On the right track? Energy use, carbon emissions, and intensities of world rail transportation, 1840–2020
(2024) In Applied Energy 367.- Abstract
The history of rail transport can offer valuable insights for future energy transitions due to its importance in promoting clean mobility. There is a complex interplay between the evolution of the railway network, fuel consumption, efficiency, energy service, and CO2 emissions that requires further exploration. We developed a dataset that covers energy use in all stages of rail transportation, as well as the length of track, energy service, and CO2 emissions at the world scale. To deal with missing data we utilized machine learning techniques for the first time in a historical energy reconstruction study. Our analysis reveals that for world rail transport (1) the final-to-useful efficiency has increased by 30-fold... (More)
The history of rail transport can offer valuable insights for future energy transitions due to its importance in promoting clean mobility. There is a complex interplay between the evolution of the railway network, fuel consumption, efficiency, energy service, and CO2 emissions that requires further exploration. We developed a dataset that covers energy use in all stages of rail transportation, as well as the length of track, energy service, and CO2 emissions at the world scale. To deal with missing data we utilized machine learning techniques for the first time in a historical energy reconstruction study. Our analysis reveals that for world rail transport (1) the final-to-useful efficiency has increased by 30-fold from 1840 to 2020, mainly due to the replacement of steam trains with diesel and electric ones, (2) the peak in final energy use occurred in the 1940s, while useful energy use and transport service continue to grow, (3) there was a reduction in the energy (carbon) intensity from approximately 20 to 0.2 MJ/tkm (2 to 0.02 kg CO2/tkm) between 1840 and 2010, due not only to the increase in final-to-useful efficiency but also to rising occupancy, better operating conditions, and reduced losses by the passive system.
(Less)
- author
- Tostes, Bernardo ; Henriques, Sofia T. LU ; Brockway, Paul E. ; Heun, Matthew Kuperus ; Domingos, Tiago and Sousa, Tânia
- organization
- publishing date
- 2024
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Carbon emissions, Energy efficiency, Energy history, Energy service, Machine learning, Railway
- in
- Applied Energy
- volume
- 367
- article number
- 123344
- publisher
- Elsevier
- external identifiers
-
- scopus:85192882774
- ISSN
- 0306-2619
- DOI
- 10.1016/j.apenergy.2024.123344
- language
- English
- LU publication?
- yes
- id
- caa1f68f-da0b-4951-a13a-5ab62205ec68
- date added to LUP
- 2024-05-27 08:37:53
- date last changed
- 2024-05-27 08:38:35
@article{caa1f68f-da0b-4951-a13a-5ab62205ec68,
abstract = {{<p>The history of rail transport can offer valuable insights for future energy transitions due to its importance in promoting clean mobility. There is a complex interplay between the evolution of the railway network, fuel consumption, efficiency, energy service, and CO<sub>2</sub> emissions that requires further exploration. We developed a dataset that covers energy use in all stages of rail transportation, as well as the length of track, energy service, and CO<sub>2</sub> emissions at the world scale. To deal with missing data we utilized machine learning techniques for the first time in a historical energy reconstruction study. Our analysis reveals that for world rail transport (1) the final-to-useful efficiency has increased by 30-fold from 1840 to 2020, mainly due to the replacement of steam trains with diesel and electric ones, (2) the peak in final energy use occurred in the 1940s, while useful energy use and transport service continue to grow, (3) there was a reduction in the energy (carbon) intensity from approximately 20 to 0.2 MJ/tkm (2 to 0.02 kg CO<sub>2</sub>/tkm) between 1840 and 2010, due not only to the increase in final-to-useful efficiency but also to rising occupancy, better operating conditions, and reduced losses by the passive system.</p>}},
author = {{Tostes, Bernardo and Henriques, Sofia T. and Brockway, Paul E. and Heun, Matthew Kuperus and Domingos, Tiago and Sousa, Tânia}},
issn = {{0306-2619}},
keywords = {{Carbon emissions; Energy efficiency; Energy history; Energy service; Machine learning; Railway}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Applied Energy}},
title = {{On the right track? Energy use, carbon emissions, and intensities of world rail transportation, 1840–2020}},
url = {{http://dx.doi.org/10.1016/j.apenergy.2024.123344}},
doi = {{10.1016/j.apenergy.2024.123344}},
volume = {{367}},
year = {{2024}},
}