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Record W4409462282 · doi:10.1021/acs.est.4c12108

Emission Dynamics and Public Health Implications of Airborne Pathogens and Antimicrobial Resistance from Urban Waste Collection Facilities

2025· article· en· W4409462282 on OpenAlexaff
Xiang Zhang, Bingjie Lu, Ling Jin, Shuo Yang, Chuan Wang, Jun Tai, Dan Li, Jianmin Chen

Bibliographic record

VenueEnvironmental Science & Technology · 2025
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsImpact
Fundersnot available
KeywordsAntibiotic resistancePublic healthEnvironmental scienceResistance (ecology)AntimicrobialWaste managementEnvironmental healthEnvironmental engineeringEnvironmental planningEngineeringMicrobiologyBiologyMedicineEcologyAntibiotics

Abstract

fetched live from OpenAlex

Airborne pathogens and antimicrobial resistance (AMR) present significant global health threats. Household waste collection facilities (WCFs), crucial initial nodes in urban waste management systems, have been understudied in regards to their role in emitting these hazards. This study investigated the abundance, composition, sources, driving mechanisms, and health risks associated with pathogens and AMR originating from WCFs in a major city, using culture-based analysis, high-throughput sequencing, and health risk modeling, respectively. The atmospheric escape rates of culturable bacteria (43.4%), fungi (71.7%), and antibiotic-resistant bacteria (ARB) (43.7%) were estimated based on the concentration differences between the interior and exterior of the WCFs by using SourceTracker2 analysis. Health risk assessments showed that annual infection risks for waste-handling workers ranged from 0.194 to 0.489, far exceeding the World Health Organization’s acceptable limit of 10 –4 . Community exposure risks were notable up to 220 m downwind from WCFs, marking the maximum extent of pathogen dispersion. Our analysis suggests that approximately 6.3% of the megacity’s area (equivalent to 400 km 2 ) is within potential risk zones influenced by WCF emissions. These results underscore the critical need to evaluate and mitigate the public health risks posed by airborne pathogens and AMR emitted from WCFs in megacities globally.

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)0.000
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 score0.430
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.006
GPT teacher head0.229
Teacher spread0.223 · 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

Citations7
Published2025
Admission routes1
Has abstractyes

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