Evidence map›Paper›PMID 38267587›Full record

ArticleScientific reports2024

Decarbonising road freight transport: The role of zero-emission trucks and intangible costs.

Vahid Aryanpur, Fionn Rogan

Open access · goldAbstract 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. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
12.3field-weighted citation impact, top 1% of its field
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

5 citing papers in PubMed, 59 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Vahid AryanpurSFI MaREI Centre for Energy, Climate and Marine, Environmental Research Institute, University College Cork, Cork, Ireland. vahid.aryanpur@ucc.ie.ORCID http://orcid.org/0000-0001-7390-704X
Fionn RoganSFI MaREI Centre for Energy, Climate and Marine, Environmental Research Institute, University College Cork, Cork, Ireland.
University College Cork · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The road freight sector faces significant challenges in decarbonisation, driven by high energy demand and limited availability of low-emission fuels and commercialised zero-emission vehicles. This study investigates intangible costs associated with advanced electric and hydrogen-powered trucks, including recharging/refuelling time, cargo capacity limitations, and buyer reluctance towards emerging technologies. Utilising a comprehensive whole-systems modelling approach considering low- and zero-emission fuels, inter-sectoral dynamics, and the carbon budget, we explore cost-optimal decarbonisation pathways for heavy, medium, and light trucks. Scenario and sensitivity analyses reveal the following insights: (1) Electric trucks dominate the market under mitigation pathways across all weight categories. However, the inclusion of intangible costs triggers a shift, leading to the emergence of hydrogen fuel cell vehicles for heavy trucks, while battery electric vehicles are preferred for medium and small trucks. (2) Prioritising heavy truck decarbonisation and taking early action are crucial to avoid carbon lock-in effects. (3) Considering limited decarbonisation options, where electric and hydrogen-fuelled trucks are pivotal, this research highlights the significance of policy instruments targeting operational expenditures over conventional purchase price incentives. Such policies offer dual benefits by supporting truck owners and directing incentives more precisely towards achieving measurable emission reductions.

Identifiers

PMID38267587
PMCPMC10810084
OpenAlexW4391160375

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.