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Effect of Gas-Particle Partitioning on Source Apportionment of Ambient Mass Spectrometry Data
SAHIL BHANDARI, Andrew Dinh, Gazala Habib, Joshua Apte, Lea Hildebrandt Ruiz, University of Texas at Austin
Abstract Number: 580
Working Group: Source Apportionment
Abstract
As a part of the Delhi Aerosol Supersite (DAS) campaign, submicron organic aerosol (OA) was measured in spring 2018 in Delhi, India using an Aerodyne aerosol chemical speciation monitor. Previously, we conducted positive matrix factorization (PMF) on this particle-only dataset. We obtained three factors: a hydrocarbon-like OA (HOA) factor, a biomass burning OA factor, and an oxidized organic aerosol (OOA) factor. Recent research suggests that the inclusion of measured or modeled gaseous organic compounds allows improved characterization of sources by accounting for the non-linearity effects of gas-particle partitioning (Xie et al., 2014).
Here, we estimated gas-phase concentrations corresponding to HOA, BBOA, and OOA by using volatility basis set (VBS) parameters for particle-only PMF factors and assuming equilibrium. We applied PMF to the combined gaseous and particle-phase data using the EPA PMF tool. This combined PMF yielded three factors similar in mass spectra to the particle-only analysis but different in contributions. Particularly, compared to the particle-only analysis, the combined analysis amplifies the contributions of the HOA and BBOA factors, especially during nighttime. This combined particle-gas phase source apportionment of mass spectrometry data may more accurately reflect the relative importance of different sources contributing to particulate matter formation.
Reference:
Xie, M., Hannigan, M.P., and Barsanti, K.C., 2014. Impact of gas/particle partitioning of semivolatile organic compounds on source apportionment with positive matrix factorization. Environmental Science & Technology, 48(16), pp.9053-9060.