• 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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• 제23권12호
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• pp.1963-1970
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• 2014

Ambient particulate matters($PM_{10}$ and $PM_{2.5}$) were investigated at GNTECH university in Jinju city. Samples were collected using a dichotomous sampler(series 240, Andersen Corp.) and a TEOM(Tapered Element Oscillating Microbalance) monitor period from November 2012 to October 2013. For the dichotomous sampler measurements, daily 24-h integrated $PM_{2.5}$ and $PM_{10-2.5}$ ambient air samples were collected at a total flow rate of 16.7 L /min. For the TEOM monitor measurements, daily 1-h integrated $PM_{10}$ ambient air samples were collected at a flow rate of 16.7 L /min. The annual average concentrations of $PM_{10-2.5}$ and $PM_{2.5}$ by a dichotomous sampler were $10.0{\pm}6.1{\mu}g/m^3$ and $22.6{\pm}9.3{\mu}g/m^3$, respectively. And $PM_{10}$ concentration by dichotomous sampler were similar to TEOM monitor by $32.7{\pm}12.9{\mu}g/m^3$ and $31.7{\pm}11.3{\mu}g/m^3$, respectively. And good correlation ($R^2=0.964$) between the two methods was observed. The annual average of $PM_{2.5}/PM_{10}$ ratio was $0.70{\pm}0.12$.

• 한국환경보건학회지
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• 제43권1호
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• pp.71-76
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• 2017

Objectives: This study aimed to assess the environmental factors that affect particulate matters (PM10) and to compare with outdoor PM10 concentrations in an underground subway stations. Methods: The PM10 level was determined from May 2013 to September 2013 in the Seoul subway stations in four lines. PM mini-vol portable sampler sampler was used to collect PM10 for 6 hrs. Arithmetic means of PM10 concentrations with standard deviation (SD) were calculated. Paired t-test was used to compare the differences between indoor PM10 and outdoor PM10 concentrations with correlation analysis which was used to identify the association between indoor PM10 concentrations and environmental factors. Results: There were no different PM10 concentrations significantly between line 1, 2, 3 and 4 in an underground subway stations. Passenger number was positively associated with PM10 concentration while construction year was negatively associated with PM10 concentrations. Indoor PM10 concentrations were significantly higher than those in outdoor PM10 concentrations. PM10 concentrations were higher in the stations which were constructed before 1990s rather than the stations constructed after 1990s. Conclusion: PM10 levels in the underground subway stations varied greatly depending on the construction year. Therefore, it might need to be more careful management to the stations which constructed in before 1990s.

• Journal of Applied Biological Chemistry
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• 제63권2호
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• pp.161-168
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• 2020

식물 종마다 잎에 미세먼지(PM)를 흡착하는 정도가 서로 다르며 잎을 통해 PM을 흡수할 수 있는 것으로 알려져 있다. PM에 포함된 중금속은 인체 및 식물에 영향을 미칠 수 있으며 입자 크기에 따라 미치는 영향이 다를 수 있다. 따라서 충북대학교 내 도로변에 위치한 회양목 (Buxus koreana), 주목 (Taxus cuspidate), 철쭉 (Rhododendron yedoense), 이팝나무 (Chionanthus retusa)와 같은 가로수 잎에 축적된 PM을 입자 크기(PM_>10 및 PM_2.5-10)에 따라 분획 및 정량화하였다. 잎에 축적된 크기 별 PM의 금속 농도는 유도 결합 플라스마 질량 분석법(ICP-MS)으로 분석하였다. 나무 잎 표면에 축적된 PM_>10의 질량은 6.11-32.7 ㎍/㎠, PM_2.5-10의 질량은 0-14.8 ㎍/㎠이었다. 잎 표면에 홈이 있고 털을 갖고 있는 철쭉이 작은 PM 입자를 잘 유지하고 있었으며 광택이 있는 잎 표면을 가진 주목과 회양목은 많은 PM을 축적하고 있었다. PM은 Al, Ca, Mg, Fe와 같은 지각 구성 원소와 Cu, Pb, Zn와 같은 중금속을 포함하고 있었다. 지각 구성 원소의 농도는 PM_>10 입자에서 더 높았고, 중금속 농도는 PM_2.5-10 입자에서 상대적으로 더 높았다. 잎에 흡수된 Mn, Cd, Cu, Ni, Pb, Zn과 PM_2.5-10의 중금속 농도는 유의한 상관관계를 보여 나무 잎을 통해 PM이 흡수될 수 있음을 확인하였다.

• 인간식물환경학회지
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• 제23권6호
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• pp.647-654
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• 2020

Background and objective: Particulate matter (PM) is one of the serious environmental problems and threatens human health. Plants can clean the air by removing PM from the atmosphere. This study was carried out to investigate the PM removal efficiency of 12 species of woody plants. Methods: Actinidia arguta, Dendropanax morbiferus, Fraxinus rhynchophylla, Parthenocissus tricuspidata, Pittosporum tobira, Rhaphiolepis indica, Rhapis, Salix integra, Salix koreensis, Schisandra chinensis, Viburnum odoratissimum var. awabuki, and Vitis coignetiae were used as plant material. Six 15 cm (D) pots were placed in an acrylic chamber of 800 (D) × 800 (W) × 1000 (H) mm. The LED panel was used as a light source. The reduction of PM10, PM2.5, and PM1 for 300 minutes after the injection of PM was automatically measured. Results: The leaf area and the amount of PM in the chamber showed a negative correlation. 12 species of plants were compared by dividing the plants into 3 groups according to their characteristics: vines, trees, and shrubs and small trees. In the vine plant group, the averages of PM10, PM2.5, and PM1 were 7.917%, 8.796%, and 30.275%, respectively. In the shrubs and small trees group, the average of PM10, PM2.5, and PM1 were 10.142%, 11.133%, and 36.448%, respectively. In the trees group, the average of PM10, PM2.5, and PM1 were 11.475%, 12.892%, and 40.421%, respectively. When the initial concentration was 100%, PM10, PM2.5, and PM1 of Viburnum odoratissimum var. awabuki with the largest leaf area were 5.6%, 6.3%, and 21.0% after 5 hours, respectively, the best results among 12 species of plants. Conclusion: The vine plant group was more effective in removing PM than the other two groups. In the tree groups, the fact that the leaf development was relatively inactive at a plant height of 30 cm was considered to have an effect on the removal of particulate matter.

• Communications for Statistical Applications and Methods
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• 제25권2호
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• pp.199-215
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• 2018

Interest in $PM_{10}$ concentrations have increased greatly in Korea due to recent increases in air pollution levels. Therefore, we consider a forecasting model for next day $PM_{10}$ concentration based on the principal elements of air pollution, weather information and Beijing $PM_{2.5}$. If we can forecast the next day $PM_{10}$ concentration level accurately, we believe that this forecasting can be useful for policy makers and public. This paper is intended to help forecast a daily mean $PM_{10}$, a daily max $PM_{10}$ and four stages of $PM_{10}$ provided by the Ministry of Environment using various data mining techniques. We use seven models to forecast the daily $PM_{10}$, which include five regression models (linear regression, Randomforest, gradient boosting, support vector machine, neural network), and two time series models (ARIMA, ARFIMA). As a result, the linear regression model performs the best in the $PM_{10}$ concentration forecast and the linear regression and Randomforest model performs the best in the $PM_{10}$ class forecast. The results also indicate that the $PM_{10}$ in Seoul is influenced by Beijing $PM_{2.5}$ and air pollution from power stations in the west coast.

• 한국안전학회지
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• 제32권5호
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• pp.157-167
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• 2017

Millions of People die every year from diseases caused by exposure to outdoor air pollution. Especially, one of the most severe types of air pollution is fine particulate matter (PM10, PM2.5). South Korea also has been suffered from severe PM. This paper analyzes regional risks induced by PM10 and PM2.5 that have affected domestic area of Korea during 2014~2016.3Q. We investigated daily maxima of PM10 and PM2.5 data observed on 284 stations in South Korea, and found extremely high outlier. We employed extreme value distributions to fit the PM10 and PM2.5 data, but a single distribution did not fit the data well. For theses reasons, we implemented extreme mixture models such as the generalized Pareto distribution(GPD) with the normal, the gamma, the Weibull and the log-normal, respectively. Next, we divided the whole area into 16 regions and analyzed characteristics of PM risks by developing the FN-curves. Finally, we estimated 1-month, 1-quater, half year, 1-year and 3-years period return levels, respectively. The severity rankings of PM10 and PM2.5 concentration turned out to be different from region to region. The capital area revealed the worst PM risk in all seasons. The reason for high PM risk even in the yellow dust free season (Jun. ~ Sep.) can be inferred from the concentration of factories in this area. Gwangju showed the highest return level of PM2.5, even if the return level of PM10 was relatively low. This phenomenon implies that we should investigate chemical mechanisms for making PM2.5 in the vicinity of Gwangju area. On the other hand, Gyeongbuk and Ulsan exposed relatively high PM10 risk and low PM2.5 risk. This indicates that the management policy of PM risk in the west side should be different from that in the east side. The results of this research may provide insights for managing regional risks induced by PM10 and PM2.5 in South Korea.

• 한방안이비인후피부과학회지
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• 제31권3호
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• pp.1-11
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• 2018

Objectives : The purpose of this study is to analyze the correlation between fine dust(PM10.5, PM2.5) and the number of acute/chronic sinusitis patients. Methods : A simple regression analysis was performed based on the concentration of PM10 and PM2.5 as independent variables and the number of acute/chronic sinusitis patients as dependent variables. Results : As a result of simple regression analysis, if PM10 increases by $1{\mu}g/m^3$, the number of acute sinusitis patients increases by 7,000.291(P<.001, 95%CI :4,951.983-9,048.600). If PM2.5 increases by $1{\mu}g/m^3$, the number of acute sinusitis patients increases by 17,524.476.(P<.001, 95%CI:9,728.725-25,320.228) In addition, PM10 increases by $1{\mu}g/m^3$, the number of acute sinusitis patients increases by 3,163.471 (P<.001, 95% CI:2,268.642-4,058.301). If PM2.5 increases by $1{\mu}g/m^3$, the number of chronic sinusitis patients increases by 8,651.644.(P<.001, 95%CI:5,115.697-12,187.592) Conclusions : Both PM10 and PM2.5 are correlated with changes in the number of sinusitis patients. PM2.5 has effect on the number of patients than PM10. PM10 is the highest correlation in their 50s, PM2.5 in their 60s and 70s.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.128-135
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• 2022

Because construction work is conducted outdoors, construction workers are affected by harmful environmental factor. Especially, Particulate Matter (PM₁₀) is one of the harmful environmental factors with a diameter of 10㎍/m³ or less. When PM₁₀ is inhaled by human, it can cause fatal impact on the human. Contrary to the various analyses of health impact on PM₁₀, the research on the relationship between construction accidents and PM₁₀ are few. Therefore, this study aims to conduct the relative frequency analysis which find out the correlation between construction accidents and PM₁₀, and the modified PM₁₀ grade is suggested to expect accidents probability caused by PM₁₀ in the construction industry. This study is conducted by four steps. i) Establishment of the database; ii) Classification of data; iii) Analysis of the Relative Frequency of accidents in the construction industry by PM₁₀ concentration; iv) Modified PM₁₀ groups to classify the impact of PM₁₀ on accident. In terms of frequency analysis, the most accidents were occurred in the average concentration of PM₁₀ (32㎍/m³). However, we found that the relative frequency of accident was increased as the concentration of PM₁₀ increased. This means the higher PM₁₀ concentration can cause more accidents during construction. In addition, PM₁₀ concentration was divided as 6 groups by the WHO, but the modified PM₁₀ grade by the relative frequency on accident was suggested as 3 groups.

• 자원ㆍ환경경제연구
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• 제12권3호
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• pp.469-485
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• 2003

본 연구는 최근 선진국에서 기존의 미세먼지 규제대상인 PM10의 대안으로서 부각되고 있는 PM2.5의 국내 실측자료를 대상으로 미세먼지의 호흡기질환 영향을 투입반응함수를 통해 추정한 것이다. 총 3차에 걸친 110여 일의 조사기간 동안 일별 PM10, PM2.5, 온도, 습도 등을 측정하였으며, 동시에 해당 지역에 거주하는 80여명의 노인들을 대상으로 일별 역학조사 및 설문조사를 통한 각종 호흡기질환 여부를 확인하였다. 미세먼지에 따른 호흡기 반응을 나타내는 최대호기유속량(PEFR)에 대한 투입반응함수 추정 결과 미세먼지인 PM2.5에 대한 계수는 음의 값을 갖는 것으로 추정되어 미세먼지의 증가는 호흡기능의 저하를 통해 호흡기질환을 유발할 수 있는 것으로 확인되었다. 또한 10여 가지 항목에 대한 호흡기질환 증세 유무를 대상으로 이산적 선택모형인 probit모형 추정 결과 PM10은 유의한 추정치를 보이지 않은 반면, PM2.5의 증가는 각종 호흡기질환의 증가를 가져오는 것으로 추정되었다. 이는 PM2.5가 정부의 대기정책에 있어 보다 바람직한 미세먼지 규제대상이 될 수 있음을 시사하는 것이다.