• 한국대기환경학회지
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• 제26권6호
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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.

• 한국항행학회논문지
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• 제28권1호
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• pp.149-154
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• 2024

미세먼지에 대한 연구는 실시간으로 발전하고 있으며, 예측 모델의 정확도를 향상시키기 위해 다양한 방법이 연구되고 있다. 또한 미세먼지의 정확한 원인과 영향을 파악하기 위해 이러한 다양한 요소들을 고려하는 연구들이 활발히 이루어지고 있다. 본 논문에서는 PM_2.5와 상관성이 있는 데이터를 계절을 기준으로 구분하여 학습하는 예측 모델과 특정 농도를 기준으로 저농도와 고농도를 구분하여 학습하는 모델을 통해 예측 성능의 비교 및 분석을 진행하였다. 기상데이터와 대기오염 물질 데이터를 사용하였으며 PM_2.5와 상관관계를 확인하여 학습 및 평가를 위한 데이터를 구성하였다. 계절별 예측 모델과 농도별 예측 모델은 LSTM으로 설계하였으며, 세부 파라미터는 하이퍼 파라미터 탐색을 통해 적용하였다. 예측 모델의 성능 평가는 정확도, RMSE, MAPE, 저농도와 고농도 구간에서의 정확도 그리고 AQI를 기준으로 4개의 범위에 대한 정확도로 진행하였다. 성능 평가 결과, 농도별 학습을 진행한 예측 모델이 AQI 기준 "나쁨" 구간의 정확도에서 91.02%의 정확도를 보였으며, 계절별 학습을 진행한 예측 모델보다 전반적으로 좋은 성능을 보였다.

• 해양환경안전학회지
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• 제26권2호
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• pp.163-174
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• 2020

미세먼지 등 대기오염이 일상화되고 국민 건강을 위협하면서 육상뿐만 아니라 해상 선박에서 발생하는 대기오염물질에 대한 관리 필요성이 대두되고 있다. 이에 본 연구는 선박 배출량 현황을 바탕으로 해양경찰 업무 중심의 선박 대기오염물질 점검 실태를 진단하고 배출 저감을 위한 국가 관리 대책을 제안한다. 최근 국립환경과학원(NIER, 2018)에 따르면 선박에서 배출된 총량(CO, NOx, SOx, TSP, PM10, PM2.5, VOCs, NH₃, BC)은 국내 전체 발생량의 6.4 %로 나타났고, 이 중 NOx는 13.1 %, SOx는 10.9 %, 미세먼지(PM10/PM2.5)는 9.6 %를 차지하고 있다. 선박 발생량 중에서는 국내외 입출항 화물선이 50.6 %로 가장 많은 배출을 보였고, 어선의 배출 비율도 42.6 %로 적지 않음을 알 수 있었다. 지역적으로 해양경찰 관할 5개 권역을 기준으로는 부산항, 울산항을 포함한 남해권 44.1 %와 광양항, 여수항을 포함한 서해권 24.8 % 순으로 배출이 많았다. 해양경찰은 대기오염물질 관리를 위해 승선 점검을 통한 선박 배출 상황을 관리하고 있지만, 각종 배출 장치의 가동이나 연료유 기준 등의 실측에는 많은 시간과 노력이 필요하고, 또한 선박의 바쁜 운항스케줄에 따른 제약으로 대부분 서류상의 점검으로 진행됨으로써 관리에 한계가 있다. 따라서 선박 대기오염물질 관리를 위해서는 대기오염물질 발생을 실측 점검으로 바꾸도록 규제를 강화하고 해경 함정 등을 활용한 해역별 모니터링 시스템을 구축하여 실질적 현장 데이터에 기초한 관리가 이뤄지도록 하는 한편, 장단기적으로 환경친화적 선박 도입을 위한 기술 개발과 법·제도적 지원이 필요하다.

• 한국대기환경학회지
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• 제33권4호
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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.

• 한국환경과학회지
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• 제31권12호
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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.

• 한국군사과학기술학회지
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• 제10권4호
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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.

• 한국대기환경학회지
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• 제24권4호
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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.

• 한국입자에어로졸학회지
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• 제7권4호
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• pp.131-138
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• 2011

우리나라의 대표적인 배경지역 측정소인 안면도의 지구배경관측소에서 20010년에 채취한 미세먼지(PM10) 시료에 대해 n-alkane과 수용성 유기성분(WSOC) 농도를 분석하였다. 우리나라의 또 다른 배경지역인 고산에 비해 봄철의 수용성 유기성분의 농도는 세배 정도 높았다. 안면관측소의 수용성 유기성분의 농도는 서울이나 아시아 다른 도시지역의 농도와 비슷한 수준이었다. 그러나 아시아 도시는 겨울에 농도가 높았으나, 안면관측소는 가을에 높아 배출원, 또는 생성원이 다른 것으로 보인다. 한편 n-alkane 성분의 농도는 안면관측소가 고산보다 약간 낮았고, 서울 등의 아시아 도시의 1/3-1/2 수준으로 낮았다. 그러나 고산은 자연적인 기원의 n-alkane 농도가 높은 반면에 안면관측소는 인위적인 n-alkane이 대부분이어서 대조를 보이고 있다. 따라서 안면관측소는 우리나라의 대표적인 배경지역임에도 불구하고 수용성 유기성분과 n-alkanes 농도측면에서는 배경지역과 도시지역의 특성을 갖고 있어, 인위적인 영향을 많이 받고 있는 것으로 보인다. 보다 상세한 배출원과 생성원 분석은 무기이온농도와 다른 유기성분 분석을 추가하여 이루어질 예정이다.

• 한국대기환경학회지
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• 제33권6호
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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.

• 한국환경보건학회지
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• 제43권3호
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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.