Life cycle assessment of the power-to-gas process in the context of Quebec
Bibliographic record
Abstract
Storing electricity from renewable energy sources for long term is a power-to-gas (PtG) concept. This electricity then produces fuels for industry, transportation, and household. However, this technology has different system variations with various environmental performances that should be investigated and compared to the conventional technologies before industrialization. Hydropower, as a low-carbon electricity source, is the highest contributor to Quebec electricity (about 94%), making the life cycle assessment of power to gas valuable to be investigated. In this study, life cycle assessment of PtG in Quebec was conducted as a baseline scenario and compared with the natural gas. Then, the sensitivity analyses were carried based on different electricity sources from different provinces in Canada (Alberta and Quebec). For the baseline scenario, CO2 was assumed to captured from the cement plant gas emission. Human health and ecosystem quality for the baseline scenario were acquired to be 4.89E-06 (DALY) and 0.77 (PDF.m2.yr), respectively. Also, greenhouse gas emission for the baseline scenario was equal to 0.04 (kg CO2 eq). Impact categories in all damage levels were significantly higher for natural gas compared to producing methane from PtG (synthetic natural gas-SNG). 5.13 (kg CO2 eq) was obtained for the climate change impact for natural gas. The fossil fuel base of Alberta’s electricity is responsible for the %60 of impacts on the climate change in natural gas. Sensitivity analysis were implemented based on different sources of electricity for producing SNG. It was concluded that if Alberta electricity is used in the system, more environmental impacts can be seen. The outcome of this study showed that the climate change impact for Alberta scenario is five times higher than the climate change for the Quebec scenario. CO2 unit was calculated to demonstrate higher contributions to the impacts on the environment, whereas these impacts can be mitigated by employing more clean electricity in this unit process. Outcomes showed that methanation with Quebec electricity source leads to larger environmental benefits compared to the conventional natural gas and other sources of electricity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".