Application of uncertainty analysis based on Monte Carlo (MC) simulation for life cycle inventory (LCI)

Abstract

The use of Monte Carlo (MC) simulation was presented inorder to assess uncertainty in life cycle inventory (LCI) studies. The MCmethod is finded as an important tool in environmental science and can beconsidered the most effective quantification approach for uncertainties.Uncertainty of data can be expressed through a definition of probabilitydistribution of that data (e.g. through standard deviation or variance). Thepresented case in this study is based on the example of the emission ofSO2, generated during energy production in Integrated Steel Power Plant(ISPP) in Kraków, Poland. MC simulation using software Crystal Ball®(CB), software, associated with Microsoft® Excel, was used for theuncertainties analysis. The MC approach for assessing parameteruncertainty is described. Analysed parameter (SO2,) performed in MCsimulation were assigned with log-normal distribution. Finally, the resultsobtained using MC simulation, after 10,000 runs, more reliable than thedeterministic approach, is presented in form of the frequency charts andsummary statistics. Thanks to uncertainty analysis, a final result is obtainedin the form of value range. The results of this study will encourage otherresearchers to consider this approach in their projects, and the results ofthis study will encourage other LCA researchers to consider the uncertaintyin their projects and bring closer to industrial application.