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Record W7044151193

Vihreän vedyn kasvihuonekaasupäästöjen arviointi Saksan markkinalle : kansainvälisten tuotantoreittien vertaileva tarkastelu RED III- ja ISO 19870 -standardeja käyttäen

2025· other· en· W7044151193 on OpenAlexaboutno aff

Bibliographic record

VenueLUTPub (LUT University) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsRenewable energyElectricityGreenhouse gasSustainabilityFossil fuelPower to gasProduction (economics)Natural gas
DOInot available

Abstract

fetched live from OpenAlex

This master’s thesis evaluates the sustainability of different production chains of green hydrogen and its derivatives. A Microsoft Excel-based model was developed to compare green hydrogen, ammonia, methanol, and methane produced for German market. Calculations follow the Renewable Energy Directive III and ISO 19870, which are compared with each other and to a broader scope of ISO 14067 guidelines. Commissioned by Wärtsilä, the aim is to identify international production pathways for producing hydrogen and its derivatives that meet the EU Taxonomy's green financing threshold of 100 gCO₂e/kWh and 70% GHG savings relative to fossil fuels. The production scenarios include Canadian wind-powered ammonia, Middle Eastern solar powered hydrogen derivatives, and Finnish grid produced hydrogen transported to Germany. Key findings reveal the highest emissions arising from electricity source and the choice of transportation. All reviewed production chains utilizing renewable energy sources achieved at least the 70% GHG savings even under worst scenarios. These fuels can also be combusted in engines for electricity production with emissions below the EU Taxonomy threshold of 100 gCO₂e/kWh. However, hydrogen produced with current Finnish grid electricity does not meet the 70% GHG savings requirement in any scenario. Future decarbonization of the Finnish grid, reducing its emission intensity to 40 gCO2e/kWh, would allow compliance with the 70% GHG savings threshold under all scenarios, allowing for renewable hydrogen production using grid electricity.

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), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0080.006
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0040.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0190.004

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 head0.007
GPT teacher head0.193
Teacher spread0.186 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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 routes1
Has abstractyes

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