Fungal bioaerosols in biomethanization facilities
Bibliographic record
Abstract
Biomethanization is a new technology used for green-waste valorization where organic waste is biodegraded by microbial communities under anaerobic conditions. The main product of this type of anaerobic digestion is a biogas used as an energy source. Moving and handling organic waste may lead to the emission of high concentrations of bioaerosols. High exposure levels are associated with adverse health effects amongst green environment workers. Fungal spores are suspected to play a role in many respiratory illnesses. There is a paucity of information related to the detailed fungal diversity in biomethanization facilities. The aim of this study was to provide an in-depth description of fungal bioaerosols in biomethanization work environments using a next-generation sequencing approach combined with real-time polymerase chain reaction (PCR). Two biomethanization facilities treating different wastes were visited during the sampling campaign (n = 16). Quantification of Penicillium/Aspergillus and Aspergillus fumigatus revealed a greater exposure risk during summer for both facilities visited. Concentrations of Penicillium and Aspergillus were similar in all work areas in both biomethanization facilities. Taxonomy analyses showed that the type of waste treated affects the fungal diversity of aerosols emitted. Although eight classes were evenly distributed in all samples, Eurotiomycetes were more dominant in the first facility and Agaricomycetes were dominant in the second one. A large diversity profile was observed in bioaerosols from both facilities showing the presence of pathogenic fungi. The following fungi detected are known allergens and/or are opportunistic pathogens: Aspergillus, Malassezia, Emericella, Fusarium, Acremonium, and Candida. Daily exposure to these fungi may put workers at risk. The information from this study can be used as a reference for minimizing occupational exposure in future biomethanization facilities. Implications: Biomethanization is a new technology used for green-waste valorization where organic waste is biodegraded by microbial communities. Effective waste management is increasingly recognized as a strategic approach for achieving newly created regulations concerning the disposal of organic residues; therefore, an expansion of facilities is expected. Workers' exposure to diverse fungal communities is certain, as fungi are ubiquitous and necessary in organic matter decomposition. Monitoring this occupational exposure is important in order to prevent workers' health problems.
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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 | 0.001 | 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 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".