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Record W1986280557 · doi:10.2166/wst.2013.011

Wastewater reclamation using discarded reverse osmosis membranes for reuse in irrigation in Djibouti, an arid country

2013· article· en· W1986280557 on OpenAlexaff
M.O. Awaleh, Moussa Mahdi Ahmed, Youssouf Djibril Soubaneh, Farhan Bouraleh Hoch, Samatar Mohamed Bouh, E.S. Dirieh

Bibliographic record

VenueWater Science & Technology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Reuse
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsReverse osmosisDesalinationWastewaterLand reclamationEffluentReuseEnvironmental scienceEnvironmental engineeringTurbidityWaste managementIrrigationFecal coliformOsmosisAridPulp and paper industryMembraneEngineeringChemistryWater qualityGeographyEcology

Abstract

fetched live from OpenAlex

The purpose of this paper is to establish the feasibility of recovering discarded reverse osmosis (RO) membranes in order to reduce the salinity of domestic treated wastewater. This study shows that the reuse of RO membranes is of particular interest for arid countries having naturally high mineralized water such as Djibouti. The pilot desalination unit reduces the electrical conductivity, the turbidity and the total dissolved salt respectively at 75-85, 96.7 and 95.4%. The water produced with this desalination unit contains an average of 254 cfu/100 mL total coliforms and 87 cfu/100 mL fecal coliforms. This effluent meets the World Health Organization standards for treated wastewater reuse for agricultural purposes. The annual cost of the desalination unit was evaluated as US $/m(3) 0.82, indicating the relatively high cost of this process. Nevertheless, such processes are required to produce an effluent, with a high reuse potential.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.237
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2013
Admission routes1
Has abstractyes

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