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Cited by 304

The DOI matches its Crossref record; 98 of the 98 references it cites were found in a registry or an index.

Indoor bioaerosol dynamics

Open access
Nazaroff, William W·2016·Indoor Air

Abstract

Inhaling indoor air is the primary means by which humans are exposed to bioaerosols. Considering bacteria, fungi, and viruses, this study reviews the dynamic processes that govern indoor concentrations and fates of biological particulate material. Bioaerosol behavior is strongly coupled to particle size; this study emphasizes the range 0.1-10 μm in aerodynamic diameter. The principle of material balance allows concentrations to be determined from knowledge of important source and removal processes. Sources reviewed here include outdoor air introduced by air exchange plus indoor emission from occupants, occupant activities, and moldy materials. Important mechanisms that remove bioaerosols from indoor air include air exchange, deposition onto indoor surfaces, and active filtration. The review summarizes knowledge about size-dependent particle deposition in different regions of the respiratory tract, techniques for measuring indoor bioaerosols, and evidence for diseases caused by airborne exposure to bioaerosols. Future research challenges and opportunities are highlighted.

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Crossref · 10.1111/ina.12174

Cites

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Metadata

Authors
Nazaroff, W. W.
Venue
Indoor Air
Publisher
Wiley
Published
2014-12-27
Volume
26
Issue
1
Pages
61-78
ISSN
  • 0905-6947 (ISSN-L)
  • 1600-0668
OpenAlex
W2157714024
Cited by
304
References
98
FWCI
8.19
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Indoor bioaerosol dynamics. https://app.cochat.ai/papers/10.1111/ina.12174
The paper
Nazaroff, W. W. (2016). Indoor bioaerosol dynamics. Indoor Air. https://doi.org/10.1111/ina.12174

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.