Life Cycle assessments (LCAs) on electric mobility are providing a plethora of diverging results. 44 articles, published from 2008 to 2018 have been investigated in this review, in order to find the extent and the reason behind this deviation. The first hurdle can be found in the goal definition, followed by the modelling choice, as both are generally incomplete and inconsistent. These gaps influence the choices made in the Life Cycle Inventory (LCI) stage, particularly in regards to the selection of the electricity mix. A statistical regression is made with results available in the literature. It emerges that, despite the wide-ranging scopes and the numerous variables present in the assessments, the electricity mix's carbon intensity can explain 70% of the variability of the results. This encourages a shared framework to drive practitioners in the execution of the assessment and policy makers in the interpretation of the results.

Electricity generation in LCA of electric vehicles: A review

Marmiroli, Benedetta;Dotelli, Giovanni;
2018-01-01

Abstract

Life Cycle assessments (LCAs) on electric mobility are providing a plethora of diverging results. 44 articles, published from 2008 to 2018 have been investigated in this review, in order to find the extent and the reason behind this deviation. The first hurdle can be found in the goal definition, followed by the modelling choice, as both are generally incomplete and inconsistent. These gaps influence the choices made in the Life Cycle Inventory (LCI) stage, particularly in regards to the selection of the electricity mix. A statistical regression is made with results available in the literature. It emerges that, despite the wide-ranging scopes and the numerous variables present in the assessments, the electricity mix's carbon intensity can explain 70% of the variability of the results. This encourages a shared framework to drive practitioners in the execution of the assessment and policy makers in the interpretation of the results.
2018
Attributional; Consequential; Electric vehicle; Electricity mix; Energy system; LCA; Marginal; Meta-analysis; Plug-in hybrid; System modelling; Well-to-wheel; Materials Science (all); Instrumentation; Engineering (all); Process Chemistry and Technology; Computer Science Applications1707 Computer Vision and Pattern Recognition; Fluid Flow and Transfer Processes
File in questo prodotto:
File Dimensione Formato  
P238. Electricity Generation in LCA of Electric Vehicles A Review_2018_applsci.pdf

accesso aperto

Descrizione: published version
: Publisher’s version
Dimensione 4.51 MB
Formato Adobe PDF
4.51 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1069494
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 73
  • ???jsp.display-item.citation.isi??? 67
social impact