Disentangling multiple PM emission sources in the Po Valley (Italy) using honey bees

Giulia Papa, Ilaria Negri, Marco Pellecchia, Giancarlo Capitani

Risultato della ricerca: Contributo in rivistaArticolo in rivista

Abstract

Particulate matter (PM) is a complex mixture of airborne chemical compounds commonly classified by their aerodynamic diameter. Although PM toxicity strongly depends on the morphology, chemical composition, and dimensions of particles, exposure limits set by environmental organisations only refer to the mean mass concentration of PM sampled daily or annually by monitoring stations. In this study, we used honey bees as sensors of airborne PM10 and PM2.5 in a highly polluted area of the Po Valley, northern Italy. Honey bees are an efficient sampler of airborne PM because, during flight and foraging activities, their pubescence promotes the accumulation of electrical charge on the body surface owing to air resistance, thus enhancing airborne PM attraction. Particles attached to the body of bees are readily accessible for physico-chemical characterisation using a scanning electron microscope coupled with X-ray spectroscopy (SEM/EDX). Our results demonstrate that residents in the study area are intermittently but chronically exposed to a well-defined spectrum of metal-bearing particles and mineral phases known to induce specific health outcomes. The morphology, size, and chemical composition of PM10 and PM2.5 detected on bees in the monitoring area were indicative of traffic, agricultural operations, and high-temperature combustion processes. The contribution of the A1 Milano-Bologna highway, local wheat and alfalfa cultivation, and the Parma incineration plant were clearly distinguishable. Our data also demonstrated that PM exposure levels may vary sharply throughout the year based on recurrent local activities.
Lingua originaleEnglish
pagine (da-a)e06194-e06194
RivistaHeliyon
Volume7
DOI
Stato di pubblicazionePubblicato - 2021

Keywords

  • Agriculture
  • Honey bee
  • Waste incineration
  • SEM/EDX
  • Vehicular traffics
  • PM sensors

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