• KEPCO Journal on Electric Power and Energy
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• 제6권4호
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• pp.455-460
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• 2020

In order to identify the characteristics of fine particle emissions from thermal power plants, this study conducted measurement of the primary emission concentration of TPM, PM₁₀ and PM_2.5 according to Korea standard test method (ES 01301.1) and ISO 23210 method (KS I ISO 23210). Particulate matters were sampled in total 74 units of power plants such as 59 units of coal-fired power plants, 7 units of heavy oil power plants, 2 units of biomass power plant, and 6 units of liquid natural gas power plants. The average concentration of TPM, PM₁₀, PM_2.5 by fuel are 3.33 mg/m³, 3.01 mg/m³, 2.70 mg/m³ in coal-fired plant, 3.02 mg/m³, 2.99 mg/m³, 2.93 mg/m³ in heavy oil plant, 0.114 mg/m³, 0.046 mg/m³, 0.036 mg/m³ in LNG plant, respectively. These results of TPM, PM₁₀ and PM_2.5 were satisfied with the standards of fine dust emission allowance in all units of power plants, respectively. Also, this study evaluated the characteristics of fine particle emissions by conditions of power plants including generation sources, boiler types and operation years and calculated emission factors and then evaluated fine particle emissions by sources of electricity generation.

• 한국지하수토양환경학회지:지하수토양환경
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• 제25권3호
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• pp.74-83
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• 2020

Since fine dust (PM₁₀) has a significant influence on soil and groundwater composition during dry and wet deposition processes, it is of a vital importance to understand the fate and transport of aerosol in geological environments. Fine dust is formed after the chemical reaction of several precursors, typically observed in short intervals within a few hours. In this study, deep learning approach was applied to predict the fate of fine dust in an urban area. Deep learning training was performed by combining convolutional neural network (CNN) and recurrent neural network (RNN) techniques. The PM₁₀ concentration after 1 hour was predicted based on three-hour data by setting SO₂, CO, O₃, NO₂, and PM₁₀ as training data. The obtained coefficient of determination value, R², was 0.8973 between predicted and measured values for the entire concentration range of PM₁₀, suggesting deep learning method can be developed into a reliable and viable tool for prediction of fine dust concentration.

• Journal of the Korean Data and Information Science Society
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• 제26권2호
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• pp.289-299
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• 2015

본 연구는 PM10 농도에 대한 계량치 예측모형 개발을 목적으로 한다. 세 종류의 자료 (기상관측 자료, 세계기상통신망 중국 관측자료, 대기질 화학수치모델자료)를 예측인자로 사용하였으며, 일일 단기예보 시스템에 쉽게 적용할 수 있도록 시간자료를 일자료로 변환하였고 시차변환을 수행하였다. 상관분석과 다중공선성 진단을 통하여 예측인자를 선택하고 두 종류의 모형 (중회귀모형, 문턱치 회귀모형)을 각각 적합하였다. 모형 안정성 검사를 위하여 모형검증을 수행하였으며, 전체자료를 사용하여 모형을 재추정한 후 예측치와 관측치 사이의 산점도와 시계열그림, RMSE, 예측성 평가측도를 작성 및 산출하여 두 모형을 비교하였다. 문턱치 회귀모형의 예측력이 고농도 PM10예측에서 다소 우수한 결과를 보였다.

• 한국환경복원기술학회지
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• 제24권2호
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• pp.57-69
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• 2021

Urban green spaces supply ecosystem services (ESs), which are consumed by city residents and generate demand, to improve air quality. It is important to determine supply and demand for ESs and reduce the gap for efficient management. This study proposed a method to use the concept of supply and demand for ESs in the decision-making process for urban planning or management. PM₁₀ concentrations were converted to weight for demand assessment on PM₁₀ reduction, and PM₁₀ absorption capacity of all green spaces including the forests, and that of urban green spaces excluding forests, was calculated for each supply assessment. The differences in the calculated supply and demand were analyzed to derive the mismatched regions in Suwon. As a result, regions with big forested areas showed sufficient supply, indicating that the degree of mismatch among administrative neighborhoods (dong) varied greatly depending on whether they had a forest. An analysis of only urban green spaces showed that all neighborhoods lacked supply. Forests with high PM₁₀ absorption capacity had a great effect, but urban green spaces can be considered a key element in reducing PM₁₀ in daily life. Considering the mismatch of supply and demand, spatial distribution, and population distribution, it is possible to prioritize the supply of urban green spaces to reduce PM₁₀ and, furthermore, support decision making for priority zones subject to forest conservation and designation and cancellation of green spaces, which gives significance to this study.

• 대기
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• 제21권4호
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• pp.447-454
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• 2011

As dust storms originated in Neimongu Plateau and Manchuria became more frequent in Korea, there was a growing need for Asian Dust (Hwangsa) monitoring stations in North Korea, which is a pathway of Asian Dust to South Korea. The South Korean and the North Korean Governments agreed to build the Automatic Weather System and the PM10 measurement instruments in the Gaeseong Industrial Zone and the Keumgangsan Tourist Region, North Korea in 2007. PM10 mass concentration data in the Keumgangsan Tourist Region could be collected only during the period from September 2007 to May 2008. In this study, daily, monthly and diurnal variations of PM10 mass concentration of the Keumgangsan are analyzed and compared with those of Sokcho and Gwangdeoksan. Three sites show similar variations in daily and monthly means. Correlation coefficients (r) between Sokcho and Keumgangsan, and between Gwangdeoksan and Keumgangsan are 0.89 and 0.67, respectively. But diurnal variation at Keumgangsan has a distinct feature compared to the other sites. Diurnal PM10 variation shows two peaks around 8 AM and 4-5 PM and very low at night. The difference between the daily maximum and minimum is $20{\sim}60{\mu}g\;m^{-3}$ during September to November 2007. Temperature, relative humidity and wind speed from the Keumgangsan AWS data were compared with those from the Changjon station, and showed good correlation each other except wind speed.

• 한국터널지하공간학회 논문집
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• 제22권5호
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• pp.591-610
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• 2020

활성탄(Activated carbon) 및 이산화티탄(TiO₂)이 혼합된 콘크리트는 질소산화물(NOx) 저감에 있어 우수한 성능을 나타내기 때문에 지하공간 및 터널 내부의 미세먼지 저감 목적으로 활용되고 있다. 환경 및 구조물 노후 영향으로 터널 내부에 설치된 미세먼지 저감 콘크리트 표면에서 손상이 발생된다. 따라서 미세먼지 저감 콘크리트의 성능 유지를 위해 손상(박리) 유무평가가 필요하다. 본 연구에서는 전기비저항 특성을 이용하여 콘크리트 박리 유무 평가를 위한 기초연구를 수행하였다. 활성탄(0~15%) 및 TiO₂ (0~25%) 혼합비(시멘트 중량 기준)가 증가함에 따라 전기비저항 값은 감소하였다. 건조 조건에서 활성탄 및 TiO₂가 혼합된 시멘트 경화시편은 일반 시멘트 경화시편보다 전기비저항 값이 최대 2.3배 감소되었다. 또한, 포화 조건(포화도 = 85~98%)에서 활성탄만 혼합된 경화시편은 일반 시멘트 경화시편보다 전기비저항 값이 최대 3.5배 감소하는 결과를 보였다. 시편 상태(건조 또는 포화)와 관계없이 활성탄(15%) 및 TiO₂ (25%)가 혼합된 미세먼지 저감 시편의 경우, 일반 시멘트 시편과 비교하여 전기비저항 값은 약 2.3~2.8배 차이를 보였다. 본 연구결과는 전기비저항을 이용하여 터널 내 미세먼지 저감 콘크리트의 박리를 평가하기 위한 기초자료로 유용하게 활용될 것으로 기대된다.

• 한국지리정보학회지
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• 제26권2호
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• pp.68-81
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• 2023

본 연구는 도시화 과정에서 발생한 도시 내 폭염 및 미세먼지를 저감하기 위해 가로수의 간격과 배열에 기반한 시나리오를 설정하고, 저감 정도를 정량적으로 분석하는 것을 목표로 한다. 가로수 조성 시나리오에 따른 열환경 및 미세먼지 개선 정도를 분석하기 위해서 미기후 시뮬레이션 프로그램인 ENVI-met 5.0.2v 모델을 사용하였다. 가로수 간격에 따른 기온 분석 결과, 가로수의 간격이 좁아져 식재한 수목의 양이 많아질수록 낮 시간대의 기온이 낮아졌으며, 오전 및 저녁 시간대에는 가로수 간격에 상관없이 비슷한 양상을 보였다. 가로수 배열에 따른 기온은 배열이 증가하여 식재한 수목의 양이 많아질수록 감소하는 경향을 보였다. 하지만, 같은 양의 수목을 식재하고 배열의 간격을 넓힌 시나리오에서 기온 저감폭이 더 크게 나타났기 때문에 수목의 양뿐만 아니라 수관투영면적 역시 기온 저감에 큰 영향을 주는 것으로 판단되었다. 가로수 배열에 있어서 미세먼지 농도는 간격에 따른 결과와 차이를 보였는데, 이는 주풍향과 수목 식재 방향의 관계에 따라 미세먼지 농도가 변화할 수 있음을 시사한다. 본 연구는 가로녹지에 의한 열환경 및 미세먼지 개선 정도를 정량적으로 분석함으로써, 가로수 조성·관리 기본 계획, 바람길숲 조성 사업 등 효율적인 가로환경 개선을 위한 정책 및 사업 추진에 활용될 수 있을 것으로 기대된다.

• 한국환경보건학회지
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• 제35권4호
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• pp.315-321
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• 2009

Under-fired charbroiling cooking processes are known as important contributors of particulate matter (PM). In this study, we characterized the emission of particulate matters from under-fired charbroiling cooking processes using the hood method. Accumulated mass concentration of $PM_{10}$ was 92.2~99.5% and particle size of 2.0~2.5 ${\mu}m$ was highest. The concentration of PM increased very sharply at the beginning of charbroiling meats and then gradually decreased as the charbroiling continued. PM concentration also increased very sharply when gravy from meat spilled onto the frame of fire. However, mass concentration during charbroiling using only charcoals was very low compared to that of meats. We estimated the emission factors of charcoal, pork belly and pork shoulder respectively; 0.01~0.02 g/kg, 5.02~6.26 g/kg, 2.86~4.15 g/kg of $PM_{2.5}$, 0.01~0.03 g/kg, 7.44~7.91 g/kg, 4.54~5.56 g/kg of $PM_{10}$, and 0.02~0.05 g/kg, 7.59~7.95 g/kg, 4.93~5.68 g/kg of TSP. The emission factors of charcoal were negligible and the emission factors of pork belly were higher than that of pork shoulder. Emission rates of particulate matters from under-fired charbroiling cooking process were estimated as 578,009~1,265,152 kg/yr of $PM_{2.5}$, 917,539~1,598,619 kg/yr of $PM_{10}$ and 996.358~1,606,703 kg/yr of TSP. But emission factors should be verified with an in-stack cascade impactor because the reported method involves some assumptions.

• 한국대기환경학회지
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• 제31권6호
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• pp.585-592
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• 2015

In this study, by applying mobile based GIS and image analysis of particulate matter ($PM_{10}$) concentration in Seoul and Ulsan in Korea, to identify the user's location and also implemented the application to information exchange. It strengthened citizens' access to air quality information through the application and derived the expanded environment information sharing through real-time user participation. Through atmospheric concentrations image analysis, it showed a new environmental information construction possibility. It had the effect of expanding the information collecting through the local user participation on the limited information collected area which place is not yet constructed atmospheric monitoring network. Location-based particulate matter information service application provides a user location's $PM_{10}$ information from the 25 urban air monitoring network real-time database of the Ministry of Environment. Furthermore, if the user sent a picture of the atmosphere to the server, should match the image density values of the database and express on Seoul's maps through the IDW interpolation. And then a $PM_{10}$ concentration result is transmitted to user in real time.

• 한국환경과학회지
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• 제12권2호
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• pp.217-225
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• 2003

Samples of size-fractionated PM10 (airborne particulate matter with aerodynamic diameter less than $10\mu\textrm{m}$) were collected at an urban site in Jeju city from May to September 2002. The mass concentration and chemical composition of the samples were measured. The data sets were then applied to the CMB receptor model to estimate the source contribution of PM10 in Jeju area. The average PM10 mass concentration was 28.80$\mu\textrm{g}/m^3$ ($24.6~33.49\mu\textrm{g}/m^3$), and the FP (fine particle with aerodynamic diameter less than $2.l\mu\textrm{m}$ fraction in PM10 was approximately 8% higher than the CP (coarse particle with aerodynamic diameter greater than $2.l\mu\textrm{m}$ and less than $10\mu\textrm{m}$ fraction in PM10. The CP composition was obviously different from the FP composition, that is, the most abundant water soluble species was nitrate ion in the FP, but sulfate ion in the CP. Also sulfur was the most dominant element in the FP, however, sodium was that in the CP. From CMB receptor model results, it was found that road dust was the largest contributor to the CP mass concentration (45% of the CP) and ammonium nitrate, domestic boiler, and marine aerosol were major sources to the CP mass. However, the secondary aerosol was the most significant contributor to the FP mass concentration (45% of the FP). In this study, it was suggested that the contributions of soil dust and gasoline vehicle became very low due to collinearity with road dust and diesel vehicle, respectively.