Spatiotemporal evolution of bioaerosols from the Yellow River in the southern North China Plain: microbial composition, pathogenic risk assessment, and biomarker identification

Wang, Yanjie; Li, Jinlong; Hao, Changfu; Li, Yan; Zhu, Haoran; Liu, Yang; Lai, Bisheng; Liu, Yifan

doi:.0..

DOI: https://doi.org/10.4491/eer.2024.728

Spatiotemporal evolution of bioaerosols from the Yellow River in the southern North China Plain: microbial composition, pathogenic risk assessment, and biomarker identification

Yanjie Wang¹^†, Jinlong Li¹, Changfu Hao¹, Yan Li², Haoran Zhu¹, Yang Liu¹, Bisheng Lai¹, and Yifan Liu¹

¹School of Public Health, Zhengzhou University, Zhengzhou 450001, P. R. China.
²Center for Medical Experiment, The Second Clinical Medical School of Zhengzhou University, The second affiliated hospital of Zhengzhou University. Zhengzhou, Henan, China. 450014

Corresponding Author: Yanjie Wang ,Tel: +86-67781795, Email: wangyanjie_2008@126.com

Received: December 29, 2024; Accepted: April 18, 2025.

ABSTRACT

The Yellow River may generate bioaerosols through water disturbance during its flow due to geological formations, climate change, and human activities. Such biological particles have the potential to carry pathogenic microorganisms, thereby posing health risks to local residents and visitors. This study used high-throughput sequencing to analyze the Yellow River bioaerosols in the southern North China Plain during 2023 and 2024. The results indicated that the mean concentrations of bacteria in bioaerosols for 2023 and 2024 were 226 ± 138 CFU/m3 and 456 ± 218 CFU/m3, respectively. Over the two-year period, the proportion of fine particulate bioaerosols (< 3.3 μm) consistently remained above 50%. Pathogenic bacteria such as Pseudomonas, Enterobacter, Stenotrophomonas, and Lysinibacillus were detected at some sampling sites. The non-carcinogenic exposure risk of the Yellow River bioaerosols was within acceptable limits, but prolonged exposure might cause damage to human health. The Radial Basis Function Neural Network (RBFNN) was successfully employed to identify Enterobacteriaceae, Bacillus, and Micrococcaceae as significant risk biomarkers within bioaerosols. The HYSPLIT model showed that the maximum dispersion area of bioaerosols covered 417.86 km2. This study aimed to provide a scientific basis for ecological environmental protection and public health initiatives in the Yellow River Basin.

Keywords: Bioaerosol | Genetic prediction | Pathogenic bacteria transmission | Radial basis function neural network | Yellow River