Improving Source Apportionment of Urban Aerosol Using Multi-Isotopic Fingerprints (MIF) and Positive Matrix Factorization (PMF): Cross-Validation and New Insights

Abstract

Urban air pollution is a matter of concern due to its health hazards and the continuous population growth exposed to it at different urban areas worldwide. Nowadays, more than 55% of the world population live in urban areas. One of the main challenges to guide pollution control policies is related to pollutant source assessment. In this line, U.S. Environmental Protection Agency's Positive Matrix Factorization (EPA-PMF) has been extensively employed worldwide as a reference model for quantification of source contributions. However, EPA-PMF presents issues associated to source identification and discrimination due to the collinearities among the source tracers. Multi-Isotopic Fingerprints (MIF) have demonstrated good resolution for source discrimination, since urban sources are characterized by specific isotopic signatures. Source quantification based on total aerosol mass is the main limitation of MIF. This study reports strategies for PMF and MIF combination to improve source identification/discrimination and its quantification in urban areas. We have three main findings: (1) cross-validation of PMF source identification based on Pb and Zn isotopic fingerprints, (2) source apportionment in the MIF model for total PM mass, and (3) new insights into potential Zn isotopic signatures of biomass burning and secondary aerosol. We support future studies on the improvement of isotopic fingerprints database of sources based on diverse elements or compounds to boost advances of MIF model applications in atmospheric sciences.