Enhanced Detection of Primary Biological Aerosol Particles Using Machine Learning and Single-Particle Measurement-Reference-Cited by-同舟云学术

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Enhanced Detection of Primary Biological Aerosol Particles Using Machine Learning and Single-Particle Measurement

Published:2024-08-07 Issue: Volume: Page:
ISSN:2690-0645
Container-title:ACS ES&T Engineering
language:en
Short-container-title:ACS EST Eng.

Author:

Rahman Ashfiqur¹,Lata Nurun Nahar¹,Sebben Bruna Grasielli²,Dexheimer Darielle³,Cheng Zezhen¹^ORCID,Godoi Ricardo Henrique Moreton²^ORCID,Bilbao Aivett¹^ORCID,China Swarup¹^ORCID

Affiliation:

1. Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States

2. Department of Environmental Engineering, Federal University of Paraná, Curitiba 81531, Brazil

3. Sandia National Laboratories, Albuquerque, New Mexico 87123, United States

Funder

Biological and Environmental Research

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acsestengg.4c00262

Reference56 articles.

1. Bioaerosols in the Earth system: Climate, health, and ecosystem interactions

2. Frequency of occurrence of rain from liquid-, mixed-, and ice-phase clouds derived from A-Train satellite retrievals

3. Primary biological aerosol particles in the atmosphere: a review

4. Regionally sourced bioaerosols drive high-temperature ice nucleating particles in the Arctic

5. Bioaerosols are the dominant source of warm-temperature immersion-mode INPs and drive uncertainties in INP predictability

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