Sustainability considerations are becoming increasingly important in geotechnical engineering, driven by climate legislation and sustainability goals. Life cycle assessment (LCA) and life cycle cost analysis (LCCA) are commonly applied to evaluate environmental impacts and life cycle costs (LCC) of geotechnical design alternatives. However, uncertainties exist in life cycle inventory parameters, and a structured framework for incorporating these uncertainties into LCA and LCCA when comparing geotechnical design alternatives is currently lacking. This paper proposes a methodology in which input parameters are modelled as stochastic variables within the planning and decision making processes to identify geotechnical design alternatives with the lowest potential life cycle impact. Specifically, the methodology models uncertainties in material quantities, emission factors, unit costs, and monetisation parameters; combines LCA and LCCA results into a single decision-support metric using weighting factors; and provides a probabilistic evaluation for decision making by quantifying the probability of selecting a suboptimal design alternative. The methodology is illustrated by comparing the climate impact and LCC of two railway embankment design alternatives using Monte Carlo simulations: piled embankment and excavation and fill.
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Samuelsson et al. (2026) studied this question.
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