Phosphorus Speciation and Heavy Metal Levels in Ogun River Sediments at Different Anthropogenic Locations in Abeokuta, Ogun State
Bibliographic record
Abstract
Phosphorus (P) is an essential nutrient for phytoplankton growth in water bodies and an important element in biochemical processes. Also, excessive P in river causes eutrophication which endangers aquatic organisms while sediment acts as sink for inorganic and organic pollutants and nutrients. To assess the availability of P and heavy metals (HMs) in Ogun River, surface sediment samples were collected at twelve anthropogenic sites for three months. The surface sediment samples were sequentially extracted to determine five phosphorus fractions [loosely-sorbed P (LS-P), iron-bound P (Fe-P), authigenic apatite, biogenic apatite and CaCO3-bound P (CFA-P), detrital apatite (Det-P) and other inorganic P (IP) as well as organic P (OP)] and levels of selected HMs (Pb, Cr and Zn). Phosphorus fractions were determined spectrophotometrically and HMs were determined using atomic absorption spectrophotometer (AAS) after wet digestion. The average percentages of fractions of P in surface sediments were Det-P (34.66±1.00%) > Fe-P (27.67± 0.02%) > OP (18.11±2.00%) > authigenic apatite, biogenic apatite and CaCO3-bound P (14.38±4.56%) > LS-P (5.18±0.78%). It was observed that IP was dominant (86.38%) of the total phosphorus (TP) compared to OP (13.62%). One of the sites, Garri processing, had highest TP (710 µg P g-1) which was above the standard values for Chinese Environmental Dredging (500 µg P g-1) and Canadian Province of Ontario (600 µg P g-1) Sediment Quality Guidelines (SQG). The mean concentrations of HMs determined in sediments were below the SQG values except Zn in some sites. The results revealed moderate pollution of P and Zn and also, accumulation of these pollutants overtime might pose threat to aquatic organisms. The results obtained would serve as baseline values for P speciation in Ogun River.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".