• 한국기후변화학회지
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• 제6권3호
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• pp.243-248
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• 2015

This study was conducted to predict the changes of potential distribution for invasive alien plant, Conyza bonariensis in Korea. C. bonariensis was found in southern Korea (Jeju, south coast, southwest coast). The habitats of C. bonariensis were roadside, bare ground, farm area, and pasture, where the interference by human was severe. Due to the seed characteristics of Compositae, C. bonariensis take long scattering distance and it will easily spread by movement of wind, vehicles and people. C. canadensis in same Conyza genus has already spread on a national scale and it is difficult to manage. We used maximum entropy modeling (MaxEnt) for analyzing the environmental influences on C. bonariensis distribution and projecting on two different RCP scenarios, RCP 4.5 and RCP 8.5. The results of our study indicated annual mean temperature, elevation and temperature seasonality had higher contribution for C. bonariensis potential distribution. Area under curve (AUC) values of the model was 0.9. Under future climate scenario, the constructed model predicted that potential distribution of C. bonariensis will be increased by 338% on RCP 4.5 and 769% on RCP 8.5 in 2100s.

• 환경생물
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• 제36권4호
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• pp.687-693
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• 2018

The active development of the global marine trade industries has been known to increase the inflows of marine invasive species and harmful organisms into the ecosystem, and the marine ecological disturbances. One of these invasive species, Ciona robusta, has now spread to the Korea Strait, the East Sea, and Jeju Island in connection with the climate change but not the Yellow Sea in Korea. Currently, the spread and distribution of C. robusta is increasingly damaging aquaculture and related facilities. Therefore, this study aims to identify the spread of C. robusta and potential habitats and to secure a data for the prevention of effective management measures due to climate change as well as damage the reduction in future through the prediction of spread. We used environmental variables in BioOracle. Also, the potential habitat and distribution of C. robusta was predicted using MaxEnt, a species distribution model. Two different RCP scenarios(4.5 and 8.5) were specified to predict the future distributions of C. robusta. The results showed that the biggest environmental factor affecting the distribution of C. robusta was the salinity as well as the highest distribution and potential habitats existent in the East Sea and around Jeju Island.

• Journal of Ecology and Environment
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• 제45권3호
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• pp.130-142
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• 2021

Background: Climate change is occurring rapidly around the world, and is predicted to have a large impact on biodiversity. Various studies have shown that climate change can alter the geographical distribution of wild bees. As climate change affects the species distribution and causes range shift, the degree of range shift and the quality of the habitats are becoming more important for securing the species diversity. In addition, those pollinator insects are contributing not only to shaping the natural ecosystem but also to increased crop production. The distributional and habitat quality changes of wild bees are of utmost importance in the climate change era. This study aims to investigate the impact of climate change on distributional and habitat quality changes of five wild bees in northwestern regions of Iran under two representative concentration pathway scenarios (RCP 4.5 and RCP 8.5). We used species distribution models to predict the potential range shift of these species in the year 2070. Result: The effects of climate change on different species are different, and the increase in temperature mainly expands the distribution ranges of wild bees, except for one species that is estimated to have a reduced potential range. Therefore, the increase in temperature would force wild bees to shift to higher latitudes. There was also significant uncertainty in the use of different models and the number of environmental layers employed in the modeling of habitat suitability. Conclusion: The increase in temperature caused the expansion of species distribution and wider areas would be available to the studied species in the future. However, not all of this possible range may include high-quality habitats, and wild bees may limit their niche to suitable habitats. On the other hand, the movement of species to higher latitudes will cause a mismatch between farms and suitable areas for wild bees, and as a result, farmers will face a shortage of pollination from wild bees. We suggest that farmers in these areas be aware of the effects of climate change on agricultural production and consider the use of managed bees in the future.

• 한국환경보건학회지
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• 제34권5호
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• pp.343-350
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• 2008

Quantifying greenhouse gas (GHG) emissions in the waste sector is important to evaluating measures for reduction of GHG emissions. To forecast GHG emissions and identify potential emission reduction for GHG emissions, scenarios applied with environmental policy such as waste reduction and structural change of waste treatment were developed. Scenario I estimated GHG emissions under the business as usual (BAU) baseline. Scenario II estimated GHG emissions with the application of the waste reduction policy while scenario III was based on the policy of structural change of waste treatment. Scenario IV was based on both the policies of waste reduction and structural change of waste treatment. As for the different scenarios, GHG emissions were highest under scenarios III, followed by scenarios IV, I, and II. In particular, GHG emissions increased under scenario III due to the increased GHG emissions from the enhanced waste incineration due to the structural change of waste treatment. This result indicated that the waste reduction is the primary policy for GHG reduction from waste. GHG emission from landfill was higher compared to those from incineration. However, the contribution of GHG emission from incineration increased under scenario III and IV. This indicated that more attention should be paid to the waste treatment for incineration to reduce GHG emissions.

• 한국농공학회논문집
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• 제56권3호
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• pp.19-29
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• 2014

This study was to evaluate the potential climate change impact on watershed hydrological components of evapotranspiration, surface runoff, lateral flow, return flow, and streamflow using Soil and Water Assessment Tool (SWAT). For Yongdam dam watershed (930 $km^2$), the SWAT model was calibrated for five years (2002-2006) and validated for three years (2004-2006) using daily streamflow data at three locations and daily soil moisture data at five locations. The Nash-Sutcliffe model efficiency (NSE) and coefficient of determination ($R^2$) were 0.43-0.67 and 0.48-0.70 for streamflow, and 0.16-0.65 and 0.27-0.76 for soil moisture, respectively. For future evaluation, the HadGEM3-RA climate data by Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios were adopted. The biased future data were corrected using 30 years (1982-2011, baseline period) of ground weather data. The HadGEM3-RA 2080s (2060-2099) temperature and precipitation showed increase of $+4.7^{\circ}C$ and +22.5 %, respectively based on the baseline data. The impacts of future climate change on the evapotranspiration, surface runoff, baseflow, and streamflow showed changes of +11.8 %, +36.8 %, +20.5 %, and +29.2 %, respectively. Overall, the future hydrologic results by RCP emission scenarios showed increase patterns due to the overall increase of future temperature and precipitation.

• 자원ㆍ환경경제연구
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• 제21권3호
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• pp.543-572
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• 2012

본 연구는 2000년부터 현재까지 한국과 일본의 에너지 수급 현황을 비교하는 한편, 2000년 이후 발표된 중장기 저탄소 에너지 계획 및 시나리오 관련 문헌들을 검토하였다. 에너지수급 측면에서 한국과 일본은 모두 에너지 수입의존도가 높고, OECD 국가들 중에서 제조업의 비중이 높으며, 전력 계통은 외부와 고립된 시스템이며, 발전량에서 원전이 차지하는 비중이 높고, 재생에너지 잠재량은 높지만 실제 생산량은 낮다는 점 등이 유사하다. 차이점은 에너지 소비량 추세가 일본은 감소하는 반면, 한국은 증가하고 있으며, 지역간 전력 교류가 한국은 가능한 반면, 일본은 그렇지 않으며, 향후 원자력 확대가 일본은 어려울 전망인 반면, 한국의 현 정부는 원자력 확대 방침을 유지하고 있다는 점 등이다. 후쿠시마 원전 사고 전후로, 일본과 한국의 정부에서 수립한 에너지계획은 원자력을 약 2배 수준으로 확대할 계획으로 하고 있었지만, 시민사회에서는 에너지 수요 저감, 원자력의 단계적 축소, 재생에너지 확대를 내용으로 하는 시나리오들을 발표하였다. 본 연구는 일본과 한국의 중장기 에너지 시나리오 및 계획 수립 연구에 활용될 수 있을 것이다.

• Journal of Preventive Medicine and Public Health
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• 제50권2호
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• pp.83-90
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• 2017

Objectives: The aim of this study was to model the avoidable burden of the risk factors of road traffic crashes in Iran and to prioritize interventions to reduce that burden. Methods: The prevalence and the effect size of the risk factors were obtained from data documented by the traffic police of Iran in 2013. The effect size was estimated using an ordinal regression model. The potential impact fraction index was applied to calculate the avoidable burden in order to prioritize interventions. This index was calculated for theoretical, plausible, and feasible minimum risk level scenarios. The joint effects of the risk factors were then estimated for all the scenarios. Results: The highest avoidable burdens in the theoretical, plausible, and feasible minimum risk level scenarios for the non-use of child restraints on urban roads were 52.25, 28.63, and 46.67, respectively. In contrast, the value of this index for speeding was 76.24, 37.00, and 62.23, respectively, for rural roads. Conclusions: On the basis of the different scenarios considered in this research, we suggest focusing on future interventions to decrease the prevalence of speeding, the non-use of child restraints, the use of cell phones while driving, and helmet disuse, and the laws related to these items should be considered seriously.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.268-272
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• 2010

The research presented here represents a collaborative effort with the SFWMD on developing scenarios for future climate for the SFWMD area. The project focuses on developing methodology for simulating precipitation representing both natural quasi-oscillatory modes of variability in these climate variables and also the secular trends projected by the IPCC scenarios that are publicly available. This study specifically provides the results for precipitation modeling. The starting point for the modeling was the work of Tebaldi et al that is considered one of the benchmarks for bias correction and model combination in this context. This model was extended in the framework of a Hierarchical Bayesian Model (HBM) to formally and simultaneously consider biases between the models and observations over the historical period and trends in the observations and models out to the end of the 21st century in line with the different ensemble model simulations from the IPCC scenarios. The low frequency variability is modeled using the previously developed Wavelet Autoregressive Model (WARM), with a correction to preserve the variance associated with the full series from the HBM projections. The assumption here is that there is no useful information in the IPCC models as to the change in the low frequency variability of the regional, seasonal precipitation. This assumption is based on a preliminary analysis of these models historical and future output. Thus, preserving the low frequency structure from the historical series into the future emerges as a pragmatic goal. We find that there are significant biases between the observations and the base case scenarios for precipitation. The biases vary across models, and are shrunk using posterior maximum likelihood to allow some models to depart from the central tendency while allowing others to cluster and reduce biases by averaging. The projected changes in the future precipitation are small compared to the bias between model base run and observations and also relative to the inter-annual and decadal variability in the precipitation.

• 대한지리학회지
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• 제49권6호
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• pp.833-848
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• 2014

풍력발전단지의 신규 개발과 안정적인 운영 계획 수립을 위해 기후변화에 따른 미래 풍력에너지의 변동성 정보를 파악하는 것이 필요하다. 본 연구는 IPCC 5차 보고서에서 새롭게 도입된 대표농도경로(Representative Concentration Pathway)를 적용한 기후변화 시나리오 자료를 활용하여 2006년부터 2040년까지의 가까운 미래에 대한 풍력에너지(풍력에너지밀도와 잠재전력생산량)의 시 공간적 변동성을 분석하고자 한다. 사용된 기후변화 시나리오는 지역기후모델 HadGEM3-RA를 이용해 생산된 RCP2.6과 8.5자료이다. 시나리오 생산의 기반이 된 지역기후모델을 과거기간에 대하여 ECMWF의 ERA-interim 재분석자료와 비교분석한 결과, 지역 기후모델은 풍력에너지를 육지에서는 과소, 바다에서는 과대 모의하였다. 그리고 변동성 역시 육지에서 과소, 바다에서는 과대 모의하였다. 미래 풍력에너지는 RCP 시나리오별로 다소 차이가 나타나지만 육지에서 증가, 바다에서는 감소할 것으로 예측되었으며 고도가 높은 산지 및 해안지역에서 미래 풍력에너지의 변동성이 증가할 것으로 분석되었다. 지역별 풍력에너지밀도 분석결과 제주에서 크게 증가할 것으로 예상되었으며 변동성도 크게 증가하였다. 미래 풍력에너지의 변동은 주변 기상장의 변화와 연관 지어 해석이 가능하였으나 큰 변동성으로 인한 불확실성이 증가할 것으로 판단할 수 있다. 본 연구를 통해서 분석된 결과는 미래 에너지 수급 및 활용계획 수립에 있어 기초자료로 활용될 수 있으리라 판단한다.

• 한국농림기상학회지
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• 제15권4호
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• pp.219-233
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• 2013

본 연구는 산림에서 나타나는 수종의 분포 패턴을 해석하고 예측하기 위한 목적으로 수행되었다. 국내에서 처음으로 시도된 전국 규모의 체계적 산림조사라 할 수 있는 NFI (National Forest Inventory)의 수종별 출현 정보와 출현지점별 풍부도를 기반으로 소나무의 현존분포도를 작성하였다. 생태적 지위 모형의 하나인 GARP (Genetic Algorithm for Ruleset Production)를 이용하여 소나무 현존분포와 연관성이 높은 환경요인변수들을 선정하였고, 선정된 변수들을 설명변수로 하는 소나무 잠재분포 모형을 작성한 후 기후변화 시나리오를 적용하여 미래의 잠재분포를 예측하였다. 기후, 지리 지형, 토양 지질, 토지이용 및 식생현황 등 27개 환경요인변수를 각각 설명변수로 하여 모형을 구동함으로써 소나무 현존분포와의 연관성을 평가한 결과 1월 평균기온이 최상위를 차지하였고 연평균기온, 8월평균기온, 연교차 등도 영향을 미치는 것으로 분석되었다. NFI 정보로부터 추출하여 소스개체군으로 선정된 조사지점들을 소나무의 최종출현정보로, 환경요인변수 간의 연관성 분석을 통해 최종적으로 선정된 변수 세트를 설명변수로 하여 모형을 구동함으로써 최적의 모형을 선정한 후 잠재분포도를 작성하였다. 현재 시점의 환경요인변수들에 의해 트레이닝 된 잠재분포 모형에서 기후관련변수들을 RCP 8.5 기후변화시나리오에서 산출한 변수들로 대체하여 2020년대, 2050년대, 2090년대의 소나무의 예측 잠재분포도를 작성하였다. 최종적으로 작성된 소나무 잠재분포모형의 평가 통계량인 AUC (Area Under Curve)는 0.67로 다소 미흡하였으나 향후 기후변화 환경 하에서 소나무림의 보전 및 관리를 위한 최소한의 실마리를 제공할 수 있을 것으로 판단되었다.