Characterization and Health Risk Assessment of Airborne Fungi in a Semiunderground Municipal Wastewater Treatment Plant
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Municipal wastewater treatment plants (WWTPs) are recognized as the significant source of fungal aerosols, which pose a significant threat to human health globally. Herein, the occurrences characterization, community structure, and health risk assessment of airborne fungi were investigated from a semiunderground WWTP. The concentrations of culturable fungi emitted into the air from the WWTP ranged from 30.6 to 1431.1 colony forming units (CFU)/m 3, with primary and biochemical treatments constituting the principal sources of emission ( P < 0.05). Diversity analysis revealed seasonal and facility-dependent fluctuations in culturable fungal communities. Approximately 13.5% of the total airborne fungal genera detected in the WWTP were culturable. Some airborne fungi in the WWTP with relatively low abundance but high cultivability, such as Cladosporium, Trichoderma, Neurospora, Filobasidium, and Hannaella, tended to be overlooked because of their limited presence in airborne environments. We also developed a health risk assessment method for fungi, utilizing seven indicators to characterize the risk posed by fungal pathogens from multiple perspectives, providing a comprehensive evaluation of potential health impacts. The simulated risk values of the air outlet and biochemical treatment exceeded those of other treatment facilities, with median risks of 2.2 × 10 2 and 1.4 × 10 2, respectively. Consequently, management strategies should prioritize enhanced controls for fungal aerosols to mitigate the risk of disease transmission.
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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 | 0.000 | 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 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".