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The purpose of the paper is to present the results of the stochastic modelling with uncertainty performed with the use of Monte Carlo (MC) simulation with 10,000 cycles and a confidence interval of 95 %, as recommended. Analysed REEs were fitted by lognormal distributions by using the Crystal Ball® (CB) spreadsheet-based software after defining the geometric mean value (μg) and the standard deviation...
The use of Monte Carlo (MC) simulation was presented in order to assess uncertainty in life cycle inventory (LCI) studies. The MC method is finded as an important tool in environmental science and can be considered the most effective quantification approach for uncertainties. Uncertainty of data can be expressed through a definition of probability distribution of that data (e.g. through standard deviation...
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