Embodied GHG emissions of high speed rail stations: Quantification, data-driven prediction and cost-benefit analysis

• Published in: Journal of cleaner production Vol. 366; p. 133006
• Main Authors: Jia, Siyi, Liu, Minghui
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.09.2022
• Subjects: carbon; China; Cost-benefit analysis; Embodied GHG emissions; High speed rail stations; infrastructure; inventories; multivariate analysis; Neural network; prediction; rail transportation; risk; China; Cost-benefit analysis; High speed rail stations; Neural network; Embodied GHG emissions

The embodied green-house gas (GHG) emissions from the high speed rail (HSR) stations are non-negligible given the considerable scale of modern HSR stations that serve as multifunctional complex. However, the magnitude of the GHG emissions is often underestimated owing to the limited use of reliable...