Stochastic parametric LCA of GHG footprints of hyperloop systems

Abstract

Hyperloop systems offer high-speed, low-emission transport, yet existing life-cycle assessments (LCA) report inconsistent greenhouse gas (GHG) results because of differing system boundaries and assumptions. This study introduces a stochastic parametric LCA framework that quantifies both expected GHG emissions and associated uncertainties across four hyperloop configurations. A unified variance-decomposition model captures uncertainty arising from both design-type decisions and cross-design parameters, and maps these to stakeholder groups. Applied to a Zurich–Geneva case study, results show that tube material has the greatest impact on mean emissions, while component service life is the largest single source of uncertainty and operational parameters collectively contribute the second-largest share. Among stakeholders, operators have the greatest influence on GHG footprint by controlling most of the operational parameters and affecting component lifespans through maintenance. Infrastructure designers show the second greatest influence, primarily via their decision between using concrete or steel tubes. Pod designers rank third by determining the levitation technology and pod design characteristics, while constructors have the least influence, with their most impactful decision being the selection of material suppliers. This decision-centric framework enables transparent evaluation of carbon impacts and uncertainty and supports sustainable infrastructure planning for next-generation transport systems.