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Record W4390491204 · doi:10.1080/10962247.2023.2299424

Assessment of waste workers occupational risk to microbial agents and cytotoxic effects of mixed contaminants present in the air of waste truck cabin and ventilation filters

2024· article· en· W4390491204 on OpenAlexafffund
Geneviève Marchand, Loïc Wingert, Carla Viegas, Liliana Aranha Caetano, Susana Viegas, Magdalena Twarużek, Nancy Lacombe, Delphine Lanoie, Isabelle Valois, F. Gouin, Ewelina Soszczyńska, Robert Kosicki, Marta Dias, Maximilien Debia

Bibliographic record

VenueJournal of the Air & Waste Management Association · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsUniversité de MontréalInstitut de recherche Robert-Sauvé en santé et en sécurité du travail
FundersFundação para a Ciência e a TecnologiaMinistério da Ciência, Tecnologia e Ensino SuperiorUniversité de MontréalCanada Excellence Research Chairs, Government of CanadaInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsContaminationTruckWaste managementEnvironmental scienceMunicipal solid wasteEnvironmental chemistryWastewaterToxicologyEnvironmental engineeringChemistryBiologyEngineeringEcology

Abstract

fetched live from OpenAlex

Workers in the waste-processing industry are potentially exposed to high concentrations of biological contaminants, leading to respiratory and digestive problems and skin irritations. However, few data on the exposure of waste collection truck (WCT) drivers are available. The goal was to document the microbial risk of the waste collection truck (WCT) workers while in the vehicle cab. Long-period sampling using the truck air filters (CAF) and short time ambient air sampling in the cab were used. The potential release of microbial particles from CAFs was also investigated since it could contribute to the microbial load of the cabin air. A combination of analytical methods also helped assess the complex mixture of the biological agents. Aspergillus sections Fumigati and Flavi, E. coli, Enterobacter spp. and Legionella spp. were detected in the CAF of trucks collecting three types of waste. The highest levels of bacteria and fungi were found in the CAF from organic WCT. The highest endotoxin concentrations in CAF were 300 EU/cm2. Most of the CAF showed cytotoxic effects on both lung cells and hepatocytes. Only one mycotoxin was detected in a CAF. The maximal concentrations in the ambient WCT air varied according to the type of waste collected. The highest proportion (84%) of the air samples without cytotoxic effects on the lungs cells was for the recyclable material WCTs. The results revealed the potential microbial risk to workers from a complex mixture of bio-contaminants in the cabs of vehicles collecting all types of waste. The sustained cytotoxic effect indicates the potential adverse health-related impact of mixed contaminants (biological and non-biological) for the workers. Overall, this study highlights the benefits of using complementary sampling strategy and combined analycal methods for a the assessment of the microbial risk in work environments and the need to implement protective measures for the workers.Implications Exposure to microbial agents is a well-known occupational hazard in the waste management sector. No previous study had evaluated the cytotoxicity of ambient air and ventilation filters to document worker exposure to a combination of contaminants during waste collection. This research confirms the usefulness of ventilation filters for long-term characterization of exposure to infectious agents, azole-resistant fungi, coliform bacteria and mycotoxin. Overall, this study highlights the importance of using several sampling and analysis methods for a comprehensive assessment of microbial risk in work environments, as well as the need to implement appropriate protective measures for collection workers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.246
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2024
Admission routes2
Has abstractyes

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