• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.536-539
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• 2018

In this paper, we propose a system that analyzes environment information by using deep learning and then provides a suitable environment for users by predicting environmental information change. As the level of living improves, interest in improving the quality of life is increasing. In particular, as the air quality deteriorated due to the recent occurrence of dust, smog, fine dust, and ultrafine dust, the indoor air quality as well as the outdoor air became a serious problem. The increase of indoor pollution due to the lack of ventilation and the use of chemicals is a serious problem for modern people who have a lot of indoor living. In order to solve this indoor air pollution, a system has been proposed that measures the state of air quality through sensors and maintains proper temperature and humidity. However, existing system has a difficulty to apply most of the atmospheric environment information to various users depending on sensors only. The system proposed in this paper predicts the indoor environment by analyzing the indoor pollution information collected through the sensor using the deep learning. Then, the predicted indoor environment is modeled and learned in this system, and the environment suitable for the user is suggested. Afterwards, the system receives feedback from the user and repeats the process of re-learning the proposed environment so that it can create the optimal environment for the user.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.5
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• pp.687-696
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• 2018

In order to develop effective emission abatement strategies for coal-fired power plants, we analyzed the shutdown effects of coal-fired power plants on $PM_{2.5}$ concentration in June by employing air quality model for the period from 2013 to 2016. WRF (Weather Research and Forecast) and CMAQ(Community Multiscale Air Quality) models were used to quantify the impact of emission reductions on the averaged $PM_{2.5}$ concentrations in June over Chungcheongnam-do area in Korea. The resultant shutdown effects showed that the averaged $PM_{2.5}$ concentration in June decreased by 1.2% in Chungcheongnam-do area and decreased by 2.3% in the area where the surface air pollution measuring stations were located. As a result of this study, it was confirmed that it is possible to analyze policy effects considering the change of meteorology and emission and it is possible to quantitatively estimate the influence at the maximum impact region by utilizing the air quality model. The results of this study are expected to be useful as a basic data for analyzing the effect of $PM_{2.5}$ concentration change according to future emission changes.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1511-1519
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• 2014

The objective of this paper is to propose a modelling of a small compressed air energy storage system, which drives an induction generator based on a field-oriented control (FOC) principle for a renewable power generation. The proposed system is a hybrid technology of energy storage and electrification, which is developed to use as a small scale of renewable energy power plant. The energy will be transferred from the renewable energy resource to the compressed air energy by reciprocating air compressor to be stored in a pressurized vessel. The energy storage system uses a small compressed air energy storage system, developed as a small unit and installed above ground to avoid site limitation as same as the conventional CAES does. Therefore, it is suitable to be placed at any location. The system is operated in low pressure not more than 15 bar, so, it easy to available component in country and inexpensive. The power generation uses a variable speed induction generator (IG). The relationship of pressure and air flow of the compressed air, which varies continuously during the discharge of compressed air to drive the generator, is considered as a control command. As a result, the generator generates power in wide speed range. Unlike the conventional CAES that used gas turbine, this system does not have any combustion units. Thus, the system does not burn fuel and exhaust pollution. This paper expresses the modelling, thermodynamic analysis simulation and experiment to obtain the characteristic and performance of a new concept of a small compressed air energy storage power plant, which can be helpful in system designing of renewable energy electrification. The system was tested under a range of expansion pressure ratios in order to determine its characteristics and performance. The efficiency of expansion air of 49.34% is calculated, while the efficiency of generator of 60.85% is examined. The overall efficiency of system of approximately 30% is also investigated.

• Atmosphere
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• v.30 no.4
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• pp.439-454
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• 2020

This study investigates the change in the fine particulate matter (PM2.5) concentration and World Health Organization (WHO) air quality index (AQI) in East Asia (EA) under Shared Socioeconomic Pathways (SSPs). AQI is an indicator of increasing levels about health concern, divided into six categories based on PM2.5 annual concentrations. Here, we utilized the ensemble results of UKESM1, the climate model operated in Met Office, UK, for the analysis of long-term variation during the historical (1950~2014) and future (2015~2100) period. The results show that the spatial distributions of simulated PM2.5 concentrations in present-day (1995~2014) are comparable to observations. It is found that most regions in EA exceeded the WHO air quality guideline except for Japan, Mongolia regions, and the far seas during the historical period. In future scenarios containing strong air quality (SSP1-2.6, SSP5-8.5) and medium air quality (SSP2-4.5) controls, PM2.5 concentrations are substantially reduced, resulting in significant improvement in AQI until the mid-21st century. On the other hand, the mild air pollution controls in SSP3-7.0 tend to lead poor AQI in China and Korea. This study also examines impact of increased in PM2.5 concentrations on downward shortwave energy at the surface. As a result, strong air pollution controls can improve air quality through reduced PM2.5 concentrations, but lead to an additional warming in both the near and mid-term future climate over EA.

• Journal of Environmental Impact Assessment
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• v.22 no.1
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• pp.79-87
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• 2013

The purpose of this study is to establish PM-10 management manual for developing large scale sites by assessing the status of PM-10 reduction at ongoing large scale development sites. After analyzing the meteorological conditions and air quality characteristics of Sihwa MTV development site, ISCST3 (Industrial Source Complex Short Term Model 3) was implemented to predict PM-10 generation. The outcomes of ISCST3 modelling were utilized for verification of site survey data. As a result of applying air pollution modeling, the diffusion rate of PM-10 decreases according as the wind speed decreases. And the emission rate of PM-10 increase is linear to the concentration of PM-10. The reduction target of PM-10 can be derived quantitatively from the difference between the forecasted emission rate and the permissible emission limit of PM-10. The assessment of PM-10 characteristics which is deduced from ISCST3 and site survey can be practically applied to accomplish environmentally acceptable air quality manual for large scale development sites.

• Journal of Preventive Medicine and Public Health
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• v.40 no.5
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• pp.363-370
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• 2007

Objectives: The principal objective of this study was to determine the relationship between maternal exposure to air pollution and low birth weight and to propose a possible environmental health surveillance system for low birth weight. Methods: We acquired air monitoring data for Seoul from the Ministry of Environment, the meteorological data from the Korean Meteorological Administration, the exposure assessments from the National Institute of Environmental Research, and the birth data from the Korean National Statistical Office between January 1, 2002 and December 31, 2003. The final birth data were limited to singletons within $37{\sim}44$ weeks of gestational age. We defined the Low Birth Weight (LBW) group as infants with birth weights of less than 2500g and calculated the annual LBW rate by district. The air monitoring data were measured for $CO,\;SO_2,\;NO_2,\;and\;PM_{10}$ concentrations at 27 monitoring stations in Seoul. We utilized two models to evaluate the effects of air pollution on low birth weight: the first was the relationship between the annual concentration of air pollution and low birth weight (LBW) by individual and district, and the second involved a GIS exposure model constructed by Arc View 3.1. Results: LBW risk (by Gu, or district) was significantly increased to $1.113(95%\;CI=1.111{\sim}1.116)\;for\;CO,\;1.004(95%\;CI=1.003{\sim}1.005)\;for\;NO_2,\;1.202(95%\;CI=1.199{\sim}1.206\;for\;SO_2,\;and\;1.077(95%\;CI=1.075{\sim}1.078)\;\;for\;PM_{10}$ with each interquartile range change. Personal LBW risk was significantly increased to $1.081(95%\;CI=1.002{\sim}1.166)\;for\;CO,\;1.145(95%\;CI=1.036{\sim}1.267)\;for\;SO_2,\;and\;1.053(95%\;CI=1.002{\sim}1.108)\;for\;PM_{10}$ with each interquartile range change. Personal LBW risk was increased to $1.003(95%\;CI=0.954{\sim}1.055)\;for\;NO_2$, but this was not statistically significant. The air pollution concentrations predicted by GIS positively correlated with the numbers of low birth weights, particularly in highly polluted regions. Conclusions: Environmental health surveillance is a systemic, ongoing collection effort including the analysis of data correlated with environmentally-associated diseases and exposures. In addition. environmental health surveillance allows for a timely dissemination of information to those who require that information in order to take effective action. GIS modeling is crucially important for this purpose, and thus we attempted to develop a GIS-based environmental surveillance system for low birth weight.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1869-1880
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• 2021

Korean Journal of Remote Sensing (KJRS), leading the field of remote sensing and GIS in South Korea for over 37 years, has published interdisciplinary research papers. In this study, we performed the topic modeling based on Latent Dirichlet Allocation (LDA), a probabilistic generative model, to identify the research topics and trends using 1) the whole articles, and 2) specific articles related to natural and environmental disasters published in KJRS by analyzing titles, keywords, and abstracts. The results of LDA showed that 4 topics('Polar', 'Hydrosphere', 'Geosphere', and 'Atmosphere') were identified in the whole articles and the topic of 'Polar' was dominant among them (linear slope=3.51 × 10^-3, p<0.05) over time. For the specific articles related to natural and environmental disasters, the optimal number of topics were 7 ('Marine pollution', 'Air pollution', 'Volcano', 'Wildfire', 'Flood', 'Drought', and 'Heavy rain') and the topic of 'Air pollution' was dominant (linear slope=2.61 × 10^-3, p<0.05) over time. The results from this study provide the history and insight into natural and environmental disasters in KRJS with multidisciplinary researchers.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.5
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• pp.571-580
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• 2012

Epidemiologic studies of air pollution need accurate exposure assessments at unmonitored locations. A land use regression (LUR) model has been used successfully for predicting traffic-related pollutants, although its application has been limited to Europe, North America, and a few Asian region. Therefore, we modeled traffic-related pollutants by LUR then examined whether LUR models could be constructed using a regulatory monitoring network in Metropolitan area in Korea. We used the annual-mean nitrogen dioxide ($NO_2$) in 2010 in the study area. Geographic variables that are considered to predict traffic-related pollutants were classified into four groups: road type, traffic intensity, land use, and elevation. Using geographical variables, we then constructed a model to predict the monitored levels of $NO_2$. The mean concentration of $NO_2$ was 30.71 ppb (standard deviation of 5.95) respectively. The final regression model for the $NO_2$ concentration included five independent variables. The LUR models resulted in $R^2$ of 0.59. The mean concentration of $NO_2$ of elementary schools was 34.04 ppb (standard deviation of 5.22) respectively. The present study showed that even if we used regulatory monitoring air quality data, we could estimate $NO_2$ moderately well. These analyses confirm the validity of land use regression modeling to assign exposures in epidemiological studies, and these models may be useful tools for assessing health effects of long-term exposure to traffic related pollution.

• Journal of Environmental Impact Assessment
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• v.12 no.1
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• pp.23-34
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• 2003

The emergency response modeling system CARIS has been developed at CCSM (Center for Chemical Safety Management), NIER (National Institute of Environmental Research) to track and predict dispersion of hazardous chemicals for the environmental decision support in case of accidents at chemical or petroleum companies in Korea. The main objective of CARIS is to support making decision by rapidly providing the key information on the efficient emergency response of hazardous chemical accidents for effective approaches to risk management. In particular, the integrated modeling system in CARIS consisting of a real-time numerical weather forecasting model and air pollution dispersion model is supplemented for the diffusion forecasts of hazardous chemicals, covering a wide range of scales and applications for atmospheric information. In this paper, we introduced the overview of components of CARIS and described the operational modeling system and its configurations of coupling/integration in CARIS. Some examples of the operational modeling system is presented and discussed for the real-time risk assessments of hazardous chemicals.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.195-200
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• 2020

With the growing interest in fossil fuel depletion and environmental pollution, railroad cars operating in Korea are in progress as the conversion from diesel to electric vehicles expands. The photovoltaic system, which is applied as an example of the conversion of electric vehicles, is infinite and pollution-free, and can produce energy without generating hazards such as air pollution, noise, heat, and vibration, and maintain fuel transportation and power generation facilities. There is an advantage that is rarely needed. However, the amount of electricity produced depends on the amount of solar radiation by region, and the energy density is low due to the power generation of about 25㎡/ kWp, so a large installation area is required and the installation place has limited problems. In view of these problems, many studies have been applied to fuel cells in the railway field. In particular, the plan to link the fuel cell power generation system railroad power supply system must be linked to the power supply system that supplies power to the railroad, unlike solar and wind power. Therefore, it has a close relationship with railroad cars and the linkage method can vary greatly depending on the system topology. Therefore, in this paper, we study the validity through simulation modeling related to linkage analysis according to system topology.