• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.1-20
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• 2022

As unmanned aerial vehicle (UAV) technology grew in popularity over the years, it was introduced for air quality monitoring. This can easily be used to estimate the sidewalk emission concentration by calculating road traffic emission factors of different vehicle types. These calculations require a simulation of the spread of pollutants from one or more sources given for estimation. For this purpose, a Gaussian plume dispersion model was developed based on the US EPA Motor Vehicle Emissions Simulator (MOVES), which provides an accurate estimate of fuel consumption and pollutant emissions from vehicles under a wide range of user-defined conditions. This paper describes a methodology for estimating emission concentration on the sidewalk emitted by different types of vehicles. This line source considers vehicle parameters, wind speed and direction, and pollutant concentration using a UAV equipped with a monocular camera. All were sampled over an hourly interval. In this article, the YOLOv5 deep learning model is developed, vehicle tracking is used through Deep SORT (Simple Online and Realtime Tracking), vehicle localization using a homography transformation matrix to locate each vehicle and calculate the parameters of speed and acceleration, and ultimately a Gaussian plume dispersion model was developed to estimate the CO, NOx concentrations at a sidewalk point. The results demonstrate that these estimated pollutants values are good to give a fast and reasonable indication for any near road receptor point using a cheap UAV without installing air monitoring stations along the road.

• New & Renewable Energy
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• v.20 no.1
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• pp.79-87
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• 2024

This study introduces a method for estimating Aerosol Optical Depth (AOD) using Broadband Aerosol Optical Depth (BAOD) derived from direct normal irradiance and meteorological factors observed between 2016 and 2017. Through correlation analyses between BAOD and atmospheric components such as Rayleigh scattering, water vapor, and tropospheric nitrogen dioxide, significant relationships were identified, enabling accurate AOD estimation. The methodology demonstrated high correlation coefficients and low Root Mean Square Errors (RMSE) compared to actual AOD₅₀₀ measurements, indicating that the attenuation effects of water vapor and the direct impact of tropospheric nitrogen dioxide concentration are crucial for precise aerosol optical depth estimation. The application of BAOD for estimating AOD₅₀₀ across various time scales-hourly, daily, and monthly-showed the approach's robustness in understanding aerosol distributions and their optical properties, with a high coefficient of determination (0.96) for monthly average AOD₅₀₀ estimates. This study simplifies the aerosol monitoring process and enhances the accuracy and reliability of AOD estimations, offering valuable insights into aerosol research and its implications for climate modeling and air quality assessment. The findings underscore the viability of using BAOD as a surrogate for direct AOD₅₀₀ measurements, presenting a promising avenue for more accessible and accurate aerosol monitoring practices, crucial for improving our understanding of aerosol dynamics and their environmental impacts.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.5
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• pp.545-557
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• 2011

The objective of this study was to estimate the trends of each pollutant using the air pollution monitoring networks data from January 2005 to December 2008 in Daegu area. Also, the spatial characteristics of each pollutant were determined using the Pearson correlation coefficients and COD (coefficients of divergence). In this study, the trends of hourly, monthly, seasonal, and total average concentrations of each pollutant for the 10 sites were analyzed. The Ihyeon site showed highest concentration for the $SO_2$, $NO_2$, and PM10}. In the case of $O_3$, the Jisan site showed highest concentration among the other sites. Also, industrial area presented highest concentration for the $SO_2$, CO, and PM10. On the other hand, $NO_2$ showed highest in commercial area. The IDW (inverse distance weighting) method was used to estimate characteristics of spatial distribution. The results provide identify spatial distribution for each pollutant. Also, the Pearson correlation coefficients and COD values provide spatial variability among the monitoring sites. The COD of each pollutant showed very low values for all of the sites pairs. On the other hand, the Pearson correlation coefficients showed high values for all of the sites pairs. Finally, analysis of spatial variability can be used to characterize the spatial uniformity and similarity of concentrations from each pollutant.

• Proceedings of the KIEE Conference
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• 2006.04b
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• pp.365-368
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• 2006

The objective of this research is to investigate usage of 3KW photovoltaic-wind power hybrid generation system composed of 500W solar power generator and 400W wind power generator in a parallel circuit. In addition, solar radiation meter and wind monitor have been installed into each generation system to obtain the practical operating data that monitored in monthly, daily and hourly. These data that are independent to weather change and location would provide adequate generation output on average and cope with emergency situation in generation system In conclusion, based on this study, it could be considered for 3KW combined generation system to be gradually propagated to houses and small-size public facilities.

• 한국태양에너지학회:학술대회논문집
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• 2011.11a
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• pp.130-133
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• 2011

This paper reports the Survey results from a field monitoring study of office occupancy densities. The field measurement of a office in Yongin was carried out from 19 September to 30 September 2011. The survey has an aim to reveal the building energy consumption relationship between occupancy densities of a realistic office and the previous studies. The results showed that hourly occupied density of the previous studies is more higher than a field survey. we investigated the effects of difference occupancy densities on annual heating and cooling energy consumption using EnergyPlus. Heating and cooling consumption was raised because of the increased occupancy density. therefore, accurately measure the occupnacy schedule is important in order to reduce excessive building energy consumption, and is an significant element to be considered in the energy simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2075-2083
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• 2016

The real time IAQ (Indoor Air Quality) management is very important for large buildings and underground facilities such as subways because poor IAQ is immediately harmful to human health. Such IAQ management requires monitoring, prediction and control in an integrated and real time manner. In this paper, we present three PM10 hourly prediction models for such realtime IAQ management as both Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models. Both MLR and ANN models show good performances between 0.76 and 0.88 with respect to R (correlation coefficient) between the measured and predicted values, but the MLR models outperform the corresponding ANN models with respect to RMSE (root mean square error).

• Bulletin of the Korean Chemical Society
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• v.35 no.4
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• pp.1149-1153
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• 2014

Real-time monitoring of hourly atmospheric radon (Rn-222) concentration was performed throughout 2011 at Gosan station, Jeju Island, one of the least polluted regions in Korea, in order to characterize the background levels, and temporal variations on diurnal to seasonal time-scales. The annual mean radon concentration for 2011 was $2527{\pm}1356$ mBq $m^{-3}$, and the seasonal cycle was characterized by a broad winter maximum, and narrow summer minimum. Mean monthly radon concentrations, in descending order of magnitude, were Oct > Sep > Feb > Nov > Jan > Dec > Mar > Aug > Apr > Jun > May > Jul. The maximum monthly mean value (3595 mBq $m^{-3}$, October), exceeded the minimum value (1243 mBq $m^{-3}$, July), by almost a factor of three. Diurnal composite hourly concentrations increased throughout the night to reach their maximum (2956 mBq $m^{-3}$) at around 7 a.m., after which they decreased to their minimum value (2259 mBq $m^{-3}$) at around 3 p.m. Back trajectory analyses indicated that the highest radon events typically exhibited long-term continental fetch over Asia before arriving at Jeju. In contrast, low radon events were generally correlated with air mass fetch over the North Pacific Ocean. Radon concentrations typical of predominantly continental, and predominantly oceanic fetch, differed by a factor of 3.8.

• Journal of Environmental Science International
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• v.24 no.8
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• pp.993-1001
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• 2015

Comparing to the other air pollutants like $SO_2$, CO, the number of exceedance of the ozone national ambient air quality standard(NAAQS) and the ozone warning increased recently in Busan. The purpose of this study is to find out the preliminary symptoms for high ozone days in Busan area. In order to find out the preliminary symptoms, the hourly ozone data at air quality monitoring stations and the hourly meterological parameters at Busan regional meteorological 2007 to 2013 were used for the analysis. Averaged daily max ozone concentration was the highest(0.055 ppm) at Noksan and Youngsuri in the ozone season from 2007 to 2013. The horizontal distributions of daily max. ozone including all stations in Busan at high ozone days(the day exceeding 0.1 ppm of ozone concentration at least one station) were classified from two to five clusters by hierarchial cluster analysis. The meteorological variables showing strong correlation with daily max. ozone were the daily mean dew point temperature, averaged total insolation, the daily mean relative humidity and the daily mean cloud amount. And the most frequent levels were $19-23^{\circ}C$ in dew point temperature, $21-24 MJ/m^2$ in total insolation on the day before, $2.6-3.0 MJ/m^2$ on the very day, 67-80% in relative humidity and 0-3 in cloud amount.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.777-788
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• 2021

Since aerosol has a relatively short duration and significant spatial variation, satellite observations become more important for the spatially and temporally continuous quantification of aerosol. However, optical remote sensing has the disadvantage that it cannot detect AOD (Aerosol Optical Depth) for the regions covered by clouds or the regions with extremely high concentrations. Such missing values can increase the data uncertainty in the analyses of the Earth's environment. This paper presents a spatial gap-filling framework using a univariate statistical method such as DCT-PLS (Discrete Cosine Transform-based Penalized Least Square Regression) and FMM (Fast Matching Method) inpainting. We conducted a feasibility test for the hourly AOD product from AHI (Advanced Himawari Imager) between January 1 and December 31, 2019, and compared the accuracy statistics of the two spatial gap-filling methods. When the null-pixel area is not very large (null-pixel ratio < 0.6), the validation statistics of DCT-PLS and FMM techniques showed high accuracy of CC=0.988 (MAE=0.020) and CC=0.980 (MAE=0.028), respectively. Together with the AI-based gap-filling method using extra explanatory variables, the DCT-PLS and FMM techniques can be tested for the low-resolution images from the AMI (Advanced Meteorological Imager) of GK2A (Geostationary Korea Multi-purpose Satellite 2A), GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI2 (Geostationary Ocean Color Imager) of GK2B (Geostationary Korea Multi-purpose Satellite 2B) and the high-resolution images from the CAS500 (Compact Advanced Satellite) series soon.

• Journal of Environmental Health Sciences
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• v.50 no.4
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• pp.257-266
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• 2024

Background: Exposure to fine particulate matter (PM_2.5) and ozone (O₃) poses potential health risks. The Indoor-to-Outdoor ratio (I/O ratio) is a valuable tool for understanding indoor air quality and identifying potential indoor sources. Objectives: The objective of this study was to determine I/O ratios of PM_2.5 and O₃ by different microenvironments and seasons in Korea. Methods: From December 2021 to November 2023, indoor concentrations of PM_2.5 and O₃ were monitored every hour in 13 microenvironments (residential indoor, office, school, restaurant, pub, café, study café, private educational institute, PC room, billiard room, screen golf center, supermarket, and shopping mall) in Korea. Hourly outdoor concentrations of PM_2.5 and O₃ were obtained from local air quality monitoring stations, provided by airkorea.or.kr. The hourly I/O ratio was calculated by the indoor and outdoor concentrations. Results: At the pub, billiard room, and PC room, the median PM_2.5 I/O ratio exceeded 1 in all seasons, except in spring at the PC room (0.9), suggesting indoor smoking as a potential cause. The median PM_2.5 I/O ratio at the restaurant exceeded 1 in winter, autumn, and summer, except for spring (0.9), indicating significant PM_2.5 emission sources in the restaurant. The median O₃ I/O ratio was below 0.5 in all seasons and microenvironments. Conclusions: This study provided useful data on relationships between indoor and outdoor pollution in various microenvironments by seasons. These I/O ratios could be applied for more accurate exposure assessment to protect health of human.