Renewable Powered Desalination in the Coastal Mekong Delta
Bibliographic record
Abstract
Global climate destabilization is exacerbating water problems in Vietnam, most acutely in the South and Central regions where most of the inhabited area lies in the low elevation coastal zone. Using a geographical information system (GIS) platform, a wind resources atlas developed by the Asia Sustainable and Alternative Energy Program and the projected rural population available from Columbia University’s Center for International Earth Science Information Network, this paper explores the potential for off-grid medium to small-scale reverse osmosis desalination powered by small wind turbines for the coastal fringe of Vietnam’s Mekong Delta. The analysis estimated that in the absence of all other water supply facilities, off-grid wind desalination could provide clean water to 5.4 million rural residents living in 18.9 thousand km2 of the Mekong Delta coastal provinces at the rate of 60 liters per capita per day. In addition to providing clean water, the use of wind powered desalination in the region would have educational benefits, combat poverty and unemployment, ease water-related conflicts, and has been shown to be improve environmental and agricultural sustainability. Thus this technology was found to represent a decentralized and community-based method to adapt to and mitigate climate change in the coastal fringe of the Mekong Delta.
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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) | 0.001 | 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".