• Journal of Korea Water Resources Association
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• v.40 no.11
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• pp.851-859
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• 2007

In this study, the chukwookee data were evaluated by applying that for the historical rainfall frequency analysis. To derive a two parameter log-normal distribution by using historical data and modem data, censored data MLE and binomial censored data MLE were applied. As a result, we found that both average and standard deviation were all estimated smaller with chukwookee data then those with only modern data. This indicates that rather big events rarely happens during the period of chukwookee data then during the modern period. The frequency analysis results using the parameters estimated were also similar to those expected. The point to be noticed is that the rainfall quantiles estimated by both methods were similar. This result indicates that the historical document records like the annals of Chosun dynasty could be valuable and effective for the frequency analysis. This also means the extension of data available for frequency analysis.

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.747-759
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• 2018

Multivariate regional frequency analysis has advantages of regional and multivariate framework as adopting a large number of regional dataset and modeling phenomena that cannot be considered in the univariate frequency analysis. To the best of our knowledge, the multivariate regional frequency analysis has not been employed for hydrological variables in South Korea. Applicability of the multivariate regional frequency analysis should be investigated for the hydrological variable in South Korea in order to improve our capacity to model the hydrological variables. The current study focused on estimating parameters of regional copula and regional marginal models, selecting the most appropriate distribution models, and estimating regional multivariate growth curve in the multivariate regional frequency analysis. Annual maximum rainfall and duration data observed at 71 stations were used for the analysis. The results of the current study indicate that Frank and Gumbel copula models were selected as the most appropriate regional copula models for the employed regions. Several distributions, e.g. Gumbel and log-normal, were the representative regional marginal models. Based on relative root mean square error of the quantile growth curves, the multivariate regional frequency analysis provided more stable and accurate quantiles than the multivariate at-site frequency analysis, especially for long return periods. Application of regional frequency analysis in bivariate rainfall-duration analysis can provide more stable quantile estimation for hydraulic infrastructure design criteria and accurate modelling of rainfall-duration relationship.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.29 no.1
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• pp.34-41
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• 2019

Objective: This study is conducted to evaluate airborne lead concentration in and around lead production plant. Methods: Airborne lead concentration was monitored simultaneously inside of the processes of lead recycling factory and outside of factory which include stack, boundary of factory and residential area 1 km and 7.5 km from factory, respectively. All samples were measured three times at 1.5 m from the ground and analyzed using inductively coupled plasma mass spectrometer, inductively coupled plasma optical emission spectrometer or flame atomic absorption spectrometer. Results: All airborne lead concentrations measured inside of factory($13.9{\mu}g/m^3-252.9{\mu}g/m^3$) and outside of factory($0.001{\mu}g/m^3-54.97{\mu}g/m^3$) showed log-normal distribution. Geometric mean lead concentration, $54.81{\mu}g/m^3$, measured inside of factory was significantly higher than outside of factory, $0.20{\mu}g/m^3$(p<0.01). Among the samples measured inside the factory, lead concentration was the highest in the refining process($59.02{\mu}g/m^3-252.9{\mu}g/m^3$). In the case of the samples outside the factory, the nearest chimney was the highest($3.84{\mu}g/m^3-54.97{\mu}g/m^3$), and the lead concentration at the farthest place, 7.5 km from the factory was the lowest($0.001{\mu}g/m^3-1.7{\mu}g/m^3$). The arithmetic lead concentration, $0.45{\mu}g/m^3$ in the residential area near the factory was below the atmospheric environment standard of $0.5{\mu}g/m^3$, but the maximum concentration of $3.4{\mu}g/m^3$ was exceeded. Conclusions: Airborne lead concentration in residential area, 1 km away from lead recycling plant, may exceed ambient air standard of $0.5{\mu}g/m^3$.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.1
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• pp.21-30
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• 2022

Objectives: The purpose of this study is to suggest an optimal method by comparing the analysis methods of work environment measurement datasets including left-censored data where one or more measurements are below the limit of detection (LOD). Methods: A computer program was used to generate left-censored datasets for various combinations of censoring rate (1% to 90%) and sample size (30 to 300). For the analysis of the censored data, the simple substitution method (LOD/2), β-substitution method, maximum likelihood estimation (MLE) method, Bayesian method, and regression on order statistics (ROS)were all compared. Each method was used to estimate four parameters of the log-normal distribution: (1) geometric mean (GM), (2) geometric standard deviation (GSD), (3) 95th percentile (X95), and (4) arithmetic mean (AM) for the censored dataset. The performance of each method was evaluated using relative bias and relative root mean squared error (rMSE). Results: In the case of the largest sample size (n=300), when the censoring rate was less than 40%, the relative bias and rMSE were small for all five methods. When the censoring rate was large (70%, 90%), the simple substitution method was inappropriate because the relative bias was the largest, regardless of the sample size. When the sample size was small and the censoring rate was large, the Bayesian method, the β-substitution method, and the MLE method showed the smallest relative bias. Conclusions: The accuracy and precision of all methods tended to increase as the sample size was larger and the censoring rate was smaller. The simple substitution method was inappropriate when the censoring rate was high, and the β-substitution method, MLE method, and Bayesian method can be widely applied.

• Analytical Science and Technology
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• v.22 no.3
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• pp.191-200
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• 2009

The aim of this study was to evaluate and establish of emission test method for liquid phase building materials such as paint, adhesive, sealant by emission cell. A small-scale emission chamber and emission cell were used to evaluate emission of TVOC from paint, adhesive, sealant. The quantity of TVOC emission were measured by a gas chromatography/mass spectrometry (GC/MS). Background concentration of TVOC was below $10{\mu}g/m^3$ in the emission chamber and cell. Air tightness and recovery in chamber and cell showed good results. The recovery of thermal desorber for toluene and n-dodecane were about 120%. The repeatability of response factor and retention time in GC/MS below 30%. The method detection limit of VOCs ranged 0.04~8.82 ng. The concentration of TVOC emission using emission cell was 1.35~1.41 times higher than emission chamber. The correlation of TVOC emission using chamber and cell method was significantly high (r=0.91~0.97).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3B
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• pp.285-293
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• 2010

Soil moisture is a key factor to control the exchange of water and energy between the surface and the atmosphere. In recent, many researches for spatial and temporal variability analyses of soil moisture have been conducted. In this study, we analyzed the spatio-temporal variability of soil moisture in Walnut Gulch Experimental Watershed, Arizona, U.S. during the Soil Moisture Experiment 2004 (SMEX04). The spatio-temporal variability analyses were performed to understand sensitivity of five observation sites with precipitation and relationship between mean soil moisture, and its standard deviation and coefficient of variation at the sites, respectively. It was identified that log-normal distribution was superior to replicate soil moisture spatial patterns. In addition, precipitation was identified as a key physical factor to understand spatio-temporal variability of soil moisure based on the temporal stability analysis. Based on current results, higher spatial variability was also observed which was agreed with the results of previous studies. The results from this study should be essential for improvement of the remotely sensed soil moisture retrieval algorithm.