Urbanisation and Lockdown Impact on Airborne Fungal Communities in Tropical Landscapes: A Comparative Study of Urban...

This study assessed the concentration, composition, and spatiotemporal distribution of airborne fungi in a metropolitan area, comparing urban and peri-urban sites across rainy and dry seasons. An 8-month fungal bioaerosol monitoring was conducted using a six-stage Andersen cascade impactor. Data analysis involved generalised linear regression models and multifactorial ANOVA to assess the relationships between meteorological conditions, sampling sites, campaigns, fungal concentrations, and impactor stages. Additionally, a Bayesian neural network was developed to predict bioaerosol dynamics based on the analysed variables. We identified 10 viable fungal species, including Aspergillus niger, Aspergillus nidulans, Aspergillus. fumigatus, Aspergillus terreus, Aspergillus flavus, Aspergillus versicolor, Penicillium spp. and Fusarium oxysporum. Notable differences in the aerodynamic sizes of fungal particles influenced their distribution and potential impact on the respiratory system. The Bayesian neural network successfully predicted fungal bioaerosol concentrations with an accuracy of 76.87%. Our findings reveal the significant role of environmental and human-related factors in shaping bioaerosol distribution in tropical urban contexts. This research provides essential insights into the behaviour of fungal bioaerosols, highlighting their relevance for public health, especially for immunocompromised populations, and their impact on local agriculture. Furthermore, it demonstrates the potential of fungal bioaerosols as bioindicators for environmental monitoring and predictive modelling.