• Journal of the Korean Society of Safety
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• v.11 no.2
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• pp.102-108
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• 1996

Urban air pollution has been gradually increasing by the increase of population and vehicles recently. There are shown larger effects of air pollution in Incheon city which has more than 2 million people and has heavy holding amounts ratio of transportation vehicles as compared with other cities. However, it is very difficult to predict the air quality condition of their moving pollutants. Therefore, in this study air pollution measuring model was designed to estimate the air pollution level by line sources(transprtation vehicles ) of air pollutants and to detect the $NO_x$ emission amounts in ordinary times, and it became clear that it is functionally operative.

• Journal of Environmental Impact Assessment
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• v.22 no.5
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• pp.537-546
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• 2013

In the Seoul Metropolitan Area(SMA) photochemical air pollutants, nitrogenic compound and particulate matters have increased substantially due to mobile sources, power plants and so on. Therefore 'Special Act on Seoul Metropolitan Air Quality Improvement' was enacted on 2003 in order to improve air quality in the SMA. According to the Special Act, Central and local government have developed the state implementation plan(SIP) to reduce air pollutant emissions from various local sources. One of the key elements of the SIP development is the air quality modeling since modeling results can be used to establish emissions control strategies as well as to demonstrate attainment of air quality goals for ozone, particulate matter, and so on. Air quality modeling, therefore, can be usefully utilized to investigate the effects of government's efforts according to control strategies or measures. Using the air quality model, we can determine whether the implementation plan should be revised or not. A number of questions, however, has been raised concerning accuracy, consistency and transparency of modeling results because if we do not trust modeling results, all the measures dependent on modeling becomes in vain. So, without dealing with these questions, we can not guarantee the reliability and utilizability of air quality modeling results. In this study, we tried to establish standard methodology for air quality modeling in order to ensure consistency and transparency of modeling results used in the development and evaluation of national air policy. For this purpose, we established air quality modeling guideline to provide or recommend modeling procedures, vertical and horizontal domains, input data of meteorological and air quality modeling and so on.

• Journal of Environmental Science International
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• v.7 no.6
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• pp.745-751
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• 1998

The well-mixed room model has been traditionally used to predict the concentrations of contaminants in indoor environments. However, this is inappropriate because the flow fields in many indoor environments distribute contaminants non-uniformly, due to imperfect air mixing. Thus, some means used to describe an imperfectly mixed room are needed. The simplest model that accounts for imperfect air mixing is a two-zone model. Therefore, this study on development of computer program far the two-zone model is carried out to propose techniques of estimating the concentration of contaminants in the room. To do this, an important consideration is to divide a room into two-zone, i.e. the lower and upper zone assuming that the air and contaminants are well mixed within each zone. And between the zones the air recirculation is characterized through the air exchange parameter. By this basic assumption, the equations for the conservation of mass are derived for each zone. These equations are solved by using the computational technique. The language used to develope the program is a VISUAL BASIC. The value of air exchange coefficient($f_12$) is the most difficult to forecast when the concentrations of contaminants in an imperfectly mixed room are estimated by the two-zone model. But, as the value of $f_12$ increases, the air exchange between each zone increases. When the value of $f_12$ is approximately 15, the concentrations in both zone approach each other, and the entire room may be approximately treated as a single well-mixed room. Therefore, this study is available for designing of the ventilation to improve the air quality of indoor environments. Also, the two-zone model produces the theoretical base which may be extended to the theory for the multi-zone model, that will be contributed to estimate the air pollution in large enclosures, such as shopping malls, atria buildings, atria terminals, and covered sports stadia.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.11
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• pp.631-639
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• 2013

This study derives quality checking items in Building Mechanical Systems Design Criteria, and suggests quality criteria to review BIM models in the duct system of an air conditioning system for rule-based automatic checking. First, components for the duct system of an air conditioning system were reviewed, and the quality checking items were drawn from Building Mechanical Systems Design Criteria, through assessment according to object, attribute and relationship composing the BIM model. Second, quality checking types were derived, by analyzing the quality checking items and Rule set of the Solibri Model Checker. Finally, methods of algorithm functioning for checking the BIM models for mechanical systems in computers were drawn, and Elements to comprise the quality checking criteria (rule) were suggested. This study means that that checking items are derived from domestic criteria, and a way for the development process of determining quality checking criteria (rules) is suggested.

• 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.

• Asian Journal of Atmospheric Environment
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• v.11 no.4
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• pp.235-253
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• 2017

This study was conducted for analyzing the contribution factors on ozone concentrations and its long term trends in each major city and province in Korea through several statistical methods such as simple linear regression, generalized linear model, KZ-filer, correlation matrix, Kringing method, and cluster analysis. The overall ozone levels in South Korea have been consistently increasing over the past 10 years. The ozone concentrations in Seoul, the biggest city in Korea, are the lowest in all areas with the highest increasing ratio for $95^{th}%$ ozone. It is thought that the active photochemical reaction could affect the higher ozone concentration increase. On the other hand, the ozone concentrations in Jeju are the highest in Korea with the highest increasing ratio for $5^{th}%$, $33^{th}%$, and $50^{th}%$ ozone. It is also thought that the weak $NO_x$ titration could be the reason of higher ozone concentrations in Jeju. In case of Jeju, transport related factors is the major factor affecting the ozone trend. Thus, it is assumed that the variation of ozone trend of Asian region affecting the ozone trend in Jeju, where domestic ozone photochemical reaction is less active than urban area. It is thought that the photochemical reaction plays the role of increasing of ozone concentrations in the urban area, even though the LRT affected on the increase of ozone concentrations in non-urban area.

• Asian Journal of Atmospheric Environment
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• v.11 no.4
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• pp.330-343
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• 2017

Climate change is an important issue, with many researches examining not only future climatic conditions, but also the interaction of climate and air quality. In this study, a new version of the emissions processing software tool - Python-based PRocessing Operator for Climate and Emission Scenarios (PROCES) - was developed to support climate and atmospheric chemistry modeling studies. PROCES was designed to cover global and regional scale modeling domains, which correspond to GEOS-Chem and CMAQ/CAMx models, respectively. This tool comprises of one main system and two units of external software. One of the external software units for this processing system was developed using the GIS commercial program, which was used to create spatial allocation profiles as an auxiliary database. The SMOKE-Asia emissions modeling system was linked to the main system as an external software, to create model-ready emissions for regional scale air quality modeling. The main system was coded in Python version 2.7, which includes several functions allowing general emissions processing steps, such as emissions interpolation, spatial allocation and chemical speciation, to create model-ready emissions and auxiliary inputs of SMOKE-Asia, as well as user-friendly functions related to emissions analysis, such as verification and visualization. Due to its flexible software architecture, PROCES can be applied to any pregridded emission data, as well as regional inventories. The application results of our new tool for global and regional (East Asia) scale modeling domain under RCP scenario for the years 1995-2006, 2015-2025, and 2040-2055 was quantitatively in good agreement with the reference data of RCPs.

• Journal of Environmental Impact Assessment
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• v.11 no.2
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• pp.109-116
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• 2002

The diagnostic and prognostic methods for generating 3 dimensional wind field were comparatively analyzed and 4 dimensional data assimilation (FDDA) technique by incorporating Automatic Weather System (AWS) into the prognostic methods was discussed for the urban scale air quality model. The A WS covered the urban scale grid distance of 10.6 km and 4.3 km in South Korea and Kyong-in region, respectively. This is representing that AWS for FDDA could be fairly well accommodated in prognostic model with the meso${\gamma}$~ microa scale (~5 km), indicating that the 3 dimensional wind field by FDDA technique could be a useful interpretative tool in urban area for the atmospheric environmental impact assessment.

• Journal of Korean Society for Quality Management
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• v.44 no.3
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• pp.677-688
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• 2016

Purpose: In this study, we examine the effects of circulatory diseases mortality in South Korea 2005-2013 using the air pollution index, Methods: We cluster the region of high risk mortality by SaTScan$^{TM}$9.3.1 and compare this result with the regional distribution of air pollution. We use the Geographically Weighted Regression (GWR) to consider the spatial heterogeneity of data collected by administrative district in order to estimate the model. As GWR is spatial analysis techniques utilizing the spatial information, regression model estimated for each region on the assumption that regression coefficients are different by region. Results: As a result of estimating model of the collected air pollution index, circulatory diseases mortality data combined with the spatial information, GWR was found to solve the problem of spatial autocorrelation and increase the fit of the model than OLS regression model. Conclusion: GWR is used to select the air pollution affecting the disease each year, the K-means cluster analysis discover the characteristics of the distribution of air pollution by region.

• Journal of Environmental Science International
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• v.20 no.12
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• pp.1647-1661
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• 2011

The Government had devised legislation of Special Act and drew up guidelines for improving air quality in Seoul Metropolitan area. In 2007 local government of Seoul, Incheon and Gyeonggi conducted the results of application policy by reduced air pollutants emission for the first time. Although there was reduction of air pollutant emission in each local government, it was ineffective as expected using air pollution monitoring database. Therefore we worked out a way to prepare modeling input data using the results of enforcement plan. And we simulated surface $NO_2$ and PM10 before and after decrease in air pollutants emission and examine reduction effects of air pollution according to enforcement regulation except other influence, by using MM5-SMOKE-CMAQ system. Each local government calculated the amount of emission reduction under application policy, and we developed to prepare input data so as to apply to SMOKE system using emission reduction of enforcement plan. Distribution factor of emission reduction were classified into detailed source and fuel codes using code mapping method in order to allocate the decreased emission. The code mapping method also included a way to allocate spatial distribution by CAPSS distribution. According to predicted result using the reduction of NOx emission, $NO_2$ concentration was decreased from 19.1 ppb to 18.0 ppb in Seoul. In Gyeonggi and Incheon $NO^2$ concentrations were down to 0.65 ppb and 0.68 ppb after application of enforcement plan. PM10 concentration was reduced from 18.2 ${\mu}g/m^3$ to 17.5 ${\mu}g/m^3$ in Seoul. In Gyeonggi PM10 concentration was down to 0.51 ${\mu}g/m^3$ and in Incheon PM10 concentration was decreased about 0.47 ${\mu}g/m^3$ which was the lower concentration than any other cities.