Greenhouse gas emission driving factors and reduction strategies for operational phase of urban rail transit in China

Abstract

To promote the sustainable development of urban rail transit (URT) in China, it is necessary to quantitatively analyze the greenhouse gas (GHG) emissions and its internal driving factors. Based on the LMDI algorithm, this research constructs an assessment model and makes a quantitative analysis of internal driving factors for GHG emissions in the operational phase of the URT system in China. According to the official investigated data, the GHG emission of URT in the operational phase is between 600 × 10⁴ and 2000 × 10⁴ tons of carbon dioxide equivalent (CO₂e) per year from 2012 to 2023. The results of the driving factors decomposition showed that the passenger demand intensity was the key and positive factor affecting carbon emissions in the operational phase and the contribution rate was 12.93%–60.81% from 2013 to 2023. Therefore, it is necessary to formulate targeted policies in terms of management and technical means to reduce the average traveling distance demanded by passengers and reasonably control the scale of the line network for GHG reduction in the Chinese URT system.