• Journal of environmental and Sanitary engineering
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• v.10 no.3
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• pp.85-98
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• 1995

In order to ensure that all major cations and anions were accurately measured, the quality assurance checks of chemical analysis data by considering ion and conductivity balance of each precipitation sample were performed. To check the quality assurance of chemical analysis data, precipitation samples were collected by wet- only precipitation sampler at Seoul site and their chemical components were analyzed. By checking the problems for the screening methods of chemical analysis data used until recently, the f value expressed as the ratio of the sum of cations and anions equivalent concentration( $\Sigma $C/$\Sigma $A ) was found to be not ap priorate for data screening. Also, the scattering plot between cation and anion equivalent concentrations in each sample was found to show the general tendency of ion balance but was proved to not quantitate the standard of data screening at a set of samples of various concentration levels.4 more appropriate value was therefore required, h value is defined as (A-C)/C for C≥A and ( A-C)/A for C<4. This value was showed to check the ion balance in a viewpoint of quantitative as well as qualitative and to be useful in applying this expression to a measurement data set. However, the standard o( data screening must vary in response to the ion concentration of sample. In this study, the quality assurance of chemical analysis data was checked by considering both the ion balance evaluating by h value and the electrical conductivity. As these quality assurance checks were applied to Seoul data serf 67 valid samples were obtained. The result of statistical summary in the analytical parameter of precipitation samples collected for a certain period was found to be computed in the precipitation volume- weighted mean( VWM) rather than the arithmetic mean( AM), but PH In the VWM of hydrogen ion concentration. The annual VWM of pH values was 5.0(4.9 ∼ 5.1).

• Journal of the Korean earth science society
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• v.21 no.2
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• pp.159-167
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• 2000

We tested the randomness and estimated the degree of concentration for the earthquake occurrence in the Korean Peninsula by using the statistical methods for spatial data. For the randomness test, we applied both of the test statistics based method and the empirical distribution based method to the both of historical and instrumental seismicity data. It was found that the earthquake occurrences for historical and instrumental seismicity data are not random and clustered rather than scattered. A nonparametric density estimation method was used to estimate the concentration degree in the Peninsula. The earthquake occurrences show relatively high concentration on Seoul, Choongnam, Chonbook and Kyungbook areas for the historical seismicity data. Also,'L" shaped concentrations connecting Whanghaedo -the coast of Choongnam -the inland of Kyungbook area are revealed for the instrumental seismicity data.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2052-2057
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• 2010

In December 2006, the Ministry of Environment in Korea established the "Indoor Air Quality Management Guidelines in Public Transportation." As the items of the guideline, $CO_2$(Carbon dioxide) and PM10(Particulate matter). Therefore, the air quality inside the train is supposed to be ruled by this guideline. This study calculated the increase or decrease rate of the $CO_2$ concentration by using the data measured in accordance with flap operation. In case of flap close or open, the calculated $CO_2$ concentration variation was 6.32ppm/min. The $CO_2$ concentration prediction equation was derived from the general equation and the actual measured value are compared with the predicted $CO_2$ concentration suggested during the KyungBu high speed railway construction. The predicted value show good agreement with the measured data.

• Journal of Korean Society for Atmospheric Environment
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• v.4 no.2
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• pp.67-71
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• 1988

To estimate the probability of short term concentration of air pollution using long term arithmetic average concentration, the procedure was developed and added to Texas Climatological Model version 2. In the procedure, such statistical characteristics that frequency distribution of short term concentration may be approximated by a lognormal distribution, were applied. This procedure is capable of estimating not only highest concentration for a variety of averaging times but also concentrations for arbitrary occurrence frequency. Evaluation of the procedure with the results of short term concentrations calculated by Texas Episodic Model version 8 using the meteorological data and emission data in Seoul shows that the procedure estimates concentrations fairly well for wide range of percentiles.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.53-54
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• 2022

There is an increasing demand for prediction of asbestos concentration which has an fatal effect on human body. While demolishing asbestos, the dust scatters and makes workers be exposed to danger. Up to this date, however, factors that particularly influences have not considered in predicting asbestos concentration. Most of the studies could not quantify the distribution of asbestos. Also, they did not use nominal data on buildings as important factors. Therefore, this study aims to build an asbestos concentration prediction model by quantifying distribution of asbestos and using nominal data of buildings based on Artificial Neural Network (ANN). This model can give significant contribution of improving the safety of workers and be useful for finding effective ways to demolish asbestos in planning.

• Bulletin of the Korean Chemical Society
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• v.16 no.2
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• pp.110-112
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• 1995

A LOGIT transformation is a method to estimate IC50 values with two arbitrary concentration data when complete dose response curves(DRCs) are not available. We propose a modified LOGIT transformation (MLOGIT) which predicts IC50 values more accurately than the conventional LOGIT method.

• KIEAE Journal
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• v.4 no.4
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• pp.11-18
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• 2004

In this study, the measurement system was developed for the measurement of pollutants from building materials, and specimens were made with concrete, gypsum board, mortar and wall paper. Characteristics of VOCs and TVOC concentration and Emission Factor as a function of time were assessed, and the conclusion was drawn as follows. (1) From predicting TVOC concentration decrease of specimen 7 with the wall paper attached to the concrete, the graph may become linear by converting the value of y-axis into the log function, and the prediction equation can be expressed as $y=34906{\ast}e^{-0.0093{\ast}time}$. Moreover, chi-square value was 0.83 which is relatively high value, indicating that TVOC concentration can be properly predicted if the same materials are used indoors. (2) From predicting VOCs Emission Factor decrease of specimen 7, the prediction equation can be expressed as $EF=15111{\ast}e^{-0.0093{\ast}time}$, and chi-square value was 0.83. (3) From predicting TVOC concentration decrease of specimen 7, prediction equation can be considered to be $y=254323{\ast}(1-e^{-0.1046{\ast}time})$, and chi-square was 0.994 which is significantly high value, indicating that indoor TVOC concentration can be properly predicted if the same materials are used indoors. Furthermore, the prediction of concentration decrease using cumulative value of hourly measured concentration is considered to be more accurate than that using just hourly measured value directly. (4) From predicting Emission Factor decrease with cumulative hourly data of Emission Factor, chi-square appeared to be higher than that by just using hourly data of Emission Factor directly. Therefore, the prediction of Emission Factor with cumulative hourly data can provide more reliable prediction equation than the case by using just hourly concentration directly.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.5.1-5.14
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• 2023

Background: Perfluoroalkyl substances (PFAS) are chemicals widely used in various products in everyday life. Due to its unique strong binding force, the half-life of PFAS is very long, so bioaccumulation and toxicity to the human body are long-standing concerns. In particular, effects on kidney function have recently emerged and there are no studies on the effect of PFAS on kidney function through epidemiological investigations in Korea. From 2018 to 2020, the Korean National Environmental Health Survey (KoNEHS) cycle 4, conducted an epidemiological investigation on the blood concentration of PFAS for the first time in Korea. Based on this data, the relationship between PFAS blood concentration and kidney function was analyzed for adolescents. Methods: We investigated 5 types of PFAS and their total blood concentration in 811 middle and high school students, living in Korea and included in KoNEHS cycle 4, and tried to find changes in kidney function in relation to PFAS concentration. After dividing the concentration of each of the 5 PFAS and the total concentration into quartiles, multivariable linear regression was performed to assess the correlation with kidney function. The bedside Schwartz equation was used as an indicator of kidney function. Results: As a result of multivariable linear regression, when observing a change in kidney function according to the increase in the concentration of each of the 5 PFAS and their total, a significant decrease in kidney function was confirmed in some or all quartiles. Conclusions: In this cross-sectional study of Korean adolescents based on KoNEHS data, a negative correlation between serum PFAS concentration and kidney function was found. A well-designed longitudinal study and continuous follow-up are necessary.

• Journal of Microbiology and Biotechnology
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• v.13 no.3
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• pp.332-337
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• 2003

Enzyme kinetics data play a vital role in the design of reactors and control of processes. In the present study, kinetic studies on pectinases were carried out. Partially purified polymethylgalacturonase (PMG) and polygalacturonase (PG) were the two pectinases studied. The plot of initial rate vs. initial substrate concentration did not follow the conventional Michaelis-Menten kinetics, but substrate inhibition was observed. For PMG, maximum rate was attained at an initial pectin concentration of 3 g/l, whereas maximum rate was attained when the initial substrate concentration of 2.5 g/l of polygalacturonic acid for PG I and PG II. The kinetic data were fitted to five different kinetic models to explain the substrate inhibition effect. Among the five models tested, the combined mechanism of protective diffusion limitation of both high and inhibitory substrate concentrations (semi-empirical model) explained the inhibition data with 96-99% confidence interval.

• Journal of Korea Multimedia Society
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• v.22 no.9
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• pp.1069-1079
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• 2019

In this study, we developed a $PM_{10}$ forecasting model using DNN and Membership Function, and improved the forecasting performance. The model predicts the $PM_{10}$ concentrations of the next 3 days in the Seoul area by using the weather and air quality observation data and forecast data. The best model(RM14)'s accuracy (82%, 76%, 69%) and false alarm rate(FAR:14%,33%,44%) are good. Probability of detection (POD: 79%, 50%, 53%), however, are not good performance. These are due to the lack of training data for high concentration $PM_{10}$ compared to low concentration. In addition, the model dose not reflect seasonal factors closely related to the generation of high concentration $PM_{10}$. To improve this, we propose Julian date membership function as inputs of the $PM_{10}$ forecasting model. The function express a given date in 12 factors to reflect seasonal characteristics closely related to high concentration $PM_{10}$. As a result, the accuracy (79%, 70%, 66%) and FAR (24%, 48%, 46%) are slightly reduced in performance, but the POD (79%, 75%, 71%) are up to 25% improved compared with those of the RM14 model. Hence, this shows that the proposed Julian forecast model is effective for high concentration $PM_{10}$ forecasts.