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      Bottom-Up Projection of Regional Carbon Emissions from Passenger Road Vehicles Based on Discrete-Time Markov Chain

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      https://www.riss.kr/link?id=A108813603

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      다국어 초록 (Multilingual Abstract)

      Accounting for a significant portion of global carbon emissions, the road transportation sector is unequivocally one of the largest emitter among various sectors and a wide variety of mitigation measures has been developed and adopted. The estimation of carbon emissions is a prerequisite for assessing the effectiveness of individual measures. This study outlines the estimation of carbon emissions from road transport based on a discrete-time Markov chain employed to describe the population of road vehicles by fuel type over time. The procedure outlined in the IPCC Guidelines for National Greenhouse Gas Inventories is adopted to estimate the carbon emissions based on the country-specific parameters, which is then applied to the projection of regional carbon emissions from road transport in the Metropolitan Busan City, Republic of Korea. More specifically, country-specific parameters are derived from publicly available data related to carbon emissions from road transport. It is asserted that publicly available data can be effectively collated and incorporated to develop the discrete-time Markov chain to estimate the population of road vehicles, based on which carbon emissions from road transport can then be estimated.
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      Accounting for a significant portion of global carbon emissions, the road transportation sector is unequivocally one of the largest emitter among various sectors and a wide variety of mitigation measures has been developed and adopted. The estimation ...

      Accounting for a significant portion of global carbon emissions, the road transportation sector is unequivocally one of the largest emitter among various sectors and a wide variety of mitigation measures has been developed and adopted. The estimation of carbon emissions is a prerequisite for assessing the effectiveness of individual measures. This study outlines the estimation of carbon emissions from road transport based on a discrete-time Markov chain employed to describe the population of road vehicles by fuel type over time. The procedure outlined in the IPCC Guidelines for National Greenhouse Gas Inventories is adopted to estimate the carbon emissions based on the country-specific parameters, which is then applied to the projection of regional carbon emissions from road transport in the Metropolitan Busan City, Republic of Korea. More specifically, country-specific parameters are derived from publicly available data related to carbon emissions from road transport. It is asserted that publicly available data can be effectively collated and incorporated to develop the discrete-time Markov chain to estimate the population of road vehicles, based on which carbon emissions from road transport can then be estimated.

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      참고문헌 (Reference)

      1 최기홍 ; 윤성민, "한국 탄소배출권 시장의 효율성 분석" 한국자료분석학회 25 (25): 235-247, 2023

      2 김영덕 ; 한현옥, "에너지기본계획이 온실가스배출 저감과 에너지효율 개선에 미친 영향에 대한 실증적 분석" 한국자료분석학회 20 (20): 1281-1292, 2018

      3 박건진 ; 김필수 ; 최상진 ; 한용희 ; 이헌주 ; 이갑상 ; 장영기, "실차 운행정보를 이용한 온실가스 배출량 산정에 관한 연구" 한국기후변화학회 6 (6): 143-158, 2015

      4 김기동 ; 고현기 ; 이태정 ; 김동술, "배출량 산정방법에 따른 지자체 도로수송부문의 온실가스 배출량 산정 비교" 한국대기환경학회 27 (27): 405-415, 2011

      5 이성희 ; 문승호, "난방열 절약이벤트 효과 분석의 불확도 평가" 한국자료분석학회 16 (16): 1907-1916, 2014

      6 우주희 ; 신동훈, "국내 탄소배출권거래시장 수요측면의 가격결정요인분석" 한국자료분석학회 24 (24): 1391-1404, 2022

      7 "Total Registered Motor Vehicles"

      8 Bell, M. J., "The Effect of Changing CowProduction and Fitness Traits on Net Income and Greenhouse Gas Emission from Australian DairySystems" 96 (96): 7918-7931, 2013

      9 "Statistics Korea"

      10 Alhindawi, R., "Projection of Greenhouse Gas Emissions for the Road Transport Sector Based on Multivariate Regression and the Double Exponential Smoothing Model" 12 : 9152-, 2020

      1 최기홍 ; 윤성민, "한국 탄소배출권 시장의 효율성 분석" 한국자료분석학회 25 (25): 235-247, 2023

      2 김영덕 ; 한현옥, "에너지기본계획이 온실가스배출 저감과 에너지효율 개선에 미친 영향에 대한 실증적 분석" 한국자료분석학회 20 (20): 1281-1292, 2018

      3 박건진 ; 김필수 ; 최상진 ; 한용희 ; 이헌주 ; 이갑상 ; 장영기, "실차 운행정보를 이용한 온실가스 배출량 산정에 관한 연구" 한국기후변화학회 6 (6): 143-158, 2015

      4 김기동 ; 고현기 ; 이태정 ; 김동술, "배출량 산정방법에 따른 지자체 도로수송부문의 온실가스 배출량 산정 비교" 한국대기환경학회 27 (27): 405-415, 2011

      5 이성희 ; 문승호, "난방열 절약이벤트 효과 분석의 불확도 평가" 한국자료분석학회 16 (16): 1907-1916, 2014

      6 우주희 ; 신동훈, "국내 탄소배출권거래시장 수요측면의 가격결정요인분석" 한국자료분석학회 24 (24): 1391-1404, 2022

      7 "Total Registered Motor Vehicles"

      8 Bell, M. J., "The Effect of Changing CowProduction and Fitness Traits on Net Income and Greenhouse Gas Emission from Australian DairySystems" 96 (96): 7918-7931, 2013

      9 "Statistics Korea"

      10 Alhindawi, R., "Projection of Greenhouse Gas Emissions for the Road Transport Sector Based on Multivariate Regression and the Double Exponential Smoothing Model" 12 : 9152-, 2020

      11 "Our World in Data"

      12 IPCC, "Mobile Combustion, In 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 2"

      13 Sim, S., "Measuring Greenhouse Gas Emissions for the Transportation Sector inKorea" 230 : 129-151, 2015

      14 Bencekri, M., "Investigation of Transport Carbon Emissions in Korea" 97 : 175-180, 2022

      15 Yang, J., "GHG Mitigation Plan of Busan Metropolitan City by 2030" Busan Development Institute 93-99, 2020

      16 Charabi, Y., "GHG Emissions fromthe Transport Sector in Oman : Trends and Potential Decarbonization Pathways" 32 : 100548-, 2020

      17 Bell, M. J., "Effects of Changing Cow Productionand Fitness Traits on Profit and Greenhouse Gas Emissions of UK Dairy Systems" 153 (153): 138-151, 2015

      18 Kim, S., "Decomposition Analysis of Greenhouse Gas Emissions in Korea’s Transportation Sector" 11 : 1986-, 2019

      19 Ministry of Environment, "Code on GHG Emissions Trading Act: Verification and Certification"

      20 "Climate Action Tracker"

      21 "Carbon Pollution from Transportation"

      22 Abbas, S., "Analysis and Projection of Transport Sector Demand for Energy and Carbon Emission : An Application of the Grey Model inPakistan" 11 : 1443-, 2023

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