• Journal of Korean Society for Atmospheric Environment
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• v.30 no.5
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• pp.504-509
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• 2014

Twenty-five stations of the urban monitoring network in Seoul were assessed with a focus on surveillance function of the exceedances of 8-hour ozone and 24-hour $PM_{10}$ standards. The two standards were selected because their attainment rates were particularly low. Two hierarchical cluster analyses were performed to group stations with similar atmospheric environments-one using daily highest 8-hour [$O_3+NO_2$], 8-hour $O_3$ concentrations plus corresponding 8-hour $NO_2$ concentrations considering the interconversion of $O_3$ and $NO_2$, and the other using 24-hour $PM_{10}$ concentrations. An index to measure higher concentration and exceedances of the standards was introduced. Within a cluster, sufficiently high score was assigned to the trends station or the station with higher index. Scores for $O_3+NO_2$ and $PM_{10}$ of a given station were added and ranked in the descending order to determine the relative importance.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2005.04a
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• pp.363-370
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• 2005

There are approximately 2,000 metallic mines which have been abandoned in Korea. Most of the mines are located in the watershed area, which is main source of drinking water for Seoul Metropolitan area. Untreated mining wastes are remained around abandoned mines in study area. These mining wastes, flowing into farmland and stream in the downstream of abandoned mines, would cause water and soil pollution. The mining waste samples from Guedo mine, Manjung mine and Joil mine recently abandoned were collected for the evaluation of the potential of water pollution by mine waste. Index of geoaccumulation($M\"{u}ller$, 1979), fractional composition and removal efficiency of some heavy metals by different concentration of HCl treatment were analyzed. Index of geoaccumulation of Cd, Pb, Zn, Cu, Ni and Cr are 6, $4{\sim}6,\;0{\sim}6,\;4{\sim}5$, 2 and 0 respectively. Index of geoaccumulation of Cd, Pb, Zn and Cu reveals the mining wastes has high pollution pottential in the area. Organic fraction of Cu, reducible fraction of Pb, residual fraction of Ni and Zn were the most abundant fraction of heavy metals in mining wastes.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.150-150
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• 2019

The development of prolong and severe drought can directly impact on the environment, agriculture, economics and society of country. A lot of efforts have been made across worldwide in the planning, monitoring and mitigation of drought. Currently, different drought indices such as the Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) are developed and most commonly used to monitor drought characteristics quantitatively. However, it will be very meaningful and essential to develop a more effective technique for assessment and monitoring of onset and end of drought. Therefore, in this study, the hidden Markov Bayesian classifier (MBC) was employed for the assessment of onset and end of meteorological drought classes. The results showed that the probabilities of different classes based on the MBC were quite suitable and can be employed to estimate onset and end of each class for meteorological droughts. The classification results of MBC were compared with SPI and with past studies which proved that the MBC was able to account accuracy in determining the accurate drought classes. For more performance evaluation of classification results confusion matrix was used to find accuracy and precision in predicting the classes and their results are also appropriate. The overall results indicate that the MBC was effective in predicating the onset and end of drought events and can utilized for monitoring and management of short-term drought risk.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.329-329
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• 2016

Rapid urbanization has taken environmental toll on the surrounding which can be witnessed by the advent of global warming and climate change. Driven by environmental needs, Green Building Index (GBI) was established in Malaysia to drive initiative to lead the property industry towards becoming more environmental friendly. Green roofs (roof with vegetated cover) as one of the assessment criteria of GBI, are gaining attention in the Malaysian society as a versatile new environmental friendly mitigation technology. This paper evaluates the qualitative and quantitative performances of an extensive green roof at Humid Tropics Centre under local tropical climate. Simulations showed that the extensive green roof system could reduce the peak discharge up to 26% in relation to impervious brown roof. Its reduction ability decreased for storms with intense rainfall. Increment of pH was observed for the green roof runoff and the runoff water quality ranged between class I and II under Water Quality Index (WQI). High concentrations of phosphate were noticed in the runoff samples and substrates (fertilized planting soil) might be the potential contributor. Findings indicate that there was a reduction of around $1.5^{\circ}C$ for indoor temperature of the building after installation of the extensive green roof.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.725-726
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• 2005

• Ocean and Polar Research
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• v.30 no.1
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• pp.109-117
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• 2008

Application of biomarkers for assessing marine environmental health risk is a relatively new field. According to the National Research Council and the World Health Organization, biomarkers can be divided into three classes: biomarkers of exposure, biomarkers of effect, and biomarkers of susceptibility. In order to assess exposure to or effect of the environmental pollutants on marine ecosystem, the following set of biomarkers can be examined: detoxification, oxidative stress, biotransformation products, stress responses, apoptosis, physiological metabolisms, neuromuscular responses, reproductions, steroid hormones, antioxidants, genetic modifications. Since early 1990s, several biomarker research groups have developed health indices of marine organisms to be used for assessing the state of the marine environment. Biomarker indices can be used to interpret data obtained from monitoring biological effects. In this review, we will summarize Health assessment Index, Biomarker Index, Bioeffect Assessment Index and Generalized Linear Model. Measurements of biomarker responses and development of biomarker index in marine organisms from contaminated sites offer great a lot of information, which can be used in environmental monitoring programs, designed for various aspects of ecosystem risk assessment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.2
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• pp.89-97
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• 2012

This study was conducted to estimate forest site productivity and productive areas of Quercus acutissima and Quercus mongolica using environmental factors including climatic variables. Using the data set from digital forest site map and forest climatic map, a total of 42 environmental variables were regressed on site index for developing the best site index equations for Quercus acutissima and Quercus mongolica. Five to six environmental factors by species were selected as independent variables in the best site index equations. For the site index equations, three evaluation statistics (i.e., mean difference, standard deviation of difference, and standard error of difference) were applied to the test data set for the validation of the results, The site index equations fitted well to the test data set with relatively low bias and variation. As a result, it was concluded that the site index equations by species were well capable of estimating site quality. Finally, based on the site index equations, the productive areas by species were estimated by applying GIS technique to the digital forest maps. In addition, the distribution of productive areas by species was illustrated.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.781-791
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• 2022

It is crucial to provide forest fire risk forecast information to minimize forest fire-related losses. In this research, forecast models of forest fire risk at a mid-range (with lead times up to 7 days) scale were developed considering past, present and future conditions (i.e., forest fire risk, drought, and weather) through random forest machine learning over South Korea. The models were developed using weather forecast data from the Global Data Assessment and Prediction System, historical and current Fire Risk Index (FRI) information, and environmental factors (i.e., elevation, forest fire hazard index, and drought index). Three schemes were examined: scheme 1 using historical values of FRI and drought index, scheme 2 using historical values of FRI only, and scheme 3 using the temporal patterns of FRI and drought index. The models showed high accuracy (Pearson correlation coefficient >0.8, relative root mean square error <10%), regardless of the lead times, resulting in a good agreement with actual forest fire events. The use of the historical FRI itself as an input variable rather than the trend of the historical FRI produced more accurate results, regardless of the drought index used.

• Proceedings of the Optical Society of Korea Conference
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• 2009.02a
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• pp.291-292
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• 2009

Refractive index monitoring using U-shaped POF (Plastic optical fiber) in the sugar solution and salt solution were performed. The various bending losses of U-shaped POF due to the environmental refractive index changes of the measurand solution. The loss increases according to the amounts of solute in the solution which causes the refractive index change in the solution.

• Journal of Korea Water Resources Association
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• v.47 no.2
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• pp.171-182
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• 2014

The objective of this study is to evaluate the utilization of bivariate joint drought index in South Korea. In order to develop the bivariate joint drought index, in this study, Clayton copula was used to estimate the joint distribution function and the calibration method was employed for parameter estimation. Precipitation and soil moisture data were selected as input data of bivariate joint drought index for period of 1977~2012. The time series analysis, ROC (Receiver Operating Characteristic) analysis, spatial analysis were used to evaluate the bivariate joint drought index with SPI (Standardized Precipitation Index) and SSI (Standardized Soil moisture Index). As a result, SPI performed better for drought onset and SSI for drought demise. On the other hand the bivariate joint drought index captured both drought onset and demise very well. The ROC score of bivariate joint drought index was higher than that of SPI and SSI, and it also reflected the local drought situations. The bivariate joint drought index overcomes the limitations of existing drought indices and is useful for drought analysis.