Advancements in Artificial Intelligence for Bioaerosol Detection, Characterization, and Modeling

Dear Colleagues,

Applying artificial intelligence (AI) techniques in atmospheric and environmental sciences has opened new perspectives for understanding complex phenomena, such as bioaerosol dynamics. Bioaerosols, comprising biological particles like bacteria, fungi, pollen, molds, and viruses, represent a crucial aspect of atmospheric processes with direct implications for public health and ecosystems. The study of bioaerosols, however, faces significant challenges due to their complex nature and the need for advanced methodologies to detect, quantify, and model their behavior in diverse environments.

This Special Issue aims to explore the use of AI-driven approaches in the study and research of bioaerosols, focusing on integrating machine learning, deep learning, and other AI techniques in bioaerosol detection, characterization, and prediction. We invite contributions demonstrating how AI is being utilized to analyze large datasets from sensors, remote sensing technologies, and field measurements to gain insights into bioaerosol distribution, sources, and transport mechanisms. Moreover, we encourage manuscripts that investigate AI's potential in advancing bioaerosol monitoring systems, improving models of bioaerosol behavior, and enhancing the accuracy of risk assessment models in relation to human health and ecosystem services.

We welcome both experimental and computational studies that demonstrate the role of AI in addressing the challenges associated with bioaerosol research, and we are particularly interested in contributions that bridge the gap between technology development and practical applications in the field.

Dr. Salvatore Romano
Dr. Mattia Fragola
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Aerobiology is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• artificial intelligence
• bioaerosols
• machine learning
• deep learning
• bioaerosol detection
• environmental monitoring
• aerosol dynamics
• public health