• Journal of Environmental Science International
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• v.24 no.6
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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.

• Journal of Environmental Science International
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• v.23 no.12
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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 $0.70{\pm}0.12$.

• Journal of Environmental Health Sciences
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• v.43 no.1
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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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• v.63 no.2
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• pp.161-168
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• 2020

It is known that different plant species have ability to deposit different amounts of particulate matter (PM) on their leaves and plants can absorb heavy metals in PM through their leaves. Heavy metals in PM can have toxic effect on human body and plants. Therefore, PM on different roadside trees at Chungbuk national University including box tree (Buxus koreana), yew (Taxus cuspidate), royal azalea (Rhododendron yedoense), and retusa fringetree (Chionanthus retusa) was quantified based on particle size (PM_>10 and PM_2.5-10). The metal concentration in PM accumulated on leaves was analyzed using inductively coupled plasma-mass spectroscopy. In this study, the mass of PM_>10 deposited on the surface of the tree leaves ranged from 6.11 to 32.7 ㎍/㎠, while the mass of PM_2.5-10 ranged from 0 to 14.8 ㎍/㎠. The royal azaleas with grooves and hair on the leaf surface retained PM particles for longer time, while the yews and box trees with wax on leaf surfaces accumulated more PM. The PM contained elements in crustal material such as Al, Ca, Mg, and Fe and heavy metals including Cu, Pb and Zn. The concentration of elements in crustal material was higher in the coarser size, while heavy metal concentration was relatively higher in the finer size fraction. The Mn, Cd, Cu, Ni, Pb, and Zn concentrations of leaves and PM_2.5-10 were significantly correlated indicating that PM was taken up through tree leaves.

• Journal of People, Plants, and Environment
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• v.23 no.6
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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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• v.25 no.2
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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.

• Journal of the Korean Society of Safety
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• v.32 no.5
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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.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.31 no.3
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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.

• International conference on construction engineering and project management
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• 2022.06a
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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.

• Environmental and Resource Economics Review
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• v.12 no.3
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• pp.469-485
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• 2003

This paper reports on the results of epidemiological investigation of daily health effects in the elderly associated with daily exposure to particulate matters in Korea. Our main focus is on the potential difference in health effects between PM10 and PM2.5. While the Korean environmental authority has set an ambient standard for PM10, the government currently does not monitor PM2.5, which has no national standard. A daily data on respiratory symptoms as well as PM concentrations are collected for a total of 120 days. Using a probit model, we find statistically significant negative health effects of PM2.5 on respiratory symptoms among the nonsmoking elderly, while PM10 does not show such effects from the estimation. This result suggests that, for air quality regulatory purposes, PM2.5 can be a more appropriate air pollutant than PM10.