• Journal of Soil and Groundwater Environment
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• v.25 no.2_spc
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• pp.70-85
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• 2020

This paper introduces the 'Smart Scoping for Environmental Investigations Technical Guide' issued by the US Environmental Protection Agency in 2018, which describes the use of smart scoping during lifecycle of remedial investigation projects. This paper also briefly summarizes the guidelines of soil and groundwater contamination investigation of South Korea. The smart scoping practices can support the development of a robust and realistic conceptual site model that is very useful for investigations and evaluations of the contaminated site. The application of evaluation tools relevant for the site-specific characteristics is important for the development of a conceptual site model. The smart scoping recommends the use of previous investigation data and implementation of best proven strategies for successful remedial investigation project. The use of smart scoping in contaminated site investigation will provide better management of contaminated sites.

• Journal of IKEEE
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• v.24 no.4
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• pp.1136-1140
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• 2020

As air pollution caused by fine dust becomes serious, interest in the spread of fine dust and prediction of air quality is increasing. The causes of fine dust are very diverse, and some fine dust naturally occurs through forest fires and yellow dust, but most of them are known to be caused by air pollutants from burning fossil fuels such as petroleum and coal or from automobile exhaust gas. In this paper, the CALPUFF model recommended by the US EPA is used, and CALPUFF diffusion modeling is performed by generating a wind field through the CALMET model as a meteorological preprocessing program that generates a three-dimensional wind field, which is a meteorological element required by CALPUFF. Through this, we propose a fine dust diffusion modeling and air quality prediction system that reflects complex topography.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.50-50
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• 2023

농업용수는 우리나라 수자원 사용량 중 약 61%를 차지하고 있으며, 효율적인 수자원 관리를 위한 핵심적인 관리목표 중 하나이다. 논으로 공급되는 관개용수는 필지에서의 증발산량 및 침투량과 용배수로를 통한 자연적 및 인위적인 배수량으로 소비된다. 관개회귀수량 (irrigation return flow)은 관개를 통해 농경지에 공급된 수량 중 증발산에 의해 소비되지 않고 침투 또는 배수 등을 통해 하천으로 회귀되는 수량이다. 관개회귀수량 및 회귀율은 농업용수 물순환 관리에 중요한 역할을 하며, 관개용수 사용량 결정, 합리적인 용수의 공급과 수요 관리계획 및 수질 관리계획 등에 중요한 요소로 작용한다. 하지만, 기상, 작물, 토양 등의 물리적 요소와 농업용수 공급량, 물꼬 조절, 담수심 관리 방식 등 인위적 요소의 영향을 동시에 받기 때문에 그 기작이 복잡한 특징을 갖는다. 따라서, 합리적인 수자원 개발 계획 및 관리를 위해 정확한 관개회귀수량 추정 연구가 필수적이다. 본 연구에서는 전국 4대강 (한강, 금강, 낙동강, 영산강·섬진강) 권역 중심의 9개 대상지구를 선정하였으며, EPA-SWMM (Environmental Protection Agency-Storm Water Management Model) 모델 기반 수로 네트워크 모의를 활용한 수원공 단위 관개회귀수량을 산정하고자 한다. EPA-SWMM 모의 시 공급량은 농업기반시설관리시스템 (Rural Infrastructure Management System, RIMS) 저수율 자료와 수원공 단위용수량을 활용하였으며, 모의결과 시점부 공급량 및 배수량과 강수량, 증발산량 및 침투량을 활용하여 신속회귀수량과 지연회귀수량을 추정하였다. 본 연구 결과는 최적 농업용수 공급방안에 대한 기초자료 구축에 활용 가능할 것으로 사료된다.

• Journal of Radiation Protection and Research
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• v.42 no.2
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• pp.130-140
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• 2017

Background: With the need for a domestic level 3 probabilistic safety assessment (PSA), it is essential to develop a Korea-specific code. Health effect assessments study radiation-induced impacts; in particular, long-term health effects are evaluated in terms of cancer risk. The objective of this study was to analyze the latest cancer risk models developed by foreign organizations and to compare the methodology of how they were developed. This paper also provides suggestions regarding the development of Korean cancer risk models. Materials and Methods: A review of cancer risk models was carried out targeting the latest models: the NUREG model (1993), the BEIR VII model (2006), the UNSCEAR model (2006), the ICRP 103 model (2007), and the U.S. EPA model (2011). The methodology of how each model was developed is explained, and the cancer sites, dose and dose rate effectiveness factor (DDREF) and mathematical models are also described in the sections presenting differences among the models. Results and Discussion: The NUREG model was developed by assuming that the risk was proportional to the risk coefficient and dose, while the BEIR VII, UNSCEAR, ICRP, and U.S. EPA models were derived from epidemiological data, principally from Japanese atomic bomb survivors. The risk coefficient does not consider individual characteristics, as the values were calculated in terms of population-averaged cancer risk per unit dose. However, the models derived by epidemiological data are a function of sex, exposure age, and attained age of the exposed individual. Moreover, the methodologies can be used to apply the latest epidemiological data. Therefore, methodologies using epidemiological data should be considered first for developing a Korean cancer risk model, and the cancer sites and DDREF should also be determined based on Korea-specific studies.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.407-407
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• 2023

최근 환경부에서 발표한 국가물관리기본계획에서 수자원 총량 중 생활·공업·농업·유지용수의 이용량은 365억m³/년으로 약 29.4%로 발표되었다. 유지용수를 제외한 농업용수 이용량의 비중은 약 60.5%이며, 이 중 약 80%가 논에서 활용되고 있다. 이러한 농업용수 이용량 중 사용되지 않고 하천으로의 방류량이 존재하는데 이를 관개회귀수량이라하며, 농업용수의 약 35%가 하천으로 회귀된다 발표하나 지역에 따른 편차가 존재하기에 정확한 회귀수량을 산정하기엔 미흡한 실정이다. 따라서 본 연구에서는 네트워크 모형을 통한 용배수로 구축 이후 회귀수 정량화를 하고자 하며, 정량화를 위한 네트워크 모형은 EPA-SWMM(Storm Water Management Model) 모형을 활용하였다. 해당 모형은 미국 환경 보호국(U.S. Environmental Protection Agency, EPA)에서 개발한 네트워크 물리모형으로 다양한 환경적 요소에 따른 수문 영향을 확인 가능한 모형이다. 해당 모형의 다양한 네트워크 기능을 통해 논배수로 네트워크를 구축하여 회귀수 정량화를 진행하고자 한다. 논배수로 네트워크를 구축하기 이전 현장조사를 진행하였다. 현장조사를 통한 용수계통도를 작성하였으며, 모형의 입력자료로 필요한 네트워크 용배수로관 표고값을 측량하였다. 이후 현장조사 및 측량 자료를 활용하여 네트워크 물리모형의 입력자료 구축을 진행하였으며, 해당 자료 구축은 지리 정보 시스템 중 ArcGIS와의 연계를 통해 구축하였다. 모형의 수리학적 입력자료는 해당지역의 계측자료를 활용하였으며, 필지 사이의 내리흐름 및 펌프를 통한 용수 또한 네트워크 물리모형의 기능을 활용하여 구축하였다. 이후 계측자료와의 비교를 통한 매개변수 보정을 진행하였으며, 전체 논배수로에 대한 농업용수의 흐름 및 회귀수량을 분석하였다. 해당 연구를 통해 농업용수의 회귀수 산정 및 지역 편차에 따른 회귀수 정량화 등의 연구에 활용될 것으로 기대한다.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.6
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• pp.789-803
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• 2003

The purpose of this study is to compare the usefulness between Gaussian dispersion model and receptor model with the experimental result of the dispersion tracing of the particulate pollutants from Taean coal-fired power plants. For this purpose, the component analysis of the collected PM 10 samples was performed. In order to trace the pollution sources, factor analysis was done with the result of the component analysis. As a result of the correlativity analysis of the fifteen power plants' profiles offered by US EPA, the correlativity of No.11202 source profile showed highest rate up to 84.5%. Thus it was adopted as proper one and the contribution rate by each pollution source was calculated by Chemical Mass Balance (CMB)-8 model. The contribution rate, which was the effect rate of the power plants on each measuring point, were calculated with a range of 24∼52％ and the standard error was below 0.9 $\mu\textrm{g}$/㎥. This indicates the selection of the source profile was appropriate. Also, the concentrations of each point were calculated by the ISCST3 which is suggested by US EPA as one of the regulatory Gaussian dispersion model. The calculation result showed that the predicted concentration was 50∼58 $\mu\textrm{g}$/㎥, comparing with the measured result of 9∼65 $\mu\textrm{g}$/㎥. It was found that the concentration calculated by ISCST3 was underpredicted. It was thought that the receptor model was more favorable than the Gaussian dispersion model in estimating the effect of the particulate matter on a certain receptive point.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3066-3079
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• 2016

Recent years have witnessed a dramatic increase in topology research of wireless sensor networks (WSNs) where both energy consumption and survivability need careful consideration. To balance energy consumption and ensure survivability against both random failures and deliberate attacks, we resort to complex network theory and propose an energy-aware preferential attachment (EPA) model to generate a robust topology for WSNs. In the proposed model, by taking the transmission range and energy consumption of the sensor nodes into account, we combine the characters of Erdős -Rényi (ER) model and Barabasi-Albert (BA) model in this new model and introduce tunable coefficients for balancing connectivity, energy consumption, and survivability. The correctness of our theoretic analysis is verified by simulation results. We find that the topology of WSNs built by EPA model is asymptotically power-law and can have different characters in connectivity, energy consumption, and survivability by using different coefficients. This model can significantly improve energy efficiency as well as enhance network survivability by changing coefficients according to the requirement of the real environment where WSNs deployed and therefore lead to a crucial improvement of network performance.

• Journal of Korea Water Resources Association
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• v.50 no.3
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• pp.181-190
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• 2017

Population congestion and increasing porosity caused by urbanization and increasing rainfall intensity are the main reasons for urban inundation damage. In order to reduce the damage to urban flooding, it is necessary to take a inundation analysis model that can be considered the topographic impact (i.e., building and road) and simulate the detailed inundation areas. In this study, Grid based Inundation Analysis Model (GIAM) is developed using a two-dimensional shallow water equations. The study area is Gangnam basin, with a surface area of $7.4km^2$, which includes 5 drainage areas such as Nonhyun, Yeoksam, Seocho 1, 2, and 3. EPA SWMM5 is used for simulating the overflows at each manhole. GIAM model is constructed to allow for simulating a inundation area with 6 m grid size. The inundation analysis is conducted in two heavy rainfall events (Sep. 21, 2010 and July 27, 2011) for the model evaluation. The accuracy of the simulated inundation area is calculated 0.61 and 0.57 at POD index using the historical flooded area report. The developed model will be used as a tool for analyzing the flood prone areas based on rainfall scenario, and a tool for predicting the detailed inundation area in the real-time.

• Journal of the Korean Data and Information Science Society
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• v.22 no.1
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• pp.125-136
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• 2011

Ground-level ozone, an air pollutant that is monitored by the Environmental Protection Agency (EPA), damages human health by irritating the respiratory system, reducing lung function, damaging lung cells, and aggravating asthma and other chronic conditions. In March 2008, the EPA strengthened ozone standards by lowering acceptable limits from 84 parts per billion to 75 parts per billion. Here epidemiologic data is used to study the effects of ozone regulation on human health and assessed how various regulatory standards for ozone may affect nonaccidental mortality, including respiratory-related deaths during ozone season. The assessment uses statistical methods based on hierarchical Bayesian models to predict the potential effects of the different regulatory standards. It also analyzes the variability of the results and ho they are impacted by different modeling assumptions. We focused on the technical an statistical approach to assessing relationship between new ozone regulations and mortality while other researches have detailed the relationship between ozone and human mortality. We shows a statistical correlation between ozone regulations and mortality, with lower limits of acceptable ozone linked to a decrease in deaths, and projects that mortality is expected to decrease by reducing ozone regulatory standards.

• Journal of Environmental Science International
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• v.14 no.2
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• pp.141-156
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• 2005

The importance of atmospheric conditions for the assessment of an air pollution situation has been demonstrated by their influence on the various compartments of an air pollution system, comprising all stages from emission to effects. Especially, air pollutants dispersion phenomenon are very sensitive according to wind data. But the discussions of how to apply representative meteorological data in air pollution dispersion model are not frequent in Korean environmental assessment processes. In this study, we investigated the difference of air pollutants dispersion phenomenon using U.S EPA ISCLT3 model according to applying the different meteorological data observed at two points for Seongseo industrial complex of Daegu. Two points are the spot site of Seongseo industrial complex and Daegu meteorological observatory. The winds speed of the spot site were smaller than those of Daegu meteorological observatory. In the winter season, the differences came to about $64\%$ for the period$(I\;February\;2001\~31\;January\;2002)$. Wind directions were also fairly different at two points. The air pollutants dispersion phenomenon estimated from our numerical experiments were also fairly different owing to the meteorological conditions at two points.