• 한국대기환경학회지
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• 제28권4호
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• pp.454-465
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• 2012

The Korean government decided to reduce 30% of GHG (greenhouse gas) emissions BAU in 2020. Since many efforts to reduce emissions are urgently needed in Korea, the central administrative organization urges local governments to establish their own reduction schemes. Among many GHG emission categories, the emission from mobile source in Gyeonggi Province accounted for 25.3% of total emissions in 2007 and further the emission from road transport sector occupied the most dominant portion in this transportation category. The objective of this study was to compare 3 types of GHG emissions from road transport sector in 31 local cities/counties of Gyeonggi Province, which have been estimated by Tier 1, Tier 2, and Tier 3 methodologies. As results, the GHG emission rates by the Tier 1 and Tier 2 were $19,991kt-CO_2\;Eq/yr$ and $18,511kt-CO_2\;Eq/yr$, respectively. On the other hand, the emission rate by Tier 3 excluding a branch road emission portion was $18,051kt-CO_2\;Eq/yr$. In addition, the total emission rate including all the main and branch road portions in Gyeonggi Province was $24,152kt-CO_2\;Eq/yr$, which was estimated by a new Tier 3 methodology. Based on this study, we could conclude that Tier 3 is a reasonable methodology than Tier 1 or Tier 2. However, more accurate and less uncertain methodology must be developed by expanding traffic survey areas and adopting a suitable model for traffic volumes.

• 한국대기환경학회지
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• 제16권5호
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• pp.499-509
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• 2000

Next to carbon dioxide, methane is the second largest contributor to global warming among anthropogenic greenhouse gases. Methane is emitted into the atmosphere from both natural and anthropogenic sources. Natural sources include wetlands, termites, wildries, ocean and freshwater. Anthropogenic sources include landfill, natural gas and oil production, and agriculture. These manmade sources account for about 70% of total global methane emissions; and among these, landfill accounts for approximately 10% of total manmade emissions. Solid waste landfills produce methane as bacteria decompose organic wastes under anaerobic conditions. Methane accounts for approximately 45 to 50 percent of landfill gas, while carbon dioxide and small quantities of other gases comprise the remaining to 50 to 55 percent. Using the closed enclosure technique, surface emission fluxes of methane from the selected landfill sites were measured. These data were used to estimate national methane emission rate from domestic landfills. During the three different periods, flux experiments were conducted at the sites from June 30 through December 26, 1999. The chamber technique employed for these experiments was validated in situ. Samples were collected directly by on-site flux chamber and analyzed for the variation of methane concentration by gas chromatography equipped with FID. Surface emission rates of methane were found out to vary with space and time. Significant seasonal variation was observed during the experimental period. Methane emission rates were estimated to be 64.5$\pm$54.5mgCH$_4$/$m^2$/hr from Kimpo landifll site. 357.4$\pm$68.9mgCH$_4$/$m^2$/hr and 8.1$\pm$12.4mgCH$_4$/$m^2$/hr at KwanJu(managed and unmanaged), 472.7$\pm$1056mgCH$_4$/$m^2$/hr at JonJu, and 482.4$\pm$1140 mgCH$_4$/$m^2$/hr at KunSan. These measurement data were used for the extrapolation of national methane emission rate based on 1997 national solid waste data. The results were compared to those derived by theoretical first decay model suggested by IPCC guidelines.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2008년도 학술발표회 논문집
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• pp.1097-1101
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• 2008

본 연구에서는 SLURP 수문모형을 이용하여 미래기후와 예측된 토지이용자료 및 식생의 활력도를 고려한 상태에서 하천유역의 유출 및 증발산량에 미치는 영향을 분석하였다. 경안천 상류유역($260.04\;km^2$)을 대상유역으로 선정하여 4개년(1999-2002) 동안의 일별 유출량 자료를 바탕으로 모형의 보정(1999-2000)과 검증(2001-2002)을 실시하였다. 모형의 보정 및 검정 결과 Nash-Sutcliffe 모형효율은 0.79에서 060의 범위로 나타났다. 미래 기후자료는 IPCC(Intergovernmental Panel on Climate Change)에서 제공하는 A1B 기후변화시나리오의 MIROC3.2 hires, ECHAM5-OM, HadCM3 모델의 결과값을 이용하였다. 먼저 과거 30년 기후자료(1977-2006, baseline)를 바탕으로 각 모델별 20C3M(20th Century Climate Coupled Model)의 모의 결과값을 이용하여 강수와 온도를 보정한 뒤 Change Factor Method로 Downscaling하였다. 미래 기후자료는 2020s(2010-2039), 2050s(2040-2069), 2080s(2070-2099)의 세 기간으로 나누어 분석하였다. 미래 토지이용은 과거 시계열 Landsat 토지이용도를 이용하여 CA-Markov기법으로 예측된 토지이용을 사용하였으며, 미래의 식생정보 예측을 위하여 NOAA/AVHRR 위성영상으로부터 추출된 월별 NDVI(1998-2002)와 월평균기온간의 선형 회귀식을 도출하여 미래의 식생지수 정보를 추정하였다. 모형의 적용결과, 미래기후변화에 따른 연평균 하천유출은 현재보다 최대 2020s는 23.9%, 2050s는 40.7%, 2080s는 39.5% 증가하였다. 봄 강수량 패턴의 변화로 유출량 증가하는 것으로 나타났으며 여름에는 유출량은 감소하고 증발산량은 증가하는 결과를 보였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2008년도 학술발표회 논문집
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• pp.189-193
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• 2008

본 연구는 충주댐 유역을 대상으로 미래의 기후변화, 그에 따른 식생상태, 그리고 미래의 토지이용 변화를 고려한 상태에서 SWAT-K 모형에 의한 수문순환인자들의 변화가 댐의 유입량에 미치는 영향을 파악하고자 한다. SWAT 모형의 검보정은 6년간($2000{\sim}2006$, 2001년 제외)의 댐유입량 자료를 이용하여 실시하였으며, Nash_Sutcliffe 모형효율은 $0.52{\sim}0.88$의 범위로 검보정되었다. 기후변화 시나리오는 IPCC에서 제공하고 있는 GCM들 중에서 CCCma CGCM2의 A2, B2 시나리오를 이용하였으며, 댐유역의 기후변화를 모의하기 위하여 과거 30년간($1977{\sim}2006$)의 기상자료 통계정보를 기준으로 Change Factor Downscaling 기법을 적용하여 2030년, 2060년, 2090년 전후의 각 30년간의 미래 정보를 재생산하였다. 미래의 식생정보는 7년($2000{\sim}2006$)간의 MODIS 위성 영상에 의한 엽면적 지수를 월단위로 구축하여 엽면적 지수와 평균기온간의 상관회귀식을 도출하여 미래 기후변화에 따른 식생의 활력도를 예측하였다. 미래의 토지이용 변화는 CA-MArkov 기법을 개선, 적용하여 총 9개의 토지이용 항목에 대하여 각 항목별 예측을 실시하였다. 2000년의 기상자료 및 댐유입량을 기준으로 이상의 미래기후, 식생, 토지이용 에측 정보를 적용하여 미래의 댐유입량을 모의한 결과를 분석하였다. 그 결과 강수량 및 온도의 변동이 가장 크게 영향을 주어 유입량의 변화가 모의되었으며, 이에 따른 수문인자의 변동은 2000년 기준으로 증발산량, 토양수분의 변동을 분석하였다. 미래의 수문순환에 가장 큰 영향을 주는 수문인자는 토양수분으로 나타나, 미래에는 산림지역 및 토지이용 개발에 따른 토양수분의 함양량 유지를 위한 유역관리가 중요한 요인이 될 것으로 나타났다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2008년도 학술발표회 논문집
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• pp.529-533
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• 2008

본 연구는 미래기후변화가 공간해상도(5, 10, 30m)에 따른 토양유실량의 변화에 미치는 영향을 분석하고 자하였다. 연구대상지역은 경안천 최상류에 위치한 $1.16km^2$의 농촌 소유역을 대상으로 공간해상도별(5, 10, 30m) RS 및 GIS 자료를 생성하고, GIS 기반의 RUSLE(Revised Universal Soil Loss Equation) 모형을 채택하여 토양유실량을 분석하였다. 기후변화 시나리오는 IPCC(Intergovernmental Panel on Climate Change)에 서 제공하는 GCM(Global climate model) 중에서 MIROC3.2 hire의 A1B, B1 시나리오를 이용하였으며, 과거 30년간(1977-2006)의 기상자료 통계정보를 기준으로 Change Factor Downscaling 기법을 적용하여 2020s년 (2010-2039), 2050s년(2040-2069), 2080s년(2069-2099) 전후의 각 30년간의 미래 강우량을 재생산하여 사용하였다. 그 결과 강수량은 2080s년에 A1B 시나리오의 경우 연평균 강수량은 270.37mm, 최대 강수량은 65.71mm 증가하였고, B1 시나리오의 경우 연평균 강수량은 37.11mm, 최대 강수량은 48.46mm 증가하는 것으로 나타났다. 구축한 미래 강우량을 RUSLE 인자 중 R 인자에 적용하여 2020s년, 2050s년, 2080s년의 토양유실량을 분석한 결과, 미래강수량이 증가함에 따라 공간해상도별 토양유실량도 증가하는 것으로 분석되었다. 평균토양유실량을 시나리오별로 보면, A1B 시나리오의 경우 2080s을 기준으로 1/5,000 scale에서는 약 0.18 ton/ha/year, 1/25,000 scale에서는 약 0.07 ton/ha/year, 1/50,000 scale에서는 약 0.07 ton/ha/year의 유실량이 각 공간해상도별로 증가하였다. B1 시나리오의 경우 2080s을 기준으로 1/5,000 scale에서는 약 0.03 ton/ha/year, 1/25,000 scale에서는 약 0.01 ton/ha/year, 1/50,000 scale에서는 약 0.01 ton/ha/year의 토양유실량이 증가한 것으로 분석되었다.

• 한국환경과학회지
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• 제24권3호
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• pp.303-316
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• 2015

The relationship between urban spatial structures and GHG-AP integrated emissions was investigated by statistically analyzing those from 25 administrative districts of Seoul. Urban spatial structures, of which data were obtained from Seoul statistics yearbook, were classified into five categories of city development, residence, environment, traffic and economy. They were further classified into 10 components of local area, population, number of households, residential area, forest area, park area, registered vehicles, road area, number of businesses and total local taxes. GHG-AP integrated emissions were estimated based on IPCC(intergovernmental panel on climate change) 2006 guidelines, guideline for government greenhouse inventories, EPA AP-42(compilation of air pollutant emission factors) and preliminary studies. The result of statistical analysis indicated that GHG-AP integrated emissions were significantly correlated with urban spatial structures. The correlation analysis results showed that registered vehicles for GHG (r=0.803, p<0.01), forest area for AP (r=0.996, p<0.01), and park area for AP (r=0.889, p<0.01) were highly significant. From the factor analysis, three groups such as city and traffic categories, economy category and environment category were identified to be the governing factors controlling GHG-AP emissions. The multiple regression analysis also represented that the most influencing factors on GHG-AP emissions were categories of traffic and environment. 25 administrative districts of Seoul were clustered into six groups, of which each has similar characteristics of urban spatial structures and GHG-AP integrated emissions.

• 한국환경복원기술학회지
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• 제12권2호
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• pp.95-105
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• 2009

Land Use Changes (LUCs) have effects on greenhouse gas emissions and carbon stocks in soil and vegetation. Therefore, predictions for LUC are very important for achieving quantitative targets of $CO_2$ reduction rates. Some research exists on carbon fluxes and carbon cycles to estimate carbon stocks in terrestrial ecosystems in Korea. However, these researches have limitations in terms of helping us understand future potential reductions of $CO_2$ that reflect the influence of LUC. The aim of this study is to analyze the reduction levels of $CO_2$ emissions while considering LUC scenarios that effect carbon fluxes for LCS basic study in the year 2030. In this study, a common approach to model the effects of LUC on carbon stocks is the use of CA-Markov technical process with LUC patterns in the past. Potential reduction of $CO_2$ is calculated by change of land use that contains different soil organic carbon, each land use type, and biomass in vegetation. An IPCC analytical method of natural carbon sink and coefficient results from previous study in Korea is used as a calculation method for potential reduction of $CO_2$. As a result, 12,419 KtC will be reduced annually, which is 8.3% percent of 2005 $CO_2$ emissions in Korea. This will result in 3,226 hundred million won of economic efficiency. In conclusion, conservation of natural carbon sinks is necessary even if the amount of potential reduction change is little.

• 한국농공학회논문집
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• 제56권2호
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• pp.47-57
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• 2014

This study was conducted to predict greenhouse gas (GHG) emission from paddy by future climate change scenario in Korea. Chuncheon city in Kangwon province were selected as study area. A1B Special Report on Emission Scenario (SRES) of the IPCC (Intergovernmental panel on climate change) was used to assess the future potential climate change. The rainfall and temperature was projected to increase by 8.4 % and 1.9 % (2040s), 35.9 % and 27.0 % (2060s), 19.2 % and 30.8 % (2090s), respectively, compare to the 2010s value. Under the climate change, Denitrification-Decomposition (DNDC) predicted an increase in $N_2O$, $CO_2$ and $CH_4$ emissions from paddy. The simulations resulted in annual net emissions of 0.4~2.4, 500.5~734.5 and 29.4~160.4 kg/ha/year of $N_2O-N$, $CH_4-C$ and $CO_2-C$, respectively, with a cumulated global warming potential (GWP) of $14.5{\sim}21.7t{\cdot}CO_2/ha/year$ were affected by rainfall, temperature, manure amendment and fertilizer amount. The simulation results suggested that implementation of manure amendment or reduction of water consumption instead of increased fertilizer application rates would more efficiently mitigate GHG emissions.

• 한국제4기학회지
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• 제23권1호
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• pp.42-53
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• 2009

최근 급격한 온실가스 증가에 기인하여 대기와 해양 그리고 빙권의 변화가 나타나고 또한 기온과 수분의 함량 변화에 따라서 지표 환경도 서서히 변하기 시작하는 것으로 보고되고 있다. 지표환경의 반응은 생지화학적 반응과 생물리학적 반응으로 구분 할 수 있는데, 생지화학적 반응은 기후변화에 따른 광합성이나 이와 유사한 지표환경의 변화 그리고 이에 따른 화학적인 피드백을 지칭하며 이는 대기의 온실가스 농도를 변화 시키는 역할을 한다. 생물리학적 반응은 기후변화에 따라 식생의 분포가 변하게 되고 이에 따른 태양에너지의 입사율 변화 등과 같은 물리적 반응을 나타낸다. 과거 기후변화역사에도 식생의 변화가 기후변화에 미치는 영향이 매우 컸던 경우가 있었고, 앞으로의 기후변화는 거대하고 급격하게 일어날 것으로 예측되기 때문에, 미래 기후변화의 정확한 예측을 위해서는 지표환경변화의 물리 화학적 변화를 이해하고 예측 모형에 정확히 포함시킬 필요가 있다.

• 한국농공학회논문집
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• 제55권4호
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• pp.55-63
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• 2013

This study investigates the trends and uncertainty of the impacts of climate change on paddy rice production in the Geumho river basin. The Long Ashton Research Station stochastic Weather Generator (LARS-WG) was used to derive future climate data for the Geumho river basin from 15 General Circulation models (GCMs) for 3 Special Report on Emissions Scenarios (SRES) (A2, A1B and B1) included in the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report. The Food and Agricultural Organization (FAO) AquaCrop, a water-driven crop model, was statistically calibrated for the 1982 to 2010 climate. The index of agreement (IoA), prediction efficiency ($R^2$), percent bias (PBIAS), root mean square error (RMSE) and a visual technique were used to evaluate the adjusted AquaCrop simulated yield values. The adjusted simulated yields showed RMSE, NSE, IoA and PBIAS of 0.40, 0.26, 0.76 and 0.59 respectively. The 5, 9 and 15 year central moving averages showed $R^2$ of 0.78, 0.90 and 0.96 respectively after adjustment. AquaCrop was run for the 2020s (2011-2030), 2050s (2046-2065) and 2090s (2080-2099). Climate change projections for Geumho river basin generally indicate a hotter and wetter future climate with maximum increase in the annual temperature of $4.5^{\circ}C$ in the 2090s A1B, as well as maximum increase in the rainfall of 45 % in the 2090s A2. The means (and ranges) of paddy rice yields are projected to increase by 21 % (17-25 %), 34 % (27-42 %) and 43 % (31-54 %) for the 2020s, 2050s and 2090s, respectively. The A1B shows the largest rice yield uncertainty in all time slices with standard deviation of 0.148, 0.189 and $0.173t{\cdot}ha^{-1}$ for the 2020s, 2050s and 2090s, respectively.