Global assessment of biomass suitability for ironmaking – Opportunities for co-location of sustainable biomass, iron and steel production and supportive policies
Bibliographic record
Abstract
Iron and steel production processes are amongst the biggest industrial contributors to the global carbon emissions, and national as well as international obligations are set to drive their significant emission reductions. One of the possible strategies is to partially substitute fossil fuels used during the iron ore reduction process by sustainably-sourced biomass. The extent of the opportunities for such fuel switching, however, varies for each country. Theoretically, biomass into ironmaking should be only supported for countries which present co-location of sustainably domestically sourced biomass in sufficient quantity, a substantial iron and steel industry and supportive national policies. Using a multi-criteria global suitability assessment approach developed in this research, the status of countries’ steel industry, sustainable biomass resources and supportive policies were examined for top 40 steel production countries via the blast furnace ironmaking route. The results highlight those countries with significant potential to use domestically sourced biomass for such application and advance the efficient use of the limited biomass resources from the global perspective. Specifically countries such as Canada, Sweden, China, USA and France were identified as the most suitable, but other countries present opportunities that could be overcome if the corresponding barriers are identified.
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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 | 0.001 |
| 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".