국가 리스크 관리를 위한 기후변화 적응역량 구축·평가 : 극한기후 리스크의 경제적 분석

Abstract

Ⅰ. Introduction 1. Research background ？ There is an increasing need to quantitatively assess the risks that result from uncertain socioeconomic and climate changes, as well as the cost and effectiveness of policies for adapting to these changes. ㅇ The scale of damage caused by future climate change and extreme climate phenomena is not completely understood. Risk and adaptive capacity analyses have not been systematically conducted. ㅇ According to Weyant (2014), the use of Integrated Assessment Models (IAMs), which can predict the impact of climate change and consider policy countermeasures, needs to be further explored. ？ Within this new changing climate regime, it is vitally important to ensure strong adaptive capacity. ㅇ The submission of reports regarding the achievement and adaptation of Sustainable Development Goals (SDGs) has become mandatory. ㅇ The 50th session of the subsidiary body of the Nairobi Work Programme (NWP) regarding the impacts, vulnerability, and adaptation to climate change determined nine priority areas: extreme climate, drought, water scarcity, land degradation neutrality, forests and grasslands, oceans, coastal areas and ecosystems, agriculture, and food security. 2. Necessity and differentiation of research ？ Although some domestic studies have been conducted to quantify the economic impact of climate change, few have explored the socioeconomic environment and extreme climate phenomena. ㅇ The purpose of this research is to develop a tool that can economically quantify the risk of extreme climate phenomena and assess the effectiveness and adaptive capacity of countermeasures. ㅇ Climate change adaptation plans can be established and prioritized by quantifying sectoral bottom-up economic risks that are caused by extreme weather. They should reflect domestic conditions and analyze the economic risks for multiple future socioeconomic and climate scenarios through top-down models. 3. Purpose and scope of the research ？ This study seeks to develop a policy support tool that can quantitatively analyze domestic climate change risks and adaptation policy effects. ㅇ This is achieved by first developing a tool that determines the effects of climate change-related risks and adaptation policies based on an active reflection of the domestic climate, socioeconomic, and environmental conditions. ㅇ Then, a second tool is developed that can multilaterally analyze the risks of uncertain future climate and socioeconomic conditions, and the cost effects of adaptation policies that aim to mitigate these risks. ？ Annual progress plan ㅇ In 2020, the focus was placed on analyzing the tool development status for economic analysis, developing measures to quantify sectoral economic risks in extreme climates, and conducting a pilot analysis on the impacts of extreme climates. ㅇ In 2021, the representative extreme climate and socioeconomic scenarios will be developed and adaptation options and capacities will be analyzed through an impact analysis of the various developed scenarios. ㅇ Finally, in 2022, the potential implications of each extreme climate- socioeconomic scenario will be reported by analyzing policy effects for several constructed adaptation models used to combat extreme climate risks. Ⅱ. A Top-down Analysis Methodology for the Impact of Extreme Climates based on Integrated Assessment Models 1. Analysis of integrated assessment models ？ Generally, the structure and method of integrated climate and economic assessment models include similar climate-economy policy modules. 2. Methodology for quantifying the impact of climate change ？ Comparison of climate change quantification methodologies in each integrated climate economy assessment model ㅇ In all IAMs mentioned in this paper except DICE, the impact is divided into 4 to 12 sectors of concern and analyzed by region. ㅇ In the FUND model, the impact is divided into 12 sectors so as to make it possible to derive a more detailed overview of the impact in each sector. ㅇ In the PAGE model, impacts are analyzed based on the difference between the effects simulated using the average temperature and those simulated using the set limit temperature. ㅇ The FUND model assumes that there is a linear relationship between temperature change and climate change, whereas all other models in this comparison assume a nonlinear relationship. 3. Methodology for quantifying adaptation effects ？ Features of the methods used to quantify adaptation effects in each model ㅇ AD-DICE and WITCH maximize social welfare by considering the costs and effects of adaptation policies. ㅇ The PAGE model develops and assesses the simulation scenarios which take adaptation policies into consideration. ㅇ The AD-DICE model calculates the effects of adaptation by combining them into a single category. ㅇ The WITCH, FUND, and PAGE models consider the adaptation effects by subdividing them into different sectors according to each model. 4. Integrated assessment model development plan ？ Currently, the utilization and scope of applications for IAMs are limited and not yet well-established. However, a few studies have used IAMs to estimate the damage and impacts of climate change. ㅇ Hwang (2017) used the FUND model to estimate the cost of damage from climate change in Korea taking uncertainty into account. ㅇ Ahn et al. (2017) developed KRICE, a Korean integrated analysis model based on the DICE and RICE models. ㅇ Chae et al. (2017) calculated the cost of damage from climate change in several different scenarios in Korea using the PAGE model and the analysis of socioeconomic pathways. ？ The coefficients need to be measured and functions that reflect the advantages of IAMs as well as domestic data and research need to be developed to explain damage to the economy, quality of life, and human lives caused by extreme climates. ㅇ Further research is required to examine the effects of extreme climate in several at-risk regions. ㅇ Coefficients and functions must be developed to build assessment models through the generalization of research results. Ⅲ. Bottom-up and Top-down Economic Quantification Analyses by Sector 1. Health ？ Effects of extreme climates ㅇ Extreme climate adversely affects or damages various organs of the body, thereby causing new diseases, worsening pre-existing diseases, and sometimes leading to death. ㅇ McMichael (2013) classified the effects of heat and cold waves on health into biological effects from direct exposure and indirect effects from processes and societal changes. ㅇ Mora et al. (2017) summarized the direct effects of heatwaves on the human body in terms of ischemia, cell damage, inflammation, disseminated intravascular coagulation, and rhabdomyolysis. ㅇ Several different diseases such as cardiovascular disease, heart disease, and stroke are also associated with heatwaves (Kovats, Hajat, and Wilkinson, 2004; Lin et al., 2009). ？ Quantification methodology ㅇ Patients with heat-related illnesses: The total medical expenses are estimated using the number of patients with diseases due to extreme climate and the medical expenses per person. ㅇ Mortality: The amount of economic loss is estimated using the number of excess deaths and the Value of Statistical Life measurement. ㅇ Labor productivity: The amount of economic loss due to a decrease in labor productivity is estimated through analysis of the decrease in work efficiency in each occupation by estimating the WBGT heat index using temperature and humidity. ？ Pilot analysis results ㅇ During the heatwave in Korea in 2018, economic losses estimated through the quantification methodology were reported to be 3.9 billion, 41.0 billion, and 345 billion KRW due to patients with heat-related illness, deaths of patients with heat-related illness, and the decrease in labor productivity, respectively. ？ Analysis of the effects of adaptation policy ㅇ The heatwave response policy in Korea, which focuses on heat-related illnesses in vulnerable social groups, is being implemented through intensive management of groups such as elderly people who live alone, homeless people, and residents of slice rooms. This initiative strengthens the safety of children and educational facilities, as well as safety management in various places such as outdoor construction sites. In the future, additional related policies will need to be created that focus not only on the direct impacts but also on the indirect impacts of extreme climate, such as a decrease in labor productivity. 2. Energy ？ Effects of extreme climates ㅇ Energy supply - The efficiency and durability of the energy supply may be reduced due to extreme climates. - An example of bottom-up analysis (POLES) of the impact of extreme weather events / conditions on energy supply provides an influence function for the relationship between climate change effects and thermal and hydroelectric power plant capacity and power generation, the wind loading coefficient, and solar PV efficiency. The quantification index provides the amount of power generated and the energy mix compared to the baseline scenario. - Top-down analysis (GRACE) of the impact of climate change on energy supply reflects an influence function relating the change in the annual average temperature and annual average precipitation to the power generation supply. The quantification index provides the power supply compared to the baseline scenario. ㅇ Energy demand - Extreme climates change the amount of energy consumed for cooling and heating in summer and winter; this effect varies depending on the temporal and spatial range. - Mensbrugghe (2010), Aaheim et al. (2012), and Tol (2002) presented changes in energy consumption due to extreme climates along with the subsequent changes in GDP by using the top-down models of ENVISAGE, GRACE, and FUND, respectively. - Many prior studies have estimated changes in energy consumption as a function of temperature using the bottom-up panel fixed effect models (Davis and Gertler, 2015; Kim, 2017, etc.). ？ Quantification methodology ㅇ Energy supply - Bottom-up methodology: The effect of extreme climates on the energy supply sector can be derived by using the influence function of extreme climates in the generation mix optimization model for the power sector. For the impact of climate change on the energy supply, Solaun and Cerda (2019) and Dowling (2013) were referred to; the final influence function that can be used in the model was derived taking the data availability into account. - Top-down methodology: The economic impact of extreme climates on the power generation sector can be analyzed by reflecting the climate change influence function suggested by the GRACE model in a single country recursive dynamic computable general equilibrium model. The influence function is established using the coefficients of the East Asia region presented in the GRACE model. ㅇ Energy demand - The changes in energy consumption in summer due to temperature rise are estimated based on city-, county-, and district-panel fixed-effect models using domestic data. - The difference in the sensitivity of changes in energy consumption is estimated according to the income level. ？ Pilot analysis results ㅇ Using the number of days of exposure per temperature bin as an independent variable, energy consumption increased by approximately 3.341% when the number of days with the maximum temperature between 34-36 °C per month increased by one day, compared to days with the maximum temperature between 12-14 °C. ㅇ When the monthly average temperature was used as an independent variable, a 1 °C rise in temperature caused a 4.6-4.8% increase in energy consumption and losses of 43.4 billion KRW occurred due to the increase in electricity bills. ㅇ Energy consumption in high-income regions is more sensitive to temperature rise than in low-income regions. ？ Analysis of the effects of adaptation policy ㅇ Energy supply - Based on the analysis in this paper, a system that is differentiated from the current power generation facility management system which is centered on large power generation companies needs to be established. This will enable the effective utilization of renewable energy which is expected to expand in the future. - Although the 2nd National Climate Change Adaptation Plan (2016-2020) suggested the “establishment of a vulnerability management system for energy supply facilities (key industry) and preparation of plans to minimize the decrease in efficiency for each power generation source [complementing and expanding the current plan]” as one of the tasks, specific countermeasures against climate change risks for energy supply facilities were not included in the plans or guidelines related to energy supply facilities. - Although engineering designs are required to quantify the effects of adaptation policy, there may still be limitations. Therefore, the effectiveness of each adaptation plan must be identified and quantified through expert surveys while considering experimental trends in engineering from a long-term perspective. ㅇ Energy demand - Various energy demand adaptation policies such as energy efficiency improvement policies, demand response programs, and energy labeling programs are currently being implemented. However, more effective energy welfare policies still need to be developed.

Ⅰ. 서론 1. 연구배경 ？ 불확실한 기후 및 사회·경제 여건 변화에 따른 리스크와 적응 정책의 비용 및 효과를 정량적으로 평가할 필요성 증대 ㅇ 미래 기후변화 및 극한기후로 인한 피해 규모 파악, 리스크 및 적응역량 분석이 체계적으로 이루어지지 않음 ㅇ Weyant(2014)는 기후변화의 영향을 예측하고 정책적 대응방안을 고려할 수 있는 기후변화에 대한 통합평가 모형(IAM)을 분석할 필요가 있다고 제안 ？ 신기후체제에서 적응역량 확보에 대한 중요성 강조 ㅇ 지속가능개발(SDG) 달성과 적응 관련 보고서 제출 의무화 ㅇ 기후변화 영향, 취약성 적응에 관한 나이로비 작업 프로그램(NWP) 제50차 부속기구회의는 우선순위 분야로 극한기후, 가뭄, 물부족, 토지 황폐화 중립, 산림과 초원, 해양, 연안지역 및 생태계, 농업과 식량안보에 대해 논의 2. 연구의 필요성 및 차별성 ？ 국내 연구에서 기후 및 사회·경제 시나리오가 개발되었으나 합리적 정책 평가에 대한 적용 사례가 부족하고, 극한기후 현상에 대한 고려가 미흡 ㅇ 이에 본 연구에서 극한기후에 대한 리스크를 경제적으로 정량화하고 적응역량 및 적응 정책의 효과를 평가할 수 있는 도구를 개발하고자 함 3. 연구의 목적 및 범위 ？ 국내 기후변화 리스크 및 적응 정책 효과를 정량적으로 분석할 수 있는 정책 지원 도구 개발을 목적으로 함 ㅇ 국내 실정을 적극적으로 반영하여 국내의 기후 사회·경제 환경 여건 등에 의해 기후변화 관련 리스크 및 적응 정책의 효과 등이 결정되는 도구 개발 ㅇ 미래 불확실한 기후 및 사회·경제 여건에 대한 리스크를 다각도로 분석하고, 미래 다양한 시나리오에 대한 적응 정책의 비용 효과 분석이 가능한 도구 개발 ？ 연차별 진행계획 ㅇ 2020년에는 경제성 분석을 위한 도구 개발 현황 분석 및 극한기후의 부문별 경제적 리스크 정량화 방안 도출, 극한기후 영향에 대한 시범 분석 진행 ㅇ 2021년에는 극한기후 및 사회·경제 시나리오를 개발하고 부문별 시나리오에 따른 영향 분석으로 적응 옵션 및 역량 분석 ㅇ 2023년에는 미래 시나리오에 따른 극한기후 리스크 적응 모형 구축으로 극한기후-사회·경제 시나리오별 정책 효과 분석 및 시사점 제시 Ⅱ. 통합분석 모형 기반 극한기후 영향의 하향식 분석 방법론 1. 통합분석 모형 분석 ？ 기후경제 통합평가 모형의 연결 구조 및 방식은 DICE 초기 모형과 유사 2. 기후변화 영향의 정량화 방법론 ？ 기후경제 통합평가 모형별 기후변화 영향의 정량화 방법론 비교 ㅇ DICE 이외 모형은 영향을 지역별로 4~12개 분야로 나누어 분석 ㅇ FUND 모형은 12개 분야로 나누어 분야별로 영향을 세밀하게 도출할 수 있도록 함 ㅇ PAGE 모형은 한계온도를 설정하여 평균온도 변화와의 차이를 바탕으로 영향을 분석 ㅇ FUND 이외 모형은 온도변화와 기후변화 간의 관계를 비선형적 구조로 가정 3. 적응 효과의 정량화 방법론 ？ 모형별 적응 효과 정량법의 특징 ㅇ AD-DICE, WITCH모형은 적응의 비용과 효과를 고려하여 사회적 후생의 극대화가 목적 ㅇ PAGE 모형은 적응 정책을 고려한 시나리오를 구축하여 평가하는 방식 사용 ㅇ AD-DICE 모형의 경우 적응에 대한 효과를 단일 부분으로 설정하여 계산 ㅇ WITCH, FUND, PAGE 모형은 적응 효과를 각 모형에 따라 세분화하여 고려 4. 결어: 국내에 적용 가능한 극한기후 리스크 분석 도구 개발을 위한 제언 ？ 국내에 적용 가능한 기후변화 통합분석 모형은 한국의 상황과 가치를 우선순위로 반영 필요 ㅇ 황인창(2017)은 FUND 모형을 활용하여 불확실성을 고려한 국내 기후변화 피해비용을 산출 ㅇ 안영환, 김동구(2017)는 DICE 모형과 RICE 모형을 토대로 한국형 통합분석 모형인 KRICE 모형을 개발 ㅇ 채여라 외(2017)는 PAGE 모형과 사회·경제 경로 분석을 통해 한국의 시나리오별 기후변화 피해비용을 산출 ？ 극한기후로 인한 경제 및 인명 피해의 설명이 가능한 계수 측정 및 함수 개발 필요 ㅇ 극한기후로 인해 일어날 수 있는 다양한 분야의 개별적인 연구 필요 ㅇ 연구 결과에 따르면 일반화 작업을 통해 평가 모형 구축을 위한 계수 및 함수 개발 가능 [이하 본문 확인]