ABSTRACT
The emergence of the COVID-19 pandemic and airborne particulate matter pollution have caused a surge in the consumption of face masks in recent years. Typically, face masks are made from nondegradable petroleum-derived nonwoven materials adding to global plastic pollution and aggravating environmental concerns. Therefore, it is important to fabricate sustainable biodegradable replacements. This review intends to highlight and discuss state-of-the-art research activities that centre on the development of biodegradable nonwoven materials for face mask applications. We also identify potential candidates and strategies for future research and product development efforts. Finally, we present our perspectives on a wide avenue in need of further exploration concerning materials, methods, advanced functionalities, cost, scalability, and shelf life of sustainable advanced face masks. © 2023 The Royal Society of Chemistry.
ABSTRACT
SARS-CoV-2 is responsible for the COVID-19 pandemic. Airflows sustain the infection spread, and in densely urbanized areas airborne particulate matters (PMs) are deemed to aggravate the viral transmission. Apis mellifera colonies are used as bioindicators as they allow environmental sampling of different nature, PMs included. This experiment demonstrates for the first time the possible use of honey bee colonies in the SARS-CoV-2 monitoring. The trial was conducted in Bologna on 18 March 2021, when the third wave of the Italian pandemic was at its peak and environmental conditions allowed high PM concentrations in the air. Sterile swabs were lined up at the hive entrance to sample the dusty material on the body of returning foragers. All of them resulted positive for the target genes of viral SARS-CoV-2 RNA. Likewise, internal samples were taken, but they resulted in no amplification of the target sequences. This experiment does not support speculations about the role of honey bees or their products in SARS-CoV-2 transmission. However, it indicates a novel use of A. mellifera colonies in the environmental detection of airborne human pathogens, at least in a densely urbanized area, deserving better understanding and possible integration with data from automatic air samplers.