Economics of Sea Water Desalination with Innovative Nuclear Reactors and Other Energy Sources: The EURODESAL Project
Bibliographic record
Abstract
This paper summarises our recent investigations undertaken as part of the EURODESAL project on nuclear desalination, currently being carried out by a consortium of 4 EU, and one Canadian, Industrials and two leading EU R&D organisations.\nResults obtained so far seem to be quite encouraging as regards the economical viability of nuclear desalination options.\nThus, for example, specific desalination costs ($/m3 of desalted water) for nuclear systems such as the AP600 and the French PWR900 (reference base case), coupled to MED (Multiple Effect Distillation) or the RO (Reverse Osmosis) processes, are 30 to 60% lower than fossil energy based systems using pulverised coal and natural gas with combined cycle, at low discount rates and recommended fuel prices. Even in the most unfavourable scenarios for nuclear energy (discount rates = 10%, low fossil fuel prices) desalination costs with the nuclear options with innovative reactors are 7 to 15% lower, depending upon the desalination capacities. Furthermore, with the high performance coupling schemes developed by EURODESAL partners, specific desalination costs of nuclear systems are reduced by another 2 to 14%, even without system and design optimisation.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".