• Journal of Climate Change Research
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• v.7 no.3
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• pp.341-349
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• 2016

This study is intended to set a greenhouse gas emission scenario based on green remodeling pilot project (Annex building of Seoul Customs Office) using LEAP model, a long-term energy plan analysis model, to calculate the energy saving and greenhouse gas emission till year 2035 as well as to analyze the effect of electric power saving cost. Total 4 scenarios were made, Baseline scenario, assuming the past trend is to be maintained in the future, green remodeling scenario, reflecting actual green remodeling project of Seoul Customs Office, behavior improvement and renewable energy supply, and Total scenario. According to the analysis result, the energy demand in 2035 of Baseline scenario was 6.1% decreased from base year 2013, that of green remodeling scenario was 17.5%, that of behavior improvement and renewable energy supply scenario was 21.1% and that of total scenario was 27.3%. The greenhouse emission of base year 2013 was $878.2tCO_2eq$, and it was expected $826.3tCO_2eq$, approx. 5.9% reduced, in 2035 by Baseline scenario. the cumulative greenhouse gas emission saving of the analyzing period were $-26.5tCO_2eq$ by green remodeling scenario, $2.8k\;tCO_2eq$ by behavior improvement and renewable energy supply scenario, and $2.0k\;tCO_2eq$ by total scenario. In addition the effect of electricity saving cost through energy saving has been estimated, and it was approx. 634 million won by green remodeling scenario and appro. 726 million won by behavior improvement and renewable energy supply scenario. So it is analyzed that of behavior improvement and renewable energy supply scenario would be approx. 12.7% higher than that of green remodeling scenario.

• Journal of Climate Change Research
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• v.7 no.1
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• pp.85-93
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• 2016

This study the efficiency of greenhouse gas reduction of 'low carbon car collaboration fund' and its alternative 'control of average fuel efficiency and greenhouse gas', and 'improving driving behavior' were analyzed by using LEAP, long term energy analysis model. Total 4 scenarios were set, baseline scenario, without energy-saving activity, 'low carbon car collaboration fund' scenario, 'fuel efficiency improving scenario', and 'improving driving behavior' scenario. The contents of analysis were forecast of energy demand by scenario and application as well as reduction of greenhouse gas emission volume, and the period taken for analysis was every 1 year during 2015~2030. Baseline scenario, greenhouse gas emission volume in 2015 would be 7,935,697 M/T and 13,081,986 M/T in 2030, increased 64.8%. The analysis result was average annual increase rate of 3.4%. The expected average annual increase rate of other scenarios was, 'low carbon car collaboration fund' scenario 1.7%, 'fuel efficiency improving' scenario 3.0%. and 'improving driving behavior' scenario 3.4%. and these were each 1.7%, 0.3%. 0.3% reduce from baseline scenario. The largest reduction was 'low carbon car collaboration fund' scenario, and there after were 'fuel efficiency improving scenario', and 'improving driving behavior' scenario.

• Journal of Environmental Policy
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• v.5 no.2
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• pp.69-93
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• 2006

This paper considers major three steps to arrive at accurate baseline emissions against which actual emission reductions attributable to CDM projects are accounted for. The first step is to select most likely baseline scenario among plausible alternatives. Then, the additionality of the project in question would be assessed by demonstrating that the project is not included in the baseline scenario selected. Finally, baseline emissions are calculated under the baseline scenario. In this paper, these three steps are integrated into a single flow chart in order to help understand the procedures for application of a baseline methodology better. Following the flow chart, a landfill gas-to-electricity project in Korea is analyzed as a case study. In consequence, this paper concludes that landfill gas-to-electricity projects in Korea have great potential for CDM projects, and it could also be concluded that data availability and reliability are a prerequisite for successful application of baseline methodologies for landfill gas projects to Korean specific situations.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.75-84
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• 2011

The objective of this study is to evaluate the hydrologic impacts of climate and land use changes in a rural small watershed. HadCM3 (Hadley Centre Coupled Model, ver.3) A2 scenario and LARS-WG (Long Ashton Research Station - Weather Generator) were used to generate future climatic data. Future land use data were also generated by the CA-Markov (Cellular Automata-Markov) method. The Soil and Water Assessment Tool (SWAT) model was used to evaluate hydrologic impacts. The SWAT model was calibrated and validated with stream flow measured at the Baran watershed in Korea. The SWAT model simulation results agreed well with observed values during the calibration and validation periods. In this study, hydrologic impacts were analyzed according to three scenarios: future climate change (Scenario I), future land use change (Scenario II), and both future climate and land use changes (Scenario III). For Scenario I, the comparison results between a 30-year baseline period (1997~2004) and a future 30-year period (2011~2040) indicated that the total runoff, surface runoff, lateral subsurface runoff, groundwater discharge, and evapotranspiration increased as precipitation and temperature for the future 30-year period increased. The monthly variation analysis results showed that the monthly runoff for all months except September increased compared to the baseline period. For Scenario II, both the total and surface runoff increased as the built-up area, including the impervious surface, increased, while the groundwater discharge and evapotranspiration decreased. The monthly variation analysis results indicated that the total runoff increased in the summer season, when the precipitation was concentrated. In Scenario III, the results showed a similar trend to that of Scenario II. The monthly runoff for all months except October increased compared to the baseline period.

• Journal of Climate Change Research
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• v.7 no.3
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• pp.257-268
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• 2016

Both economic growth and industrial structure have great influence on energy consumption and GHG emissions. This study analyzed long-term scenarios for GHG emissions projections considering economic growth and industry value added change. In consideration of 3 GDP and 3 industry value added outlook, total 9 scenarios were set; 'Assembly Industry Baseline(AI)', 'Assembly KEIT industry(AK)', 'Assembly Advanced Country industry(AA)', 'KDI Industry Baseline(KI)', 'KDI KEIT industry(KK)', 'KDI Advanced Country industry(KA)', 'OECD Industry Baseline(OI)', 'OECD KEIT industry(OK)', and 'OECD Advanced Country industry(OA)' scenarios. In consideration of the GDP increase rate and industry value added outlook, it is estimated that AI scenario's GHG emissions would be 777 million tons of $CO_2eq$ in 2030. On the other hand, in the case of OA scenario, GHG emissions would be 560.2 million tons of $CO_2eq$ in 2030. Differences between AI scenario's and OA scenario's were 216.8 million tons of $CO_2eq$. It can be identified by that GDP and industry value added change have great influence on GHG emissions. In view of the fact that Korea's amount of GHG emission reduction targets in 2030 were 218.6 million tons of $CO_2eq$ that the result of this research could give us valuable insight.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.833-842
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• 2013

The quantile mapping is utilized to reproduce reliable GCM(Global Climate Model) data by correct systematic biases included in the original data set. This scheme, in general, projects the Cumulative Distribution Function (CDF) of the underlying data set into the target CDF assuming that parameters of target distribution function is stationary. Therefore, the application of stationary quantile mapping for nonstationary long-term time series data of future precipitation scenario computed by GCM can show biased projection. In this research the Nonstationary Quantile Mapping (NSQM) scheme was suggested for bias correction of nonstationary long-term time series data. The proposed scheme uses the statistical parameters with nonstationary long-term trends. The Gamma distribution was assumed for the object and target probability distribution. As the climate change scenario, the 20C3M(baseline scenario) and SRES A2 scenario (projection scenario) of CGCM3.1/T63 model from CCCma (Canadian Centre for Climate modeling and analysis) were utilized. The precipitation data were collected from 10 rain gauge stations in the Han-river basin. In order to consider seasonal characteristics, the study was performed separately for the flood (June~October) and nonflood (November~May) seasons. The periods for baseline and projection scenario were set as 1973~2000 and 2011~2100, respectively. This study evaluated the performance of NSQM by experimenting various ways of setting parameters of target distribution. The projection scenarios were shown for 3 different periods of FF scenario (Foreseeable Future Scenario, 2011~2040 yr), MF scenario (Mid-term Future Scenario, 2041~2070 yr), LF scenario (Long-term Future Scenario, 2071~2100 yr). The trend test for the annual precipitation projection using NSQM shows 330.1 mm (25.2%), 564.5 mm (43.1%), and 634.3 mm (48.5%) increase for FF, MF, and LF scenarios, respectively. The application of stationary scheme shows overestimated projection for FF scenario and underestimated projection for LF scenario. This problem could be improved by applying nonstationary quantile mapping.

• Environmental Analysis Health and Toxicology
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• v.19 no.1
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• pp.49-58
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• 2004

It is important to select a risk based priority area for environmental policy formation and decision-making. We estimated the health risks and associated damage costs from exposure to fine particles and assigned priority areas for twenty -five districts in Seoul. In order to estimate the theoretical mortality incidence of the health risk, baseline risks were estimated from mortality rates in two low level areas of fine particles, Seocho Gu and Cheju city To estimate the damage cost from the risk estimates, we investigated and estimated the willingness to pay (WTP) for specific risk reduction. We assumed two different locations as the reference area, Cheju city as Scenario I and Seocho gu as Scenario II. From the results, the five districts, Kwangjin, Chungnang, Kangbuk, Nowon, and Kangnam, ranked high in the categories of both health risk and economic risk. Damage costs were over twenty billion won in each of these districts. As there are uncertainties in these results, the parameter values such as PM$_{2.5}$ level, dose -response slope factor, baseline risk, exposure population and WTP should be continuously validated and refined.d.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.5
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• pp.37-48
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• 2013

The objective of this study is to assess the impact of potential climate change on the hydrological components, especially on the streamflow, evapotranspiration and snowmelt, by using the Soil Water Assessment Tool (SWAT) for 17 Hanriver middle watersheds of South Korea. For future assessment, the SWAT model was calibrated in multiple sites using 4 years (2006-2009) and validated by using 2 years (2010-2011) daily observed data. For the model validation, the Nash-Sutcliffe model efficiency (NSE) for streamflow were 0.30-0.75. By applying the future scenarios predicted five future time periods Baseline (1992-2011), 2040s (2021-2040), 2060s (2041-2060), 2080s (2061-2080) and 2100s (2081-2100) to SWAT model, the 17 middle watersheds hydrological components of evapotranspiration, streamflow and snowmelt were evaluated. For the future precipitation and temperature of RCP 4.5 scenario increased 41.7 mm (2100s), $+3^{\circ}C$ conditions, the future streamflow showed +32.5 % (2040s), +24.8 % (2060s), +50.5 % (2080s) and +55.0 % (2100s). For the precipitation and temperature of RCP 8.5 scenario increased 63.9 mm (2100s), $+5.8^{\circ}C$ conditions, the future streamflow showed +35.5 % (2040s), +68.9 % (2060s), +58.0 % (2080s) and +63.6 % (2100s). To determine the impact on snowmelt for Hanriver middle watersheds, snowmelt parameters of SWAT model were determined through evaluating observed streamflow data during snowmelt periods (November-April). The results showed that average SMR (snowmelt / runoff) of 17 Hanriver middle watersheds was 62.0 % (Baseline). The annual average SMR were 42.0 % (2040s), 39.8 % (2060s), 29.4 % (2080s) and 27.9 % (2100s) by applying RCP 4.5 scenario. Also, the annual average SMR by applying RCP 8.5 scenario were 40.1 % (2040s), 29.4 % (2060s), 18.3 % (2080s) and 12.7 % (2100s).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.39-45
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• 2016

This study analyses the macroeconomic effects of the direct payment system (DPS) for environment-friendly agriculture in Korea. We utilized the applied general equilibrium model (AGE model) for the general agricultural sector as well as the environmentally-friendly agricultural sector. We considered several scenarios based on various direct payment amounts to measure and analyze economic impacts. Scenario 1 considers the current direct payment system. Scenario 2 examines an additional 5% increase from the direct payment amount in scenario 1. Scenario 3 reviews an increase of 10% in direct payment amount while Scenario 4 considers an additional increase of 15% compared with Scenario 1. Lastly, scenario 5 examines a 20% increase in direct payment amounts compared with scenario 1. In addition, the baseline considers conditions prior to the introduction of the direct payment system. The simulation analysis results show that capital formation, production volume, and labor productivity increased in the environment-friendly agricultural sector. In contrast, employment in the environment-friendly agricultural sector decreased. The price of environment-friendly agricultural products following the introduction of the DPS remain consistent with the price of environment-friendly agricultural product before introducing the DPS. This results from price elasticity of supply and demand are inelastic, and there is no change in the income of consumers during the analysis period. However, additional research is necessary for improvement of the model using complementary statistical data for the environmental-friendly agriculture sector.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.5
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• pp.27-43
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• 2019

This study applied the LANDIS-II model to the forest vegetation of the study area in Yeongdong-gun, Korea to identify climate effects on ecosystems of forest vegetation. The main purpose of the study is to examine the long-term changes in forest aboveground biomass(AGB) under three different climate change scenarios; The baseline climate scenario is to maintain the current climate condition; the RCP 4.5 scenario is a stabilization scenario to employ of technologies and strategies for reducing greenhouse gas emissions; the RCP 8.5 scenario is increasing greenhouse gas emissions over time representative with 936ppm of $CO_2$ concentration by 2100. The vegetation survey and tree-ring analysis were conducted to work out the initial vegetation maps and data for operation of the LANDIS model. Six types of forest vegetation communities were found including Quercus mongolica - Pinus densiflora community, Quercus mongolica community, Pinus densiflora community, Quercus variabilis-Quercus acutissima community, Larix leptolepis afforestation and Pinus koraiensis afforestation. As for changes in total AGB under three climate change scenarios, it was found that RCP 4.5 scenario featured the highest rate of increase in AGB whereas RCP 8.5 scenario yielded the lowest rate of increase. These results suggest that moderately elevated temperatures and $CO_2$ concentrations helped the biomass flourish as photosynthesis and water use efficiency increased, but huge increase in temperature ($above+4.0^{\circ}C$) has resulted in the increased respiration with increasing temperature. Consequently, Species productivity(Biomass) of trees decrease as the temperature is elevated drastically. It has been confirmed that the dominant species in all scenarios was Quercus mongolica. Like the trends shown in the changes of total AGB, it revealed the biggest increase in the AGB of Quercus mongolica under the RCP 4.5 scenario. AGB of Quercus mongolica and Quercus variabilis decreased in the RCP 4.5 and RCP 8.5 scenarios after 2050 but have much higher growth rates of the AGB starting from 2050 under the baseline scenario. Under all scenarios, the AGB of coniferous species was eventually perished in 2100. In particular they were extinguished in early stages of the RCP 4.5 and RCP 8.5 scenarios. This is because of natural selection of communities by successions and the failure to adapt to climate change. The results of the study could be expected to be effectively utilized to predict changes of the forest ecosystems due to climate change and to be used as basic data for establishing strategies for adaptation climate changes and the management plans for forest vegetation restoration in ecological restoration fields.