Persistent Chlorinated Pesticides in Air, Water, and Precipitation from the Lake Malawi Area, Southern Africa
Bibliographic record
Abstract
Concentrations of chlorinated pesticides were analyzed in air (biweekly 1997−1998), water, and precipitation at Lake Malawi, in southeast Africa. The pesticides in air in Senga Bay on the southwest shore of Lake Malawi were not extensively weathered, implying recent use. Elevated levels of heptachlor, chlorobenzenes, aldrin, and dieldrin were detected periodically, which indicated use on a regular basis. Annual average concentrations for those pesticides ranged from 31 to 257 pg/m 3 . Levels of HCHs, DDTs, chlordanes, and α-endosufan in air at Senga Bay were comparable to those of the Laurentian Great Lakes, ranging from 24 to 40 pg/m 3 . Considering air−water gas exchange and wet deposition, the net fluxes of chlorinated pesticides to the lake surface were depositional. Concentrations of chlorinated pesticides in the water from Lake Malawi were relatively low compared to the Laurentian Great Lakes and Lake Baikal. This indicates rapid transformation of chemicals in the water column, which was further supported by high metabolite-to-parent ratios. The results suggests that tropical regions may act as both a global source and sink for chlorinated pesticides, since removal processes may be faster compared to temperate and Arctic regions.
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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 | 0.000 | 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 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".