• Journal of Wetlands Research
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• v.19 no.4
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• pp.383-392
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• 2017

In 2013, August and September(early) as summer and October and November as Fall the probe of eutrophication has been done at 22 sampling points from the entrance of Danghang Bay (Jinhae Bay) to Geosan reservoir. In Danghang Bay, total chlorophyll(TChl) concentration of summer was 3.7 times higher than that of fall, and sampling points closer to the center showed 1.8 times higher concentrations than sampling points near the fringe where fresh water encountered. Eutrophication Index(EI) exceeded 1 at all sampling points in Danghang Bay during summer and fall, and if other conditions for algae growth met there was a possibility red tide to bloom at any place. There was a tendency of EI to gradually increase moving up from the entrance of bay to the inner side during summer and fall. Especially there was a sudden increase by 2.3 times higher at sampling points of 13~22 (planned region as Madong reservoir) than at other points during fall. Nitrogen was a limiting nutrient for growth of algae during summer and fall in Danghang Bay, but phosphorus was a limiting nutrient during summer rainy season. During summer and fall, multiple linear regression analysis between EI and COD, DIN, and DIP showed a significant positive relationship and that DIP was the most effective variable. Whereas multiple linear regression analysis between TChl and COD, DIN, DIP, and DSi showed a significant positive relationship and that DIP was also the most effective variable during summer. There was no significant correlation between TChl and the other parameters during fall.

• Journal of the Korean GEO-environmental Society
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• v.15 no.8
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• pp.5-11
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• 2014

In this study, chemical analysis and ecotoxicity tests of leachate from disposal site for foot-and-mouth disease carcasses (FMD leachate) were conducted to collect fundamental data that will be used to develop environmental risk assessment tools for FMD leachate. For chemical analysis, concentration of $Cl^-$, $NH{_4}{^+}-N$, Korea standard method indicators for detection of leachate released from animal carcasses burial site into groundwater and NRN (Ninhydrin-Reactive Nitrogens), a newly suggested screening test indicator to detect groundwater contamination by FMD leachate, were assessed. For ecotoxicity tests, luminescent bacteria (V. fischeri), micro-algae (P. subcapitata) and water flea (D. magna) were selected as test species. Correlation analysis between the concentration of $Cl^-$, $NH{_4}{^+}-N$, NRN and the toxicity to V. fischeri was performed to identify the better indicators to monitor FMD leachate contamination. From regression analysis, the concentration of the indicators in FMD leachate contaminated sample that induced halfmaximal toxic effect to V. fischeri was evaluated. Results obtained from this study can be applied to assess the risk by FMD leachate and to establish the guideline to manage risk in relation to FMD leachate.

• Korean Chemical Engineering Research
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• v.56 no.2
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• pp.229-239
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• 2018

The purpose of this study was to effectively produce the biosugar from cell wall of lipid extracted microalgae (LEA) by using microwave-assisted pretreatment without enzymatic hydrolysis process. Response surface methodology (RSM) was applied to optimization of microwave-assisted pretreatment conditions for the production of biosugar based on enzyme-free process from LEA. Microwave power (198~702 W), extraction time (39~241 sec), and sulfuric acid (0~1.0 mol) were used as independent variables for central composite design (CCD) in order to predict optimum pretreatment conditions. It was noted that the pretreatment variables that affect the production of glucose (C6) and xylose (C5) significantly have been identified as the microwave power and extraction time. Additionally, the increase in microwave power and time had led to an increase in biosugar production. The superimposed contour plot for maximizing dependent variables showed the maximum C6 (hexose) and C5 (pentose) yields of 92.7 and 74.5% were estimated by the predicted model under pretreatment condition of 700 w, 185.7 sec, and 0.48 mol, and the yields of C6 and C5 were confirmed as 94.2 and 71.8% by experimental validation, respectively. This study showed that microwave-assisted pretreatment under low temperature below $100^{\circ}C$ with short pretreatment time was verified to be an effective enzyme free pretreatment process for the production of biosugar from LEA compared to conventional pretreatment methods.

• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.47-56
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• 1997

In this paper, remote sensing is used to estimate trophic state which is primary concern in a lake. In using remote sensing, this study estimated trophic state not with conventional method such as regression equations but with classification methods. As europhication is caused by the extraodinary proliferation of the algae, chlorophyll a and transparency are applied to remote sensing data.. Maximum Likelihood Classification and Minimum Distance Classification which are kinds of classification methods enabled trophic state to be confirmed in a lake. These are obtained as the result of applying remote sensing to classify trophic state in a lake. Firest, when we evaluate tropic state in a large area of water body, the application of remote sensing data can obtain more than 70% accuracies just in using basic classification methods. Second, in the aspect of classification, the accuracy of Minimum Distance Classification is usually better than that of Maximum Likelihood Classification. This result is caused that samples have normal distribution, but their numbers are a few to apply statistical method. Therefore, classification method is required such as artificial neural networks which are not influenced by statistical distribution. Third, this study enables the trophic state of water body to be analyzed and evaluated rapidly, periodically and visibly. Also, this study is good for forming proper countermeasure accompanying with trophic state progress extent in a lake and is useful for basic-data.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.416-416
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• 2019

육상 담수는 대기중 이산화탄소($CO_2$) 배출의 중요한 발생원으로 주목되고 있다. 하천 및 강에서 대기중으로 배출되는 $CO_2$는 전 세계 탄소순환의 핵심요소이며, 대부분의 하천과 강은 $CO_2$로 과포화 되어있다. 세계적으로 하천 및 강의 $CO_2$ 배출량은 호수 및 저수지의 배출량보다 약 5배 많은 것으로 보고되고 있으나, 국내연구에서는 연구사례가 드물다. 따라서 본 연구의 목적은 낙동강 중하류에 위치해있는 강정고령보(GGW), 달성보(DSW), 합천창녕보(HCW), 창녕함안보(CHW)에서 발생되는 순 대기 배출 플럭스(Net Atmospheric Flux, NAF)의 동적 변동 특성을 분석하고, 데이터마이닝 기법을 적용하여 쉽게 수집할 수 있는 물리적 및 수질 변수로 $CO_2$ NAF를 추정하는데 사용할 수 있는 간략한 예측 모델을 개발하는데 있다. $CO_2$ NAF는 대기-수면 경계면에서의 $CO_2$ 부분압($pCO_2$)의 차에 기체전달속도를 곱하여 산정하였으며, 기체전달속도는 Cole and Caraco(1998)가 제안한 식을 사용하였다. 담수와 해수의 탄산염 시스템에서 열역학적 화학평형을 모두 고려한 $CO_2$SYS 프로그램을 사용하여 수중의 $pCO_2$를 산정하였고, $CO_2$ NAF는 Henry의 법칙과 Fick의 1차 확산법칙을 사용하여 계산하였다. $CO_2$ NAF의 시간적 변동성에 영향을 미치는 환경요인을 평가하기 위해서 상관분석, 주성분분석(Principal Component Analysis; PCA), 단계적다중회귀모델(Step-wise Multiple Linear Regression; SMLR), 랜덤포레스트(Random Forest; RF)방법을 사용하였다. SMLR 모델은 R package인 olsrr, RF 모델은 R package인 caret, randomForest를 이용하여 분석하였다. 연구 결과, 4개 보 상류 하천구간은 조류의 성장이 활발한 일부 기간을 제외한 대부분의 기간에서 $CO_2$를 대기로 배출하는 종속영양시스템(Heterotrophic system)을 보였다. $CO_2$ NAF의 중위값은 HCW에서 최소 $391.5mg-CO_2/m^2day$, DSW에서 최대 $1472.7mg-CO_2/m^2day$였다. 모든 보에서 NAF는 pH와 강한 음의 상관관계를 보였으며, $pCO_2$와 Chl-a도 음의 상관관계를 보였다. 이는 조류가 수중에서 $CO_2$를 소비하고 pH를 증가시키기 때문이다. PCA 분석 결과, NAF와 $pCO_2$가 높은 공분산을 보였으며, pH와 Chl-a는 반대 방향으로 군집되어 상관분석과 동일한 결과를 보였다. 이 연구를 통해 개발된 SMLR 모델과 RF 모델의 Adj. $R^2$ 값은 모든 보에서 0.77 이상으로 나왔으며, $pCO_2$ 측정 데이터가 없더라도 하천의 $CO_2$ NAF를 추정하는 방법으로 사용될 수 있을 것으로 평가된다.

• Journal of the Korean GEO-environmental Society
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• v.12 no.4
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• pp.25-31
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• 2011

In this study, the experimental design methodology was applied to optimize 1,4-dioxane treatment in E-beam process. Main factor was mathematically described as a function of parameters 1,4-dioxane removal efficiencies(%), TOC removal efficiencies(%) modeled by the use of the central composite design(CCD) method among the response surface methodology(RSM). Concentration of 1,4-dioxane is designated as "$x_1$" and Irradiation intensity is designated as "$x_2$". The regression equation in coded unit between the 1,4-dioxane concentration and removal efficiencies(%) was $y=71.00-10.85x_1+20.67x_2+{1.53x_1}^2-{7.92x_2}^2-1.23x_1x_2$. The regression equation in coded unit between the 1,4-dioxane concentration and TOC removal efficiencies(%) was $y=44.48-13.25x_1+9.54x_2+{5.43x_1}^2-{1.35x_2}^2+4.45x_1x_2$. The model predictions agreed well with the experimentally observed results $R^2$(Adj) over 90%. Toxicity test using algae Pseudokirchneriella Subcapitata showed that the inhibition was reduced according to increasing an E-beam irradiation.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.12
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• pp.886-892
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• 2011

In a study on THMs formation at the distribution facilities in Seoul water supply for past 3 years from 2007 to 2009, THMs production was increased from inlet to outlet during the process in water treatment plant. However, such increased THMs amount was very small compared to THMs production formed after pre-chlorination and post chlorination. Accordingly, this study is aimed to investigate the characteristics of water quality parameters of Han River related to THMs formation in 6 water treatment plants in Seoul. The results showed that THMs and other factors such as temperature (r = 0.539~0.846) and turbidity (r = 0.421~0.863) had positive correlation while THMs had negative correlation with pH (r = -0.613~-0.800) and algae (r = -0.582~-0.901). There is no correlation between THMs and $NH_3-N$. According to the factor analysis, generally metabolite and organic matter factor $X_1$ (pH, BOD, algae), and seasonal and natural factor $X_2$ (temperature, turbidity) played an important role in the formation of THMs. Multiple regression analysis for THMs formation showed significance of regression appeared in most water systems.

• Journal of Korean Society of Environmental Engineers
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• v.37 no.5
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• pp.253-261
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• 2015

In this study, Chlorophyll-a (chl-a) prediction model and multiple parameters affecting algae occurrence in Mulgeum site were evaluated by statistical analysis using water quality, hydraulic and climate data at Mulgeum site (1998~2008). Before the analysis, control chart method and effect period of typhoon were adopted for improving reliability of the data. After data preprocessing step two methods were used in this study. In method 1, chl-a prediction model was developed using preprocessed data. Another model was developed by Method 2 using significant parameters affecting chl-a after data preprocessing step. As a result of correlation analysis, water temperature, pH, DO, BOD, COD, T-N, $NO_3-N$, $PO_4-P$, flow rate, flow velocity and water depth were revealed as significant multiple parameters affecting chl-a concentration. Chl-a prediction model from Method 1 and 2 showed high $R^2$ value with 0.799 and 0.790 respectively. Validation for each prediction model was conducted with the data from 2009 to 2010. Training period and validation period of Method 1 showed 20.912 and 24.423 respectively. And Method 2 showed 21.422 and 26.277 in each period. Especially BOD, DO and $PO_4-P$ played important role in both model. So it is considered that analysis of algae occurrence at Mulgeum site need to focus on BOD, DO and $PO_4-P$.

• Korean Journal of Ecology and Environment
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• v.46 no.4
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• pp.499-506
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• 2013

To estimate the effect of algae to particulate organic matter in the upper regions of brackish Lake Sihwa, temporal and spatial variations of particulate organic carbon (POC) and phytoplankton pigments (chlorophyll a; Chl-a, pheophytin-a; Pheo-a), and their relationships were studied at seven sites of the brackish regions from March to October 2005 and 2006. POC concentration varied from 1.0 to $76.6mgL^{-1}$ (mean $7.4mgL^{-1}$), with maximal concentrations occurring in the middle parts of the study area in spring of 2005 and 2006. Concentrations of Chl-a and Pheo-a varied from 1.3 to $942.9{\mu}gL^{-1}$ (mean $71.0{\mu}gL^{-1}$) and $1.4{\sim}1,545.5{\mu}gL^{-1}$ (mean $59.9{\mu}gL^{-1}$), respectively, and corresponded closely with variation in POC. During the study period Pheo-a concentration was 44.2% of total Chl-a, implying that non-living or inactive phytoplankton is also the important part of phytoplankton-derived POC in brackish regions of Lake Sihwa. From the positive linear relationships between POC and phytoplankton pigments (POC with Chl-a (r=0.93), total Chl-a (r=0.88), and Pheo-a (r=0.81)), it is suggested that phytoplankton was a significant component of POC in the upper regions of brackish Lake Sihwa. On the other hand, the ratios of POC/Chl-a and POC/total Chl-a (Chl-a+Pheo-a) were 82.9 and 35.9, respectively. The ratio of POC/total Chl-a is similar to those reported in previous studies, including 40~60 in estuaries. This study suggests that Pheo-a concentration is considered in estimation of POC concentration from phytoplankton pigments in aquatic systems with high content of Pheo-a, like an upper region of blackish Lake Sihwa.

• Korean Journal of Poultry Science
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• v.50 no.1
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• pp.41-50
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• 2023

Over the last decade, avian influenza (AI) has been considered an emerging disease that would become the next pandemic, particularly in countries like South Korea, with continuous animal outbreaks. In this situation, risk assessment is highly needed to prevent and prepare for human infection with AI. Thus, we developed the risk assessment matrix for a high-risk area of human infection with AI in South Korea based on the notion that risk is the multiplication of hazards with vulnerability. This matrix consisted of highly pathogenic avian influenza (HPAI) in poultry farms and the number of poultry-associated production facilities assumed as hazards of avian influenza and vulnerability, respectively. The average number of HPAI in poultry farms at the 229-municipal level as the hazard axis of the matrix was predicted using a negative binomial regression with nationwide outbreaks data from 2003 to 2018. The two components of the matrix were classified into five groups using the K-means clustering algorithm and multiplied, consequently producing the area-specific risk level of human infection. As a result, Naju-si, Jeongeup-si, and Namwon-si were categorized as high-risk areas for human infection with AI. These findings would contribute to designing the policies for human infection to minimize socio-economic damages.