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Record W6929221998 · doi:10.4224/40002781

Life cycle assessment of hydrogen production pathways in Canada

2022· report· en· W6929221998 on OpenAlexaffvenueabout

Bibliographic record

VenueNPARC · 2022
Typereport
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicATP Synthase and ATPases Research
Canadian institutionsNational Research Council CanadaGDG Environnement
Fundersnot available
KeywordsLife-cycle assessmentHydrogen productionGreenhouse gasContext (archaeology)Fossil fuelProduction (economics)ElectricityRenewable energyHydrogen economyHydrogen technologies

Abstract

fetched live from OpenAlex

Canada has the potential to produce hydrogen as part of the clean fuel transition of its existing energy sector to a low-carbon economy, commitment that will support reaching net-zero emissions goal by 2050. Domestic hydrogen production is leveraged by the availability of diverse energy sources from fossil fuels to renewable electricity. Canada has the one of the cleanest electricity systems in the world with over 83% of electricity from non-emitting sources. Additionally, production of low-carbon hydrogen has the potential to be internationally traded. However, it is necessary to define and measure the carbon intensities of potential hydrogen production pathways in Canada in order to define low-carbon hydrogen in future standards. It is within this context that the National Research Council Canada (NRC), through its Advanced Clean Energy Program, has undertaken the development of a Life Cycle Assessment of Hydrogen Production Pathways in Canada Study, with support of the Natural Resources Canada (NRCan)’s Office of Energy Research and Development (OERD) and collaborators CanmetENERGY in Devon (CE-D), and CanmetENERGY in Varennes (CE-V) of NRCan, which have joined their efforts and expertise to provide hydrogen production process simulation results to complete the current study. The purpose of this study is to develop a detailed and complete methodology based on a life cycle assessment (LCA) approach to assess different carbon intensities of hydrogen production in order to provide a consistent and verifiable greenhouse gases (GHG) estimation, including definition of system boundaries and building life cycle inventories for a Canadian context. Additionally, this report provides results of performing the proposed LCA-based methodological framework for two hydrogen production pathways in a Canadian context using steam methane reforming with natural gas and without carbon capture and alkaline electrolysis using grid electricity. After performing a scoping review of relevant hydrogen LCA peer-reviewed studies, critical life cycle assessment methodological options were identified for harmonizing LCA of hydrogen production frameworks. Based on current life cycle assessment normative, a methodological framework is developed to quantify carbon intensities of hydrogen production. LCA methodological choices such as definition of functional unit, system boundaries, and life cycle inventory criteria are aligned to relevant and current low-carbon intensity hydrogen standards. The LCA-based methodology is an attributional LCA, with the system boundaries being to the point of hydrogen production (‘well-to-gate’ approach). The life cycle inventory data for the foreground system comes from modelling and simulation results of the processes selected in this study. A life cycle assessment was conducted to the steam methane reforming as baseline pathway and the alkaline electrolysis pathway. Life cycle GHG emissions results show that the baseline hydrogen pathway presents a wide range of improvement in comparison to an estimated low-carbon hydrogen threshold. Electrolysis pathway shows its carbon intensities depend on the share of renewable energy sources used to generate electricity as feedstock in the electrolysis process. Further LCAs for the remaining hydrogen pathways in a Canadian context will be performed and results will be published in a new report. It is important to note that the accuracy and completeness of the life cycle inventory data could be improved with primary data from current industry, hence it is recommended that the LCA results in the present report may be revised with use cases from current hydrogen projects developed in a Canadian context. Additional recommended steps, include start a wide consultation process with stakeholders to revise life cycle GHG emissions estimates and to set the final carbon intensities threshold(s).

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.537
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

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

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 head0.029
GPT teacher head0.309
Teacher spread0.280 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations4
Published2022
Admission routes3
Has abstractyes

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