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Record W3131629941 · doi:10.2166/wst.2021.073

Physicochemical assessment of urban wastewater of Cotonou (Benin)

2021· article· en· W3131629941 on OpenAlexaff
Mohamed Moukorab Arêmou Daouda, Sena Peace Hounkpè, Metogbe Belfrid Djihouessi, Akuemaho Virgile Onésime Akowanou, Martin Pépin Aïna, Patrick Drogui

Bibliographic record

VenueWater Science & Technology · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Reuse
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsKjeldahl methodBlackwaterWastewaterBiochemical oxygen demandEffluentGreywaterChemical oxygen demandEnvironmental scienceWastewater quality indicatorsLaundrySewage treatmentEnvironmental engineeringTotal suspended solidsPulp and paper industryChemistryEnvironmental chemistryWaste managementNitrogenEngineering

Abstract

fetched live from OpenAlex

Abstract The present study aims to fill the data gap analysis in urban wastewaters characteristics in Benin and its statistical analysis. Physicochemical parameters such as pH, electrical conductivity (EC), Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD5), Total Kjeldahl Nitrogen (TKN), Total Phosphorus (TP) and UV Absorbance at 254 nm, were determined on domestic (greywater and blackwater) and industrial (hospital, pharmaceutical and commercial laundry) wastewater in Cotonou city. Analysis of variance showed a strong significant difference in the physico-chemistry of the various effluents. The pharmaceutical wastewater has the highest concentration of organic pollution (COD = 5,912 ± 1,026 mg/L, Abs.UV254 = 2.667 ± 0.327 cm−1). The organic load of blackwater is mainly in particulate and biodegradable form. Besides, the correlation study showed the limits of pH and EC as an indicator of organic load. Furthermore, the choice of COD or BOD5 as the main design parameter would be limited to blackwater treatment. Abs.UV254 was found to be the parameter having a strong relationship with other parameters of all effluents except blackwater. It then takes priority over COD for the treatment of greywater and industrial wastewater. For future wastewater treatment plant design, we recommend to consider Abs.UV254 as an important parameter.

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)0.000
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 score0.066
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.234
Teacher spread0.227 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

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