Abstract

The properties of bioaerosols are complex and diverse, and have a direct impact on the environment, climate, and human health. The effective identification of bioaerosols in the atmosphere is very significant with regard to accurately obtaining the atmospheric chemical characteristics of bioaerosols and making biological early warnings and predictions. To improve the detection of large particle bioaerosol and non-bioaerosol interference in the process of bioaerosol recognition this study detected a variety of bioaerosols and abiotic aerosols based on a single particle aerosol mass spectrometer (SPAMS). Furthermore, the bioaerosol particle identification and classification algorithm based on Zawadowicz the ratio of phosphate to organic nitrogen is optimized to distinguish bioaerosols from abiotic aerosols. The influence of ionized laser energy on classification methods is thoroughly explored here. The results show that 15 kinds of pure fungal aerosols were detected by SPAMS based on a wide size range sampling system, and that fungal aerosols with a particle size of up to 10 μm can be detected. Through the mass spectra peak ratio method of PO3−/PO2− and CNO−/CN−, when discriminating abiotic aerosols such as disruptive biomass combustion particles, automobile exhaust, and dust from pure bacterial aerosols, the discrimination degree is up to 97.7%. The optimized ratio detection method of phosphate to organic nitrogen has strong specificity, which can serve as the discriminant basis for identifying bioaerosols in SPAMS analytical processes.

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