• 한국환경보건학회:학술대회논문집
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• 한국환경보건학회 2003년도 Challenges and Achievements in Environmental Health
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• pp.183-186
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• 2003

To evaluate the effect of air pollution on respiratory health in children, we conducted a longitudinal study in which children were asked to record their daily levels of peak expiratory flow rate using potable peak flow meter (mini-Wright) far 4 weeks. The relationship between daily PEFR and ambient air particle levels was analyzed using a mixed linear regression models including gender, age in you, weight, the presence of respiratory symptoms, and relative humidity as an extraneous variable. The daily mean concentrations of PM$\_$10/ and PM$\_$2.5/ over the study period were 64.9$\mu\textrm{g}$/㎥ and 46. l$\mu\textrm{g}$/㎥, respectively. The range of daily measured PEFR in this study was 170-481 l/min. Daily mean PEFR was regressed with the 24-hour. average PM$\_$10/ (or PM$\_$2.5/) levels, weather information such as air temperature and relative humidity, and individual characteristics including sex, weight, and respiratory symptoms. The analysis showed that the increase of air particle concentrations was negatively associated with the variability in PEFR. We estimated that the IQR increment of PM$\_$10/ or PM$\_$2.5/ were associated with 1.5 l/min (95% Confidence intervals -3.1, 0.1) and 0.8 l/min (95% Cl -1.8, 0.1) decline in PEFR. Even though this study shows negative findings on the relationship between respiratory function and air particles, it is worth noting that the findings must be interpreted cautiously because exposure measurement based on monitoring of ambient air likely results in misclassification of true exposure levels and this is the first Korean study that PM$\_$2.5/ measurement is applied as an index of air particle quality.

• 한국대기환경학회지
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• 제16권5호
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• pp.453-467
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• 2000

The aim of this research is to collect and characterize fine particles (FPM:$\leq$2.5${\mu}{\textrm}{m}$) and coarse particles (CPM: 2.5~10${\mu}{\textrm}{m}$) using a low volume air sampler provided by the IAEA, at urban (Taejon) and rural area(Wonju) for a period of about two years(April 1996 to May 1998) and to promote a use of nuclear analytical techniques for air pollution studies. For the collection of airborne particulate matter (PM(sub)10), the Gent stacked filter unit sampler and polycarbonate membrane filters were employed. The concentration of trace elements in collected APM samples were determined byu instrumental Neutron Activation Analysis. For validation of the analytical data, internal quality control were implemented by using both the comparison of the analytical results of standard reference materials(NIST SRM 1648) and interlaboratory comparison for proficiency test (NAT-3). The standard uncertainty was less than 15% and Z-score of two samples were within $\pm$1. The monitoring of (PM(sub)10) mass concentration and elemental concentrations were carried out weekly. The average mass concentration of (PM(sub)10) in urban and rural areas were 59.2$\pm$36.5$\mu\textrm{g}$/㎥ and 41.4$\pm$23.7$\mu\textrm{g}$/㎥, respectively. To investigate the emission source, the enrichment factors were calculated for the fine and coarse particle fractions at two sites, respectively and these values were classified for anthropogenic and soil origin elements.

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2008년도 춘계학술대회 논문집
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• pp.359-360
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• 2008

• 한국입자에어로졸학회지
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• 제7권2호
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• pp.49-57
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• 2011

서울의 대기오염, 특히 고농도 대기오염 사례는 시민 건강에 매우 부정적일뿐만 아니라, 일반 시민들이 서울시에 대해 느끼는 체감오염도에도 중요한 변수이다. 따라서 이러한 고농도 대기오염 사례의 원인을 규명하는 것은 과학적으로 중요할 뿐만 아니라 사회적으로도 중요한 문제이다. 2005년 7월 22일부터 31일 사이에 고농도 대기오염 사례가 관측되었다. 이 대기오염 사례에 대해 측정소 간의 시계열분석, 에어로졸 성분 분석, 궤적 분석 등의 종합적인 해석을 통해, 대기오염 사례가 국지적인 것이었는지, 외부 영향에 의한 것인지 규명 하였다. 측정 결과를 바탕으로 이 사례를 7월 22~27일(기간 1)과 28~31일(기간 2)의 두 기간으로 구분하였다. 우리나라의 도시대기측정소의 PM10 농도 추이를 분석한 결과, 기간 1에는 춘천의 PM10 농도와 3시간 후에 서울의 PM10 농도가 상관관계가 높았으며, 기간 2에는 중부 지방 전체의 PM10 농도 사이에 상관관계가 높았다. 기간 1에는 풍속이 점차 강해져서 오염물질이 희석되는 경향을 보였으며, 기간 2에는 풍속이 점차 약해져 정체성 특성을 보여 고농도가 계속 유지되었다. 관측한 PM2.5 이온 조성은 기간 1보다는 기간 2에 높았으며, 두 기간 모두, 서울의 평균 농도보다는 매우 높았다. 궤적분석 결과 기간 1에는 시계열 분석 결과와 일치하게, 공기덩어리가 중국에서 북한과 강원도를 거쳐 서울로 이동하였고, 기간 2에는 중국에서 직접 서울로 이동하였다. 현재는 북한의 대기오염물질 배출 정도나 대기오염도에 대한 자료가 부족하여 보다 상세한 분석이 힘들다. 그러나 북한의 영향이 상당할 것으로 보이므로 이에 대한 연구가 필요하다 (Kim et al., 2011). 이 연구 결과는 2005년 7월 하순에 서울에서 발생한 대기오염 에피소드는 외부 영향, 특히 중국 영향에 의한 것임을 보여준다. 그러나 같은 외부 영향이라도 공기의 이동 경로와 풍속에 따라 오염 특성이 달라지는 것을 확인하였다.

• 한국대기환경학회지
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• 제26권6호
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• pp.666-682
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• 2010

The forecasting system for Today's and Tomorrow's PM10 was developed based on the statistical model and the forecasting was performed at 9 AM to predict Today's 24 hour average PM10 concentration and at 5 PM to predict Tomorrow's 24 hour average PM10. The Today's forecasting model was operated based on measured air quality and meteorological data while Tomorrow's model was run by monitored data as well as the meteorological data calculated from the weather forecasting model such as MM5 (Mesoscale Meteorological Model version 5). The observed air quality data at ambient air quality monitoring stations as well as measured and forecasted meteorological data were reviewed to find the relationship with target PM10 concentrations by the regression analysis. The PM concentration, wind speed, precipitation rate, mixing height and dew-point deficit temperature were major variables to determine the level of PM10 and the wind direction at 500 hpa height was also a good indicator to identify the influence of long-range transport from other countries. The neural network, regression model, and decision tree method were used as the forecasting models to predict the class of a comprehensive air quality index and the final forecasting index was determined by the most frequent index among the three model's predicted indexes. The accuracy, false alarm rate, and probability of detection in Tomorrow's model were 72.4%, 0.0%, and 42.9% while those in Today's model were 80.8%, 12.5%, and 77.8%, respectively. The statistical model had the limitation to predict the rapid changing PM10 concentration by long-range transport from the outside of Korea and in this case the chemical transport model would be an alternative method.

• 한국환경과학회지
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• 제21권9호
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• pp.1149-1162
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• 2012

The impact of a considerable increase in traffic volume on the emission and concentrations of air pollutants was investigated at three beaches (Haeundae (HB), Gwanganri (GB), and Songjeong (SB)) in Busan during beach opening period (BOP) in 2011. During the BOP, passenger car was the major vehicle type, followed by taxi, and van. CO was the major contributor of total air pollutant emissions followed by NOx, VOC, and $PM_{10}$. For the temporal variation of the emission of air pollutants during the BOP, it was generally the highest in the afternoon followed by the evening and morning, except for SB. For the spatial variation of their emission, it was the highest at GB followed by SB and HB. The emissions of air pollutants during the BOP were generally higher than those during the Non-BOP, except for HB. In contrast, the significant impact of the traffic volume increase on the concentrations of air pollutants at monitoring sites near the three beaches during the BOP were not found compared to the Non-BOP due to the significant distances between monitoring sites of air pollutants and monitoring sites of traffic volume at the beaches.

• Asian Journal of Atmospheric Environment
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• 제5권4호
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• pp.237-246
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• 2011

To explore the sources of carbonaceous material in the airborne particulate matter (PM), comprehensive PM sampling was performed (3 to 14 January 2010) at a traffic hot spot site (HS), Farm Gate, Dhaka using several samplers: AirMetrics MiniVol (for $PM_{10}$ and $PM_{2.5}$) and MOUDI (for size fractionated submicron PM). Long-term PM data (April 2000 to March 2006 and April 2000 to March 2010 in two size fractions ($PM_{2.2}$ and $PM_{2.2-10}$) obtained from two air quality-monitoring stations, one at Farm Gate (HS) and another at a semi-residential (SR) area (Atomic Energy Centre, Dhaka Campus, (AECD)), respectively were also analyzed. The long-term PM trend shows that fine particulate matter concentrations have decreased over time as a result of government policy interventions even with increasing vehicles on the road. The ratio of $PM_{2.5}/PM_{10}$ showed that the average $PM_{2.5}$ mass was about 78% of the $PM_{10}$ mass. It was also found that about 63% of $PM_{2.5}$ mass is $PM_1$. The total contribution of BC to $PM_{2.5}$ is about 16% and showed a decreasing trend over the years. It was observed that $PM_1$ fractions contained the major amount of carbonaceous materials, which mainly originated from high temperature combustion process in the $PM_{2.5}$. From the IMPROVE TOR protocol carbon fraction analysis, it was observed that emissions from gasoline vehicles contributed to $PM_1$ given the high abundance of EC1 and OC2 and the contribution of diesel to $PM_1$ is minimal as indicated by the low abundance of OC1 and EC2. Source apportionment results also show that vehicular exhaust is the largest contributors to PM in Dhaka. There is also transported $PM_{2.2}$from regional sources. With the increasing economic activities and recent GDP growth, the number of vehicles and brick kilns has significantly increased in and around Dhaka. Further action will be required to further reduce PM-related air pollution in Dhaka.

• 대한원격탐사학회지
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• 제28권4호
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• pp.449-458
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• 2012

본 연구에서는 덕적도와 제주도에서 2005년 10월 15일부터 2007년 10월 24일 까지 9차례에 걸친 집중 관측기간 동안 포집된 PM2.5의 질량 농도 자료와 Moderate-resoultion Imaging Spectroradiometer (MODIS) 인공위성 관측자료로 분석된 대기 에어러솔 광학두께(AOT; Aerosol Optical Thickness) 자료로부터 지역 대기 중 미세 입자의 농도 변화 특성 및 대기질 감시를 위한 인공위성 자료의 활용 가능성을 분석하였다. 전체 관측 기간 중 PM2.5의 일 평균 농도는 덕적도에서는 $25.61{\pm}22.92{\mu}g/m^3$, 제주도에서는 $17.33{\pm}10.79{\mu}g/m^3$으로 변화가 크게 나타났으며, 황사가 발생한 2006년 4월 8일에는 덕적도와 제주도에서 각각 최대값 $188.89{\mu}g/m^3$과 $50.46{\mu}g/m^3$를 기록하였다. 또한 두 지역의 MODIS AOT 값은 $0.79{\pm}0.81$(덕적도), $0.42{\pm}0.24$(제주도)였으며, AOT의 최대값은 PM2.5와 마찬가지로 황사현상이 발생한 2007년 4월 8일에 3.73(덕적도), 1.14(제주도)로 나타났다. 그리고 지상에서 관측된 PM2.5 농도의 공간 분포 양상을 파악하기 위하여 MODIS AOT와 PM2.5의 상관관계 분석결과, 덕적도는 0.85, 고산은 0.06으로서 비교적 에어러솔의 영향을 많이 받는 덕적도가 고산보다 높은 상관계수 값을 나타내었다. 이러한 상관관계를 근거로 하여 도출된 1차 선형회귀 방정식으로부터 MODIS AOT값을 PM2.5로 환산한 결과는 인공위성 자료로부터 대기환경 감시를 가능케 하는 수단이 될 수 있어 유용할 것이다.

• 한국환경과학회지
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• 제24권7호
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• pp.875-882
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• 2015

In 2013, International Agency for Research on Cancer (IARC) concluded that outdoor air pollution is carcinogenic to humans, with the particulate matter component of air pollution most closely associated with sufficient evidence of increased cancer incidence by exposure to particulate matter component of air pollution. Motor vehicles are one of a major emission sources of fine particle ($PM_{2.5}$) in urban areas. A large number of epidemiological studies have reported a positive association of morbidity or mortality with distance from the roadside. We conducted this study to assess the association of $PM_{2.5}$ concentrations measured at roadside hotspots with those at adjacent residential sites using real-time $PM_{2.5}$ monitors. We conducted real-time $PM_{2.5}$ measurements for rush hour periods (08:00~10:00 and 18:00~20:00) at 9 roadside air monitoring Hotspot sites in metropolitan Seoul over 3 weeks from October 1 to 21, 2013. Simultaneous measurements were conducted in residential sites within a 100 m radius from each roadside air monitoring site. A SidePak AM510 was used for the real-time $PM_{2.5}$ measurements. Medians of roadside $PM_{2.5}$ concentrations ranged from $9.8{\mu}g/m^3$ to $38.3{\mu}g/m^3$, while corresponding median values at adjacent residential sites ranged from $4.4{\mu}g/m^3$ to $37.3{\mu}g/m^3$. $PM_{2.5}$ concentrations of residential sites were 0.97 times of hotspot roadside sites. Distributions of $PM_{2.5}$ concentrations in roadside and residential areas were also very similar. Real-time $PM_{2.5}$ concentrations at residential sites, (100 m adjacent), showed similar levels to those at roadside sites. Increasing the distance between roadside and residential sites, if needed, should be considered to protect urban resident populations from $PM_{2.5}$ emitted by traffic related sources.

• 한국환경보건학회지
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• 제47권3호
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• pp.279-291
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• 2021

Objectives: This study investigated the association between air pollutant levels and medical usage rates for environmental disease in a general residential area during the period 2015-2017. Methods: Air pollutant (PM₁₀, PM_2.5, SO₂, NO₂, CO, O₃) data were collected from Air-Korea. Medical usage data on environmental disease (asthma, allergic rhinitis, atopic dermatitis) for the period 2015-2017 in a general residential area in Gyeongsangnam-do Province were provided by the National Health Insurance Corporation. Pearson correlation analysis and multiple regression analysis were conducted to investigate the association between air pollutant levels and medical usage rates (SAS 9.4). In the multiple regression analysis, environmental disease was set as the dependent variable and air pollutants were set as independent variables and analyzed using the General Linear Model. Results: Except for PM_2.5, the average concentration of air pollutants in the surveyed area was below than the air environment standards of Korea. NO₂ was higher than Korea's national average, but CO was similar. The others were lower than the Korea's national average. The daily medical usage rates for environmental disease were 1.38‰ for asthma, 9.90‰ for allergic rhinitis, and 0.32‰ for atopic dermatitis. As a result of correlation analysis, PM₁₀ and SO₂, NO₂ and CO were significantly correlated with asthma, PM₁₀ and NO₂ and CO were correlated with allergic rhinitis, and PM₁₀ and PM_2.5, SO₂, NO₂ and CO were correlated with atopic dermatitis. As a result of multiple regression analysis, PM₁₀ and SO₂ were found to have a higher effect on asthma, PM₁₀ and NO₂ on allergic rhinitis, and SO₂ and NO₂ on atopic dermatitis, compared to other air pollutants. Conclusion: According to these results, air pollutants such as PM₁₀ and SO₂ and NO₂ were associated with the medical usage rates of environmental disease even in relatively low concentrations. Therefore, continuous monitoring will be required for general residential areas.