The Impacts of Hospital Effluent Discharges on the Physico-chemical Water Quality of a Receiving Stream at Ile-Ife, Southwestern Nigeria
Bibliographic record
Abstract
In order to contribute to the understanding of the impact of wastewater discharges from a Hospital in south-western Nigeria on the receiving water bodies, the physico-chemical qualities of the two wastewater point sources from the Obafemi Awolowo University Teaching Hospitals Complex (OAUTHC) Ile–Ife were characterized, and their impacts on the water quality of the receiving Elekete stream were assessed. Eight sampling stations were selected for the study: three, were located each on the unimpacted and impacted sections of the receiving Elekete stream while one each was located on the two wastewater point sources from OAUTHC. The physico-chemical parameters investigated include: oxygen parameters, major cations, major anions, nutrient compounds, physical parameters (temperature, turbidity, solids) as well as pH and conductivity. Samples were collected from each sampling station fortnightly for nine months and analysed using standardised laboratory methods. The results were analysed using relevant statistical methods. The result showed significant difference (P < 0.05) for all parameters between the impacted and unimpacted sections of effluent receiving stream. SO42-, Total Organic Carbon, NH4+, PO43-, and BOD5 were more than three times higher in the impacted section than in the unimpacted section while sample colour, turbidity, total suspended solids, total dissolved solids, total solids, conductivity, alkalinity, acidity, Ca2+, Mg2+, Na+, K+, Cl-, HCO3-, NO3-, and NO2- were about two times higher in the impacted section of the receiving stream than in the unimpacted section. The overall mean concentrations of 293 mg l-1 and 270 mg l-1 BOD5 in the two effluent streams indicate the medium/ strong strength of the wastewater discharges from OAUTHC. This study showed that the wastewater discharge from the (OAUTHC) Ile-Ife has significant impact on the water quality of the receiving streams. The implications are discussed.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".