On the autarchic use of solely PIXE data in particulate matter source apportionment studies by receptor modeling

Particle Induced X-ray Emission (PIXE) analysis of aerosol samples allows simultaneous detection of sev- eral elements, including important tracers of many particulate matter sources. This capability, together with the possibility of analyzing a high number of samples in very short times, makes PIXE a very effec- tive tool for source apportionment studies by receptor modeling. However, important aerosol compo- nents, like nitrates, OC and EC, cannot be assessed by PIXE: this limitation may strongly compromise the results of a source apportionment study if based on PIXE data alone. In this work, an experimental dataset characterised by an extended chemical speciation (elements, EC–OC, ions) is used to test the effect of reducing input species in the application of one of the most widely used receptor model, namely Positive Matrix Factorization (PMF). The main effect of using only PIXE data is that the secondary nitrate source is not identified and the contribution of biomass burning is overestimated, probably due to the similar seasonal pattern of these two sources.