• Journal of Climate Change Research
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• v.3 no.4
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• pp.281-291
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• 2012

Forests act as carbon sinks and also improve water resources and biodiversity to climate change. Secure funding, administrative support, and sustainable management systems are essential to conserve forests and to implement international forestry related projects to climate change. Public private partnership (PPP) could be an effective way for forestry sector in developing countries. Awareness analysis should be preceded in order to encourage participation of enterprises for the diversification of funding and the enhancing quality of projects. We conducted a survey targeting more than 129 private enterprises for awareness analysis. As a result, lack of information, complexity of processes and low profit resulted in low interest on forest projects from private enterprises. Improving awareness of recipient countries on forest resources, financial and institutional supports from the public sector, information sharing, performance management and equal partnership between sectors were suggested to encourage PPP in international forestry related projects to climate change.

• Ecology and Resilient Infrastructure
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• v.8 no.2
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• pp.112-119
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• 2021

In 2012, the National Park Service conducted an ecological health assessment to efficiently preserve and manage the ecosystem. The need for improving pre-existing management indicators was recognized from the revised Natural Park Act because, while the indicators of the existing evaluation system focused on endangered species, ecosystem disturbance, diversity, water quality (BOD, DO), and habitat fragmentation, they did not reflect the lack of indicators for marine ecological assessment, policy changes, and the time demands. The evaluation results comprised a five-point grading system, which made the analysis of immediate changes, difficult. Therefore, the benthic pollution index (BPI) and habitat restoration indicators were added to improve the evaluation system. The National Park was assessed using 10 classifications, however, only four classifications were evaluated. The ratings were divided into five states, and ten classes were presented as pictograms. The assessment results showed a similar trend as the indicators were improved, increasing from level 3 to level 5. However, the results of the Wolaksan National Park after improvement in the indicators were lower than that before the improvement, whereas, for the Juwangsan National Park, it was higher. This study aims at contributing to the scientific and systematic management of the national park ecosystem by improving the ecological health assessment system.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.79-96
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• 2021

Green infrastructure planning represents landscape planning measures to reduce particulate matter. This study aimed to derive factors that may be used in planning green infrastructure for particulate matter reduction using text mining techniques. A range of analyses were carried out by focusing on keywords such as 'particulate matter reduction plan' and 'green infrastructure planning elements'. The analyses included Term Frequency-Inverse Document Frequency (TF-IDF) analysis, centrality analysis, related word analysis, and topic modeling analysis. These analyses were carried out via text mining by collecting information on previous related research, policy reports, and laws. Initially, TF-IDF analysis results were used to classify major keywords relating to particulate matter and green infrastructure into three groups: (1) environmental issues (e.g., particulate matter, environment, carbon, and atmosphere), target spaces (e.g., urban, park, and local green space), and application methods (e.g., analysis, planning, evaluation, development, ecological aspect, policy management, technology, and resilience). Second, the centrality analysis results were found to be similar to those of TF-IDF; it was confirmed that the central connectors to the major keywords were 'Green New Deal' and 'Vacant land'. The results from the analysis of related words verified that planning green infrastructure for particulate matter reduction required planning forests and ventilation corridors. Additionally, moisture must be considered for microclimate control. It was also confirmed that utilizing vacant space, establishing mixed forests, introducing particulate matter reduction technology, and understanding the system may be important for the effective planning of green infrastructure. Topic analysis was used to classify the planning elements of green infrastructure based on ecological, technological, and social functions. The planning elements of ecological function were classified into morphological (e.g., urban forest, green space, wall greening) and functional aspects (e.g., climate control, carbon storage and absorption, provision of habitats, and biodiversity for wildlife). The planning elements of technical function were classified into various themes, including the disaster prevention functions of green infrastructure, buffer effects, stormwater management, water purification, and energy reduction. The planning elements of the social function were classified into themes such as community function, improving the health of users, and scenery improvement. These results suggest that green infrastructure planning for particulate matter reduction requires approaches related to key concepts, such as resilience and sustainability. In particular, there is a need to apply green infrastructure planning elements in order to reduce exposure to particulate matter.

• Korean Journal of Ecology and Environment
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• v.46 no.2
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• pp.145-153
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• 2013

It is a global trend that the water management policy is shifting from a water quality-oriented assessment to the aquatic ecosystem-based assessment. The majority of aquatic ecosystem assessment systems were developed solely based on physicochemical factors (e.g., water quality and bed structure) and a limited number of organisms (e.g., plankton and benthic organisms). Only a few systems use plants for a health assessment, although plants are sensitive indicators reflecting long-term disturbances and alterations in water regimes. The development of an assessment system is underway to evaluate and manage lakes as ecosystem units in the Korean Ministry of Environment. We reviewed the existing multivariate health assessment methods of other leading countries, and discussed their applicability to Korean lakes. The application of multivariate assessment methods is costly and time consuming, in addition to the correlation problem among variables. However, a single variable is not available at this moment, and the multivariate method is an appropriate system due to its multidimensional evaluation and cumulative data generation. We, therefore, discussed multivariate assessment methods in three steps: selecting metrics, scoring metrics and assessing indices. In the step of selecting metrics, the best available metrics are species-related variables, such as composition and abundance, as well as richness and diversity. Indicator species, such as sensitive species, are the most frequently used in other countries, but their system of classification in Korea is not yet complete. In terms of scoring metrics, the lack of reference lakes with little anthropogenic impact make this step difficult, and therefore, the use of relative scores among the investigated lakes is a suitable alternative. Overall, in spite of several limitations, the development of a plant-based multivariate assessment method in Korea is possible using mostly field research data. Later, it could be improved based on qualitative metrics on plant species, and with the emergence of further survey data.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.221-227
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• 2012

In Korea, ocean dumping has been widely used as the ultimate disposal of sewage sludge. However, ocean dumping of food wasted and sewage sludge from 2013 is expected to legally restricted as London convention on marine pollution prevention has been effective in 2009. This research aims to examine the effect of HEAS in treating the environmental pollution load caused by organic high concentrated sludge. Thus, onsite laboratory scale treatability test using HEAS was adopted to treat the high concentrated organic sludge from sewage and industrial wastewater treatment plant. The research results showed that the HEAS is useful to reduce the environmental pollution caused by organic high concentrated sludge. Specific results are as follows. 1. The organic removal after the sludge digestion using the high efficiency aeration system was 55.2-85.8%. Although these results were lower than those from the general sewage treatment, the high efficiency aeration system could be evaluated as efficient, considering the object sludge contained the industrial waster water. 2. The average removal efficiency was about 25.2%. 3. It was revealed that sludge digestion by the high efficiency aeration system could effectively contribute to the sludge treatment cost. Especially, the high efficiency aeration system is more applicable to the onsite treatment of small sewage and wastewater treatment plant that contains high solid content sludge, industrial wastewater sludge, high fixed solid sludge.

• Journal of Digital Convergence
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• v.11 no.5
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• pp.119-133
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• 2013

This study aims to provide power generating plants with eco-efficiency information. To implement the purposes, of study, both DEA(Data, Envelopment Analysis) model and interview were incorporated in terms of methodologies. To analyze the managerial efficiency, total labor cost and number of employees were considered as input factors. CO2, NOx, and water also were considered as input factors to analyze eco-efficiency. Both annual total power product and annual total revenue were used as output factors. CRS(Constant Return to Scale) and VRS(Variable Return to) model were facilitated in this analysis. According to the findings, most of the power plants were evaluated as 'Efficient'' taking into consideration of average value, both 0.928 from CCR model and 0.969 from VRS model. 7 DMUs including DMU3 and DMU12 are efficient out of 35 DMUs relatively, other DMUs are inefficient. For results of inefficient output factors distribution, it was found that inefficiency for NOx was marked relatively higher than CO2. In order to improve the eco-efficiency in the power plants in the long term, the target amount of Co2 as well as NOx reduction needs to be properly proposed in consideration of particularity of power plants. In the long run, renewable energy, alternative fuels should be adapted to reduce the eco-inefficient.

• Journal of Digital Convergence
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• v.15 no.11
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• pp.513-522
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• 2017

We tried to analyze the inflammation reactions by treatment of AG, AS and AA in murine RAW 264.7 cells. To investigate the effect of AG, AS and AA on cell viability of RAW 264.7 cells, AG, AS and AA were treated for 24 h and MTS assay was performed. Cell viabilities were increased in $1,600{\mu}g/ml$ concentration by AS, AA and AG treatments, respectively. The mRNA expression levels of $IL-1{\beta}$, $TNF-{\alpha}$ and iNOS were increased by AG and AA treatment at a concentration of $200{\mu}g/ml$ in RAW 264.7 cells without Lipopolysaccharide (LPS) treatment. The mRNA expression levels of $IL-1{\beta}$, $TNF-{\alpha}$ and iNOS were increased by AG and AA 6 h treatment at a concentration of $200{\mu}g/ml$ with LPS treatment. In this study, we observed that AG, AS and AA show various activities on inflammation reaction depend on their treatment time. In the future, studies should be conducted to investigate the effects of AG, AS and AA on the various inflammatory responses of macrophages.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4717-4737
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• 2017

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

• Journal of Environmental Policy
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• v.12 no.1
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• pp.37-58
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• 2013

In recently, the low impact development(LID) is discussed at various fields being related to urban stormwater, non-point source pollution, and quality of life. It is understood as an integrated development tool to induce sustainable development with various value-social, economic, and aesthetic. As concerning the development of waterfront area, the low impact development is interested in environmental planning. But the planning process and factors are not considered in precedent research. This study has two purposes. The one is to understand the planning process and factors of low impact development from literature review. The other is to apply the planning factors using case study and to know the effect of low impact development as the simulation plan. The simulation plan is based on some landuse planning. It is divided into the setting the region for environmental protection and the function of public facilities, spatial planning for enlarging permeable area, and spatial planning for circulation of water. The simulation model uses the LIDMOD2. The 14 planning factors of low impact development is applied to case region. And the effect is about 7~10 percent in reduction of nonpoint source pollution and surface runoff.

• Journal of Korean Society of Environmental Engineers
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• v.35 no.5
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• pp.321-333
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• 2013

As environmental sustainability becomes a key consideration in policy-making, more responsible consumption and utilization in daily life concern both health and quality of life. To address inequities in health in relation to environments, waste management has taken more progressive ways, and one of them is biomass-to-energy conversion that utilizes energy recovery from food waste. By extension, a food waste zero-emission system using fermentation and extinction technology gains much attention, so that this study is designed to examine residents' attitudes toward recycling food waste produced at home and toward food waste zero-emission system. Utilizing a survey questionnaire, this research collected data from 400 individual units of multifamily housing estates nationwide, and the data were analyzed using descriptive and inferential statistics. The findings indicate that food waste generated at home was highly water-contained and produced in the stage of food preparation before cooking while respondents viewed that food waste collection and treatment needed to be improved. It's noted that respondents strongly supported the use of food waste as a energy source and would have the use of the food waste zero-emission system built in kitchen sink. Regression analysis showed that educational attainment of housewives, cooking style, and planning food purchase were statistically significant factors in the attitude of the responded residents toward recycling food waste while none of the factors were in the attitude toward the food waste zero-emission system.