Evaluating Water Quality Indicators of Some Water Sources in the Bitumen-Rich Areas of Ondo State, Nigeria
Bibliographic record
Abstract
Contaminated water, sourced from wells and streams has for long remained the major available water for domestic, industrial and some others uses in the bitumen-rich areas of Ondo State, Nigeria. In this work, the effects of bitumen contamination on some of the quality of water from the wells and streams in the area are determined from the water samples taken from the sources. Sample collections are during the successive dry and wet seasons. They are subjected to physicochemical analyses, using the American Public Health Association (APHA) standard. Water temperatures, pH values, turbidity, electrical conductivities, water hardness, suspended solids (SS), water hardness, toxic metals and presence of hydrocarbons, benzene, toluene, ethylbenzene and xylene (BTEX) in the samples are determined. There are significant differences between the values of the indicators determined during the dry season and the wet season ( 0.05 ).Hardness was higher during the dry seasons. The inhabitants of the areas reported increased use of soap for washing during the dry season. Some indicator temperatures, zinc, iron, calcium levels are within the World Health Organization (WHO) and National Environmental Standards Regulatory and Enforcement Agency (NESREA) standards for potable water while others lead, chromium, cadmium, hardness and hydrocarbons are found to be slightly higher. Some quality values for the water collected during the wet and dry seasons were respectively: temperature: 26.250.05 to 26.650.05; 29.850.07 to 30 0.05 o C, pH value 5.150.04 to 6.800. 07, 4.490.05 to 5.451.07, Suspended solids:114.938 to 39010, 5022.4 to 810.910.3,cadmium: 0.5420.2 to 0.1450.14,0.2340.23, hardness of water:73042.43 to 3100100, 19013.13 to 29602100mg/L, hydrocarbons for benzene, toluene, ethylbenzene and xylene:6.1893.98 to 10.12.35 g/L. Strong correlations existed among physical and chemical parameters determined in all the locations S1 to S4 at 95% confidence level. Bitumen accumulations on available water sources might be the source of the level of heavy metals and BTEX recorded, as they are reportedly associated with bitumen. They are potential health risk to the people living in the area.
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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 | 0.002 | 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 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".