Location is a major barrier for transferring US fossil fuel employment to green jobs.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
26 09 2023
Historique:
received: 20 02 2023
accepted: 23 08 2023
medline: 4 10 2023
pubmed: 27 9 2023
entrez: 26 9 2023
Statut: epublish

Résumé

The green energy revolution may displace 1.7 million fossil fuel workers in the US but a Just Transition to emerging green industry jobs offers possibilities for re-employing these workers. Here, using 14 years of power plant data from the US Energy Information Administration, job transition data from the Census Bureau, as well as employment and skills data from the Bureau of Labor Statistics, we assess whether people employed in fossil fuel resource extraction today are co-located and have the transferable skills to switch to expected green jobs. We find that these workers could leverage their mobility to other industries and have similar skills to green occupations. However, today's fossil fuel extraction workers are not co-located with current sources of green energy production. Further, after accounting for federal employment projections, fossil fuel extraction workers are mostly not located in the regions where green employment will grow despite attaining the appropriate skillsets. These results suggest a large barrier to a Just Transition since fossil fuel extraction workers have not historically exhibited geospatial mobility. While stakeholders focus on re-skilling fossil fuel extraction workers, this analysis shows that co-location with emerging green employment will be the larger barrier to a Just Transition.

Identifiants

pubmed: 37752111
doi: 10.1038/s41467-023-41133-9
pii: 10.1038/s41467-023-41133-9
pmc: PMC10522673
doi:

Substances chimiques

Fossil Fuels 0

Banques de données

figshare
['10.6084/m9.figshare.23907732']

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

5711

Informations de copyright

© 2023. Springer Nature Limited.

Références

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Auteurs

Junghyun Lim (J)

Department of Political Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, USA.

Michaël Aklin (M)

PASU Chair, College of Management of Technology, EPFL, 1015, Lausanne, Switzerland.
Enterprise for Society, 1015, Lausanne, Switzerland.

Morgan R Frank (MR)

Department of Informatics and Networked Systems, University of Pittsburgh, Pittsburgh, PA, 15216, USA. mrfrank@pitt.edu.
Digital Economy Lab, Institute for Human-Centered Artificial Intelligence, Stanford University, Stanford, CA, 94305, USA. mrfrank@pitt.edu.
Media Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. mrfrank@pitt.edu.

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