• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2008년도 춘계학술대회 논문집
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• pp.221-223
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• 2008

• 대한환경공학회지
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• 제27권8호
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• pp.852-858
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• 2005

대기질 예측 모델링은 대기질 관리의 유용한 도구이다. 특히, 도시지역에서 대기질은 건물과 자동차와 같은 국부적인 장애물에 의해 크게 영향을 받는다. 일반적으로 도로를 따라 건물이 연속적으로 형성되어있는 도시거리협곡에서의 대기질을 예측하고자 할 때 현재 이용 가능한 대기확산모델은 대기질을 정확하게 예측하는데 많은 한계점을 가지고 있다. 본 연구에서는 도시거리협곡에서 대기질 예측을 위한 경험적인 모델을 제안하고자 하였다. 이를 위해 풍동실험을 수행하고, 그 결과를 통계적으로 분석하였다. 풍동실험 결과 넓은 협곡인 경우와 도로축과 직각을 이루는 바람일 때 도시거리협곡의 대기질을 향상시키는데 유용하다는 것을 확인하였다. 또한, 제안한 모델을 이용한 모델 예측치는 풍동실험 결과와 상관성이 양호하게 나타났다.

• 한국대기환경학회지
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• 제29권3호
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• pp.251-263
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• 2013

The surface ozone concentrations changes were investigated in response to climate change over the Korean peninsula for summertime using the global-regional one way coupled Integrated Climate and Air quality Modeling System (ICAMS). The future simulations were conducted under the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 and B1 scenarios. The modeling system was applied for four 10-year simulations: 1996~2005 as a present-day case, 2016~2025, 2046~2055, and 2091~2100 as future cases. The results in this study showed that the mean surface ozone concentrations increased up to 0.5~3.3 ppb under the A2, but decreased by 0.1~10.9 ppb under the B1 for the future, respectively. However, its increases were lower than an increase of the average daily maximum 8-hour (DM8H) surface ozone concentrations which was projected to increase by 2.8~6.5 ppb under the A2. The DM8H surface ozone concentrations seem to be therefore far more affected by the climate and emissions changes than mean values. The probability of exceeding 60 ppb was projected to increase by 6~19% under the A2. In the case of B1, its changes were presented with an increase of 2.9% in the 2020s but no occurrence in the 2100s due to the effect of the reduced emissions. Future projection on surface ozone concentrations was generally shown to have almost the similar trend as the emissions of $NO_x$ and NMVOC.

• 한국대기환경학회지
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• 제24권3호
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• pp.284-299
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• 2008

Emission input modules was developed to produce emission input data and change some profiles for Sparse Matrix Operator Kernel Emissions (SMOKE) using Clean Air Policy Support System (CAPSS)'s activities and previous studies. Specially, this study was focused to improve chemical speciation and temporal allocation profiles of SMOKE. At first, SCC cord mapping was done. 579 SCC cords of CAPSS were matched with EPA's one. Temporal allocation profiles were changed using CAPSS monthly activities. And Chemical speciation profiles were substituted using Kang et al. (2000) and Lee et al. (2005) studies and Kim et al. (2005) study. Simulation in Seoul Metropolitan Area (Seoul, Incheon, Gyeonggi) using MM5, SMOKE and CMAQ modeling system was done for effect analysis of changed input modules of SMOKE. Emission model results adjusted with new input modules were slightly changed as compared to using EPA's default modules. SMOKE outputs shows that aldehyde emissions were decreased 4.78% after changing chemical profiles, increased 0.85% after implementing new temporal profiles. Toluene emissions were decreased 18.56% by changing chemical speciation profiles, increased 0.67% by replacing temporal profiles as well. Simulated results of air quality were also slightly elevated by using new input modules. Continuous accumulation of domestic data and studies to develop input system for air quality modeling would produce more improved results of air quality prediction.

• Asian Journal of Atmospheric Environment
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• 제2권1호
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• pp.34-46
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• 2008

Emissions inputs for use in air quality modeling of Korea were generated with the emissions inventory data from the National Institute of Environmental Research (NIER), maintained under the Clean Air Policy Support System (CAPSS) database. Source Classification Codes (SCC) in the Korea emissions inventory were adapted to use with the U.S. EPA's Sparse Matrix Operator Kernel Emissions (SMOKE) by finding the best-matching SMOKE default SCCs for the chemical speciation and temporal allocation. A set of 19 surrogate spatial allocation factors for South Korea were developed utilizing the Multi-scale Integrated Modeling System (MIMS) Spatial Allocator and Korean GIS databases. The mobile and area source emissions data, after temporal allocation, show typical sinusoidal diurnal variations with high peaks during daytime, while point source emissions show weak diurnal variations. The model-ready emissions are speciated for the carbon bond version 4 (CB-4) chemical mechanism. Volatile organic carbon (VOC) emissions from painting related industries in area source category significantly contribute to TOL (Toluene) and XYL (Xylene) emissions. ETH (Ethylene) emissions are largely contributed from point industrial incineration facilities and various mobile sources. On the other hand, a large portion of OLE (Olefin) emissions are speciated from mobile sources in addition to those contributed by the polypropylene industry in point source. It was found that FORM (Formaldehyde) is mostly emitted from petroleum industry and heavy duty diesel vehicles. Chemical speciation of PM2.5 emissions shows that PEC (primary fine elemental carbon) and POA (primary fine organic aerosol) are the most abundant species from diesel and gasoline vehicles. To reduce uncertainties in processing the Korea emission inventory due to the mapping of Korean SCCs to those of U.S., it would be practical to develop and use domestic source profiles for the top 10 SCCs for area and point sources and top 5 SCCs for on-road mobile sources when VOC emissions from the sources are more than 90% of the total.

• International Journal of Computer Science & Network Security
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• 제22권1호
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• pp.85-92
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• 2022

In this article, we look at the application of BIM (Building Information Modeling) in sustainable infrastructures. In response to global warming, energy shortages, and environmental degradation, people are trying to build eco-friendly, low-carbon cities and promote eco-friendly homes. A "green" building is the entire life cycle of a building that includes maximizing the conservation of resources (energy, water, land, and materials), protecting the environment, reducing pollution, providing people with healthy, comfortable, and efficient use of space, and establishing harmony between nature and architecture. In the field of ecological and sustainable buildings, BIM modeling can be integrated into buildings with analog energy, air flow analysis, and solar building ecosystems. Using BIM technologies, you can reduce the amount of waste and improve the quality of construction. These technologies create "visualization" of digital building models through multidimensional digital design solutions that provide" modeling and analysis "of Scientific Collaboration Platforms for designers, architects, utility engineers, developers, and even end users. Moreover, BIM helps them use three-dimensional digital models in project design and construction and operational management.

• Asian Journal of Atmospheric Environment
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• 제8권4호
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• pp.212-224
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• 2014

There are several studies on the effects of emissions of highly reactive volatile organic compounds (HRVOC) from the industrial sources in the Houston-Galveston-Brazoria (HGB) area on the high ozone events during the Texas Air Quality Study (TexAQS) in summer of 2000. They showed that the modeled atmosphere lacked reactivity to produce the observed high ozone event and suggested "imputation" of HRVOC emissions from the base inventory. Byun et al. (2007b) showed the imputed inventory leads to too high ethylene concentrations compared to the measurements at the chemical super sites but still too little aloft compared to the NOAA aircraft. The paper suggested that the lack of reactivity in the modeled Houston atmosphere must be corrected by targeted, and sometimes of episodic, increase of HRVOC emissions from the large sources such as flares in the Houston Ship Channel (HSC) distributed into the deeper level of the boundary layer. We performed retrospective meteorological and air quality modeling to achieve better air quality prediction of ozone by comparison with various chemical and meteorological measurements during the Texas Air Quality Study periods in August-September 2006 (TexA QS-II). After identifying several shortcomings of the forecast meteorological simulations and emissions inputs, we prepared new retrospective meteorological simulations and updated emissions inputs. We utilized assimilated MM5 inputs to achieve better meteorological simulations (detailed description of MM5 assimilation can be found in F. Ngan et al., 2012) and used them in this study for air quality simulations. Using the better predicted meteorological results, we focused on the emissions uncertainty in order to capture high peak ozone which occasionally happens in the HGB area. We described how the ozone predictions are affected by emissions uncertainty in the air quality simulations utilizing different emission inventories and adjustments.

• 한국환경과학회지
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• 제15권10호
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• pp.929-933
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• 2006

Indoor air quality is the dominant contributor to total personal exposure because most people spend a majority of their time Indoors. Especially when indoor environments have sources of contaminants, exposure to in-door air can potentially pose a greater threat than exposure to ambient air. In this study, estimations of volatile organic compounds and formaldehyde omission rate in indoor environments of new apartments were carried out using mass balance model in indoor environment, because indoor air quality can be affected by source generation, outdoor air level, ventilation, decay by reaction, temperature, humidity, mixing condition and so on. Considering the estimated emission rate of volatile organic compounds and formaldehyde, it Is suggested that new apartment should be designed and constructed in the aspect of using construction materials to emit low hazardous air pollutants.

• 한국대기환경학회지
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• 제19권1호
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• pp.13-23
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• 2003

A local wind model and a three dimensional local environmental model including advection, diffusion, deposition. and photochemical reactions were performed at Gwangyang Bay, Korea, to predict air flow and air pollutants concentrations. A large grid was used, and nesting method was employed for small grid calculation. From the meterological module simulation, we were able to reproduce local wind characteristics such as sea/land winds and mountain/valley winds simulation at Gwangyang Bay. In addition, the concentration module showed high concentration regions at Yosu industrial complex, Gwangyang steel company. and Container anchor. It was also seen that air pollutants were dispersed by sea/land winds. A comparison between the measurement and the prediction of sulfur dioxide and nitric oxide, which are relatively low-reacted pollutants, was performed. However, the measured nitrogen dioxide and ozone concentrations were higher than the simulated ones. Particularly, ozone concentration between 8 a..m. and 8 p.m. agreed well, but the measured ozone during the rest of time were generally higher.

• 한국대기환경학회지
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• 제27권6호
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• pp.711-722
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• 2011

This study is aimed to estimate the $PM_{2.5}$ source apportionment at Seoul intensive monitoring site located in Seoul metropolitan area. Time-resolved chemical compositions of $PM_{2.5}$ are measured in real time using ambient ion monitor, semi-continuous carbon monitor, and on-line XRF at Seoul intensive monitoring site in 2010. The mass concentration of $PM_{2.5}$ was simultaneously monitored with eight ionic species (${SO_4}^{2-}$, $NO_3{^-}$, $Cl^-$, $NH_4{^+}$, $Na^+$, $K^+$, $Mg^{2+}$, $Ca^{2+}$), two carbonaceous species (OC and EC), and fourteen elements (Si, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Zn, As, Se, Pb) in 1-hr interval. The data sets were then analyzed using EPA PMF version 3 to identify sources and contributions to $PM_{2.5}$ mass. EPA PMF modeling identified eight PM2.5 sources, including soil dust, secondary sulfate, secondary nitrate, motor vehicle, coal combustion, oil combustion, biomass burning, and municipal incineration. This study found that the average $PM_{2.5}$ mass was apportioned to anthropogenic sources such as motor vehicle, fuel combustion, and biomass burning (61%) and secondary aerosols, including sulfate and nitrate (38%).