Biomass combustion is a major source of particulate matter (PM). While emissions from residential and industrial biomass burning have been widely studied, limited attention has been given to smoking applications used in beekeeping, where smoke is used to calm bees. These emissions may represent a relevant but underexplored source of exposure for beekeepers. The aim of this study is to compare PM emissions from different fuels commonly used in beekeeping smokers and assess their emission characteristics and potential health implications.
Fuels including wood pellets, jute, paper, and cardboard were investigated under laboratory conditions. The elemental composition of raw materials and emitted particulate matter was determined by inductively coupled plasma mass spectrometry (ICP-MS) following collection using an electric smoker and personal air-sampling pumps equipped with mixed cellulose ester (MCE) filters. Real-time PM monitoring and high-resolution field emission scanning electron microscopy (HR-FESEM) were used to characterize PM fractions (PM₁, PM₂.₅, PM₁₀) and particle morphology.
Marked differences in particulate emissions were observed across fuel types. Pellet fuels showed higher PM₁/PM₂.₅ ratios, indicating a predominance of fine particles, whereas processed cellulosic materials exhibited broader size distributions, reflecting fuel-dependent particle formation.
Elemental analysis revealed several potentially toxic elements in both fuels and emitted particulate matter, including Cd, Cr, Cs, Cu, Mn, Pb, and Zn. Significant variability in elemental concentrations was observed across fuel types, indicating fuel composition as a driver of exposure risk. In occupational settings, repeated inhalation of contaminated smoke may pose health risks, particularly due to elements such as Cd and Pb, associated with chronic toxicity. Environmental dispersion of these emissions also raises concerns about pollinator health and the potential transfer of contaminants to honey and other hive products.
Acknowledgements: This research was partially funded by Sapienza University of Rome (projects 2023 and 2025; grant numbers RM123188F73F6255 and AR125199C0876C2A).