Evaluating the Performance of a Solar Distillation Technology in the Desalination of Brackish Waters
Bibliographic record
Abstract
Desalination is set to become a major source of drinking water in several Middle Eastern countries over the coming decades. Solar distillation is a simple power-independent method of water desalination, which can be carried out in active or passive modes. This study is among the first attempts to investigate the possibility of desalinating brackish groundwater resources under the threat of saltwater intrusion in the southern areas of Razavi Khorasan province in Iran. For this purpose, a pilot solar distillation unit was constructed to analyze the effects of the unit orientation, depth of the water pool, atmospheric conditions, input salinity, and flow continuity on the solar distillation performance. The results showed that the unit exhibited the highest efficiency when it had a 3 cm deep water pool. It was oriented facing southward while operating a continuous flow for at least 3 days under sunny weather conditions. It was found that among the studied parameters, the unit orientation and pool depth had the greatest impact on the water production performance for this type of water desalination system. Conversely, the water production efficiency was not very sensitive to the input salinity level. Overall, the solar distillation technology was able to reduce the salinity by 99.7% and the hardness by 94.7%.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".