• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.953-966
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• 2022

Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.851-861
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• 2022

In this study, we analyzed the effects of trees planted in urban areas on PM_2.5 reduction using a computational fluid dynamics (CFD) model. For realistic numerical simulations, the meteorological components(e.g., wind velocity components and air temperatures) predicted by the local data assimilation and prediction system (LDAPS), an operational model of the Korea Meteorological Administration, were used as the initial and boundary conditions of the CFD model. The CFD model was validated against, the PM_2.5 concentrations measured by the sensor networks. To investigate the effects of trees on the PM_2.5 reduction, we conducted the numerical simulations for three configurations of the buildings and trees: i) no tree (NT), ii) trees with only drag effect (TD), and iii) trees with the drag and dry-deposition effects (DD). The results showed that the trees in the target area significantly reduced the PM_2.5 concentrations via the dry-deposition process. The PM_2.5 concentration averaged over the domain in DD was reduced by 5.7 ㎍ m^-3 compared to that in TD.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1341-1352
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• 2023

The normalized difference vegetation index (NDVI) derived from satellite images is a crucial tool to monitor forests and agriculture for broad areas because the periodic acquisition of the data is ensured. However, optical sensor-based vegetation indices(VI) are not accessible in some areas covered by clouds. This paper presented a synthetic aperture radar (SAR) based approach to retrieval of the optical sensor-based NDVI using machine learning. SAR system can observe the land surface day and night in all weather conditions. Radar vegetation indices (RVI) from the Sentinel-1 vertical-vertical (VV) and vertical-horizontal (VH) polarizations, surface elevation, and air temperature are used as the input features for an automated machine learning (AutoML) model to conduct the gap-filling of the Sentinel-2 NDVI. The mean bias error (MAE) was 7.214E-05, and the correlation coefficient (CC) was 0.878, demonstrating the feasibility of the proposed method. This approach can be applied to gap-free nationwide NDVI construction using Sentinel-1 and Sentinel-2 images for environmental monitoring and resource management.

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.221-229
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• 2022

This study was aimed to investigate spatial and vertical characteristics of greenhouse environments according to the location of the environmental sensors, and to investigate the correlations between temperature, light intensity, and carbon dioxide (CO₂) concentration according to the type of greenhouse. Temperature, relative humidity (RH), CO₂, and light sensors were installed in the four-different vertical positions of the whole canopy as well as ground and roof space at the five spatial locations of the Venlo greenhouse. Also, correlations between temperature, light intensity, and CO₂ concentration in Venlo and semi-closed greenhouses were analyzed using the Curve Expert Professional program. The deviations among the spatial locations were larger in the CO₂ concentration than other environmental factors in the Venlo greenhouse. The average CO₂ concentration ranged from 465 to 761 µmol·mol^-1 with the highest value (646 µmol·mol^-1) at the Middle End (4ME) close to the main pipe (50Ø) of the liquefied CO₂ gas supply and lowest (436 µmol·mol^-1) at the Left Middle (5LM). The deviation among the vertical positions was greater in temperature and relative humidity than other environments. The time zone with the largest deviation in average temperature was 2 p.m. with the highest temperature (26.51℃) at the Upper Air (UA) and the lowest temperature (25.62℃) at the Lower Canopy (LC). The time zone with the largest deviation in average RH was 1 p.m. with the highest RH (76.90%) at the LC and the lowest RH (71.74%) at the UA. The highest average CO₂ concentration at each hour was Roof Air (RF) and Ground (GD). The coefficient of correlations between temperature, light intensity, and CO₂ concentration were 0.07 for semi-closed greenhouse and 0.66 for Venlo greenhouse. All the results indicate that while the CO₂ concentration in the greenhouse needs to be analyzed in the spatial locations, temperature and humidity needs to be analyzed in the vertical positions of canopy. The target CO₂ fertilization concentration for the semi-closed greenhouse with low ventilation rate should be different from that of general greenhouses.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.1
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• pp.329-336
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• 2013

The infrastructure of flexible pavement is composed of aggregate subbase, anti-frost layer, and subgrade. In particular, the subgrade performance is affected by climates such as frost action and precipitation. The method of TDR(Time Domain Reflectometry) sensors to measure moisture contents in subgrade layer has been used in the research. Due to the TDR method using dielectric permitivity of soil and water, the sensors can be affected by the low subgrade temperatures. The air temperatures frequently drops below $-20^{\circ}C$ in the winter in Korea. As a result, it is necessary to estimate the accuracy of the TDR moisture sensors in the range of below zero temperatures. In this study, the subgrade temperatures of lower than $-2^{\circ}C$ were extended to evaluate temperature sensitivity of the TDR moisture sensors. The test results revealed that the moisture contents around the sensors were reduced while those of the upper part of specimen showed a tendency to increase as the specimen surface temperature drops below zero under the volumetric moisture contents(VMC) of 20% and 30%. However, the impact of temperature on the function of the sensor at lower water contents was found to be negligible if any.

• Journal of Korean Society of Environmental Engineers
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• v.35 no.2
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• pp.137-143
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• 2013

This study is to develop the production method of stepwise dilution gas for the evaluation of complex odor concentration by orifice tube. The basic orifice tube for 10 and 30 times of dilution sample was made at first, and with the combination of the basic orifice tubes we can continuously manufacture the stepwise dilution sample gas for air dilution sensory test ; 10, 30, 100, 300, 1,000, 3,000 times etc. The hole size of orifice tube was 0.84 mm for 10 times of dilution sample, and was 0.34 mm for 30 times. Dilution sample gas made with the basic orifice tube have an excellent reproducibility, 2%RSD. In addition, over 90% of correlation was shown between the sample made by the orifice tube and the sample by the syringe dilution method. Because there was no concentration drift of dilution gas with changes of connected pump flow, the basic orifice tube could be mounted directly with a vacuum suction box, and could be used simply as a tool for the evaluation of odor, especially on site.

• Journal of Environmental Health Sciences
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• v.47 no.6
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• pp.521-529
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• 2021

Background: The coronavirus disease (COVID-19) has caused changes in human activity, and these changes may possibly increase or decrease exposure to fine dust (PM_2.5). Therefore, it is necessary to evaluate the exposure to PM_2.5 in relation to the outbreak of COVID-19. Objectives: The purpose of this study was to compare and evaluate the exposure to PM_2.5 concentrations by the variation of dynamic populations before and after the outbreak of COVID-19. Methods: This study evaluated exposure to PM_2.5 concentrations by changes in the dynamic population distribution in Guro-gu, Seoul, before and after the outbreak of COVID-19 between Jan and Feb, 2020. Gurogu was divided into 2,204 scale standard grids of 100 m×100 m. Hourly PM_2.5 concentrations were modeled by the inverse distance weight method using 24 sensor-based air monitoring instruments. Hourly dynamic population distribution was evaluated according to gender and age using mobile phone network data and time-activity patterns. Results: Compared to before, the population exposure to PM_2.5 decreased after the outbreak of COVID-19. The concentration of PM_2.5 after the outbreak of COVID-19 decreased by about 41% on average. The variation of dynamic population before and after the outbreak of COVID-19 decreased by about 18% on average. Conclusions: Comparing before and after the outbreak of COVID-19, the population exposures to PM_2.5 decreased by about 40%. This can be explained to suggest that changes in people's activity patterns due to the outbreak of COVID-19 resulted in a decrease in exposure to PM_2.5.

• Korean Journal of Environmental Agriculture
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• v.17 no.3
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• pp.260-267
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• 1998

This experiment used the enclosed bench-scale reactors of 242 liters was conducted to obtain basic data on temporal and spatial variations in temperature, oxygen and moisture content, which were important factors of biological activities, during composting of mixture of dairy manure and rice straw. The reactors with thermocouples, oxygen sensor and datalogger were aerated at four different rates of 0.09, 0.18, 0.90 and 1.79 l $min^{-1}kg$ dry $solids^{-1}$. The higher aeration rates were, the faster the rates of increase and decrease in composting temperature were in both of initial and turnover stage, and the smaller the temperature difference between exhaust air and composting materials. Composting temperature of initial stage increased suddenly in all aeration rates, then stationary phase of temperature in materials and exhaust air showed at $50{\sim}53^{\circ}C$ for 5 hours and at $45^{\circ}C$ between 5 and 15 hours, respectively. In initial stage the maximum temperature was decreased with increasing aeration rates but in the stage after turnover it was the opposite except for 1.79 l $min^{-1}kg^{-1}$. Time arrived at the maximum temperature of composting materials was later in low-aeration rates than high-aeration rates at both stages. Time maintained high-temperature more than $45^{\circ}C$ was rapidly decreased with increasing aeration rates. In initial stage of composting maintaining time of $65^{\circ}C$ or more was the longest in the treatments of 0.09 and 0.18 l $min^{-1}kg{-1}$, while those of $55{\sim}65^{\circ}C$ and $45{\sim}55^{\circ}C$ was in 0.90 and 1.79 l $min^{-1}kg{-1}$, respectively. The minimum oxygen content and the maximum oxygen consumption rate in exhaust air through composting materials showed the increased trends with increasing aeration rates. In initial stage the minimum oxygen content was ranged from 0.9% to 7.4% for 32 to 59.5 hours and the maximum oxygen consumption rate was $1.89{\sim}6.48$ $gh^{-1}kgVS^{-1}$. In the stage after turnover their levels were $2.1{\sim}19.9%$ and $1.76{\sim}3.49 %$g/h-㎏ VS, respectively, for 16 to 49.5 hours.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.13 no.2
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• pp.1-7
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• 2010

The study objective was to compare the interior greening volume ratios for the change in concentration of fine particle, temperature and relative humidity, and to identify the level of interior landscape volume ratio as a suitable condition to achieve the desired indoor properties. Plants were moved into a room (88m3) randomly. After moving, the volume ratio of the interior greening level was set at 0%, 1%, 2% and 3%. The concentration of fine particles was measured with a mini-volume portable air sampler (Air Metrics, USA). The temperature and relative humidity were recorded with a digital sensor (Kiwi-LTH, USA) during the experiment under different volume ratios with three replications. 1. The results of the change in concentration of the fine particles revealed a trend towards an increased volume ratio of interior greening with decreasing concentration of fine particles, compared to non-plants (0%). The concentration of fine particles at volume ratios of 0%, 1%, 2% and 3% was 55ug/$m^3$, 233ug/$m^3$, 40ug/$m^3$ and 30ug/$m^3$, respectively. 2. The change in temperature, at volume ratios of 0%, 1%, 2% and 3% was $21.2^{\circ}C$, $17.4^{\circ}C$, $16.7^{\circ}C$ and $18.9^{\circ}C$, respectively, in near interior greening, and $22.1^{\circ}C$, $18.7^{\circ}C$, $18.4^{\circ}C$ and $20.5^{\circ}C$ respectively, at a distance of 3m from the interior greening. These study results suggested that temperature was affected by volume ratio and distance from the interior greening. 3. The relative humidity, at volume ratios of 0%, 1%, 2% and 3% was 34.2%, 32.5%, 36.7%, and 46.9%, respectively, in near interior greening, and 31.2%, 26.9%, 31.4% and 38.3%, respectively, at a distance of 3m from the interior greening. With increasing volume ratio of interior landscape, there were positive and significant results between the distance difference and the relative humidity more than temperature.

• Journal of Environmental Health Sciences
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• v.45 no.1
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• pp.1-8
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• 2019

Objectives: The purpose of this study was to estimate the ventilation rate of residential homes in Korea through tracer gas methods using indoor and outdoor concentrations of carbon dioxide ($CO_2$) and $CO_2$ generation rates from breathing. Methods: In this study, we calculated the number of occupants in a home by time through data on the average number of people per household from the Korean National Statistical Office and also measured the amount of $CO_2$ generation by breathing to estimate the indoor $CO_2$ generation rate. To estimate the ventilation rate, several factors such as the $CO_2$ generation rate and average volume of residential house provided by the Korean National Statistical Office, indoor $CO_2$ concentrations measured by sensors, and outdoor $CO_2$ concentrations provided by the Korea Meteorological Administration, were applied to a mass balance model for residential indoor environments. Results: The average number of people were 2.53 per household and Koreans spend 61.0% of their day at home. The $CO_2$ generation rate from breathing was $13.9{\pm}5.3L/h$ during sleep and $15.1{\pm}5.7L/h$ in a sedentary state. Indoor and outdoor $CO_2$ concentrations were 849 ppm and 407 ppm, respectively. The ventilation rate in Korean residential houses calculated by the mass balance model were $42.1m^3/h$ and 0.71 air change per hour. Conclusions: The estimated ventilation rate tended to increase with an increase in the number of occupants. Since sensor devices were used to collect data, sustainable data could be collected to estimate the ventilation rate of Korean residential homes, which enables further studies such as on changes in the ventilation rate by season resulting from the activities of occupants. The results of this study could be used as a basis for exposure and risk assessment modeling.