Harmonized life cycle sustainability assessment of advanced hydrogen production technologies for decarbonization
Bibliographic record
Abstract
Methodological inconsistencies affect the reliability and validity of the results when conducting comparative life cycle sustainability assessments across different hydrogen production systems. In this regard, the present work aims to use some harmonized life cycle indicators of hydrogen to determine the environmental impacts of renewable hydrogen production. For this purpose, five different configurations of the sulfur‑iodine (S-I) thermochemical cycle are considered for assessment. A consistent methodology is applied across all case studies to ensure robust comparisons and reliable results. The environmental profile of every H 2 production method is characterized by well-known harmonized indicators, namely: (1) carbon footprint, (2) acidification footprint, and (3) non-renewable energy footprint. When they are assessed from a cradle-to-grave perspective, the results show that the choice of oxygen carrier (OC) significantly affects the sustainability performance of hydrogen production systems. Sensitivity analysis results show that the base-case OC pair (ZnO/ZnS) exhibits superior environmental performance with the lowest carbon footprint, acidification footprint, and non-renewable energy demand share of 37.41 %, 6.68 %, and 35.78 %, respectively. However, the OCs pair SnO/SnS, CuO/CuS, and BaO/BaS exhibit poor environmental performance with a significant share in carbon, acidification, and non-renewable energy footprints.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".