• Environmental Engineering Research
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• v.21 no.4
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• pp.355-364
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• 2016

Beijing, as a cradle of modern industry and the third largest metropolitan area in China, faces more responsibilities to adjust industrial structure and mitigate carbon emissions. The purpose of this study is aimed at predicting and comparing industrial carbon emissions of Beijing in ten scenarios under different policy focus, and then providing emission-cutting recommendations. In views of various scenarios issues, system dynamics has been applied to predict and simulate. To begin with, the model has been established following the step of causal loop diagram and stock flow diagram. This paper decomposes scenarios factors into energy structure, high energy consumption enterprises and growth rate of industrial output. The prediction and scenario simulation results shows that energy structure, carbon intensity and heavy energy consumption enterprises are key factors, and multiple factors has more significant impact on industrial carbon emissions. Hence, some recommendations about low-carbon mode of Beijing industrial carbon emission have been proposed according to simulation results.

• Journal of Korean Society on Water Environment
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• v.40 no.3
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• pp.121-129
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• 2024

Harmful cyanobacterial blooms (HCBs) are caused by the rapid proliferation of cyanobacteria and are believed to be exacerbated by climate change. However, the extent to which HCBs will be stimulated in the future due to increased temperature remains uncertain. This study aims to predict the future occurrence of cyanobacteria in the Nakdong River, which has the highest incidence of HCBs in South Korea, based on temperature rise scenarios. Representative Concentration Pathways (RCPs) were used as the basis for these scenarios. Data-driven model simulations were conducted, and out of the four machine learning techniques tested (multiple linear regression, support vector regressor, decision tree, and random forest), the random forest model was selected for its relatively high prediction accuracy. The random forest model was used to predict the occurrence of cyanobacteria. The results of boxplot and time-series analyses showed that under the worst-case scenario (RCP8.5 (2100)), where temperature increases significantly, cyanobacterial abundance across all study areas was greatly stimulated. The study also found that the frequencies of HCB occurrences exceeding certain thresholds (100,000 and 1,000,000 cells/mL) increased under both the best-case scenario (RCP2.6 (2050)) and worst-case scenario (RCP8.5 (2100)). These findings suggest that the frequency of HCB occurrences surpassing a certain threshold level can serve as a useful diagnostic indicator of vulnerability to temperature increases caused by climate change. Additionally, this study highlights that water bodies currently susceptible to HCBs are likely to become even more vulnerable with climate change compared to those that are currently less susceptible.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.4
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• pp.522-533
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• 2012

This paper presents an adaptive strategy of GENCOs for reducing the greenhouse gas by fuel mix change. Fuel mix stands for generation capacity portfolio composed of different fuel resources. Currently, the generation sector of power industry in Korea is heavily dependent on fossil fuels, therefore it is required to change the fuel mix gradually into more eco-friendly way based on renewable energies. The generation costs of renewable energies are still expensive compared to fossil fueled resources. This is why the adaptive change is more preferred at current stage and this paper proposes an optimal strategy for capacity planning based on multiple environmental scenarios on the time horizon. This study used the computer program tool named GATE-PRO (Generation And Transmission Expansion PROgram), which is a mixed-integer non-linear program developed by Hongik university and Korea Energy Economics Institute. The simulations have been carried out with the priority allocation method in the program to determine the optimal mix of NRE(New Renewable Energy). Through this process, the result proposes an economic fuel mix under emission constraints compatible with the greenhouse gas mitigation policy of the United Nations.

• Advances in environmental research
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• v.7 no.2
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• pp.121-138
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• 2018

Depending on the increased energy needs, a large number of dams have been built around the world. These dams have significant impacts on river ecology and climate change. When the climate change scenarios are examined, it is stated that the annual average temperature in Turkey will increase by 2.5-4 degrees in the future years, the south of the country will be opposed to the severe drought threat, and the northern regions will have a flood risk. In particular, it can be predicted that many dams and dam lakes built in the North of Turkey may increase the impact of climate change. In this study, the effects of the dams constructed in Çoruh basin on climate change are examined. Environmental and ecological problems of dam reservoirs have been examined. As a result of the data received from meteorological stations, it was determined that temperature and rainfall changes in the region. In this direction, solution proposal is presented.

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1149-1159
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• 2018

This study aims to predict the future flood damage cost of 113 middle range watersheds using 26 GCM outputs, hourly maximum rainfall, 10-min maximum rainfall, number of days of 80 mm/day, daily rainfall maximum, annual rainfall amount, DEM, urbanization ratio, population density, asset density, road improvement ratio, river improvement ratio, drainage system improvement ratio, pumping capacity, detention basin capacity and previous flood damage costs. A constrained multiple linear regression model was used to construct the relationships between the flood damage cost and other variables. Future flood damage costs were estimated for different RCP scenarios such as 4.5 and 8.5. Results demonstrated that rainfall related factors such as annual rainfall amount, rainfall extremes etc. widely increase. It causes nationwide future flood damage cost increase. Especially the flood damage cost for Eastern part watersheds of Kangwondo and Namgang dam area may mainly increase.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.11-20
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• 2017

This study is to estimate the spatial soil moisture using multiple linear regression model (MLRM) and 15 minutes interval Land Surface Temperature (LST) data of Communication, Ocean and Meteorological Satellite (COMS). For the modeling, the input data of COMS LST, Terra MODIS Normalized Difference Vegetation Index (NDVI), daily rainfall and sunshine hour were considered and prepared. Using the observed soil moisture data at 9 stations of Automated Agriculture Observing System (AAOS) from January 2013 to May 2015, the MLRMs were developed by twelve scenarios of input components combination. The model results showed that the correlation between observed and modelled soil moisture increased when using antecedent rainfalls before the soil moisture simulation day. In addition, the correlation increased more when the model coefficients were evaluated by seasonal base. This was from the reverse correlation between MODIS NDVI and soil moisture in spring and autumn season.

• Journal of Korea Water Resources Association
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• v.52 no.6
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• pp.381-395
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• 2019

The purpose of this study is to predict agricultural reservoir storage rate (RSR) in a month. This algorithm was developed by multiple linear regression model (MLRM) which included the past 3 months RSRs data and the future climate change scenarios. In order to improve use of predicted RSR, this study need the severe criteria in terms of drought. So, the predicted RSR was indexed as the 3 months reservoir drought index (RDI3) and then it was disaggregated into drought duration, severity, and intensity. For the future RSR estimation by climate change scenarios, the 6 RCP 8.5 scenarios of HadGEM2-ES, CESM1-BGC, MPI-ESM-MR, INM-CM4, FGOALS-s2, and HadGEM3-RA were used in three future evaluation periods (S1: 2011~2040, S2: 2041~2070, S3: 2071~2099). The future S3 period of HadGEM2-ES scenario which has the biggest increase in precipitation and temperature showed the largest decrease to 60.2% among the 6 scenarios compared to the historical RSR (1976~2005) 77.3%. In contrast, INM-CM4 scenario which has smallest changes in precipitation and temperature in S3 period showed the smallest decrease to 72.8%. For the CESM1-BGC and MPI-ESM-MR, FGOALS-s2, and HadGEM3-RA, the S3 period RSR showed 72.6%, 72.6%, 67.4%, and 64.5% decrease respectively. The future severe drought condition of RDI3 below -0.25 showed the increase trend for the number and severity up to -2.0 during S3 period.

• Journal of the Korean Institute of Landscape Architecture International Edition
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• no.2
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• pp.120-129
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• 2004

Urban stream restoration projects can improve water quality, wildlife habitats, urban landscape, outdoor recreation spaces, and urban microclimate. The objectives of this research were to investigate temperature cooling effect of urban streams by using satellite imagery, to evaluate environmental variables related to stream cooling effect, and to estimate the cooling effect of the Cheonggye stream restoration project of Seoul, Korea. Findings of this research can be summarized as follows. First, a method of estimating temperature distribution around urban streams by using satellite imagery was developed. Scatter plots of distance from stream edges and average temperature obtained through multiple buffering were used for the estimation. Second, urban temperature cooling effect of streams was estimated by comparing background temperature and temperature of each buffer zone. Third, environmental factors affecting stream cooling effect were also identified. Fourth, the temperature cooling effect of the restoration project was estimated based on three scenarios. An estimated cooling effect based on the average cooling effect of existing tributaries showed the most significant effect; $2.0^{\circ}C$ lower than the present level at the edge of the renovated stream. It was estimated that the temperature of the same area would be $1.4^{\circ}C$ cooler than the present level if the cooling effect of the Yangjaechun was used as the bench mark But the effect would be $1.2^{\circ}C$ lower than the present level if environmental variables related to the temperature cooling effect of urban streams were used as the bench mark.

• Structural Engineering and Mechanics
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• v.40 no.3
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• pp.297-313
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• 2011

As bridge conditions in the United States continue to deteriorate, rapid bridge replacement procedures are needed. Decked precast prestressed concrete (DPPC) girders are used for rapid bridge construction because the bridge deck is precast with the girders eliminating the need for a cast-in-place slab. One of the concerns with using DPPC girders as a bridge construction option is the durability of the longitudinal joints between girders. The objectives of this paper were to propose a method to use a spring element modeling procedure for representing welded steel connector assemblies between adjacent girders in DPPC girder bridges, perform a preliminary study of bridge performance under multiple loading scenarios and bridge configurations, and discuss model flexibility for accommodating future field data for model verification. The spring elements have potential to represent the contribution of joint grout materials by altering the spring stiffness.

• Structural Monitoring and Maintenance
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• v.6 no.3
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• pp.237-254
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• 2019

This paper presents an improved time series based damage detection approach with experimental verifications for detection, localization, and quantification of damage in shear-type structures under varying mass effects using output-only vibration data. The proposed method can be very effective for automated monitoring of buildings to develop proactive maintenance strategies. In this method, Auto-Regressive Moving Average models with eXogenous inputs (ARMAX) are built to represent the dynamic relationship of different sensor clusters. The damage features are extracted based on the relative difference of the ARMAX model coefficients to identify the existence, location and severity of damage of stiffness and mass separately. The results from a laboratory-scale shear type structure show that different damage scenarios are revealed successfully using the approach. At the end of this paper, the methodology limitations are also discussed, especially when simultaneous occurrence of mass and stiffness damage at multiple locations.