• Journal of Korean Society for Atmospheric Environment
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• v.26 no.6
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• pp.666-682
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• 2010

The forecasting system for Today's and Tomorrow's PM10 was developed based on the statistical model and the forecasting was performed at 9 AM to predict Today's 24 hour average PM10 concentration and at 5 PM to predict Tomorrow's 24 hour average PM10. The Today's forecasting model was operated based on measured air quality and meteorological data while Tomorrow's model was run by monitored data as well as the meteorological data calculated from the weather forecasting model such as MM5 (Mesoscale Meteorological Model version 5). The observed air quality data at ambient air quality monitoring stations as well as measured and forecasted meteorological data were reviewed to find the relationship with target PM10 concentrations by the regression analysis. The PM concentration, wind speed, precipitation rate, mixing height and dew-point deficit temperature were major variables to determine the level of PM10 and the wind direction at 500 hpa height was also a good indicator to identify the influence of long-range transport from other countries. The neural network, regression model, and decision tree method were used as the forecasting models to predict the class of a comprehensive air quality index and the final forecasting index was determined by the most frequent index among the three model's predicted indexes. The accuracy, false alarm rate, and probability of detection in Tomorrow's model were 72.4%, 0.0%, and 42.9% while those in Today's model were 80.8%, 12.5%, and 77.8%, respectively. The statistical model had the limitation to predict the rapid changing PM10 concentration by long-range transport from the outside of Korea and in this case the chemical transport model would be an alternative method.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.149-154
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• 2024

Research on particulate matter is advancing in real-time, and various methods are being studied to improve the accuracy of prediction models. Furthermore, studies that take into account various factors to understand the precise causes and impacts of particulate matter are actively being pursued. This paper trains an LSTM model using seasonal data and another LSTM model using concentration-based data. It compares and analyzes the PM_2.5 prediction performance of the two models. To train the model, weather data and air pollutant data were collected. The collected data was then used to confirm the correlation with PM_2.5. Based on the results of the correlation analysis, the data was structured for training and evaluation. The seasonal prediction model and the concentration-specific prediction model were designed using the LSTM algorithm. The performance of the prediction model was evaluated using accuracy, RMSE, and MAPE. As a result of the performance evaluation, the prediction model learned by concentration had an accuracy of 91.02% in the "bad" range of AQI. And overall, it performed better than the prediction model trained by season.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.2
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• pp.163-174
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• 2020

Particulate matter levels are rapidly increasing daily, and this can affect human health. Therefore, air pollutant emissions from sea vessels require management. This study evaluates the status of air pollutants, focusing on air pollutant emissions from the vessels of the Korea Coast Guard (KCG), and proposes national management measures to reduce emissions. According to a report recently released (2018) by the National Institute of Environmental Research (NIER), emissions from vessels constituted 6.4 % of the total domestic emissions, including 13.1 % NO_x, 10.9 % SO_x, and 9.6 % particulate matter (PM10/PM2.5). Among the rates of pollutant emission from vessels, the emission rates of domestic and overseas cargo vessels were the highest (50.6 %); the ratio of fishing boats was 42.6 %. With respect to jurisdictional sea area, 44.1 % of the emissions are from the south sea, including the Busan and Ulsan ports, and 24.8 % of the emissions are from the west sea, including the Gwangyang and Yeosu ports. The KCG inspects boarding lines to manage emission conditions and regulate air pollutant emissions, but it takes time and effort to operate various discharge devices and measure fuel oil standards. In addition, owing to busy ship schedules, inspection documents are limited in terms of management. Therefore, to reduce the air pollutant emissions of such vessels, regulations will be strengthened to check for air pollutants, and a monitoring system based on actual field data using KCG patrol ships will be established, for each sea area, to manage the emissions of such vessels. Furthermore, there is a need for technological development and institutional support for the introduction of environmentally friendly vessels.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.4
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• pp.342-350
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• 2017

We report mass concentration and size fraction of TPM, $PM_{10}$ and $PM_{2.5}$ according to Korea standard test method (ES 01301.1 and ES 01317.1) and ISO 23210 methods. Particulate matters were sampled in large stationary emission sources such as a coal power plant and B-C oil refinery. The Korea standard test method PM mass concentrations showed 3~3.5 times larger than the cascade impactor method. On the other hand, the size fraction results showed less than 5% difference (i.e. $PM_{2.5}/PM_{10}$) between two methods. Moreover, the correlation coefficient ($r^2$) is 0.84 between TPM results of the Korea standard test method and CleanSYS. These results suggested not only improvement of current test criteria in terms of technical and theoretical aspects. Further, additional measurements are required in various large stationary sources to compare current field data.

• 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 Korea Institute of Military Science and Technology
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• v.10 no.4
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• pp.168-175
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• 2007

In this study, the Indoor Air Quality(IAQ) in military barracks is evaluated and its characteristics is discussed as well. The military barracks of R.O.K Army are categorized into three types and the IAQ in these individual facilities is measured for 24 hours both in summer and winter. Test results show that the particulate matters($PM_{10}$) and carbon dioxide($CO_2$) were the main causes contaminating IAQ in military barracks. While $CO_2$ can be purified by ventilation, adequate facilities have to be installed in case of the new type of combination barracks to remove $PM_{10}$. In addition, to improve the living condition of military barracks and to recover IAQ in new combination style barracks which is planned to complete by 2011, a standard or law regulating IAQ in military barracks has to be established.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.4
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• pp.393-403
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• 2008

In an effort to estimate secondary $PM_{10}$ concentrations and their diurnal variations at different photochemical activities, $PM_{10}$, CO, and $O_3$ concentrations obtained from the ambient air quality network located in Seoul are analyzed for the period from 2000 to 2005. In order to classify the photochemical activities on a daily basis, measured ${\Delta}O_{3,\;max-min}$ (maximum $O_3$-minimum $O_3$) and ${\int}(hv)dt$ which represents accumulated daily insolation, were used to classify each day into three regimes: 1) low photochemical reactivity; ${\Delta}O_{3,\;max-min}\;{\leq}\;40\;ppb$, and ${\int}(hv)dt\;{\leq}\;4000\;W/m^2$, 2) moderate photochemical reactivity; $40\;ppb\;<\;{\Delta}O_{3,\;max-min}\;{\leq}\;60\;ppb$, and $4000\;{\leq}\;{\int}(hv)de\;{\leq}\;6000\;W/m^2$, and 3) high photochemical reactivity; ${\Delta}O_{3,\;max-min}\;>\;60\;ppb$, and ${\int}(hv)dt\;{\geq}\;6000\;W/m^2$. The ratio of ($PM_{10}$/CO) obtained at low photochemical activity regime was used as an index of tracer for the estimation of secondary $PM_{10}$ at higher photochemical activity regimes. The results show that the estimated secondary $PM_{10}$ concentrations for moderate and high photochemical regimes are found to be 18.8% ($10.9\;{\mu}g/m^3$), and 35.0% ($26.2\;{\mu}g/m^3$), respectively. Diurnal variation of secondary $PM_{10}$ for the moderate photochemical regime shows weak but noticeable patterns. However, the highly activated photochemical regime shows strong diurnal variations of secondary $PM_{10}$ concentrations with the maximum value of $35.1\;{\mu}g/m^3$ at 1300LST.

• Particle and aerosol research
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• v.7 no.4
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• pp.131-138
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• 2011

The concentration levels of n-alkanes and water soluble organic carbon (WSOC) at Anmyon, a Global Atmospheric Watch (GAW) station operated by Korea Meteorological Administration (KMA), has been characterized for the PM10 samples collected in 2010. It was found that the concentrations of WSOC at Anmyon were comparable to those in Seoul and lower than those in Gosan, another background area in Korea. However, the maximum concentration of the WSOC at Anmyon was observed in fall while that at Seoul was in winter. It suggests that the emission and/or transformation characteristics at two areas are different. The concentrations of n-alkanes at Anmyon were slightly lower than at Gosan and about one thirds at Seoul. However, it was found that at Gosan the n-alkanes from natural sources were dominant at Gosan. On the other hand, n-alkanes from anthropogenic sources were dominant at Anmyon. Study directions to further understand the characteristics of aerosols at Anmyon are discussed.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.6
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• pp.554-569
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• 2017

Sensitivity analysis on $PM_{10}$ forecasting simulations was carried out by using two different initial and boundary conditions of meteorological fields: NCEP/FNL (National Centers for Environmental Prediction/Final Analysis) reanlaysis data and NCEP/GFS (National Centers for Environmental Prediction/Global Forecast System) forecasting data, and the comparisons were made between two different simulations. The two results both yielded lower $PM_{10}$ concentrations than observations, with relatively lower biased results by NCEP/FNL than NCEP/GFS. We explored the detailed individual meteorological variables to associate with $PM_{10}$ prediction performance. With the results of NCEP/FNL outperforming GFS, our conclusion is that no particular significant bias was found in temperature fields between NCEP/FNL and NCEP/GFS data, while the overestimated wind speed by NCEP/GFS data influenced on the lower $PM_{10}$ concentrations simulation than NCEP/FNL, by decreasing the duration time of high-$PM_{10}$ loaded air mass over both coastal and metropolitan areas. These comparative characteristics of FNL against GFS data such as maximum 3~4 m/s weaker wind speed, $PM_{10}$ concentration control with the highest possible factor of 1.3~1.6, and one or two hour difference of peak time for each case in this study, were also reflected into the results of statistical analysis. It is implying that improving the surface wind speed fluctuation is an important controlling factor for the better prediction of $PM_{10}$ over Korean Peninsula.

• Journal of Environmental Health Sciences
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• v.43 no.3
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• pp.240-246
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• 2017

Objectives: This study was conducted to evaluate the vulnerability of the human health sector to $PM_{10}$ due to climate change in Incheon over the period of 2005-2014. Methods: Vulnerability to $PM_{10}$ consists of the three categories of climate exposure, sensitivity, and adaptive capacity. The indexes for climate exposure and sensitivity indicate positive effects, while adaptive capacity shows a negative effect on vulnerability to $PM_{10}$. The variables in each category were standardized by the rescaling method, and respective relative regional vulnerability was analyzed through the vulnerability index calculation formula of the Intergovernmental Panel on Climate Change. Results: Regions with a high exposure index were the western and northern urban areas with industrial complexes adjacent to a highway, including Bupyong-gu and Seo-gu. Major factors determining the climate exposure index were the $PM_{10}$ concentration, days of $PM_{10}$ >= $100{\mu}g/m^3$, and $PM_{10}$ emissions. The regions showing a high sensitivity index were urban regions with high populations; these commonly had a high mortality rate for related diseases and vulnerable populations. Conclusions: This study is able to support regionally adjusted adaptation policies and the quantitative background of policy priority since it provides information on the regional health vulnerability to $PM_{10}$ due to climate change in Incheon.