The ability to assess
the environmental performance of early-stage
technologies at production scale is critical for sustainable process
development. This paper presents a systematic methodology for uncertainty
quantification in life-cycle assessment (LCA) of such technologies
using global sensitivity analysis (GSA) coupled with a detailed process
simulator and LCA database. This methodology accounts for uncertainty
in both the background and foreground life-cycle inventories, and
is enabled by lumping multiple background flows, either downstream
or upstream of the foreground processes, in order to reduce the number
of factors in the sensitivity analysis. A case study comparing the
life-cycle impacts of two dialkylimidazolium ionic liquids is conducted
to illustrate the methodology. Failure to account for the foreground
process uncertainty alongside the background uncertainty is shown
to underestimate the predicted variance of the end-point environmental
impacts by a factor of two. Variance-based GSA furthermore reveals
that only few foreground and background uncertain parameters contribute
significantly to the total variance in the end-point environmental
impacts. As well as emphasizing the need to account for foreground
uncertainties in LCA of early-stage technologies, these results illustrate
how GSA can empower more reliable decision-making in LCA.