Life cycle analysis of the simultaneous production of lithium hydroxide monohydrate and lithium carbonate from spodumene ore using electrodialysis
Bibliographic record
Abstract
The need to combat climate change and to achieve carbon neutrality is driving demand for clean energy technologies, highlighting the importance of sustainable production pathways for lithium-ion battery precursors. Although prior research has assessed greenhouse gas (GHG) emissions from lithium hydroxide monohydrate (LHM) production in specific regions, a significant gap remains in the comprehensive life cycle analyses of electrodialysis-based systems co-producing LHM and lithium carbonate across different geographical locations and operational conditions. This study conducts a cradle-to-gate, Canada-specific baseline life cycle assessment (LCA) of flexible LHM and lithium carbonate co-production. It uses an electrodialysis-based electrochemical process, accompanied by detailed modeling of sub-processes to enhance GHG emission reduction by reducing energy consumption. The study also assesses the adaptability and feasibility of the facility under varying geographical and operational conditions. The results indicate that 175.6 Megawatts (MW) of energy is required for a spodumene input capacity of 250 tph. The primary energy consumers are the electrochemical process and mining, at 97.2 MW and 49.6 MW, respectively. Within the electrochemical process, electrolysis consumes 65.7 % of the total energy, representing approximately 36 % of the total energy used in the LHM production process. The study also found that the total life cycle GHG emission is 9.15 t CO 2 e/t LHM. The main contributors to GHG emissions in LHM production are the electrochemical process and mining, contributing 5.48 t CO 2 e/t LHM and 1.85 t CO 2 e/t LHM, respectively. These emissions can be reduced by using the hydrogen by-product from the electrodialysis process and integrating renewable energy into mining, milling, and electrochemical operations. Additionally, small modular nuclear reactors (SMNRs) present a promising low-carbon alternative for powering these stages. The model shows life cycle GHG emissions from 3.91 to 10.97 t CO 2 e/t LHM, mainly influenced by electricity emissions and scalability. Sensitivity analyses confirm its adaptability in different regions and operating conditions. The 0.06 t CO₂e/t LHM GHG emission difference between production ratios of 100 % LHM and 50 % LHM results in 4092 t annually, mainly due to CO₂ injection during carbonation and drying energy use. Overall, increased energy demand is largely offset by CO₂ injection, minimizing net emissions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".