Greener reactants, renewable energies and environmental impact mitigation strategies in pyrometallurgical processes: A review
Bibliographic record
Abstract
Abstract Metals and alloys are among the most technologically important materials for our industrialized societies. They are the most common structural materials used in cars, airplanes and buildings, and constitute the technological core of most electronic devices. They allow the transportation of energy over great distances and are exploited in critical parts of renewable energy technologies. Even though primary metal production industries are mature and operate optimized pyrometallurgical processes, they extensively rely on cheap and abundant carbonaceous reactants (fossil fuels, coke), require high power heating units (which are also typically powered by fossil fuels) to calcine, roast, smelt and refine, and they generate many output streams with high residual energy content. Many unit operations also generate hazardous gaseous species on top of large CO 2 emissions which require gas-scrubbing and capture strategies for the future. Therefore, there are still many opportunities to lower the environmental footprint of key pyrometallurgical operations. This paper explores the possibility to use greener reactants such as bio-fuels, bio-char, hydrogen and ammonia in different pyrometallurgical units. It also identifies all recycled streams that are available (such as steel and aluminum scraps, electronic waste and Li-ion batteries) as well as the technological challenges associated with their integration in primary metal processes. A complete discussion about the alternatives to carbon-based reduction is constructed around the use of hydrogen, metallo-reduction as well as inert anode electrometallurgy. The review work is completed with an overview of the different approaches to use renewable energies and valorize residual heat in pyrometallurgical units. Finally, strategies to mitigate environmental impacts of pyrometallurgical operations such as CO 2 capture utilization and storage as well as gas scrubbing technologies are detailed. This original review paper brings together for the first time all potential strategies and efforts that could be deployed in the future to decrease the environmental footprint of the pyrometallurgical industry. It is primarily intended to favour collaborative work and establish synergies between academia, the pyrometallurgical industry, decision-makers and equipment providers. Graphical abstract Highlights A more sustainable production of metals using greener reactants, green electricity or carbon capture is possible and sometimes already underway. More investments and pressure are required to hasten change. Discussion Is there enough pressure on the aluminum and steel industries to meet the set climate targets? The greenhouse gas emissions of existing facilities can often be partly mitigated by retrofitting them with green technologies, should we close plants prematurely to build new plants using greener technologies? Since green or renewable resources presently have limited availability, in which sector should we use them to maximize their benefits?
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".