• 한국입자에어로졸학회지
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• 제19권4호
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• pp.111-128
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• 2023

Chungcheongnam-do has various emission sources, including large-scale facilities such as power plants, steel and petrochemical industry complexes, which can lead to the severe PM pollution. Here, we measured concentrations of PM₁₀, PM_2.5, and its metallic elements at a suburban site in Taean, Chungcheongnam-do from September 2017 to June 2022. During the measurement period, the average concentrations of PM₁₀ and PM_2.5 were 58.6 ㎍/m³ (9.6~379.0 ㎍/m³) and 35.0 ㎍/m³ (6.1~132.2 ㎍/m³), respectively. The concentration of PM₁₀ and PM_2.5 showed typical seasonal variation, with higher concentration in winter and lower concentration in summer. When high concentrations of PM_2.5 occurred, particulary in winter, the fraction of Zn and Pb components considerably increased, indicating a significant contribution of Zn and Pb to high-PM_2.5 concentration. In addition, Zn and Pb exhibited the highest correlation coefficient among all other metallic elements of PM_2.5. A backward trajectory cluster analysis and CPF model were performed to examine the origin of PM_2.5. The high concentration of PM_2.5 was primarily influenced by emissions from industrial complexes located in the northeast and northwest areas.

• 지적과 국토정보
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• 제51권2호
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• pp.141-150
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• 2021

미세먼지는 사람의 건강에 많은 영향을 미치는 물질로서 이와 관련하여 다양한 연구가 이루어지고 있다. 미세먼지의 인체 영향으로 인해 서울시 모니터링 네트워크에서 측정된 과거 데이터를 활용하여 미세먼지를 예측하려는 다양한 연구가 진행되고 있다. 본 연구는 2019년 5월 서울시의 미세먼지를 중점으로 진행하였으며, 학습에 사용한 변수는 SO₂, CO, NO₂, O₃와 같은 대기오염물질 데이터를 활용하였다. 예측모델은 Adaboost에 기반하여 구축하였고, 훈련모델은 PM₁₀과 PM_2.5로 구분하였다. 에러 메트릭스를 통한 예측모델의 정확도 평가 결과로 Adaboost가 시도되었다. 대기오염물질은 초미세먼지와 더 높은 상관성을 보이는 것으로 나타났지만, 보다 효과적인 분포등급을 제시하기 위해서는 많은 양의 데이터를 학습하고, PM₁₀과 PM_2.5의 공간분포 등급을 효과적으로 예측하기 위해서 교통량 등의 추가적인 변수를 활용할 필요성이 있다고 판단된다.

• 한국환경보건학회지
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• 제46권3호
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• pp.276-284
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• 2020

Objectives: This study was conducted to identify the effects of PM₁₀ and PM_2.5 on hospital visits in the Incheon area over the period of 2016-2018. Methods: We applied correlation analysis and Poisson regression to perform the analysis using cardiovascular disease and respiratory disease data from the National Health Insurance Service and the daily average PM₁₀ and PM_2.5 from the Korea Environment Corporation adjusting for time lag. Results: When the daily average PM₁₀ concentration increased by 10 ㎍/㎥, the number of cardiovascular disease patients were 1.002 times higher (95% CI [Confidence Interval]; 1.000-1004) in Ganghwa County. As the daily average PM_2.5 concentration increased by 10 ㎍/㎥, the number of cardiovascular disease patients were 1.012 times higher (95% CI; 1.008-1.016) in Ganghwa County. As the daily average PM₁₀ concentration increased by 10 ㎍/㎥, the respiratory disease patients were 1.003 times (95% CI; 1.002-1.004) higher in Gyeyang and Michuhol Counties. As the PM_2.5 concentration increased by 10 ㎍/㎥, the respiratory disease patients were 1.003 times higher (95% CI; 1.002-1.005) in Bupyeong County. Conclusions: In some parts of the Incheon area there was a correlation between the number of patients with respiratory and cardiovascular conditions and the concentration of PM₁₀ and PM_2.5.

• 한국환경과학회지
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• 제31권12호
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• pp.1079-1087
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• 2022

This study investigated the effect of volcanic materials that erupted from the Nishinoshima volcano, Japan, 1,300 km southeast of the Busan area at the end of July 2020, on the fine particle concentration in the Busan area. Backward trajectory analysis from the HYSPLIT model showed that the air parcel from the Nishinoshima volcano turned clockwise along the edge of the North Pacific high pressure and reached the Busan area. From August 4 to August 5, 2020, the concentration of PM₁₀ and PM_2.5 in Busan started to increase rapidly from 1000 LST on August 4, and showed a high concentration for approximately 13 hours until 2400 LST. The PM_2.5/PM₁₀ ratio showed a relatively high value of 0.7 or more, and the SO₂ concentration also showed a high value at the time when the PM₁₀ and PM_2.5 concentrations were relatively high. The SO₄^2- concentration in PM_2.5 in Busan showed a similar trend to the change in PM₁₀ and PM_2.5 concentrations. It rose sharply from 1300 LST on August 4, at the time where it was expected to have been affected by the Nishinoshima Volcano. This study has shown that the occurrence of high concentration fine particle in Busan in summer has the potential to affect Korea not only due to anthropogenic factors but also from natural causes such as volcanic eruptions in Japan.

• 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.

• 한국환경과학회지
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• 제24권6호
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• pp.777-784
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• 2015

This study investigates weekday/weekend characteristics of $PM_{10}$ and $PM_{2.5}$ concentration and metallic elements in Busan in the springtime of 2013. $PM_{10}$ concentration on weekday/weekend were 77.54 and $67.28{\mu}g/m^3$, respectively. And $PM_{2.5}$ concentration on weekday/weekend were 57.81 and $43.83{\mu}g/m^3$, respectively. Also, $PM_{2.5}/PM_{10}$ concentration ratio on weekdays/weekend was 0.75 and 0.65, respectively. The contribution rates of Na to total metallic elements in $PM_{10}$ on weekday/weekend were 38.3% and 38.9%, respectively. It would be useful in control effectively with management of urban fine particle to understand characteristics of fine particle concentration on weekday/weekend.

• 한국환경과학회지
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• 제29권5호
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• pp.495-506
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• 2020

This study investigated the nitrate formation process, and mass closure of Particulate Matter (PM) were calculated over the urbanized area of Jeju Island. The data for eight water-soluble inorganic ions and nineteen elements in PM_2.5 and PM₁₀ were used. The results show that the nitrate concentration increased as excess ammonium increased in ammonium-rich samples. Furthermore, nitrate formation was not as important in ammonium-poor samples as it was in previous studies. According to the sum of the measured species, approximately 45~53% of gravimetric mass of PM remained unidentified. To calculate the mass closure for both PM_2.5 and PM₁₀, PM chemical components were categorized into secondary inorganic aerosol, crustal matter, sea salt, trace matter and unidentified matter. The results by the mass reconstruction of PM components show that the portion of unidentified matter was decreased from 52.7% to 44.0% in PM_2.5 and from 45.1% to 29.1% in PM₁₀, despite the exclusion of organic matter and elemental carbon.

• 한국산업보건학회지
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• 제31권4호
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• pp.331-341
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• 2021

Objectives: The aim of this study was to evaluate the concentrations and relationships of coarse particles with a diameter of 10 ㎛ (PM₁₀) with endotoxins according to the time of measurement in windowless poultry houses. Methods: In this study, measurement was performed on ten windowless poultry houses with a vertically integrated system from July to November. PM₁₀ was measured using personal environmental monitors and polytetrafluoroethylene (PTFE) filters with a 4 L/min-calibrated pump in selected sampling locations (two near the door and two near an exhaust fan). The endotoxin on PTFE filter was analyzed by the LAL turbidimetric method. Results: The range of geometric mean concentrations of PM₁₀ and endotoxins for each of the 38 samples were 0.12-3.30 mg/m³ and 11.9-3553.66 EU/m³, respectively. PM₁₀ and endotoxin concentrations varied by farm, increasing with the decrease in ventilation. The range of the coefficient of determination between PM₁₀ and endotoxin was 0.0009-0.9249. As the atmospheric temperature decreased, it was confirmed that the concentrations of PM₁₀ and endotoxin increased because the volume of ventilation was decreased. Conclusions: Endotoxins were more affected by time of measurement and ventilation than PM₁₀, which means that endotoxins could be an important indicator for intervention programs for improvement of indoor environments.

• 한국조경학회:학술대회논문집
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• 한국조경학회 2020년도 춘계학술대회 논문집
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• pp.96-96
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• 2020

• Communications for Statistical Applications and Methods
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• 제30권3호
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• pp.259-272
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• 2023

In this paper, we suggest a new method for the prediction of sharp changes in particulate matter (PM₁₀) using quantile mapping. To predict the current PM₁₀ density in Seoul, we consider PM₁₀ and precipitation in Baengnyeong and Ganghwa monitoring stations observed a few hours before. For the PM₁₀ distribution estimation, we use the extreme value mixture model, which is a combination of conventional probability distributions and the generalized Pareto distribution. Furthermore, we also consider a quantile generalized additive model (QGAM) for the relationship modeling between precipitation and PM₁₀. To prove the validity of our proposed model, we conducted a simulation study and showed that the proposed method gives lower mean absolute differences. Real data analysis shows that the proposed method could give a more accurate prediction when there are sharp changes in PM₁₀ in Seoul.