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Record W3203925073 · doi:10.11575/prism/39274

Investigating Cost Effective Pathways for Blue Hydrogen Production in Alberta

2021· dissertation· en· W3203925073 on OpenAlexaboutno aff
Abdalla Elnigoumi

Bibliographic record

VenueOpen MIND · 2021
Typedissertation
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsnot available
Fundersnot available
KeywordsProduction (economics)Hydrogen productionEnvironmental scienceChemistryHydrogenEconomicsMicroeconomics

Abstract

fetched live from OpenAlex

Large amounts of hydrogen are used in many industries in Alberta, the most significant of which is upgrading of bitumen into synthetic crude oil. Hydrogen also plays a large role in the recent Natural Gas Strategy, which aims to support diversification of the Alberta economy by growing the low carbon intensity energy sector. Because current hydrogen (H2) production is responsible for a substantial share of the greenhouse emissions from oil sands operations in Alberta, applying carbon capture and storage (CCS) to H2 production to make what is becoming known as “blue H2” would both significantly reduce the province’s emissions and unlock new opportunities for the current industry. In this thesis, I evaluate the trade-offs between location and scale of blue H2 production to decarbonize Oil Sands mining operations under different future emissions prices. I develop new cost models for steam-methane reforming (SMR) and autothermal reforming (ATR) units incorporating CCS that allow estimation of production cost and life-cycle emissions for facilities in Alberta. I also expand an existing CO2 pipeline model to be usable for H2 pipelines, and use this to estimate the cost and environmental trade-offs between moving CO2 and H2. I apply these models to compare the cost of production of blue H2 near Edmonton (with transport of H2 north and local CO2 storage) to production in Fort MacMurray (and transport of CO2 south for storage) for two different demand scenarios. Results from these models show that SMR and ATR plants capturing upwards of 90% of total direct emissions have a comparable production cost of $1.6/kgH2 (USD) at a scale of 350 tH2/day. This represents a 60% increase in cost compared to an SMR without capture. However, considering the full life cycle, the estimated cost of CO2 avoided for the SMR plant ($80/tCO2eq) are lower than for the ATR (90 $/tCO2eq) due to the Alberta electricity grid. The unit cost of moving H2 is several times that of CO2, owing to the lower (gaseous) density of H2. However, normalized to production of one kilogram of hydrogen, the costs of transport are comparable for an optimized system. The scenario analysis suggests constructing SMR with post-combustion capture in Fort MacMurray is the lowest cost option when a 170 $/tCO2 (CAD) carbon tax is applied to the full chain life cycle emissions.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.229
Threshold uncertainty score0.461

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.029
GPT teacher head0.287
Teacher spread0.258 · 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 designSimulation or modeling
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

Citations3
Published2021
Admission routes1
Has abstractyes

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