• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.556-559
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• 2007

The Urban Environmental Quality (UEQ) indicates a complex and various parameters resulting from both human and natural factors in an urban area. Vegetation, climate, air quality, and the urban infrastructure may interact to produce effects in an urban area. There are relationships among air pollution, vegetation, and degrading environmental the urban heat island (UHI) effect. This study investigates the application of multi-spectral remote sensing data from the Landsat ETM and TM sensors for the mapping of air quality and UHI intensity in Seoul from 2000 to 2006 in fine resolution (30m) using the emissivity-fusion method. The Haze Optimized Transform (HOT) correction approach has been adopted for atmospheric correction on all bands except thermal band. The general UHI values (${\Delta}(T_{urban}-T_{rural})$) are 8.45 (2000), 9.14 (2001), 8.61 (2002), and $8.41^{\circ}C$ (2006), respectively. Although the UHI values are similar during these years, the spatial coverage of "hot" surface temperature (>$24^{\circ}C$) significantly increased from 2000 to 2006 due to the rapid urban development. Furthermore, high correlations between vegetation index and land surface temperature were achieved with a correlation coefficients of 0.85 (2000), 0.81 (2001), 0.84(2002), and 0.89 (2006), respectively. Air quality is shown to be an important factor in the spatial variation of UEQ. Based on the quantifiable fine resolution satellite image parameters, UEQ can promote the understanding of the complex and dynamic factors controlling urban environment.

• International Journal of Internet, Broadcasting and Communication
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• 제12권1호
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• pp.130-136
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• 2020

There are many problems that occur currently in agriculture industries. The problems such as unexpected of changing weather condition, lack of labor, dry soil were some of the reasons that may cause the growth of the plants. Condition of the weather in local area is inconsistent due to the global warming effect thus affecting the production of the crops. Furthermore, the loss of farm labor to urban manufacturing jobs is also the problem in this industry. Besides, the condition for the plant like air humidity, air temperature, air quality index, and soil moisture are not being recorded automatically which is more reason for the need of implementation system to monitor the data for future research and development of agriculture industry. As of this, we aim to provide a solution by developing IoT-based platform along with the irrigation for increasing crop quality and productivity in agriculture field. We aim to develop a smart garden system environment which the system is able to auto-monitoring the humidity and temperature of surroundings, air quality and soil moisture. The system also has the capability of automating the irrigation process by analyzing the moisture of soil and the climate condition (like raining). Besides, we aim to develop user-friendly system interface to monitor the data collected from the respective sensor. We adopt an open source hardware to implementation and evaluate this research.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 춘계학술대회 논문집
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• pp.671-674
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• 2007

With increasing concerns of indoor air quality, $CO_2$ concentration in the public transportation, such as train, bus, and subway, draws big interests. The $CO_2$ concentration in the indoor air is regarded as index of ventilation status rather than that of adverse health effect. In this study, we measured the time-series of $CO_2$ concentrations in the subway saloon at the Subway line 1 (Suwon-station to Cheongyangri-station) with the number of passengers on board. At the same time, the concentration of particulate matter (PM), temperature, and humidity were monitored. It was found that the $CO_2$ concentration was correlated linearly with number of passengers and the relation function is suggested for the prediction of $CO_2$ conecntration by the number of passengers.

• 한국환경보건학회지
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• 제44권5호
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• pp.421-432
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• 2018

Objectives: In this study, we started to develop an indoor garden integrated IoT solution based on IAQ (indoor air quality) and interconnection with an environmental database for smart management of indoor gardens. The purpose of this study was to develop and apply an integrated solution for customized air purification from an indoor garden through big data analysis using IoT technology. Methods: An IoT-based IAQ monitoring system was established in three households within a new apartment building. Based on real-time and long-term data collected, $PM_{2.5}$, $CO_2$, temperature, and humidity changes were compared to those of indoor garden applications and the analyzed results were indexed. Results As a result of the installation, all three households had no results exceeding the standard for indoor air pollution on average $PM_{2.5}$ and $CO_2$ indices. In the case of indoor garden installation, the IAQ index increased to the "Good" section after the installation, and readings in the "Bad" section shown before the installation disappeared. The comfort index also did not dip into the "Uncomfortable" section, where it had been preinstallation, and significantly lowered the average score from "Uncomfortable for sensitive groups" to "Good". Overall, the IAQ composite index for the generation of installations decreased the "Good" interval, but "Bad" did not appear. Conclusions In this study on developing an integrated solution for IAQ based on IoT indoor gardens, big data was analyzed to determine IAQ and comfort indexes and an IAQ composite index. Through this process, it became understood that it is necessary to monitor IAQ based on IoT.

• 한국환경농학회지
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• 제37권4호
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• pp.268-276
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• 2018

본 연구는 일반인에게 안전한 실내공기질 개선수단으로 인식되는 공기정화식물의 효율적 적용을 위해 실내공조에 요구되는 총풍량 확보가 가능한 식생기반 바이오필터 시스템을 제안하고자 했다. 시스템의 정량적 성능평가는 강의실형태의 실험실 체적 $332.73m^3$ 내 16명의 재실자 조건에서 목업단위 시스템의 공조 성능, 실내공기질 및 쾌적지표 개선효과에 대한 시계열 분석으로 진행되었다. 우선, 시스템 구동을 통해 총 $1,411.22m^3/h$의 유출 총풍량을 확보하여, 4.24 ACH의 환기율을 제공할 수 있었다. 실내온도는 $1.6^{\circ}C$, 흑구온도는 $1.0^{\circ}C$ 감소가 확인되었으며, 상대습도는 24.4% 상승한 최대 82.0%까지 증가하였다. 상대습도 급증에 따른 쾌적도 감소현상은 송풍기 구동에 따라 발생되는 실내기류로 상쇄되는 것으로 판단된다. 또한, 시스템 가동에 따른 공기질 개선지표 중 $PM_{10}$은 39.5% 감소한 평균 $22.11{\mu}g/m^3$을 기록하였다. 반면, $CO_2$는 최대 1,329 ppm까지 지속적으로 농도가 상승했는데, 이는 광도조건이 광보상점을 만족하지 못해 적용 식물과 재실자에서 방출되는 $CO_2$가 처리되지 못한 것으로 해석된다. 실내쾌적지표의 경우 PMV는 평균 83.6 % 감소된 -0.082, PPD는 평균 47.0% 감소된 5.41%에 수렴하여 식생기반 바이오필터 구동에 의해 높은 쾌적범위의 실내공간조성이 가능한 것으로 판단되었다. 본 연구의 한계는 소수 참여인원과 단기간 실험으로 인하여 시스템의 성능 규명이 제한적인 부분이었으며, 보다 장기간의 실험을 통해 바이오필터에 도입된 식생의 생육상태에 따른 압력손실 변화, 미세먼지 저감에 대한 구체적인 메커니즘 규명 등의 후속연구가 진행되어야 할 것이다.

• Advances in environmental research
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• 제4권4호
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• pp.219-231
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• 2015

In recent years, raising air pollutants has become as a big concern, especially in metropolitan cities such as Tehran. Therefore, forecasting the level of pollutants plays a significant role in air quality management. One of the forecasting tools that can be used is an artificial neural network which is able to model the complicated process of air pollution. In this study, we applied two different methods of artificial neural networks, the Multilayer Perceptron (MLP) and Radial Basis Function (RBF), to predict the hourly air concentrations of toluene in Tehran. Hourly temperature, wind speed, humidity and $NO_x$ were selected as inputs. Both methods had acceptable results; however, the RBF neural network produced better results. The coefficient of determination ($R^2$) between the observed and predicted data was 0.9642 and 0.99 for MLP and RBF neural networks, respectively. The results of the mean bias errors (MBE) were 0.00 and -0.014 for RBF and MLP, respectively which indicate the adequacy of the models. The index of agreement (IA) between the observed and predicted data was 0.999 and 0.994 in the RBF and the MLP, respectively which indicates the efficiency of the models. Finally, sensitivity analysis related to the MLP neural network determined that temperature was the most significant factor in air concentration of toluene in Tehran which may be due to the volatile nature of toluene.

• 한국대기환경학회지
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• 제20권4호
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• pp.523-537
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• 2004

In order to raise the accuracy of meteorological data, several numerical experiments about the usefulness of data assimilation to prediction of air pollution was carried out. Used data for data assimilation are surface meteorological components observed by Automatical Weather System with high spatial density. The usage of surface data assimilation gives changes of temperature and wind fields and the change caused by the influence of land-use on meterological simulation is more sensitive at night than noon. The data quality in assimilation it also one of the important factors to predict the meteorological field precisely and through the static IOA (Index of Agreement), simulated meteorological components with selected limited surface data assimilation are agree well with observations.

• 농촌계획
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• 제29권3호
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• pp.91-97
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• 2023

The purpose of this research is to apply the regional development attractiveness of the national level determined in the previous study to the city and county level of Chungcheongnam-do. We verified results with the population change of the floating population data. In order to measure regional development attractiveness in 2020, Chungcheongnam-do's integrated air environment index and per capita gross regional product were gathered. Population movement data over the past five years have been used to analyze population changes in the floating population data. Regional development attractiveness depended on the data of GDP per capita, which had a large difference between the maximum and minimum values. The rate of increase or decrease in population change by city and county in Chungcheongnam-do over the past five years has changed significantly since 2021 and characteristics of each group were grouped into four groups. Based on the environment and economic feasibility of the region, it can be the starting point for a new analysis of Korea's regional development projects and the selection of target sites. Policy suggestions can also be made in spatial plans such as short-term comprehensive plans, long-term comprehensive plans, and development plans. It can be a limit of this research that regional development attractiveness was determined by the relatively large per capita gross domestic product. It is necessary to further develop regional development attractiveness by closely investigating the characteristics of the region, social problems, and emissions of environmentally harmful substances.

• 한국환경보건학회지
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• 제49권2호
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• pp.78-88
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• 2023

Background: Exposure to volatile organic compounds (VOCs) can have acute and chronic health effects on human beings in general and in working environments. In particular, VOCs are often emitted in large quantities in industrial settings. In such circumstances, there is a need to improve the indoor air quality at workplaces. Objectives: The purposes of this study were to verify the effectiveness of air cleaning devices in workplaces and provide alternative solutions for improving working environments. Methods: Personal exposure and area level of VOCs for workers were evaluated in a car-part adhesive process before and after installing an air cleaning device with a TiO₂-coated filter. Passive samplers and direct reading instruments were used to collect and analyze the VOCs, and the removal efficiency and improvement of air quality were evaluated. We also calculated the exposure index (EI) to assess the risk level in the workplace. Results: The removal efficiency for VOCs through the installation of the air cleaning device was approximately 26.9~69.0% as determined by the concentration levels before and after installation. The measured substances did not exceed the exposure limits for the work environment and the EI was less than 1. However, carcinogenic substances such as benzene, formaldehyde, carbon tetrachloride, and trichloroethylene were detected. Conclusions: The application of an air cleaning device can be a solution for controlling the indoor air quality in a workplace, particularly in cases where ventilation systems cannot be installed due to process limitations.

• Journal of Sport and Applied Science
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• 제4권4호
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• pp.27-32
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• 2020

Purpose: This study sought to explore the effects of air pollution on professional sports in South Korea. Research design, data, and methodology: The dependent variable, the number of attendances, was comprised of 2013-2017 K-league, 2015-2017 KBO, 2014-2017 KBL regular season games, resulting in 1,063, 2,121, 810 individual match-level observations, respectively. With the actual data collected from each place across the country, we created a categorical variable which identify the air quality index divided into four categories by K-eco (i.e., good, moderate, unhealthy, hazardous). To analyze data, ANOVA was employed. Results: First, there was a significant group effect on K-league attendance. Second, there was a significant group effect of KBO attendance. Lastly, there was a significant group effect on KBL attendance. Conclusions: Summary of above results showed that each professional sport leagues' attendance was significantly different depending on the levels of air pollution. Implications were also discussed. Keywords: air pollution, sport spectatorship, professional sports.