Evidence map›Paper›PMID 41266561›Full record

ArticleScientific reports2025

Simulation models for sustainable, resilient, and optimized global electric vehicles supply chain.

Tareq Alsaleh, Bilal Farooq

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

2 authors.

Tareq AlsalehLaboratory of Innovation in Transportation (LiTrans), Toronto Metropolitan University, Toronto, M5B 2K3, Canada.
Bilal FarooqLaboratory of Innovation in Transportation (LiTrans), Toronto Metropolitan University, Toronto, M5B 2K3, Canada. Bilal.Farooq@torontomu.ca.

Funding

Canada Research Chair program in Disruptive Transportation Technologies and Services CRC-2021-00480NSERC Discovery RGPIN-2020-04492
6 · The paper itself

Abstract

While the transition to electric vehicles (EVs) is essential for decarbonising the transportation system, the production and distribution of EVs entail substantial carbon costs. To ensure these emissions are accurately accounted for and effectively mitigated, this research introduces a probabilistic simulation model of the EV’s supply chain, addressing a critical gap in current EV life cycle analyses and providing the first comprehensive quantification of its environmental sustainability and resilience. This simulation model replicates global market dynamics and captures the complexity and uncertainty of the EV supply chain, enabling a thorough evaluation of its carbon footprint, sustainability, resilience, and what-if counterfactual scenarios for alternative market structures. The results reveal that average supply chain emissions range from 6.43 to 6.95 kg e-CO[Formula: see text] KWh[Formula: see text] across different battery technologies. Additionally, the mass flow analysis shows unbalanced dependencies at all supply phases, with one geographical region significantly dominating the supply chain structure, highlighting the current supply chain architecture’s low resilience and high vulnerability. In light of these findings, the study introduces an optimisation model for hub and resource allocation configuration, effectively reducing vulnerability levels and supply chain emissions by up to 80%.

Indexed as

Electric vehiclesEmissionsSimulation modelsSupply chain simulationSustainability resilienceTransportation electrification

Identifiers

PMID41266561
PMCPMC12764519

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.