• Particle and aerosol research
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• v.9 no.2
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• pp.69-78
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• 2013

In this study, the atmospheric aerosol concentration measured at different relative humidity levels was analyzed. Using an optical particle counter, PM10 and PM2.5 concentration as well as particle size distribution were measured and the relation between these size resolved data and relative humidity was studied. The results showed that mass concentration increases as relative humidity increases. The comparison between PM1, PM2.5 and PM10 showed that the fine particles grow more than coarse particles as relative humidity increases. The results also showed that PM10-2.5 and relative humidity do not show close correlation, which means that the mass increase of PM10 at high relative humidity is mainly due to the growth of PM2.5.

• Asian Journal of Atmospheric Environment
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• v.6 no.1
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• pp.1-13
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• 2012

To identify the primary factor affected the decreased $PM_{10}$ concentration in Seoul which is the capital city of Korea, wind speed and emissions in 2003 and 2004 were analyzed. The level of air pollution is intense in Seoul and continually increased since the late 1990s. However the concentration of $PM_{10}$ has been greatly declined recently. In particular, the concentration of $PM_{10}$ decreased 14% in 2003 and 2004 excluding the Asian dust periods. It is suggested that the major factors for the decrease are differences in wind speed between the two years and the period of constant breeze. In 2003, intense Asian dust events happened frequently and it increased the concentration of total $PM_{10}$. The intense dust events were influence by the speed and duration of the wind. It is considered that the meteorological condition was the primary drive for the change of the concentration of $PM_{10}$. The decreased emissions seem to be the additional factor for the change in the concentration of $PM_{10}$.

• Journal of Environmental Science International
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• v.26 no.6
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• pp.751-765
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• 2017

This research investigates the characteristics of meteorological variation and fine particles ($PM_{10}$ and $PM_{2.5}$) for case related to the haze occurrence (Asian dust, long range transport, stationary) in Busan. Haze occurrence day was 559 days for 20 years (from 1996 to 2015), haze occurrence frequency was 82 days (14.7%) in March, followed by 67 days (12.0%) in February and 56 days (10.0%) in May. Asian dust occurred most frequently in spring and least in winter, whereas haze occurrence frequency was 31.5% in spring, 29.7% in winter, 21.1% in fall, and 17.7% in summer. $PM_{10}$ concentration was highest in the occurrence of Asian dust, followed by haze and haze + mist, whereas $PM_{2.5}$ concentration was highest in the occurrence of haze. These results indicate that understanding the relation between meteorological phenomena and fine particle concentration can provide insight into establishing a strategy to control urban air quality.

• Journal of Environmental Impact Assessment
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• v.12 no.2
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• pp.99-108
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• 2003

We collected and analyzed PM10 samples to account for the characteristics of heavy metallic elements for yellow sand and non-yellow sand during springtime of 2002 at Busan, The mean PM10 mass concentration for springtime of 2002 was $219.82{\mu}g/m^3$ with the maximum $787.50{\mu}g/m^3$ and the minimum $19.44{\mu}g/m^3$. The mean concentration of metallic elements contained in PM10 are shown as follows : Si>Ca>Fe>Al>Na, respectively. The ratio of mean PM10 mass concentration for yellow sand($362.7{\mu}g/m^3$) to that for non-yellow sand($48.3{\mu}g/m^3$) was 7.5, the significant positive correlation (P<0.05) was found between yellow sand and non-yellow sand. The metallic elements concentration ratios of yellow sand to the non-yellow sand were over 10 times for Al, Ca, Mg, 4~8 times for Fe, Si, Mn. But the concentration of Na, Cu, Zn for non-yellow sand was higher than those of yellow sand. The crustal enrichment factor of Cd, Cu, Pb, Zn, Cr, K, Mn, Na, Ni for yellow sand was higher that of non-yellow sand over 10 times, and concentration rate of soil particles of yellow sand was increased 2.3 times that of nonyellow sand.

• Journal of Environmental Health Sciences
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• v.45 no.2
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• pp.186-191
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• 2019

Objectives: Subway is one of the most common transportation modes in Seoul, Korea. The objectives of this study were to determine characteristics of in-cabin $PM_{2.5}$ concentration in Seoul Metro Line Number 2 and to identify factors of the $PM_{2.5}$ concentration. Methods: In-cabin $PM_{2.5}$ concentrations in Seoul Metro Line Number 2 were measured using real-time monitors and the factors affecting $PM_{2.5}$ concentration in cabin were observed. Linear regression analysis of in-cabin $PM_{2.5}$ concentration and indoor/outdoor (I/O) ratio were performed. Results: In-cabin $PM_{2.5}$ concentration was associated with the in-cabin $PM_{2.5}$ concentration in previous station. In-cabin $PM_{2.5}$ concentration was correlated with ambient $PM_{2.5}$ concentration and associated with underground station with control of the in-cabin $PM_{2.5}$ concentration in previous station. I/O ratio increased as the number of passengers increased and when passing through the underground station with control of I/O ratio in previous station. Conclusion: In-cabin $PM_{2.5}$ concentration was affected by ambient $PM_{2.5}$ concentration. Therefore, management of in-cabin $PM_{2.5}$ concentrations should be based on outdoor air quality.

• Journal of Environmental Science International
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• v.21 no.2
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• pp.217-231
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• 2012

Hourly concentrations of $PM_1$, $PM_{2.5}$ and $PM_{10}$, were investigated at Gangneung city in the Korean east coast on 0000LST October 26~1800LST October 29, 2003. Before the intrusion of Yellow dust from Gobi Desert, $PM_{10}$($PM_{2.5}$, $PM_1$) concentration was generally low, more or less than 20 (10, 5) ${\mu}g/m^3$, and higher PM concentration was found at 0900LST at the beginning time of office hour and their maximum ones at 1700LST around its ending time. As correlation coefficient of $PM_{10}$ and $PM_{2.5}$($PM_{2.5}$ and $PM_1$, and $PM_{10}$ and $PM_1$) was very high with 0.90(0.99, 0.84), and fractional ratios of $(PM_{10}-PM_{2.5})/PM_{2.5}((PM_{2.5}-PM_1)/PM_1)$ were 1.37~3.39(0.23~0.54), respectively. It implied that local $PM_{10}$ concentration could be greatly affected by particulate matters of sizes larger than $2.5{\mu}m$, and $PM_{2.5}$ concentration could be by particulate matters of sizes smaller than $2.5{\mu}m$. During the dust intrusion, maximum concentration of $PM_{10}$($PM_{2.5}$, $PM_1$) reached 154.57(93.19, 76.05) ${\mu}g/m^3$ with 3.8(3.4, 14.1) times higher concentration than before the dust intrusion. As correlation coefficient of $PM_{10}$ and $PM_{2.5}$(vice verse, $PM_{2.5}$, $PM_1$) was almost perfect high with 0.98(1.00, 0.97) and fractional ratios of $(PM_{10}-PM_{2.5})/PM_{2.5}((PM_{2.5}-PM_1)/PM_1)$ were 0.48~1.25(0.16~0.37), local $PM_{10}$ concentration could be major affected by particulates smaller than both $2.5{\mu}m$ and $1{\mu}m$ (fine particulate), opposite to ones before the dust intrusion. After the ending of dust intrusion, as its coefficient of 0.23(0.81, - 0.36) was very low, except the case of $PM_{2.5}$ and $PM_1$ and $(PM_{10}-PM_{2.5})/PM_{2.5}((PM_{2.5}-PM_1)/PM_1)$ were 1.13~1.91(0.29~1.90), concentrations of coarse particulates larger than $2.5{\mu}m$ greatly contributed to $PM_{10}$ concentration, again. For a whole period, as the correlation coefficients of $PM_{10}$, $PM_{2.5}$, $PM_1$ were very high with 0.94, 1.00 and 0.92, reliable regression equations among PM concentrations were suggested.

• Journal of Environmental Science International
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• v.31 no.12
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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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.517-523
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• 2019

PM₁₀ concentration is a spatiotemporal phenomenta and capturing data for such continuous phenomena is a difficult task. This study designed a model that enhances spatiotemporal resolution of PM₁₀ concentration levels using satellite imagery, atmospheric and meteorological sensor data, and multiple deep learning models. The designed deep learning model was trained using input data whose factors may affect concentration of PM₁₀ such as meteorological conditions and land-use. Using this model, PM₁₀ images having 15 minute temporal resolution and 30m×30m spatial resolution were produced with only atmospheric and meteorological data.

• Journal of Environmental Health Sciences
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• v.46 no.3
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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.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1733-1741
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• 2020

This study analyzed the effect of meteorological factors on the concentration of PM10 (particulate matter 10) in the atmosphere and the variation of rainwater quality using multivariate statistical analysis. The concentration of PM10 in the atmosphere was continuously measured during eleven precipitation events with a custom-built PM sensor node. A total of 183 rainwater samples were analyzed for pH, EC (electrical conductivity), and water-soluble cations (Na+, Mg2+, K+, Ca2+, NH4+) and anions (Cl-, NO3-, SO42-). The data has been analyzed using two multivariate statistical techniques (principal component analysis, PCA, and Pearson correlation analysis) to identify relationships among PM10 concentrations in the atmosphere, meteorological factors, and rainwater quality factors. When the rainfall intensity was relatively strong (> 5 mm/h, rainfall type 1), the PM10 concentration in the atmosphere showed a negative correlation (r = -0.55, p < 0.05) with cumulative rainfall. The PM10 concentration increased the concentration of water-soluble ions (r = 0.25) and EC (r = 0.4), and decreased the pH (r = -0.7) of rainwater samples. However, for rainfall type 2 (< 5 mm/h), there was no negative correlation between the PM10 concentration in the atmosphere and cumulative rainfall and no statistically significant correlation between the PM10 concentration in the atmosphere and rainwater quality.