In this work, PM10 samples previously subjected to thorough chemical speciation and receptor modelling, have been investigated for their bio-toxicity using an inhibition test based on bacterial luminescence modulation when in contact with airborne particulate samples. The variation of light emission intensity from a luminescent bacteria strain, the Photobacterium phosphoreum, is proposed as an efficient proxy for the quantification of bio-toxic effects induced by airborne particulate matter. PM10 samples characterized by definite levels of pollutants from the pertaining air shed were found to induce a decrease in the bacterial bioluminescence intensity, expressed as percentage of Inhibition Ratio (IR%). This behaviour suggests the decay of this energy-consuming activity because of a toxic effect. Cluster analysis on chemical composition and IR% data provides evidence of a statistically significant association between the adverse effects on living cells and the range of specific chemical species in PM10.

Airborne particulate matter biotoxicity estimated by chemometric analysis on bacterial luminescence data

Laura Tositti;Erika Brattich
;
Silvia Parmeggiani;Luca Bolelli;Elida Ferri;Stefano Girotti
2018

Abstract

In this work, PM10 samples previously subjected to thorough chemical speciation and receptor modelling, have been investigated for their bio-toxicity using an inhibition test based on bacterial luminescence modulation when in contact with airborne particulate samples. The variation of light emission intensity from a luminescent bacteria strain, the Photobacterium phosphoreum, is proposed as an efficient proxy for the quantification of bio-toxic effects induced by airborne particulate matter. PM10 samples characterized by definite levels of pollutants from the pertaining air shed were found to induce a decrease in the bacterial bioluminescence intensity, expressed as percentage of Inhibition Ratio (IR%). This behaviour suggests the decay of this energy-consuming activity because of a toxic effect. Cluster analysis on chemical composition and IR% data provides evidence of a statistically significant association between the adverse effects on living cells and the range of specific chemical species in PM10.
Laura Tositti, Erika Brattich, Silvia Parmeggiani, Luca Bolelli, Elida Ferri, Stefano Girotti
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/645140
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? 3
  • Scopus 14
  • ???jsp.display-item.citation.isi??? 13
social impact