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Costs of Hydrogen Production with Net-zero Emissions: A Case Study in Kitchener

2025· article· W4415366790 on OpenAlexafffund
Laetitia Uwineza, Xiao Yu Wu

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsUniversity of Waterloo
FundersGovernment of Canada
KeywordsGreenhouse gasHydrogen productionHydrogenCarbon fibersProduction (economics)Life-cycle assessmentHydrogen technologies

Abstract

fetched live from OpenAlex

This study evaluates the cost of net-zero hydrogen production, with a focus on life cycle greenhouse gas emissions (LCA) and the inclusion of CO2removal costs. We design a PV-grid system for hydrogen production using HOMER’s energy modelling software with simulations based on data from a site in the city of Kitchener. Additionally, we examine the relationship between the hydrogen production and its carbon intensity. The findings illustrate that the levelized cost of hydrogen (LCOH), when including CO2removal costs, is $\mathbf{9. 2 2 \%}$ to $\mathbf{1 1. 3 9 \%}$ higher compared to the LCOH without carbon removal costs. These preliminary findings can serve as potential indicators for hydrogen pricing.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.927
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.008
GPT teacher head0.235
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2025
Admission routes2
Has abstractyes

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