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

• 영문명: Bottom-Up Projection of Regional Carbon Emissions from Passenger Road Vehicles Based on Discrete-Time Markov Chain
• 발행기관: 한국자료분석학회
• 저자명: Kyumin Yeom Sanghoon Ha Kiseong Kim Soohyun Kim Minseok Jeon Young Jin Kim
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.25 No.5, 1623~1635쪽, 전체 13쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2023.10.31

영문 초록

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.

목차

1. Introduction

2. Method of Emissions Estimation

3. Data on Regional Passenger Road Transport

4. GHG Emissions with Country-Specific Parameters

5. Concluding Remarks

References

키워드

Road Transportation Carbon Emissions Projection Discrete-Time Markov Chain IPCC Guidelines for National Greenhouse Gas Inventories