Large-scale long-distance land-based hydrogen transportation systems: A comparative techno-economic and greenhouse gas emission assessment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Interest in hydrogen as an energy carrier is growing as countries look to reduce greenhouse gas (GHG) emissions in hard-to-abate sectors. Previous works have focused on hydrogen production, well-to-wheel analysis of fuel cell vehicles, and vehicle refuelling costs and emissions. These studies use high-level estimates for the hydrogen transportation systems that lack sufficient granularity for techno-economic and GHG emissions analysis. In this work, we assess and compare the unit costs and emission footprints (direct and indirect) of 32 systems for hydrogen transportation. Process-based models were used to examine the transportation of pure hydrogen (hydrogen pipeline and truck transport of gaseous and liquified hydrogen), hydrogen-natural gas blends (pipeline), ammonia (pipeline), and liquid organic hydrogen carriers (pipeline and rail). We used sensitivity and uncertainty analyses to determine the parameters impacting the cost and emission estimates. At 1000 km, the pure hydrogen pipelines have a levelized cost of $0.66/kg H2 and a GHG footprint of 595 gCO2eq/kg H2. At 1000 km, ammonia, liquid organic hydrogen carrier, and truck transport scenarios are more than twice as expensive as pure hydrogen pipeline and hythane, and more than 1.5 times as expensive at 3000 km. The GHG emission footprints of pure hydrogen pipeline transport and ammonia transport are comparable, whereas all other transport systems are more than twice as high. These results may be informative for government agencies developing policies around clean hydrogen internationally.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it