• Journal of the Korean Ceramic Society
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• v.53 no.1
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• pp.1-6
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• 2016

In this year, Koreans have a shortage in agricultural and drinking water due to severe algal blooms generated in major lakes. Waste oyster shells were obtained from temporary storage near the workplace at which oysters were separated from their shells. Heating ($1000^{\circ}C$ for 1 h in air) was employed to convert raw oyster shell powders into calcium oxide powders that reacted efficiently with phosphorus and nitrogen to remove algal blooms from eutrophicated wastewater. As the dispersed amount of heated oyster shell powders was increased, water clarity and visual light penetration were improved. Coagulation, precipitation and carbonation process of the heated oyster shell powders in a water purifier facilitated removal of eutrophication nutrient such as phosphorus and nitrogen, which is both beneficial and economically viable. $CO_2$ implantation by carbonation treatment not only produced thermodynamically stable CaO in oyster shells to derive precipitated calcium carbonate (PCC) but also accelerated algal removal by activation of coagulation and precipitation process. The use of oyster shell powders led to a mean reduction of 97% in total phosphate (T-P), a mean reduction of 91% in total nitrogen (T-N) and a maximum reduction of 51% in chemical oxygen demand (COD), compared with the total pollutant load of raw algal solution. Remarkable water quality improvement of algal removal by heated oyster shell powders and PCC carbonation treatment will allow utilization as water resources to agricultural or industrial use.

• Journal of Ocean Engineering and Technology
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• v.22 no.5
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• pp.7-24
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• 2008

Masan-Jinhae Bay, in Korea, is known for its frequent algal bloom outbreaks. This study was conducted in order to examine the environmental characteristics of the area, with the aim of identifying indicators that could be used to speculate about future algal blooms. The water temperatures and salinities in Haengam Bay, one of the small inner bays within Jinhae, appeared to re relatively higher than those in Masan and Jinhae bays, across most seasons. Furthermore, stratification begins to develop in all three regions from spring to summer as a result of the local heating effects and an increase in the efficient from the surrounding land. As a result, anoxic conditions appear near the bottom layer of the bay, leading to the deterioration of water quality, which has been identified as one of the causes of bloom outbreaks. Compared to Haengam and Jinhae bays, concentrations of DIN and DIP were remarkably higher in Masan Bay. However, the mean ratio of DIN to DIP was 3.3$\sim$13.6 in all three regions throughout the year, suggesting that nitrogen can function as a growth-limiting factor for phytoplankton. The results of mathematical models showed that cumulative organic pollutants may be a trigger for direct algal bloom occurrences, since residual tidal currents appeared to be less than $3\;cm\;\cdot\;s^{-1}$. Furthermore, computed DO concentrations in the four small inner bays of Jinhae during the summer appeared to be $3\;cm\;\cdot\;l^{-1}$ indicating a hypoxic state. Likewise, computed Chl-a concentrations turned out to be more than $0.01\;mg\;\cdot\;l^{-1}$, indicating eutrophication across most seasons. Based on the overall results, Masan-Jinhae Bay appeared to possess a very high potential for algal bloom outbreaks at anytime during the year.

• ALGAE
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• v.26 no.2
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• pp.181-192
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• 2011

Ballasting and deballasting of shipping vessels in foreign ports have been reported worldwide as a vector of introduction of non-native aquatic plants and animals. Recently, attention has turned to ballast water as a factor in the global increase of harmful algal blooms (HABs). Many species of microalgae, including harmful dinoflagellate species, can remain viable for months in dormant benthic stages (cysts) in ballast sediments. Over a period of four years, we surveyed ballast water and sediment of ships docked in two ports of Tampa Bay, Florida, USA. Sampling conditions encountered while sampling ballast water and sediments were vastly different between vessels. Since no single sample collection protocol could be applied, existing methods for sampling ballast were modified and new methods created to reduce time and labor necessary for the collection of high-quality, qualitative samples. Five methods were refined or developed, including one that allowed for a directed intake of water and sediments. From 63 samples, 1,633 dinoflagellate cysts and cyst-like cells were recovered. A native, cyst-forming, harmful dinoflagellate, Alexandrium balechii (Steidinger) F. J. R. Taylor, was collected, isolated, and cultured from the same vessel six months apart, indicating that ships exchanging ballast water in Tampa Bay have the potential to transport HAB species to other ports with similar ecologies, exposing them to non-native, potentially toxic blooms.

• ALGAE
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• v.19 no.4
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• pp.321-327
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• 2004

The literature review on the dynamics of the phytoplankton communities in terms of species composition, standing crops, abundant species and dominant species in the lower part of the Han River from 1940s to 2000s was conducted for the prospective prediction of their succession patterns. Total of 326 taxa were identified and they belonged to 47 blue-green algae, 139 green algae, 12 euglenoids, 126 diatoms, 6 din flagellates and 2 silicoflagellates. Composition of phytoplankton communities were 83.6% diatoms, 10.5% blue-green algae and 5.3% green algae in the middle of 1960s, whereas those were 43.2% diatoms, 40.7% green algae and 13.6% blue-green algae in the 1990s. Before 1990s, Synedra ulna, Melosira varians, Cymbella tumida, Synedra acus, Cymbella ventricosa, Navicula cryptocephala, Nitzschia palea, Aulacoseira granulata, Gomphonema parvulum and Cymbella affinis were most frequent, while those after 1990 were Asterionella formosa, Asterionella gracillima, Aulacoseira granulate, Aulacoseira granulata var. angustissima, Chlorella vulgare, Fragilaria crotonensis and Synedra ulna. Phytoplankton blooms were frequent from winter to the late spring and rare in summer due to heavy rain and discharge. Seasonal variations of the dominant species were fairly obvious; Asterionella gracillima and Aulacoseira granulata in spring, Aulacoseira granulate and Aulacoseira granulate var. angustissima in summer and autumn, Asterionella gracillima and Stephan discus hantzschii in winter. Recently blue-green algae, Microcystis, Aphanocapsa, Dactylococcopsis have been more abundant than those of the previous reports. Based on the current situations, Stephan discus hantzschii f. tennis, Asterionella gracillima, Aulacoseira granulate and blue-green algae will be more abundant and blooms of those species will be more frequent.

• Ocean and Polar Research
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• v.32 no.4
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• pp.351-359
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• 2010

This study examined extensive patches of floating green macroalgal (Ulva prolifera) mats in the northern East China Sea (ECS) using satellite images from mid May through July 2008 and field observation made during early August 2008 cruise. It was previously reported that the massive macroalgal blooms occurred in the coastal areas of Qingdao in China. During our field survey, researchers noticed widely distributed floating patches of macroalgal mats ranging in size from tens of centimeters to a few hundred meters in diameter. Meteorological data in the northern ECS showed high irradiance, high air-temperature, and predominant southerly winds in summer. In the study area during the survey period, surface waters were characterized by the Changjiang Diluted Water (CDW) mass, which contained high concentrations of nitrate and phosphate. The internal transcribed spacer (ITS) sequence of U. prolifera found in the northern ECS was the same as those of U. prolifera sampled from Qingdao blooms, suggesting a possibility that U. prolifera found in two regions would be derived from the same origin. We suggest that U. prolifera in the nearshore Jiangsu Province drifted into the northern ECS and proliferated under favorable meteorological and oceanographic conditions during the summer of 2008.

• Korean Journal of Ecology and Environment
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• v.46 no.1
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• pp.1-9
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• 2013

Algal blooms in potable water supplies are becoming an increasingly prevalent and serious water quality problem around the world. In addition to precipitating taste and odor problems, blooms damage the environment, and some classes like cyanobacteria (blue-green algae) release toxins that can threaten human health, even causing death. There is a recognized need in the water industry for models that can accurately forecast in real-time algal bloom events for planning and mitigation purposes. In this study, using data for an interconnected system of rivers and reservoirs operated by a New Jersey water utility, various ANN models, including both discrete prediction and classification models, were developed and tested for forecasting counts of three different algal classes for one-week and two-weeks ahead periods. Predictor model inputs included physical, meteorological, chemical, and biological variables, and two different temporal schemes for processing inputs relative to the prediction event were used. Despite relatively limited historical data, the discrete prediction ANN models generally performed well during validation, achieving relatively high correlation coefficients, and often predicting the formation and dissipation of high algae count periods. The ANN classification models also performed well, with average classification percentages averaging 94 percent accuracy. Despite relatively limited data events, this study demonstrates that with adequate data collection, both in terms of the number of historical events and availability of important predictor variables, ANNs can provide accurate real-time forecasts of algal population counts, as well as foster increased understanding of important cause and effect relationships, which can be used to both improve monitoring programs and forecasting efforts.

• Journal of Life Science
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• v.14 no.2
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• pp.255-262
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• 2004

We applied nuclear DNA content stained with 4'-6'-diamidino-2-phenylindole (DAPI) and total protein concentration to predict the existence of Cochlodinium polykrikoides before huge blooms occurred, based on a short-term survey at sites in the South Sea. Fluctuations in environmental conditions and nutrients (nitrate, nitrite, and phosphate) were of a similar range, regardless of sampling sites or early and middle field observations. However, C. polykrikoides abundance was significantly different depending on the station, with a higher cell density of 34, 62, and 57 cells L$^{-1}$ at Stn C2, C5, and C6, respectively than what was found in early August, 2000. In mid August, 2000, the highest cell density of 547 cells L$^{-1}$ at Stn C3 was observed. The relationship between C. polykrikoides abundance, DAPI-stained DNA content, and total protein concentration was a positive correlation coefficient, in particular a higher positive correlation was exposed to even a smaller abundance of C. polykrikoides. These results suggest that DNA stained by DAPI and total protein concentration could play an important index in easily predicting the presence of C. polykrikoides before blooms.

• Journal of Korea Water Resources Association
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• v.49 no.9
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• pp.789-798
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• 2016

Frequent algal blooms at major river systems in Korea have been serious social and environmental problems. Especially, the appearance of cyanobacteria with toxic materials is a threat to secure a safe drinking water. In order to model the behaviour of cyanobacteria cell number, an exclusive causality analysis using prewhitening technique was introduced to delineate effective parameters to predict the cell numbers of cyanobacteria in Seungchon Weir and Juksan Weir along Youngsan river system. Both input and output transfer function models were obtained to explain temporal variation of cyanobacteria cell number. A threshold behaviour of water temperature was implemented into the model development to consider winter characteristic of cyanobacteria. The implementation of water temperature threshold into the model structure improves the predictability in simulation. Even though the input output transfer model cannot completely explained all blooms of cyanobacteria, the simple structure of model provide a feasibility in application which can be important in practical aspect.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.168-168
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• 2023

The frequent occurrence of cyanobacterial harmful algal blooms (CHABs) in inland waters under climate change seriously damages the ecosystem and human health and is becoming a big problem in South Korea. Satellite remote sensing is suggested for effective monitoring CHABs at a larger scale of water bodies since the traditional method based on sparse in-situ networks is limited in space. However, utilizing a standalone variable of satellite reflectances in common CHABs dual-models, which relies on both chlorophyll-a (Chl-a) and phycocyanin or cyanobacteria cells (Cyano-cell), is not fully beneficial because their seasonal variation is highly impacted by surrounding meteorological and bio-environmental factors. Along with the development of Artificial Intelligence (AI), monitoring CHABs from space with analyzing the effects of environmental factors is accessible. This study aimed to investigate the potential application of AI in the dual-model strategy (Chl-a and Cyano-cell are output parameters) for monitoring seasonal dynamics of CHABs from satellites over Korean inland waters. The Sentinel-3 satellite was selected in this study due to the variety of spectral bands and its unique band (620 nm), which is sensitive to cyanobacteria. Via the AI-based feature selection, we analyzed the relationships between two output parameters and major parameters (satellite water-leaving reflectances at different spectral bands), together with auxiliary (meteorological and bio-environmental) parameters, to select the most important ones. Several AI models were then employed for modelling Chl-a and Cyano-cell concentration from those selected important parameters. Performance evaluation of the AI models and their comparison to traditional semi-analytical models were conducted to demonstrate whether AI models (using water-leaving reflectances and environmental variables) outperform traditional models (using water-leaving reflectances only) and which AI models are superior for monitoring CHABs from Sentinel-3 satellite over a Korean inland water body.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.231-231
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• 2020

Unlike conventional treatment technologies, the performance of nature-based facilities were susceptible to seasonal changes and climatological variabilities. This study evaluated the effects of seasonal variables on the treatment performance of constructed wetlands (CWs). Two CWs treating runoff and discharge from agricultural and livestock areas were monitored to determine the efficiency of the systems in reducing particulates, organics, and nutrients in the influent. For all four seasons, the mean effluent suspended solids concentration in the agricultural CW (ACW) increased by -2% to -39%. The occurrence of algal blooms in the system during summer and fall seasons resulted to the greatest increase in the amount of suspended materials in the overlying water. unlike ACW, the livestock CW (LCW) performed efficiently throughout the year, with mean suspended solids removal amounting to 61% to 68%. Algal blooms were still present in LCW seasonally; however, the constant inflow in the system limited the proliferation of phytoplankton through continuous flushing. The total nitrogen (TN) and total phosphorus (TP) removal efficiencies in ACW were higher during the summer (21% to 25%) and fall (8% to 21%) seasons since phytoplankton utilize nitrogen and phosphorus during the early stages of phytoplankton blooms. In the case of LCW, the most efficient reduction in TN (24%) and TP (54%) concentrations were also noted in summer, which can be attributed to the favorable environmental conditions for microbial activities. The mean removal of organics in ACW was lowest during summer season (-52% to 35%), wherein the onset of algal decay triggered a relative increase in organic matter and stimulate bacterial growth. The removal of organics in LCW was highest (54 % to 55%) during the fall and winter seasons since low water temperatures may limit the persistence of various algal species. Variations in environmental conditions due to seasonal changes can greatly affect the performance of CW systems. This study effectively established the contributory factors affecting the feasibility of utilizing CW systems for treating agricultural and livestock discharges and runoff.