Atmospheric Concentrations of Polycyclic Aromatic Hydrocarbons in the Watershed of Lake Victoria, East Africa
Bibliographic record
Abstract
In the first study of its kind in Africa, PAHs were measured in high volume (24 h) air samples collected from two sampling stations, at Kakira and Entebbe (KAK and EBB, respectively) within the Lake Victoria watershed in Uganda, to assess source contributions and generate a baseline reference data set for future studies in the East African region. Sampling was conducted over two periods [2000-2004 (KAK and EBB1) and 2008-2010 (EBB2)]. The samples were extracted by accelerated solvent extraction and analyzed for 30 PAHs by GC-MS. The mean total PAH concentrations (ng/m(3)) were found to be 74.3 (range; 19.3-311, N = 39) for KAK, 56.8 (range; 13.3-126, N = 22) for EBB1 and 33.1 (range; 4.91-108, N = 56) for EBB2. The 3-ringed PAHs were the most predominant group with mean concentrations of 35.9 ng/m(3)(EBB1), 30.5 ng/m(3)(KAK) and 23.2 ng/m(3)(EBB2). Naphthalene had an exceptionally high mean concentration (21.9 ng/m(3)) for KAK compared to 0.44 and 0.39 ng/m(3) in EBB1 and EBB2 respectively, likely due to intensive agricultural operations nearby KAK. Principal component and diagnostic ratio analyses showed that the measured levels of PAHs were associated with mixed sources, combustion of petroleum, and biomass being the major sources.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".