Evidence map›Paper›PMID 38418451›Full record

ArticleScientific reports2024

A multi-scale lifecycle and technoeconomic framework for higher education fleet electrification.

Jason Juang, Wyatt Green Williams, Arjun T Ramshankar, John Schmidt, Kendrick Xuan, Joe F Bozeman

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jason JuangCollege of Business, Georgia Institute of Technology, Atlanta, GA, 30322, USA.
Wyatt Green WilliamsCollege of Business, Georgia Institute of Technology, Atlanta, GA, 30322, USA.
Arjun T RamshankarGeorgia Institute of Technology, Civil and Environmental Engineering, Atlanta, GA, 30322, USA.
John SchmidtComputer Science, Georgia Institute of Technology, Atlanta, GA, 30322, USA.
Kendrick XuanMechanical Engineering, Georgia Institute of Technology, Atlanta, GA, 30322, USA.
Joe F BozemanGeorgia Institute of Technology, Civil and Environmental Engineering, Atlanta, GA, 30322, USA. joe.bozeman@ce.gatech.edu.

Funding

Division of Chemical, Bioengineering, Environmental, and Transport Systems 2115453
6 · The paper itself

Abstract

Transportation accounts for one-quarter of all energy related greenhouse gas emissions. As it pertains to transport electrification, higher education institutions-such as universities-can model solutions that affect broader society. Despite this, higher education's role in fleet electrification adoption has been understudied. We, therefore, modeled an archetypical higher education institution to analyze the carbon and economic payback periods of three electrification scenarios (Business-as-Usual, Targeted Electrification, and Full Electrification) using a cradle-to-grave lifecycle and technoeconomic approach. Given the archetypical higher education institution fleet of 368 vehicles, results show an economic ratio plateau point of about 8 years at 20 fuel-based cars replaced by electric vehicles and a carbon payback period peak of roughly 10 months at 50 fuel-based cars replaced. We then performed a multi-scalar analysis by leveraging implementation theory. We find that higher education institutions that adhere to the tenets of implementation theory are poised to be pro-environmental change agents in many regions and countries. The methods and findings herein can be adapted to other institutions, regardless of fleet size, and can bolster relevant decision-making outcomes now.

Indexed as

Carbon paybackDrawdownElectric vehicleFleet electrificationHigher educationLife cycle assessmentSustainabilityTechno-economic analysis

Identifiers

PMID38418451
PMCPMC10901860

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.