• Journal of Environmental Science International
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• v.14 no.9
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• pp.827-835
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• 2005

A three-dimensional ecological model (EMT -3D) was applied to Nonylphenol in Tokyo Bay. EMT -3D was calibrated with data obtained in the study area. The simulated results of dissolved Nonylphenol were in good agreement with the observed values, with a correlation coefficient(R) of 0.7707 and a coefficient of determination (R2) of 0.5940. The results of sensitivity analysis showed that biodegradation rate and bioconcentration factor are most important factors for dissolved Nonylphenol and Nonylphenol in phytoplankton, respectively. In the case of Nonylphenol in particulate organic carbon, biodegradation rate and partition coefficient were important factors. Therefore, the parameters must be carefully considered in the modeling. The mass balance results showed that standing stocks of Nonylphenol in water, in particulate organic carbon and in phytoplankton are $8.60\times 10^5\;g,\;2.19\times 10^2\;g\;and\;3.78\times 10^0\;g$ respectively. With respect to the flux of dissolved Nonylphenol, biodegradation in the water column, effluent to the open sea and partition to particulate organic carbon were $6.02\times10^3\;g/day,\;6.02\times10^2\;g/day\;and\;1.02\times10^1\;g/day$, respectively.

• Korean Journal of Environmental Biology
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• v.39 no.3
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• pp.298-310
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• 2021

Prediction of the behavior of heavy metals over time is important to evaluate the heavy metal toxicity in algae species. Various modeling studies have been well established, but there is a need for an improved model for predicting the chronic effects of metals on algae species to combine the metal kinetics and biological response of algal cells. In this study, a kinetic dynamics model was developed to predict the copper behavior(5 ㎍ L^-1, 10 ㎍ L^-1, and 15 ㎍ L^-1) for two freshwater algae (Pseudokirchneriella subcapitata and Chlorella vulgaris) in the chronic exposure experiments (8 d and 21 d). In the experimental observations, the rapid change in copper mass between the solutions, extracellular and intracellular sites occurred within initial exposure periods, and then it was slower although the algal density changed with time. Our model showed a good agreement with the measured copper mass in each part for all tested conditions with an elapsed time (R² for P. subcapitata: 0.928, R² for C. vulgaris: 0.943). This study provides a novel kinetic dynamics model that is compromised between practical simplicity and realistic complexity, and it can be used to investigate the chronic effects of heavy metals on the algal population.

• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.3224-3235
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• 2024

Amid the ongoing discourse on clean energy solutions, the reopening of decommissioned plants, such as the Bataan Nuclear Power Plant (BNPP) in the Philippines has become a focal point in the country. This study delved into the complex web of factors influencing public acceptance of BNPP, employing the values-beliefs-norms theory. By utilizing partial-least square structural equation modeling, the research unravelled the intricate relationships among biospheric values, altruistic values, egoistic values, ecological worldview, awareness of consequences, personal norm, social norm, and the broader acceptance of BNPP establishment. With 434 respondents participating in a self-administered online survey, the study identified key correlations. Emphasizing the collaborative impact on decision-making processes by social and personal norms, the study also highlighted the role of ecological values in shaping awareness. The foundational impact of values on ecological worldviews was explored, shedding light on public attitudes toward nuclear energy. This research offers actionable insights for policymakers, advocating for targeted communication strategies and public engagement initiatives to navigate barriers and promote informed decision-making in the dynamic landscape of nuclear energy development. The study contributes to the global conversation on sustainable energy strategies, emphasizing the pivotal role of public perception in shaping the trajectory of nuclear power.

• Journal of the Korean Home Economics Association
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• v.35 no.1
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• pp.443-459
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• 1997

The purpose of this study were (1) to investigate the effect of environments on the ecological value orientation (2) to examine the effect of environments and ecological value orientation on housewives' recycling behavior and (3) to analyze the hypothesized causal model of the housewives' recycling behavior in order to explain direct and indirect effects of the selected variables. 687 samples were selected from housewives living in Seoul. Cronbach's a, descriptive statistics and stepwise multiple regression were used for data analysis The major findings are as follows: Housewives' recycling behavior In conclusion the result of the path analysis explained the contribution of variables on housewives' household recycling. It was found that the ecological value orientation makes the most significant contribution to household recycling.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.44 no.2
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• pp.167-172
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• 2011

A three-dimensional ecological model (EMT-3D) was applied to Tokyo Bay to simulate 4,4'-bis (2-sulfostyryl)biphenyl (DSBP). The simulated results were in good agreement with the observed values, with a correlation coefficient of R=0.8431 and a coefficient of determination of $R^2$=0.7108. The sensitivity analysis indicated that the photolysis rate is the most important factor. Therefore, the parameters must be considered carefully in modeling. The mass balance results showed that the standing stock of DSBP in water and in particulate organic carbon was 621.2 and 19.5 kg, respectively, and the effluent flux to the open sea was 2.63 and 0.055 kg/day, respectively.

• Proceedings of the Korean Society of Applied Entomolohy Conference
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• 2005.05a
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• pp.93-93
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• 2005

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2012.07a
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• pp.15-22
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• 2012

• Journal of Ecology and Environment
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• v.31 no.3
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• pp.177-181
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• 2008

Recently, the evolutionary study of human psychology and behavior has undergone rapid growth, diversifying into a few distinct sub-disciplines. One fundamental issue over which researchers in Human Behavioral Ecology and Evolutionary Psychology (EP) have different views is the role of formal optimality modeling for making hypotheses and deriving predictions about human adaptations. The study of EP typically rests on informal inferences and rarely uses optimality modeling, a strategy which human behavioral ecologists have severely criticized. Here I argue that EP researchers have every reason to make extensive use of optimality modeling as its research method. I show that optimality modeling can play an integral role in identifying the functional organization of human psychological adaptations.

• Environmental Engineering Research
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• v.14 no.2
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• pp.102-110
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• 2009

Application of artificial intelligence (AI) approaches in eco-environmental modeling has gradually increased for the last decade. Comprehensive understanding and evaluation on the applicability of this approach to eco-environmental modeling are needed. In this study, we reviewed the previous studies that used AI-techniques in eco-environmental modeling. Decision Tree (DT) and Artificial Neural Network (ANN) were found to be major AI algorithms preferred by researchers in ecological and environmental modeling areas. When the effect of the size of training data on model prediction accuracy was explored using the data from the previous studies, the prediction accuracy and the size of training data showed nonlinear correlation, which was best-described by hyperbolic saturation function among the tested nonlinear functions including power and logarithmic functions. The hyperbolic saturation equations were proposed to be used as a guideline for optimizing the size of training data set, which is critically important in designing the field experiments required for training AI-based eco-environmental modeling.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.264-271
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• 2023

Environmental crises caused by climate change and human-induced disturbances have become urgent challenges to the sustainability of human beings. These issues can be addressed based on a data-driven understanding and forecasting of ecosystem responses to environmental changes. In this study, we introduce a long-term ecological monitoring system in Korean Long-Term Ecological Research (KLTER), and a plan for the Korean Ecological Observatory Network (KEON). KLTER has been conducted since 2004 and has yielded valuable scientific results. However, the KLTER approach has limitations in data integration and coordinated observations. To overcome these limitations, we developed a KEON plan focused on multidisciplinary monitoring of the physiochemical, meteorological, and biological components of ecosystems to deepen process-based understanding of ecosystem functions and detect changes. KEON aims to answer nationwide and long-term ecological questions by using a standardized monitoring approach. We are preparing three types of observatories: two supersites depending on the climate-vegetation zones, three local sites depending on the ecosystem types, and two mobile deployment platforms to act on urgent ecological issues. The main observation topics were species diversity, population dynamics, biogeochemistry (carbon, methane, and water cycles), phenology, and remote sensing. We believe that KEON can address environmental challenges and play an important role in ecological observations through partnerships with international observatories.