Evidence map›Paper›PMID 41193700›Full record

ArticleScientific reports2025

Quantifying carbon reductions from mode substitution through shared electric mobility hubs in Greater Manchester.

Haoyu Wang, Margaret C Bell, Jingxin Dong, Matthew Burke, Huseyin Ayan, Dilum Dissanayake

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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.

Haoyu WangNewcastle Business School, Northumbria University, Newcastle upon Tyne, NE1 8ST, UK.
Margaret C BellSchool of Engineering, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK.
Jingxin DongBusiness School, Newcastle University, Newcastle upon Tyne, NE1 4SE, UK.
Matthew BurkeSchool of Engineering, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK.
Huseyin AyanSchool of Engineering, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK.
Dilum DissanayakeSchool of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK. d.dissanayake@bham.ac.uk.

Funding

Interreg North-West Europe 826
6 · The paper itself

Abstract

This study investigates the attitudes of 1139 participants towards eHUBS usage and daily travel patterns to assess the effectiveness of shared electric mobility hubs (eHUBS) in Greater Manchester. It explores the potential of eHUBS to replace conventional travel modes, including motor vehicles, public transport, and zero-carbon alternatives such as walking and cycling, while examining their integration with public transport and the associated carbon reduction benefits. Analysis indicates a consistent substitution rate of 30% to 35%, suggesting that eHUBS could increase public transport usage by 8% to 13% and reduce overall carbon emissions by 15% to 18% for journeys exceeding 5 km. The findings reveal that eHUBS, particularly e-bikes and e-cargo bikes, can enhance public transport utilisation for short-distance trips, while electric cars reduce reliance on motor vehicles for longer journeys. Although substituting walking and cycling with eHUBS marginally raises emissions for shorter trips, this impact is minimal compared to the overall reduction achieved. This study underscores the significant role of eHUBS in supporting modal shifts and emissions reduction, contributing to more sustainable urban mobility.

Indexed as

Carbon emissionseHUBSMode substitutionNet-zero emissionsShared electric mobility

Identifiers

PMID41193700
PMCPMC12589470

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.