• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.259-267
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• 2020

This study measured the Particulate Matter (PM) concentration according to altitude (30 m, 60 m, 90 m, 120 m, and 150 m) in three different environments: a construction site, natural environment (arboretum), and residential area. PM_2.5 and PM₁₀ values at 30 m above the construction site were 18.63 ㎍/㎥ and 24.23 ㎍/㎥ while values at 150 m were 10.89 ㎍/㎥ and 10.61 ㎍/㎥, respectively, indicating the average concentration decreased as altitude increased. PM_2.5 and PM₁₀ values at 30 m above the natural environment were 9.03 ㎍/㎥ and 11.21 ㎍/㎥ while those at 150 m were 3.42 ㎍/㎥ and 3.57 ㎍/㎥, respectively, showing lower average concentrations as altitude increased. PM_2.5 and PM₁₀ values at 30 m above the residential area were 10.65 ㎍/㎥ and 12.06 ㎍/㎥ while those at 150 m were 4.24 ㎍/㎥ and 5.17 ㎍/㎥, also demonstrating lower PM concentrations as altitude increased. The PM concentrations decreased as altitude increased at all tested sites and also decreased between environments in the following order: construction site, residential area, and natural environment. The results of this study are significant because PM concentrations were measured at various altitudes at different land-use sites. The results are expected to serve as basic data for decision-making in both regional and urban planning.

• Journal of Forest and Environmental Science
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• v.33 no.2
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• pp.113-121
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• 2017

In flight particulate matter particularly emissions generated by incomplete combustion processes has become a subject of global concern due to the health problems and environmental impacts associated with them. This has compelled most countries to set standards for coarse and fine particles due to their conspicuous impacts on environment and public health. This contribution therefore explores forest fire emissions and how its particulates affects air quality, damage to vegetation, water bodies and biological functions as architects for lung diseases and other degenerative illnesses such as oxidative stress and aging. Soot was collected from simulated forest fire using a clean glass surface and carefully transferred into amber vials for analysis. Volatile components of soot were collected over 10 mL dichloromethane and analyzed using a QTOF Premier-Water Corp Liquid Chromatography hyphenated to a mass selective detector (MSD), and Gas Chromatograph coupled to a mass spectrometer (GC-MS). To characterize the size and surface morphology of soot, a scanning electron microscope (SEM) was used. The characterization of molecular volatiles from simulated forest fire emissions revealed long chain compounds including octadec-9-enoic acid, octadec-6-enoic acid, cyclotetracosane, cyclotetradecane, and a few aromatic hydrocarbons (benzene and naphthalene). Special classes of organics (dibenzo-p-dioxin and 2H-benzopyran) were also detected as minor products. Dibenzo-p-dioxin for instance in chlorinated form is one of the deadliest environmental organic toxins. The average particulate size of emissions using SEM was found to be $11.51{\pm}4.91{\mu}m$. This study has shown that most of the emissions from simulated forest fire fall within $PM_{10}$ particulate size. The molecular by-products of forest fire and particulate emissions may be toxic to both human and natural ecosystems, and are possible precursors for various respiratory ailments and cancers. The burning of a forest by natural disasters or man-made fires results in the destruction of natural habitats and serious air pollution.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.329-352
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• 2022

It is reported that particulate matter(PM) penetrates the lungs and blood vessels and causes various heart diseases and respiratory diseases such as lung cancer. The subway is a means of transportation used by an average of 10 million people a day, and although it is important to create a clean and comfortable environment, the level of particulate matter pollution is shown to be high. It is because the subways run through an underground tunnel and the particulate matter trapped in the tunnel moves to the underground station due to the train wind. The Ministry of Environment and the Seoul Metropolitan Government are making various efforts to reduce PM concentration by establishing measures to improve air quality at underground stations. The smart air quality management system is a system that manages air quality in advance by collecting air quality data, analyzing and predicting the PM concentration. The prediction model of the PM concentration is an important component of this system. Various studies on time series data prediction are being conducted, but in relation to the PM prediction in subway stations, it is limited to statistical or recurrent neural network-based deep learning model researches. Therefore, in this study, we propose four transformer-based models including spatiotemporal transformers. As a result of performing PM concentration prediction experiments in the waiting rooms of subway stations in Seoul, it was confirmed that the performance of the transformer-based models was superior to that of the existing ARIMA, LSTM, and Seq2Seq models. Among the transformer-based models, the performance of the spatiotemporal transformers was the best. The smart air quality management system operated through data-based prediction becomes more effective and energy efficient as the accuracy of PM prediction improves. The results of this study are expected to contribute to the efficient operation of the smart air quality management system.

• Particle and aerosol research
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• v.13 no.2
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• pp.87-95
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• 2017

Radon ($Rn^{222}$) is a radioactive gas and is found at high concentrations underground. Investigations were done in many years specifically on public transportations such as in the subway stations, concourses and platforms for these are located underground areas. This study correlates the $Rn^{222}$ concentrations with the Particulate Matter (PM) concentration for the gas could be attached or trapped inside these particles. It was done on the opening subway tunnel of Miasageori Station going to Mia Station (Line 4) last August 2016. Based on the result, the $Rn^{222}$ were more influenced on the mass ratio (%) of PM present in the air instead of its mass concentration (${\mu}g/m^3$). As the $PM_{10}$ mass ratio increases ($42.32{\pm}1.03%$) during morning rush-hours, radon starts to increase up to $0.97{\pm}0.03pCi/L$. But during the afternoon $Rn^{222}$ concentrations decreased while the composition were stable at $22.96{\pm}3.0%$, $39.04{\pm}0.6%$ and $38.01{\pm}0.3%$ in $PM_1$, $PM_{2.5}$ and $PM_{10}$ respectively. It was then assumed that it could be the composition of the morning hours of the station were influencing the concentration of the radon.

• Korean Journal of Poultry Science
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• v.48 no.1
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• pp.23-30
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• 2021

In this study, we measured the concentration of particulate matter (PM) and ammonia (NH3) emission in the winters according to the breeding type of laying hen houses. Measurements were performed thrice in Barn, Aviary, and Cage houses every 2 weeks from December to January. The changes in the PM10 and PM2.5 concentrations were similar in all three breeding types. The PM10 and PM2.5 concentrations, measured three times, were the highest in the Aviary house. In the results measured by time, the PM10 and PM2.5 concentrations were the lowest during the dark period (22:00 to 4:00) of the day. The NH3 concentration was the highest in the Cage house and the lowest in the Barn house. Regarding emissions over time, the results of the three measurements showed different patterns and differed from those of the PM. In addition, with passage of time from the 1st (december) to 3rd (january), the NH3 concentration gradually increased. The daily PM10 and PM2.5 concentrations in the Aviary house, which were higher than those of the other houses, were 4,787 ㎍/㎥ and 388.6 ㎍/㎥, respectively, while, the PM10 and PM2.5 concentrations outside the poultry houses were 226.0 ㎍/㎥ and 39.3 ㎍/㎥, respectively. The daily NH3 concentration was 7.70 ppm and 9.20 ppm at the center and end of the Cage house, respectively. This was higher than that in the other houses. In conclusion, the concentrations of PM (PM10, PM2.5) and NH3 were the highest in the Aviary and Cage laying hen houses, respectively.

• Journal of Environmental Health Sciences
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• v.36 no.2
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• pp.108-117
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• 2010

In this study, ambient particulate matter ($PM_{2.5}$ and $PM_{10}$) levels were measured and their chemical and physical properties were characterized. Two sites in Gwangju were sampled once a month from December 2008 to November 2009. The annual mean concentrations of $PM_{2.5}$ and $PM_{10}$ were $26.9\;{\mu}g/m^3$ and $46.3\;{\mu}g/m^3$, respectively, in Nongseongdong and $26.1\;{\mu}g/m^3$ and $44.8\;{\mu}g/m^3$, respectively, in Duam-dong. $PM_{2.5}$ levels were 1.8 times higher than the USA Environmental Protection Agency (EPA) national ambient air quality standard for $PM_{2.5}$ ($15\;{\mu}g/m^3$). The average $PM_{2.5}/PM_{10}$ ratio of 0.58 suggested that $PM_{2.5}$ is a significant component of the ambient particle pollution. The order of concentration of metallic elements in $PM_{2.5}$ and $PM_{10}$ was Si > Al > Fe > Zn > Pb > Cu > Mn. Cd was not detected. The earth crustal enrichment factors for Cr, Cu, Pb and Zn in $PM_{2.5}$ were higher than those in $PM_{10}$. When the earth crustal enrichment factors for Cr, Cu, Pb and Zn were higher than 10, this suggested influence from anthropogenic sources. The soil contribution ratios for $PM_{2.5}$ and $PM_{10}$ were 11.3% and 16.4%, respectively, and were higher in the fall and winter. Anions (${SO_4}^{-2}$, ${NO_3}^-$, and $Cl^-$) comprise 28.7% of $PM_{2.5}$ and 21.4% of $PM_{10}$. The correlation coefficient of Zn-Fe, Mn-Cu, Fe-Cu and Fe-Mn in $PM_{2.5}$ was high in the sampling sites, and metallic elements were primarily from anthropogenic sources such as fuel combustion and vehicle emissions.

• Asian Journal of Atmospheric Environment
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• v.9 no.4
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• pp.280-287
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• 2015

The high time-resolution monitoring data are essential to estimate rapid changes in chemical compositions, concentrations, formation mechanisms, and likely sources of atmospheric particulate matter (PM). In this study, $PM_{2.5}$ sulfate, $PM_{2.5}$, $PM_{10}$, and the number concentration of size-resolved PMs were monitored in Fukuoka, Japan by good time-resolved methods during the springtime. The highest monthly average $PM_{2.5}$ sulfate was found in May ($8.85{\mu}g\;m^{-3}$), followed by April ($8.36{\mu}g\;m^{-3}$), March ($8.13{\mu}g\;m^{-3}$), and June ($7.22{\mu}g\;m^{-3}$). The cases exceed the Japanese central government's safety standard for $PM_{2.5}$ ($35{\mu}g\;m^{-3}$) reached 10.11% during four months campaign. The fraction of $PM_{2.5}$ sulfate to $PM_{2.5}$ varied from 12.05% to 68.11% with average value of 35.49% throughout the entire period of monitoring. This high proportion of sulfate in $PM_{2.5}$ is an obvious characteristic of the ambient $PM_{2.5}$ in Fukuoka during the springtime. However, the average fraction of $PM_{2.5}$ sulfate to $PM_{2.5}$ in three rain events occurred during our intensive campaign fell right down to 15.53%. Unusually high $PM_{2.5}$ sulfate (> $30{\mu}g\;m^{-3}$) marked on three days were probably affected by the air parcels coming from the Chinese continent, the natural sulfur in the remote marine atmosphere, and a large number of ships sailing on the nearby sea. The theoretical number concentration of $(NH_4)_2SO_4$ in $PM_{0.5-0.3}$ was originally calculated and then compared to $PM_{2.5}$ sulfate. A close resemblance between the diurnal variations of the theoretically calculated number concentration of $(NH_4)_2SO_4$ in $PM_{0.5-0.3}$ and $PM_{2.5}$ sulfate concentration indicates that the secondary formed $(NH_4)_2SO_4$ was the primary form of sulfate in $PM_{2.5}$ during our monitoring period.

• Journal of Environmental Impact Assessment
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• v.28 no.5
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• pp.440-456
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• 2019

The controversy of the risk perception related to particulate matters becomes significant. Therefore, in order to understand the nature of the particulate matters, we gathered articles and comments in on-line community related to bicycling which is affected by exposure of the particulate matters. As a result, firstly, the government - led particulate matter policy was strengthened and segmented every period, butthe risk perception related to particulate matters in the bicycle community has become active and serious. Second, as a result of analyzing the perception change of outdoor activities related to particulate matters, bicycle users in community showed a tendency of outdoor activity depending on the degree of particulate matters ratherthan the weather. In addition, the level of the risk perception related to particulate matters has been moved from fears of serious threat in daily life and health, combined with the disregard of domestic particulate matter levels or mask performance. Ultimately, these risk perception related to particulate matters have led some of the bicycling that were mainly enjoyed outdoors to the indoor space. However, in comparison with outdoor bicycling enjoyed by various factors such as scenery, people, and weather, the monotonous indoor bicycling was converted into another type of indoor exercise such as fitness and yoga. In summary, it was derived from mistrust of excessive information or policy provided by the government or local governments. It is considered that environmental policy should be implemented after discussion of risk communication that can reduce the gap between public anxiety and concern so as to cope with the risk perception related to particulate matters. Therefore,this study should be provided as an academic basis for the effective communication direction when decision makers establish the policy related to particulate matters.

• Korean Journal of Poultry Science
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• v.48 no.3
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• pp.151-160
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• 2021

This study was conducted to determine the concentrations of particulate matter (PM) and NH3 emissions from different types of laying hens poultry houses during spring. The concentrations of PM and NH3 were measured three times (2-week intervals; March to May) in Floor-pen-, Aviary-, and Cage-type poultry houses. Overall, PM₁₀ and PM_2.5 concentrations were found to be low from 22:00 to 04:00. The PM₁₀ and PM_2.5 concentrations in Floor-pen and Cage houses were similar with no significant daily deviation. NH₃ concentrations measured over 24 h at the center and end of Floor-pen house were relatively constant. Irrespective of measurement location, NH₃ concentrations were the lowest in Floor-pen house. Moreover, NH₃ concentrations were higher at the end of Floor-pen and Aviary houses than that at the center; however, lower concentrations of NH₃ were detected at the end of Cage house. The concentrations of PM₁₀ and PM_2.5 around the poultry houses were 57.5 and 34.0 ㎍/m³, respectively, with the daily average PM₁₀ and PM_2.5 concentrations (4,730 and 447.7 ㎍/m³, respective) being the highest in Aviary house. The concentrations of NH₃ at the center and end of Cage house were the highest at 12.0 and 9.31 ppm, respectively. Furthermore, in Cage house, the emission factor of NH₃ was the lowest, whereas there was no significant difference on that of NH₃. In conclusion, among the three types of poultry houses assessed, PM (PM₁₀, PM_2.5) concentrations were higher in Aviary house, whereas NH3 concentrations were higher in Cage house.

• Journal of Environmental Health Sciences
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• v.39 no.2
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• pp.144-150
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• 2013

Objectives: Cooking activity in indoor environments can generate particulate matter. The objective of this study was to determine the concentrations of ultrafine particles (UFP), $PM_{2.5}$, and $PM_{10}$ in cooking and non-cooking areas of major department stores in Seoul. Methods: Eighteen department stores in Seoul, Korea were measured for concentrations of particulate matter. Using real-time monitors, concentrations of UFP, $PM_{2.5}$ and $PM_{10}$ were simultaneously measured in cooking and non-cooking areas on the floor with a food court and a non-cooking floor. Results: The concentrations of UFP, $PM_{2.5}$ and $PM_{10}$ were significantly higher in cooking areas than in noncooking areas and non-cooking floors (p<0.05). UFP and $PM_{2.5}$ were significantly correlated in cooking areas and non-cooking areas but not in non-cooking floors. $PM_{2.5}$ were consisted of approximately 81% in $PM_{10}$ and highly correlated with $PM_{10}$ in all places. Conclusion: A higher correlation between UFP and $PM_{2.5}$ was shown on cooking floor than on non-cooking floor in department stores. High levels of fine particles were caused by cooking activities at food courts. The further management of PM is needed to improve the indoor PM levels at food courts in department stores.