Variability of airborne microbial communities and associations with organic pollutants in African air particulate matter across land-use types
Bibliographic record
Abstract
Exposure to particulate matter (PM) is a major global health concern, yet the potential relationships between its chemical and microbial components remains poorly understood, particularly in rapidly urbanizing, understudied settings. This study presents an integrated assessment of polycyclic aromatic hydrocarbons (PAHs), nitrated PAHs (NPAHs), bacteria, and fungi in both fine (PM 2 . 5 ) and coarse (PM 10 ) aerosols across urban, roadside, and rural sites in sub-Saharan Africa, with a focus on Rwanda across dry and wet seasons. Microbial analysis revealed that the richness and community structure of the airborne bacterial and fungal communities varied with land-use type, linked with PAH/NPAH abundance, PM size fraction, and season. Spearman correlation coefficient confirmed that bacterial communities were more strongly associated with PAH and NPAH compounds, whereas fungal communities were shaped primarily by environmental factors. One bacterial genus, Sphingobium , exhibited evidence of selective enrichment within the PAH rich PM 2 . 5 size fraction, highlighting the potential for direct interaction between the biological and chemical compositions in air. We provide a critical baseline for African cities where air quality data are scarce. Current air quality standards, which prioritize chemical thresholds, overlook the biological burden carried by PM.
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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 | 0.000 | 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".