Life cycle assessment of turning hydrogen sulfide recovered from sea waters into clean hydrogen
Bibliographic record
Abstract
The present work aims to conduct a comprehensive life cycle assessment (LCA) of the hydrogen production system utilizing hydrogen sulfide (H 2 S) obtained from the sources available in the sea waters, such as the Black Sea. A robust LCA methodology is developed by coupling the process simulation results from the Aspen Plus with the LCA capabilities of the openLCA. The H 2 S is extracted from the bottom of the Black Sea and employed as a feedstock for a thermochemical cycle to produce hydrogen. The environmental performance is characterized by six harmonized indicators: global warming potential (GWP), acidification potential (AP), particulate matter (PM), eutrophication freshwater potential (EP), ozone layer depletion (ODP), and resource use, minerals, and metals (ADP). The analysis of alternate oxygen carriers within the LCA framework demonstrates that the Fe 2 O 3 /FeS redox pair results in 66.28 % less global warming potential than the baseline ZnO/ZnS redox pair, highlighting the significance of material selection in optimizing environmental performance. The life cycle quality index and life cycle irreversibility index are considered 28.92 % and 71.09 % respectively.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".