• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.275-290
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• 2021

Sulfur dioxide (SO2) in the atmosphere is mainly generated from anthropogenic emission sources. It forms ultra-fine particulate matter through chemical reaction and has harmful effect on both the environment and human health. In particular, ground-level SO2 concentrations are closely related to human activities. Satellite observations such as TROPOMI (TROPOspheric Monitoring Instrument)-derived column density data can provide spatially continuous monitoring of ground-level SO2 concentrations. This study aims to propose a 2-step residual corrected model to estimate ground-level SO2 concentrations through the synergistic use of satellite data and numerical model output. Random forest machine learning was adopted in the 2-step residual corrected model. The proposed model was evaluated through three cross-validations (i.e., random, spatial and temporal). The results showed that the model produced slopes of 1.14-1.25, R values of 0.55-0.65, and relative root-mean-square-error of 58-63%, which were improved by 10% for slopes and 3% for R and rRMSE when compared to the model without residual correction. The model performance by country was slightly reduced in Japan, often resulting in overestimation, where the sample size was small, and the concentration level was relatively low. The spatial and temporal distributions of SO2 produced by the model agreed with those of the in-situ measurements, especially over Yangtze River Delta in China and Seoul Metropolitan Area in South Korea, which are highly dependent on the characteristics of anthropogenic emission sources. The model proposed in this study can be used for long-term monitoring of ground-level SO2 concentrations on both the spatial and temporal domains.

• Korean Journal of Environment and Ecology
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• v.34 no.1
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• pp.55-62
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• 2020

To estimate headwater stream temperature with seasonal variations, we analyzed precipitation, runoff and air temperature in experimental forest of Kangwon National University, Gangwon-do (2017~2018 years). The daily mean value of headwater stream temperature for spring was 6.9~17.7℃ and correlated with air temperature, that for summer and fall were 12.2~26.3℃ and 3.6~19.3℃, correlated with air temperature and runoff. Based on seasonal variations, we applied for stepwise multiple linear regression analyses to estimate headwater stream temperature with seasonal variations. The equations were headwater stream temperature(WT)_spring=(0.553×Air temperature)+(0.086×Runoff)+4.145 (R²=0.505; p<0.01), WT_summer=(0.756×Air temperature)+(-0.072×Runoff)+2.670 (R²=0.510; p<0.01), and WT_fall=(0.738×Air temperature)+(0.028×Precipitation)+2.660 (R²=0.844; p<0.01). The coefficient of determination (R²) was greater than when it was estimated by air temperature in all seasons and progressively increased from spring to winter. Therefore, we indicated difference on estimated magnitude of stepwise multiple linear regression, due to effects on headwater stream temperature of different environmental factors with seasonal variations. Furthermore, temporal factors with spatial characteristics (e.g., river versus headwater stream) could be recommended for estimating headwater stream temperature.

• Journal of Environmental Health Sciences
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• v.47 no.5
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• pp.486-495
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• 2021

Background: Particulate matter (PM) is one of the leading causes of premature death worldwide. Previous studies in South Korea have applied a relative risk calculated from Western populations when estimating the disease burden attributable to PM. However, the relative risk of PM on health outcomes may not be the same across different countries or regions. Objectives: This study aimed to estimate the premature deaths and socioeconomic costs attributable to long-term exposure to PM in South Korea. We considered not only the difference in PM concentration between regions, but also the difference in relative risk. Methods: National monitoring data of PM concentrations was obtained, and missing values were imputed using the AERMOD model and linear regression model. As a surrogate for relative risk, hazard ratios (HRs) of PM for cardiovascular and respiratory mortality were estimated using the National Health Insurance Service-National Sample Cohort. The nation was divided into five areas (metropolitan, central, southern, south-eastern, and Gangwon-do Province regions). The number of PM attributable deaths in 2018 was calculated at the district level. The socioeconomic cost was derived by multiplying the number of deaths and the statistical value of life. Results: The average PM₁₀ concentration for 2014~2018 was 45.2 ㎍/m³. The association between long-term exposure to PM₁₀ and mortality was heterogeneous between areas. When applying area-specific HRs, 23,811 premature deaths from cardiovascular and respiratory disease in 2018 were attributable to PM₁₀ (reference level 20 ㎍/m³). The corresponding socioeconomic cost was about 31 trillion won. These estimated values were higher than that when applying nationwide HRs. Conclusions: This study is the first research to estimate the premature mortality caused by long-term exposure to PM using relative risks derived from the national population. This study will help precisely identify the national and regional health burden attributed to PM and establish the priorities of air quality policy.

• Investigative Magnetic Resonance Imaging
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• v.26 no.2
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• pp.104-116
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• 2022

The purpose of this study is to systematically determine an optimal percentile cut-off in histogram analysis for calculating the mean parameters obtained from a non-Gaussian continuous-time random-walk (CTRW) diffusion model for differentiating individual glioma grades. This retrospective study included 90 patients with histopathologically proven gliomas (42 grade II, 19 grade III, and 29 grade IV). We performed diffusion-weighted imaging using 17 b-values (0-4000 s/mm²) at 3T, and analyzed the images with the CTRW model to produce an anomalous diffusion coefficient (D_m) along with temporal (𝛼) and spatial (𝛽) diffusion heterogeneity parameters. Given the tumor ROIs, we created a histogram of each parameter; computed the P-values (using a Student's t-test) for the statistical differences in the mean D_m, 𝛼, or 𝛽 for differentiating grade II vs. grade III gliomas and grade III vs. grade IV gliomas at different percentiles (1% to 100%); and selected the highest percentile with P < 0.05 as the optimal percentile. We used the mean parameter values calculated from the optimal percentile cut-offs to do a receiver operating characteristic (ROC) analysis based on individual parameters or their combinations. We compared the results with those obtained by averaging data over the entire region of interest (i.e., 100th percentile). We found the optimal percentiles for D_m, 𝛼, and 𝛽 to be 68%, 75%, and 100% for differentiating grade II vs. III and 58%, 19%, and 100% for differentiating grade III vs. IV gliomas, respectively. The optimal percentile cut-offs outperformed the entire-ROI-based analysis in sensitivity (0.761 vs. 0.690), specificity (0.578 vs. 0.526), accuracy (0.704 vs. 0.639), and AUC (0.671 vs. 0.599) for grade II vs. III differentiations and in sensitivity (0.789 vs. 0.578) and AUC (0.637 vs. 0.620) for grade III vs. IV differentiations, respectively. Percentile-based histogram analysis, coupled with the multi-parametric approach enabled by the CTRW diffusion model using high b-values, can improve glioma grading.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.377-385
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• 2024

We investigated the effect of spectral fitting wavelength interval variations and selection of absorption cross-section on the sulfur dioxide slant column density (SCD) retrievals from the scattered sunlight observation using a UV-Vis hyperspectral instrument. The sulfur dioxide slant column densities were retrieved from the combinations of multiple spectral fitting intervals and absorption cross-sections. The observation was carried out at the site 0.53 km away from a combustion site located in Gimhae from December 1, 2023, to January 23, 2024. The radiances were obtained on the line of measurement sight toward the stack of the combustion facility. The best spectral fitting intervals were found to be from 305.7 to 321.1 nm. In terms of the absorption cross-section dependency, the SO₂ (293 K), O₃ (223 K, 243 K) show the best spectral fitting for the observed radiances with both the smallest fitting residual and SCD error. The effects of the fitting interval and cross sections found in this study can be useful information for improving SO₂ retrievals based on UV hyperspectral measurements.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.149-153
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• 2009

Physics-based distributed rainfall-runoff models are now commonly used in a variety of hydrologic applications such as to estimate flooding, water pollutant transport, sedimentation yield and so on. Moreover, it is not surprising that GIS has become an integral part of hydrologic research since this technology offers abundant information about spatial heterogeneity for both model parameters and input data that control hydrological processes. This study presents the development of a distributed rainfall-runoff prediction system for the Guem river basin ($9,835km^2$) using an Object-oriented Hydrological Modeling System (OHyMoS). We developed three types of element modules: Slope Runoff Module (SRM), Channel Routing Module (CRM), and Dam Reservoir Module (DRM) and then incorporated them systemically into a catchment modeling system under the OHyMoS. The study basin delineated by the 250m DEM (resampled from SRTM90) was divided into 14 midsize catchments and 80 sub-catchments where correspond to the WAMIS digital map. Each sub-catchment was represented by rectangular slope and channel components; water flows among these components were simulated by both SRM and CRM. In addition, outflows of two multi-purpose dams: Yongdam and Daechung dams were calculated by DRM reflecting decision makers' opinions. Therefore, the Guem river basin rainfall-runoff modeling system can provide not only each sub-catchment outflow but also dam inand outflow at one hour (or less) time step such that users can obtain comprehensive hydrological information readily for the effective and efficient flood control during a flood season.

• Journal of Korean Society on Water Environment
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• v.32 no.6
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• pp.589-599
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• 2016

Implemented since 2004, TPLC (Total Pollution Load Control) is the most powerful water-quality protection program. Recently, uncertainty of prediction using steady state model increased due to changing water environments, and necessity of a dynamic state model, especially the watershed model, gained importance. For application of watershed model on TPLC, it needs to be feasible to adjust the relationship (mass-balance) between discharged loads estimated by technical guidance, and arrived loads based on observed data at the watershed outlet. However, at HSPF, simulation is performed as a semi-distributed model (lumped model) in a sub-basin. Therefore, if the estimated discharged loads from individual pollution source is directly entered as the point source data into the RCHRES module (without delivery ratio), the pollutant load is not reduced properly until it reaches the outlet of the sub-basin. The hypothetic RCHRES generated using the HSPF BMP Reach Toolkit was applied to solve this problem (although this is not the original application of Reach Toolkit). It was observed that the impact of discharged load according to spatial distribution of pollution sources in a sub-basin, could be expressed by multi-segmentation of the hypothetical RCHRES. Thus, the discharged pollutant load could be adjusted easily by modification of the infiltration rate or characteristics of flow control devices.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.8
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• pp.1103-1112
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• 2001

The effect of pressure gradients on the hairpin structures in three different turbulent boundary layers (ZPG : Re(sub)$\theta$=910, FPG : Re(sub)$\theta$=575, APG : Re(sub)$\theta$=1290) has been examined with instantaneous velocity fields obtained in streamwise-wall-normal planes using PIV (particle image velocimetry) method. In the outer layer hairpin vortices occur in streamwise-aligned packets that propagate with small velocity dispersion. The signature pattern of the hairpin consists of a spanwise vortex core located above a region of strong second quadrant fluctuation (u<0 and v>0 : Q2 event) is clearly observed. The formation of packets explains the occurrence of multiple VITA events in turbulent burst. Noticeable differences are found in the average inclination angles of hairpin vortex packets which are 45$^{\circ}$, 35.7$^{\circ}$, and 51.9$^{\circ}$in the case of ZPG, FPG and APG, respectively. It is found that the large, time-varying, irregularly shaped zones with nearly constant streamwise momentum exist throughout the boundary layer. Within the interior of the envelope the spatial coherence between the velocity fields induced by the individual vortices leads to strongly retarded streamwise momentum, explaining the zones of uniform momentum. The formation of the uniform momentum zone is remarkably different with respect to the pressure gradients especially in the logarithmic layer.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.1
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• pp.17-25
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• 2019

An intake of Aircraft becomes S-shaped geometry due to spatial limitation or procuring survivability. But curvature of the S-shaped geometry makes secondary flow or flow separation which is the cause of non-uniform pressure distribution. In this study, boundary layer suction is applied to RAE M 2129 S-Duct by attaching sub duct. Design variable is suction location and angle. A mass flow rate drawn out by suction at the sub duct outlet is constant over every model. A grid dependency test was conducted to verify validity of computation. The comparison among the CFD (Computation Fluid Dynamics), ARA experimental result, and ARA computation result of non-dimensional pressure distribution on the Port side and Starboard Side confirmed the validity of CFD. In this study, Distortion Coefficient was used for evaluating aerodynamic performance of S-Duct. The analysis, which was about flow separation, vortex, mass flow rate distribution, and pressure distribution were also investigated. Maximum 26.14% reduction in Distortion Coefficient was verified.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.3
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• pp.19-34
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• 2022

This study was conducted to provide basic data that can be used when establishing Net Zero policies and implementation plans for non-urban settlements by quantitatively analyzing the Net Zero contribution to green infrastructure in rural areas corresponding to non-urban settlements. The main purpose is to first, systematize green infrastructure in rural areas, secondly derive basic units for each element of green infrastructure, and thirdly quantify and present the impact on Net Zero in Korea using these. In this study, CVR(Content Validity Ration) analysis was performed to verify the adequacy of green infrastructure elements in rural areas derived through research and analysis of previous studies, is as follows. First, Hubs of Green infrastructure in rural area include village forests, wetlands, farm land, and smart farms with a CVR value of .500 or higher. And Links of Green infrastructure in rural area include streams, village green areas, and LID (rainwater recycling). Second, the basic unit for each green infrastructure element was presented by classifying it into minimum, maximum, and median values using the results of previous studies so that it could be used for spatial planning and design for Net Zero. Third, when Green infrastructure in rural areas is applied to non-urban settlements in Korea, it is analyzed that it has the effect of indirectly reducing CO₂ by at least 70.76 million tons and up to 141.16 million tons. This is 3.4 to 6.7 times the amount of CO₂ emission from the agricultural sector in 2019, and it can be seen that the contribution to Net Zero is very high. It is expected to greatly contribute to the transformation of the ecosystem. This study quantitatively presented the carbon-neutral contribution to settlements located in non-urban areas, and by deriving the carbon reduction unit for each element of green infrastructure in rural areas, it can be used in spatial planning and design for carbon-neutral at the village level. It has significance as a basic research. In particular, the basic unit of carbon reduction for each green infrastructure factors will be usable for Net Zero policy at the village level, presenting a quantitative target when establishing a plan, and checking whether or not it has been achieved. In addition, based on this, it will be possible to expand and apply Net Zero at regional and city units such as cities, counties, and districts.