• Journal of Korea Water Resources Association
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• v.46 no.7
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• pp.745-754
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• 2013

The systematic analysis and evaluation of required energy in the processes of drinking water production and supply have attracted considerable interest considering the need to overcome electricity shortage and control greenhouse gas emissions. On the basis of a review of existing research results, a practical method is developed in this study for evaluating energy in water supply networks. The proposed method can be applied to real water supply systems. A model based on the proposed method is developed by combining the hydraulic analysis results that are obtained using the EPANET2 software with a mathematical energy model on the MATLAB platform. It is suggested that performance indicators can evaluate the inherent efficiency of water supply facilities as well as their operational efficiency depending on the pipeline layout, pipe condition, and leakage level. The developed model is validated by applying it to virtual and real water supply systems. It is expected that the management of electric power demand on the peak time of water supply and the planning of an energy-efficient water supply system can be effectively achieved by the optimal management of energy by the proposed method in this study.

• Korean Journal of Construction Engineering and Management
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• v.16 no.2
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• pp.65-76
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• 2015

The Clean Development Mechanism (CDM) is the multi-lateral 'cap and trade' system endorsed by the Kyoto Protocol. CDM allows developed (Annex I) countries to buy CER credits from New and Renewable (NE) projects of non-Annex countries, to meet their carbon reduction requirements. This in effect subsidizes and promotes NE projects in developing countries, ultimately reducing global greenhouse gases (GHG). To be registered as a CDM project, the project must prove 'additionality,' which depends on numerous factors including the adopted technology, baseline methodology, emission reductions, and the project's internal rate of return. This makes it difficult to determine ex ante a project's acceptance as a CDM approved project, and entails sunk costs and even project cancellation to its project stakeholders. Focusing on hydro power projects and employing UNFCCC public data, this research developed a prediction model using logistic regression and CART to determine the likelihood of approval as a CDM project. The AUC for the logistic regression and CART model was 0.7674 and 0.7231 respectively, which proves the model's prediction accuracy. More importantly, results indicate that the emission reduction amount, MW per hour, investment/Emission as crucial variables, whereas the baseline methodology and technology types were insignificant. This demonstrates that at least for hydro power projects, the specific technology is not as important as the amount of emission reductions and relatively small scale projects and investment to carbon reduction ratios.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.378-388
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• 2016

International societies are currently working together to achieve the Climate-Smart Agriculture (CSA) initiative which aims the triple wins: (1) sustainably increasing agricultural productivity and incomes; (2) adapting and building resilience to climate change; and (3) mitigating greenhouse gases emissions. In terms of its scope and context, CSA follows the '3Nong (三農)' vision cast about 200 years ago by Dasan Jeong Yak-Yong who emphasized the triad of governance, management and monitoring towards comfortable, profitable and noble agriculture. Yet, the CSA provides the practical aims that facilitate the development of holistic indicators for quantitative evaluation and monitoring, on which decision-making support system is based. In this study, we introduce an agent-based model, i.e. Mathematical Programming Multi-Agent Systems (MP-MAS), as a tool for supporting the decision-making toward CSA. We have established the initial version of MP-MAS adapted for domestic use and present the preliminary results from an application to the rice farming case in Haenam, Korea. MP-MAS can support both farmers and policy-makers to consider diverse management options from multiple perspectives. When the modules for system resilience and carbon footprint are added, MP-MAS will serve as a robust tool that fulfills not only CSA but also Dasan's '3Nong' vision of sustainable agricultural-societal systems.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1053-1065
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• 2019

Land use statistics calculation is very informative data as the activity data for calculating exact carbon absorption and emission in post-2020. To effective interpretation by land use category, This study classify automatically image interpretation by land use category applying forest aerial photography (FAP) to deep learning model and calculate national unit statistics. Dataset (DS) applied deep learning is divided into training dataset (training DS) and test dataset (test DS) by extracting image of FAP based national forest resource inventory permanent sample plot location. Training DS give label to image by definition of land use category and learn and verify deep learning model. When verified deep learning model, training accuracy of model is highest at epoch 1,500 with about 89%. As a result of applying the trained deep learning model to test DS, interpretation classification accuracy of image label was about 90%. When the estimating area of classification by category using sampling method and compare to national statistics, consistency also very high, so it judged that it is enough to be used for activity data of national GHG (Greenhouse Gas) inventory report of LULUCF sector in the future.

• Korean Journal of Construction Engineering and Management
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• v.20 no.2
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• pp.53-59
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• 2019

As solve the shortage problems of storage space for exhibition facilities, the South Korean government is establishing plans to expand storage space for exhibition facilities. From a medium- to long-term perspective, an energy-efficient storage space for exhibition facility is needed to implement efficient state budget execution and achieve national greenhouse gas reduction goals. In this regard, this study analyzed the energy consumption of storage space for exhibition facilities according to the use of absorption materials. To this end, a case study was conducted on 12 storage spaces for exhibition facilities in South Korea. Compared to the storage space using the absorption material, the storage space without using the absorption material showed an increase in HVAC system operation time by 47.50% during summer periods and 58.85% in non-summer periods. In particular, the analysis found that in the case of storage for 'H' exhibition facility, the energy cost was reduced by 2,721,700 won/year after remodeling work using the absorption material. It is expected that the findings of this study can help the government and the person in charge from construction companies to construct energy-efficient storage space room for exhibition facilities.

• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.1-16
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• 2019

Recently, since responding to meteorological changes depending on increasing greenhouse gas and electricity demand, the importance prediction of photovoltaic power (PV) is rapidly increasing. In particular, the prediction of PV power generation may help to determine a reasonable price of electricity, and solve the problem addressed such as a system stability and electricity production balance. However, since the dynamic changes of meteorological values such as solar radiation, cloudiness, and temperature, and seasonal changes, the accurate long-term PV power prediction is significantly challenging. Therefore, in this paper, we propose PV power prediction model based on deep learning that can be improved the PV power prediction performance by learning to use meteorological and seasonal information. We evaluate the performances using the proposed model compared to seasonal ARIMA (S-ARIMA) model, which is one of the typical time series methods, and ANN model, which is one hidden layer. As the experiment results using real-world dataset, the proposed model shows the best performance. It means that the proposed model shows positive impact on improving the PV power forecast performance.

• Korean Journal of Construction Engineering and Management
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• v.20 no.5
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• pp.21-30
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• 2019

Environmental and energy issues such as abnormal climate and depletion of fossil fuel due to global warming have emerged as a critical task to threaten human survival. As a result, interest in the Zero Energy Building is increasing as it is an innovative building that can significantly contribute to building energy reduction and greenhouse gas reduction. In the market, however, the added cost of construction is a major stumbling block to the revitalization of the Zero Energy certification. In this study, general private apartment complexes were selected for research, detailed elements for Zero Energy certification were presented based on the construction criteria for eco-friendly houses from the initial design stage, and the cost efficiency analysis of the components for certification were presented. It has been analyzed that only Grade 3 certification can be implemented in apartments due to technical level and physical limitations. Also, after reviewing the cost trend during the lifecycle cost, all expenses can be recovered within 13 years after completion only in the case of grade 5 of the Zero Energy Building. The additional costs proposed in the present study are reflected appropriately in the review of projects for apartments scheduled for order in the future to contribute to the revitalization of the Zero Energy Building certification.

• Journal of Korean Society of Forest Science
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• v.100 no.3
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• pp.466-475
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• 2011

This study purposed to analyze the spatial pattern and the amount of carbon emission at the deforestation area based on the administrative and GIS data. The total size of deforestation area in last nine years (2000-2008) was about 649 ha, and it was occurred annually about 72 ha. The occurrence rate of deforestation per administrative area in Wonju was about 0.74%. It was 0.34% higher than that of Kwangwondo, and 0.06% less than that of National rate. On the other hand, the forms of deforestation by purpose were not related to the administrative district unit. The number of deforestation forms was highest at settlements. second most frequent form is other land. Grassland showed the lowest score. In addition, the deforestations were more occurred which is closed to the existing housing and building rather than roads. The number of deforestation was 1.2 times higher based on 300m. Seventy percent of deforestation was occurred which is less than 0.5 ha in size, and it increased to 91% when the size is less than 1ha. The total size of theoretical carbon emission based on deforestation area was estimated at 23,424 tc, and average annual carbon emission was estimated by 2,603 tc. Carbon emission per ha was 36.1 tC/ha. This study results will be useful to construct the greenhouse gas statistical verification system against the Post-2012 by GIS.

• Korean Journal of Construction Engineering and Management
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• v.23 no.6
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• pp.30-42
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• 2022

OSC is a type of supply chain and value chain that spans the entire process of construction production (planning, design, construction, maintenance, etc.). It is a method of producing the final object by manufacturing it in a factory, transporting it to the site, installing and construction. This research as is the construction cost was compared for each case A, which applied the PC method, and case B, which applied the RC method. In the case of applying the PC method (excluding the PC design cost), compared to the case where only the RC method was applied, the frame construction cost per unit quantity (m³) increased by about 70% (50% based on the total RC construction type). Of the total frame construction cost of PC method application, PC accounted for 90.2%, 'PC manufacturing cost' 54.8%, 'PC assembly cost' 28.5%, and 'transportation cost' accounted for 6.89%. Also a decision-making framework that can consider both costs and benefits was established. In the case of benefits, the construction period, defect repair, disaster occurrence, energy efficiency, noise/dust/waste, and greenhouse gas emission indicators reflecting OSC technical advantages were presented. It can contribute to providing a basis for helping decision-making on the introduction of PC apartment houses using OSC.

• Journal of Korean Society of Forest Science
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• v.111 no.1
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• pp.165-176
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• 2022

To raise awareness of carbon reduction in climate change, the Korea Forest Service has developed and adopted a forest carbon offset program, which aims to reduce carbon levels based on forest management. However, to maintain the forest carbon offset program, challenges such as the lack of a forest monitoring system to manage and maintain the program, must be faced. In this context, we investigated the limitations of conducting forest carbon offset programs using a number of interview techniques, including in-depth interview and questionnaire survey methods. The questionnaire surveys were developed based on the results of a literature review along with a preinterview and in-depth survey of the people in charge of the forest carbon offset program. The Irving Seidman technique was adopted for the in-depth interviews. Additionally, descriptive and frequency analyses were conducted to identify the characteristics of perception. Lastly, logistic regression was used to identify the limiting factors that affect the willingness to perform forest carbon offset monitoring activity. Results showed that the project managers or people in charge of the forest carbon offset program lacked expertise in forest carbon offset programs, which negatively affected their willingness to perform monitoring activity. Additionally, the study revealed a number of limiting factors that hindered the monitoring of forest carbon offset projects. Improving understanding using the approaches presented in this study may contribute to increasing the benefits associated with the forest carbon offset program in South Korea.