Journal of the Korean Society for Railway (한국철도학회논문집)

The Korean Society for Railway (한국철도학회)
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LMDI Decomposition Analysis on Characteristics of Greenhouse Gas Emission from the Line of Railroad in Korea

LMDI 분해 분석을 이용한 국내 철도 노선별 온실가스 배출 특성 분석

  • 이재형 (카이트엔지니어링 환경리스크팀) ;
  • 임지재 (카이트엔지니어링 환경리스크팀) ;
  • 김용기 (한국철도기술연구원 융복합연구단) ;
  • 이재영 (한국철도기술연구원 에코시스템연구실)
  • Received : 2012.05.04
  • Accepted : 2012.06.13
  • Published : 2012.06.30
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Abstract

Korean government is enforcing 'Greenhouse gas target management' in order to achieve Greenhouse gas reduction target. To attain Greenhouse gas reduction target, companies in Korea must establish their GHG inventory system and analysis their GHG emissions characteristics for deduction of mitigation measures. LMDI(Log Mean Divisia Index) decomposition analysis is widely used to understand characteristics of GHG emission and energy consumption. In this paper, the characteristics of GHG emission from the line of railroad in Korea is respectively analyzed in terms of conversion effect, intensity effect, production effect and distance effect. Data of railroad GHG emission from 2000 to 2007 are used. As a result, total effect of railroad's GHG emission is $96,813tCO_2eq$. Production effect ($39,865tCO_2eq$) and distance effect ($327,923tCO_2eq$) affect increase of railroad GHG emissions while Conversion effect ($-158,161tCO_2eq$) and intensity effect ($-112,814tCO_2eq$) influence decrease of the emissions.

국가의 온실가스 감축목표를 달성하기 위한 방안으로 온실가스 목표관리제를 시행하고 있다. 온실가스 감축목표를 달성하기 위해서는 온실가스 인벤토리가 구축되어야 하며, 효과적인 온실가스 감축 수단을 도출하기 위해서는 온실가스 배출 특성을 분석해야 한다. 국내외에서는 온실가스 배출 및 에너지 사용 특성을 분석하기 위한 방법론으로 로그평균디비지아지수(LMDI: Log Mean Divisia Index) 분석 기법이 자주 사용되고 있다. 본 논문에서는 온실가스 배출특성을 LMDI 분석 방법론을 통해 전환효과, 원단위효과, 생산효과, 거리효과 등의 4가지 요인으로 나누어 분석하였다. 분석 대상은 한국철도공사가 관리하는 광역철도 및 도시철도를 대상으로 하였으며, 자료의 분석 기간은 2000년부터 2007년까지로 설정하였다. 분해분석결과 2000년과 2007년 사이의 철도수송에 따른 온실가스 배출량의 총효과는 96,813톤$CO_2eq$으로 나타났다. 철도 수송에 따른 온실가스 배출량 증가에 영향을 미치는 효과는 생산효과와 거리효과로 나타났으며, 온실가스 배출량 감소에 영향을 미치는 효과는 전환효과와 원단위효과로 나타났다.

Keywords

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