Literature DB >> 35390387

Global environmental cost of using rare earth elements in green energy technologies.

Saeed Rahimpour Golroudbary1, Iryna Makarava2, Andrzej Kraslawski3, Eveliina Repo4.   

Abstract

Decarbonization of economy is intended to reduce the consumption of non-renewable energy sources and emissions from them. One of the major components of decarbonization are "green energy" technologies, e.g. wind turbines and electric vehicles. However, they themselves create new sustainability challenges, e.g. use of green energy contributes to the reduction of consumption of fossil fuels, on one hand, but at the same time it increases demand for permanent magnets containing considerable amounts of rare earth elements (REEs). This article provides the first global analysis of environmental impact of using rare earth elements in green energy technologies. The analysis was performed applying system dynamics modelling methodology integrated with life cycle assessment and geometallurgical approach. We provide evidence that an increase by 1% of green energy production causes a depletion of REEs reserves by 0.18% and increases GHG emissions in the exploitation phase by 0.90%. Our results demonstrate that between 2010 and 2020, the use of permanent magnets has resulted cumulatively in 32 billion tonnes CO2-equivalent of GHG emissions globally. It shows that new approaches to decarbonization are still needed, in order to ensure sustainability of the process. The finding highlights a need to design and implement various measures intended to increase REEs reuse, recycling (currently below 1%), limit their dematerialization, increase substitution and develop new elimination technologies. Such measures would support the development of appropriate strategies for decarbonization and environmentally sustainable development of green energy technologies.
Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Critical materials; Decarbonization measures; Energy supply; Environmental sustainability; Green energy

Year:  2022        PMID: 35390387     DOI: 10.1016/j.scitotenv.2022.155022

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  1 in total

1.  Detection and Relative Quantification of Neodymium in Sillai Patti Carbonatite Using Decision Tree Classification of the Hyperspectral Data.

Authors:  Muhammad Qasim; Shuhab D Khan
Journal:  Sensors (Basel)       Date:  2022-10-05       Impact factor: 3.847

  1 in total

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