**Acknowledgements**

REEs were not included in the process of generating tornado and spider charts as other thirteen

Spider chart is obtained by perturbing Ce, La, and Nd median values (input variables) at consistent (testing) range from 10 to 90% from the base case, which used percentile of the variables from the base case method. The vertical y-axis maps the location measure of distribution expressed in percentages (percentile of the variables) ranging from 10 to 90% (see **Figure 6**). The variation of each input parameter (Ce, La, and Nd) (e.g., by 10, 50, and 90%) showed how

Spider chart is obtained by perturbing Ce, La, and Ne median values (input variables) at consistent (testing) range from 10 to 90% from the base case, which used percentile of the variables from the base case method. The vertical y-axis maps the location measure of distribution expressed in percentages (percentile of the variables) ranging from 10 to 90% (see **Figure 6**). The horizontal x-axis maps the sum of analyzed REEs (in ppm). As a result, the spider chart

This study refers to uncertainty in the input parameters used to create LCI of REE recovery processes from secondary sources performed according to ISO 14040 (2006). The focus of this study is defined in the goal and scope and was developed using the primary and secondary data.

Due to uncertainty analysis, a final result is obtained in the form of value range. The results from this study suggest that MC simulation is an effective method for quantifying parameter

The analyzed parameters are assigned with lognormal distribution. It is concluded that uncertainty analysis offers a well-defined procedure for LCI studies; early phase of LCA as

The methodological approach regarding databases and boundaries was transparent and fully documented. Moreover, the results of this study can help to assess environmental impacts of rare earth mining, because production of REEs is associated with considerable environmental burdens. Additionally these result inventory data will be available for LCIA and, finally, for full LCA analysis. The obtained results may be also useful and interesting for further studies of REE recovery and could be used to other domestic and international LCA studies, and the study results demonstrate the utility of the MC simulation for a clear interpretation of LCA results. Moreover, they can also help scientist gain a cleaner understanding of the stochastic modeling in the environmental engineering and could be useful tool for decision support

And finally, consideration of uncertainty in LCA provides additional scientific information

the deterministic analysis does not include uncertainty in the input data.

for decision-making, as discussed in the work of Romero-Gámez et al. [73].

methods such as multi-criteria decision analysis.

enables the possibility to simultaneously compare the examined REEs [23, 24].

REEs are not in the field of ENVIRRE project research scope and interest.

much the output (REE Total sum) changes.

**5. Conclusions**

40 Lanthanides

uncertainty in LCA studies.

The authors are grateful for the input data provided as part of the environmentally friendly and efficient methods for extraction of rare earth elements from secondary sources (ENVIREE) project funded by NCBR within the second ERA-NET ERA-MIN Joint Call Sustainable Supply of Raw Materials in Europe 2014.
