Application of stochastic approach based on Monte Carlo (MC) simulation for life cycle inventory (LCI) of the rare earth elements (REEs) in beneficiation rare earth waste from the gold processing: case study
The study proposes an stochastic approach based on Monte Carlo (MC) simulation for life cycle assessment (LCA) method limited to life cycle inventory (LCI) study for rare earth elements (REEs) recovery from the secondary materials processes production applied to the New Krankberg Mine in Sweden. The...
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Format: | Article |
Language: | English |
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EDP Sciences
2017-01-01
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Series: | E3S Web of Conferences |
Online Access: | https://doi.org/10.1051/e3sconf/20172200018 |
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author | Bieda Bogusław Grzesik Katarzyna |
author_facet | Bieda Bogusław Grzesik Katarzyna |
author_sort | Bieda Bogusław |
collection | DOAJ |
description | The study proposes an stochastic approach based on Monte Carlo (MC) simulation for life cycle assessment (LCA) method limited to life cycle inventory (LCI) study for rare earth elements (REEs) recovery from the secondary materials processes production applied to the New Krankberg Mine in Sweden. The MC method is recognizes as an important tool in science and can be considered the most effective quantification approach for uncertainties. The use of stochastic approach helps to characterize the uncertainties better than deterministic method. Uncertainty of data can be expressed through a definition of probability distribution of that data (e.g. through standard deviation or variance). The data used in this study are obtained from: (i) site-specific measured or calculated data, (ii) values based on literature, (iii) the ecoinvent process „rare earth concentrate, 70% REO, from bastnäsite, at beneficiation”. Environmental emissions (e.g, particulates, uranium-238, thorium-232), energy and REE (La, Ce, Nd, Pr, Sm, Dy, Eu, Tb, Y, Sc, Yb, Lu, Tm, Y, Gd) have been inventoried. The study is based on a reference case for the year 2016. The combination of MC analysis with sensitivity analysis is the best solution for quantified the uncertainty in the LCI/LCA. The reliability of LCA results may be uncertain, to a certain degree, but this uncertainty can be noticed with the help of MC method. |
first_indexed | 2024-12-17T21:54:30Z |
format | Article |
id | doaj.art-c99f6eccaf234dcb8c2b417650d36034 |
institution | Directory Open Access Journal |
issn | 2267-1242 |
language | English |
last_indexed | 2024-12-17T21:54:30Z |
publishDate | 2017-01-01 |
publisher | EDP Sciences |
record_format | Article |
series | E3S Web of Conferences |
spelling | doaj.art-c99f6eccaf234dcb8c2b417650d360342022-12-21T21:31:10ZengEDP SciencesE3S Web of Conferences2267-12422017-01-01220001810.1051/e3sconf/20172200018e3sconf_asee2017_00018Application of stochastic approach based on Monte Carlo (MC) simulation for life cycle inventory (LCI) of the rare earth elements (REEs) in beneficiation rare earth waste from the gold processing: case studyBieda BogusławGrzesik KatarzynaThe study proposes an stochastic approach based on Monte Carlo (MC) simulation for life cycle assessment (LCA) method limited to life cycle inventory (LCI) study for rare earth elements (REEs) recovery from the secondary materials processes production applied to the New Krankberg Mine in Sweden. The MC method is recognizes as an important tool in science and can be considered the most effective quantification approach for uncertainties. The use of stochastic approach helps to characterize the uncertainties better than deterministic method. Uncertainty of data can be expressed through a definition of probability distribution of that data (e.g. through standard deviation or variance). The data used in this study are obtained from: (i) site-specific measured or calculated data, (ii) values based on literature, (iii) the ecoinvent process „rare earth concentrate, 70% REO, from bastnäsite, at beneficiation”. Environmental emissions (e.g, particulates, uranium-238, thorium-232), energy and REE (La, Ce, Nd, Pr, Sm, Dy, Eu, Tb, Y, Sc, Yb, Lu, Tm, Y, Gd) have been inventoried. The study is based on a reference case for the year 2016. The combination of MC analysis with sensitivity analysis is the best solution for quantified the uncertainty in the LCI/LCA. The reliability of LCA results may be uncertain, to a certain degree, but this uncertainty can be noticed with the help of MC method.https://doi.org/10.1051/e3sconf/20172200018 |
spellingShingle | Bieda Bogusław Grzesik Katarzyna Application of stochastic approach based on Monte Carlo (MC) simulation for life cycle inventory (LCI) of the rare earth elements (REEs) in beneficiation rare earth waste from the gold processing: case study E3S Web of Conferences |
title | Application of stochastic approach based on Monte Carlo (MC) simulation for life cycle inventory (LCI) of the rare earth elements (REEs) in beneficiation rare earth waste from the gold processing: case study |
title_full | Application of stochastic approach based on Monte Carlo (MC) simulation for life cycle inventory (LCI) of the rare earth elements (REEs) in beneficiation rare earth waste from the gold processing: case study |
title_fullStr | Application of stochastic approach based on Monte Carlo (MC) simulation for life cycle inventory (LCI) of the rare earth elements (REEs) in beneficiation rare earth waste from the gold processing: case study |
title_full_unstemmed | Application of stochastic approach based on Monte Carlo (MC) simulation for life cycle inventory (LCI) of the rare earth elements (REEs) in beneficiation rare earth waste from the gold processing: case study |
title_short | Application of stochastic approach based on Monte Carlo (MC) simulation for life cycle inventory (LCI) of the rare earth elements (REEs) in beneficiation rare earth waste from the gold processing: case study |
title_sort | application of stochastic approach based on monte carlo mc simulation for life cycle inventory lci of the rare earth elements rees in beneficiation rare earth waste from the gold processing case study |
url | https://doi.org/10.1051/e3sconf/20172200018 |
work_keys_str_mv | AT biedabogusław applicationofstochasticapproachbasedonmontecarlomcsimulationforlifecycleinventorylcioftherareearthelementsreesinbeneficiationrareearthwastefromthegoldprocessingcasestudy AT grzesikkatarzyna applicationofstochasticapproachbasedonmontecarlomcsimulationforlifecycleinventorylcioftherareearthelementsreesinbeneficiationrareearthwastefromthegoldprocessingcasestudy |