Source Apportionment and Risk Assessment of Heavy Metals in Soils During Dry and Rainy Seasons in Southern Malawi
Why this work is in the frame
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Bibliographic record
Abstract
The recent increase in industrial activities has raised concerns regarding environmental quality in urban areas in Malawi. In this study, the contents of heavy metals [copper (Cu), zinc (Zn) and cadmium (Cd)] were analysed in 15 sites selected from Makata, Limbe, Maselema, Chirimba, and Maone industrial zones of Blantyre City in Malawi. Soil sampling was conducted during dry and rainy seasons, followed by laboratory analysis. The results revealed a few cases of elevated content of heavy metals exceeding permissible England and Canadian standards with higher content detected during the dry season than in the rainy season. Chirimba soil had the highest mean Zn content of 822 mg/kg in the rainy season and 579 mg/kg in the dry season. Maone soils had the highest Cd content, measuring 2.09 mg/kg in the rainy season and 3.06 mg/kg in the dry season. Chirimba soils also had the highest Cu content with levels of 105 mg/kg in the dry season and 79 mg/kg in the rainy season. The geo-accumulation index indicated that Zn posed the most severe pollution. The results of the Positive Matrix Factorisation model suggest that heavy metal pollution primarily originates from metal processing and manufacturing industries, followed by plastic manufacturing industries. This finding is supported by the nature of emissions from these sectors, where metal processing activities release heavy metals through particulates and waste to the environment, suggesting collective actions to prevent soil contamination.
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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 | 0.001 | 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) | 0.000 | 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 it