Accelerating the penetration of clean electricity to promote the low carbonization of high-speed railways: A probabilistic framework

Abstract

Transitioning from carbon-intensive travel modes to high-speed railways (HSR) is widely recognized as a crucial pathway to achieving the ‘carbon peak and carbon neutrality’ goals in the transport sector. However, it remains unclear whether HSR can meet carbon peak goals on time, under the high uncertainty of future electricity development. This study integrates scenario analysis and Monte Carlo simulation into life cycle assessment, proposing a probabilistic framework for dynamically simulating the carbon dioxide (CO₂) emissions over the entire life cycle of HSR. Monte Carlo simulation-Latin hypercube sampling method is introduced to model the uncertainty in the development of electricity. The results show that with the gradual increase in the proportion of clean electricity, the time when the CO₂ emission intensity of HSR is lower than that of electric cars and electric coaches is most probable to occur in the 2nd–3rd years and the 5th–14th years of operation, respectively. The emission trend of HSR is primarily influenced by the passenger growth rate and the depth of transition to clean electricity, with minimal impact from the loading factor and initial passenger volume. When the passenger growth rate reaches 5 % by 2030, transitioning solely to clean electricity can peak CO₂ emissions from HSR by 2030. However, with passenger growth rates of 6 %, 7 %, 8 %, and 9 %, the peak time is most probable to be delayed by 6–7 years, 13–14 years, 16 years, and 19 years, respectively. These findings suggest that achieving CO₂ emission peak goals in the transport system requires collaborative efforts across multiple sectors, including transport, energy, and industry sectors. The results contribute to a deeper understanding of the pathways for achieving carbon peak in the transport sector.