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Fueling tomorrow's commute: Current status and prospects of public bus transit fleets powered by sustainable hydrogen

2024· article· en· W4394741720 on OpenAlexafffund
Sachindra Chamode Wijayasekera, Kasun Hewage, Faran Razi, Rehan Sadiq

Bibliographic record

VenueInternational Journal of Hydrogen Energy · 2024
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersMitacs
KeywordsSustainabilitySoftware deploymentStatus quoPublic transportEnvironmental economicsFossil fuelSustainable transportTransit (satellite)BusinessEnvironmental scienceHydrogen fuelHydrogen vehicleTransport engineeringAlternative fuelsNatural resource economicsComputer scienceEngineeringWaste managementFuel cellsEconomics

Abstract

fetched live from OpenAlex

Transportation is an economic sector that contributes significantly to global warming due to its high consumption of fossil fuels, and sustainably produced hydrogen is a major contender for an alternative clean energy source. Public transit is vital for environmental sustainability via reducing individual vehicle usage and traffic congestion, and the prospect of powering buses using hydrogen fuel has been extensively studied lately. This paper seeks to comprehensively review the current status of research on hydrogen-powered buses considering triple bottom line sustainability perspectives. A brief technical overview of prospective environmentally benign hydrogen production processes has been presented. Technological, economic, and environmental findings and research trends seen in recent analyses on hydrogen-powered buses have been summarized, along with the status quo of global hydrogen refuelling stations. Identified focal points for future studies include performance enhancements, refuelling infrastructure propagation, and policy formulation. The conclusions derived from this review will benefit the accelerated deployment of hydrogen-fuelled public transit fleets.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.253
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations30
Published2024
Admission routes2
Has abstractyes

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