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<p>Bioaerosols are airborne particles of biological origin, including bacteria, viruses, fungi, pollen, and their fragments,&#xa0;and are&#xa0;significant contributors to air quality and public health challenges in both indoor and outdoor environments. This review presents the current understanding of bioaerosol sources, transport mechanisms, and associated health effects. Human residents, pets, ventilation systems, and building materials are the primary indoor sources of bioaerosols, while vegetation, soil, wastewater, and various anthropogenic activities are the primary outdoor sources of bioaerosols. Environmental factors, including humidity, temperature, airflow, and particle size, play an essential role in the transport and dispersion of bioaerosols. Increasing antimicrobial resistance, airborne transmission of viral pathogens (notably SARS-CoV-2), and the effects of climate change are some of the emerging challenges that highlight the need for continued research and effective interventions. The use of machine learning and deep learning techniques has become essential for real-time detection, source apportionment, forecasting of bioaerosol concentrations, and analysis of complex metagenomic data. Moreover, artificial intelligence (AI) enhanced image analysis offers significant advancements in microbial identification through microscopy and flow cytometry. The review further discusses various bioaerosol sampling methods, innovative omics-based characterization techniques, and comprehensive frameworks for health risk assessment. In future studies, epidemiologists should consider exposure and risk factors, as well as the prevalent sampling methods for bioaerosol assessment. Control strategies, including filtration, UV disinfection, and biocides, are also examined. This study highlights significant research gaps and suggests a multidisciplinary approach for future studies.</p>

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Bioaerosols in the Atmosphere: Sources, Transport, and Public Health Concerns

  • 期刊论文

  • 发表日期：

    2026年7月24日

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  • Mushtaq Ahmad,
  • Jing Chen,
  • Sirima Panyametheekul,
  • Zunaira Asif,
  • Titaporn Supasri,
  • Muhammad Tariq Khan,
  • Ronald Macatangay,
  • Sana Ullah,
  • Phailin Thaveevong,
  • Mohammad Junaid

摘要

Bioaerosols are airborne particles of biological origin, including bacteria, viruses, fungi, pollen, and their fragments, and are significant contributors to air quality and public health challenges in both indoor and outdoor environments. This review presents the current understanding of bioaerosol sources, transport mechanisms, and associated health effects. Human residents, pets, ventilation systems, and building materials are the primary indoor sources of bioaerosols, while vegetation, soil, wastewater, and various anthropogenic activities are the primary outdoor sources of bioaerosols. Environmental factors, including humidity, temperature, airflow, and particle size, play an essential role in the transport and dispersion of bioaerosols. Increasing antimicrobial resistance, airborne transmission of viral pathogens (notably SARS-CoV-2), and the effects of climate change are some of the emerging challenges that highlight the need for continued research and effective interventions. The use of machine learning and deep learning techniques has become essential for real-time detection, source apportionment, forecasting of bioaerosol concentrations, and analysis of complex metagenomic data. Moreover, artificial intelligence (AI) enhanced image analysis offers significant advancements in microbial identification through microscopy and flow cytometry. The review further discusses various bioaerosol sampling methods, innovative omics-based characterization techniques, and comprehensive frameworks for health risk assessment. In future studies, epidemiologists should consider exposure and risk factors, as well as the prevalent sampling methods for bioaerosol assessment. Control strategies, including filtration, UV disinfection, and biocides, are also examined. This study highlights significant research gaps and suggests a multidisciplinary approach for future studies.