Global Sensitivity Analysis in Life-Cycle Assessment of Early-Stage Technology using Detailed Process Simulation: Application to Dialkylimidazolium Ionic Liquid Production

被引:13
|
作者
Baaqel, Husain A. [1 ,2 ]
Bernardi, Andrea [1 ,2 ]
Hallett, Jason P. [3 ]
Guillen-Gosalbez, Gonzalo [4 ]
Chachuat, Benoit [1 ,2 ]
机构
[1] Imperial Coll London, Dept Chem Engn, London SW7 2AZ, England
[2] Imperial Coll London, Sargent Ctr Proc Syst Engn, London SW7 2AZ, England
[3] Imperial Coll London, Dept Chem Engn, London SW7 2AZ, England
[4] Swiss Fed Inst Technol, Inst Chem & Bioengn, CH-8093 Zurich, Switzerland
关键词
uncertainty quantification; global sensitivity analysis; life-cycle assessment; environmental sustainability; ionic liquid production; ENVIRONMENTAL SUSTAINABILITY; TECHNOECONOMIC ASSESSMENTS; ECOINVENT DATABASE; UNCERTAINTY; LCA; SEPARATION; IMPACT; METHODOLOGY; SOLVENTS; MODELS;
D O I
10.1021/acssuschemeng.3c00547
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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 lifecycle 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.
引用
收藏
页码:7157 / 7169
页数:13
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