugok and Myeongjang. The correlation coefficients of $PM_{10}$ between stations ranged from 0.62 between Jangrim and Jaw to 0.9 between Gwangbok and Sujeong. Yeonsan, Daeyeon, and Myeongjang were highly correlated with other stations, so they needed to be reviewed for redundancy. Ozone monitoring stations were initially divided into two sections, north-western areas and suburban-coastal areas. The suburban-coastal areas were subsequently divided into three sections. $PM_{10}$ monitoring stations were initially divided into western and remaining areas, and then the remaining areas were subsequently divided into three sections.

• KIEAE Journal
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• 제12권6호
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• pp.93-98
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• 2012

The concerns on high ozone concentration phenomenon is significantly growing in Seoul metropolitan area including the industry complex area, like Shiwha Banwol area. The aims of this research is the analysis of relationship between high concentrations of $O_3$ and solar radiation parameters in atmosphere. The understanding of the effects of solar radiation intensity, humidity, high air temperature on ozone concentration in a day is very useful to provide a direction for reducing of the high ozone concentration to a local government or a metropolitan government. The correlation analysis between maximum ozone concentration and various meteorological parameters in 2009 - 2011 carried out using IBM's SPSS program. The results showed that the mean correlations coefficient (R) between daily Ozone maximum and solar radiation resulted R = 0.64 during 2011. May - September in 10 air pollution stations. In case of correlations between daily ozone maximum and relative humidity showed negative correlation R = -0.61. The correlation analysis with mean air temperature during 1-3 PM resulted R = 0.29. This low correlation coefficient could be corrected by using of categorized data of ozone concentration. The daily maximum ozone concentration is more dependent on peak solar radiation and high air temperature during 1-3 PM than its simple daily maximum values. The results of this research would be used to develop the high ozone alert system around Seoul metropolitan area. This correlation analysis could be partially integrated to prediction of ozone peak concentration in connection with other methods like classification and regression tree(CART).

• 한국대기환경학회지
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• 제5권2호
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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 Astronomy and Space Sciences
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• 제15권1호
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• pp.119-138
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• 1998

최근에 인공위성에 의한 대기 중의 미량 기체 관측이 활발하다. 따라서 이들 자료의 처리기법 개발이 매우 중요하다. 그러므로 이 연구에서는 인공위성에 의해 태양 엄폐범(太陽 掩蔽法: Solar Occultation Method)으로 관측한 대기 주연 경로(周緣 經路: limb path)의 접선 고도별 평균 투과율로부터 연직 오존 분포를 도출하고, 온도와 기압 오차의 민감도 오차의 민감도 실험을 하고자 한다. 여기에서 서울의 반전(Umkehr)관측에 의하여 구한 연평균 연직 오존분포로 계산된 평균 투과율을 인공위성으로부터 관측된 평균 투과율로 가정하였다. HALOE SIDS (Hallogen Occultation Experiment Simulated Instrument Data Set)의 연직 오존 자료를 초기치로 하고 온도와 기압의 연직 분포를 입력값으로 하여 대기 평균 투과율을 파장 $9.89{\mu}m$와 $10.02{\mu}m$ 사이에서 접선고도별로 계산했다. 관측 평균 투과율에 대하여 계산한 평균 투과율로부터 오존 분포 법으로 접선고도 10km에서 50km까지 매 3km마다 오존 농도를 도출하였다. 도출된 서울의 연직 오존 분포를 관측한 연직 오존 분포와 비교하였다. 이 결과에 의하면 전 고도에 걸쳐서 서울의 연직 오존 분포가 오차가 거의 없을 정도로 정확하게 도출되었다. 그리고 민감도 실험을 위하여 관측 평균 투과율에$\pm0.001$, 각 층의 온도에 $\pm3K$, 그리고 각 층에 기압의 $\pm3\%$의 강제 오차를 각각 주었다. 이들 각 오차는 ADEOS/ILAS 관측 오차에 근거하였다. 이들의 결과는 투과율 오차에 대하여 -6.5%에서 +6.9%, 온도 오차에 대하여 -9.5%에서 +10.5, 그리고 기압 오차에 대하여 -5.1%에서 +5.4%의 고도별 오존 량 오차가 각각 나타났다. 태양 엄폐 법에 의해 비교적 정확한 연직 오존 분포를 도출할 수 있었다. 이 도출 과정에서 특히 온도 관측이 중요함을 알 수 있었다.

• 환경위생공학
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• 제18권3호통권49호
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• pp.78-88
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• 2003

This study was conducted to investigate the relation between ozone concentration and the affecting factors in Seosan City of Korea from Jan. 2002 to Dec. 2002. We analyzed the air pollutants such as NO$_2$, PM$_{10} $,SO$_2$, CO and the meteorological factors including solar radiation, air temperature, wind speed and relative humidity. The analytical data were taken statistics by SPSS method. The results were as follows: The seasonal average concentration of ozone were detected 35.0 ppb in Spring, 25.4 ppb in Summer, 23.5 ppb in Autumn and 21.4 ppb in Winter. So the difference of concentrations showed significantly in statistics. The hourly ozone concentration in a day was increased at 7-9 AM, peaked at 3-4 PM. The correlation coefficients was negative to ozone concentration and NO$_2$, SO$_2$, CO, relative humidity, but positive to solar radiation, air temperature, wind speed. With stepwise multiple regression analysis on the 8 factors such as NO$ _2$, PMSO$_{10}$,SO$_2$, CO, solar radiation, air temperature, wind speed and relative humidity, the seasonal primary factors were air temperature in spring, relative humidity in summer and solar radiation in autumn and winter. The above results suggest that ozone is the secondary pollutant by photochemical reaction as the concentration of ozone was increased with the raise of solar radiation.