Optimization Study on Carbon Emissions Reduction of Tram Stations Based on Life Cycle Assessment
- DOI
- 10.2991/978-94-6463-728-1_61How to use a DOI?
- Keywords
- Urban rail transit; Tram station; Life cycle assessment; Reduction potential
- Abstract
As one of the largest carbon emissions sector in China, the transportation sector accounts for about 10% of the total carbon emissions in China. Urban rail transit plays a pivotal role in promoting the green development of the transportation sector, yet it also contributes to carbon emissions. Studying the life cycle carbon emissions of urban rail transit stations is crucial for achieving China’s dual carbon goals. This paper focuses on a tram station in Guangzhou, applying life cycle assessment (LCA) theory to compute and analyze its total carbon emissions. Furthermore, it proposes carbon reduction strategies and quantitatively assesses their potential. The analysis reveals that the life cycle carbon emissions amount to 5,475,431.8 kg CO2e, with a potential reduction of 1,109,824.5 kg CO2e, corresponding to a 20.3% reduction potential. The findings aim to provide insights for energy conservation and emissions reduction at urban rail transit stations, fostering the green development of the sector and supporting China’s strategies for Carbon peak and Carbon neutrality.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Xin Chen AU - Xun Yang AU - Gefei Yan PY - 2025 DA - 2025/05/19 TI - Optimization Study on Carbon Emissions Reduction of Tram Stations Based on Life Cycle Assessment BT - Proceedings of the 3rd International Conference on Green Building, Civil Engineering and Smart City (GBCESC 2024) PB - Atlantis Press SP - 649 EP - 666 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-728-1_61 DO - 10.2991/978-94-6463-728-1_61 ID - Chen2025 ER -