Assessment of Domestic Wastewater Disposal in Some Selected Wards of Maiduguri Metropolis, Borno State, Nigeria
Bibliographic record
Abstract
This study evaluates domestic wastewater disposal in some selected wards of urban Maiduguri. The unprecedented population growth in Maiduguri generally is directly proportional to its demand for water supply for both domestic and industrial needs. Consequently the more water is consumed, the more its waste is generated. This in turn encourages its indiscriminate disposal particularly in an environment with poor drainage system such as most parts of Maiduguri urban area. It is against this background that the study examined how domestic wastewater is disposed in Maiduguri using the following objectives: to quantify the amount of domestic wastewater generated in the sampled areas, to study and describe the methods used in disposing wastewater, and to highlight the issues due to poor drainage in the town. The scope therefore, covers only domestic wastewater disposal in the selected wards with reference to individual household wastewater disposal system. This was based on planned and unplanned drainage system areas. New G R A and Bulumkutu were selected as the combination of the planned and unplanned areas, Hausari as unplanned and Gwange as planned areas respectively. Purposive, stratified and accidental sampling methods were employed at different stages in the sampling of the wards and the respondents. Three hundred and sixty copies of questionnaire designed to capture the objectives of the study were administered in the three selected wards (120 for each ward). The data obtained were analyzed using simple descriptive statistic and ANOVA. From the results obtained, the mean responses of the residents with regard to the wastewater generated from bathing, washing, food preparation and others, Maisandari has the highest values: 2.1583a, 1.3417a, 1.1250a and 1.1250a at 0.05 significant levels. This implies that most of the wastewater generated in the study area came from Maisandari ward. As a result of the serious environmental and health implication of this indiscriminate wastewater disposal in the study area, it is therefore recommended, that Borno State government should ensure effective/efficient maintenance of the existing waste disposal system and those areas without adequate drainage system should be provided by the government. The State government should provide drainages in the urban which are channelized in to central outlet system where it can be easily treated before final disposal for other uses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 teacher head, 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".