Abstract

Abstract. Receptor modeling was performed on quadrupole unit mass resolution aerosol mass spectrometer (Q-AMS) sub-micron particulate matter (PM) chemical speciation measurements from Windsor, Ontario, an industrial city situated across the Detroit River from Detroit, Michigan. Aerosol and trace gas measurements were collected on board Environment Canada's Canadian Regional and Urban Investigation System for Environmental Research (CRUISER) mobile laboratory. Positive matrix factorization (PMF) was performed on the AMS full particle-phase mass spectrum (PMFFull MS) encompassing both organic and inorganic components. This approach compared to the more common method of analyzing only the organic mass spectra (PMFOrg MS). PMF of the full mass spectrum revealed that variability in the non-refractory sub-micron aerosol concentration and composition was best explained by six factors: an amine-containing factor (Amine); an ammonium sulfate- and oxygenated organic aerosol-containing factor (Sulfate-OA); an ammonium nitrate- and oxygenated organic aerosol-containing factor (Nitrate-OA); an ammonium chloride-containing factor (Chloride); a hydrocarbon-like organic aerosol (HOA) factor; and a moderately oxygenated organic aerosol factor (OOA). PMF of the organic mass spectrum revealed three factors of similar composition to some of those revealed through PMFFull MS: Amine, HOA and OOA. Including both the inorganic and organic mass proved to be a beneficial approach to analyzing the unit mass resolution AMS data for several reasons. First, it provided a method for potentially calculating more accurate sub-micron PM mass concentrations, particularly when unusual factors are present, in this case the Amine factor. As this method does not rely on a priori knowledge of chemical species, it circumvents the need for any adjustments to the traditional AMS species fragmentation patterns to account for atypical species, and can thus lead to more complete factor profiles. It is expected that this method would be even more useful for HR–ToF–AMS data, due to the ability to understand better the chemical nature of atypical factors from high-resolution mass spectra. Second, utilizing PMF to extract factors containing inorganic species allowed for the determination of the extent of neutralization, which could have implications for aerosol parameterization. Third, subtler differences in organic aerosol components were resolved through the incorporation of inorganic mass into the PMF matrix. The additional temporal features provided by the inorganic aerosol components allowed for the resolution of more types of oxygenated organic aerosol than could be reliably resolved from PMF of organics alone. Comparison of findings from the PMFFull MS and PMFOrg MS methods showed that for the Windsor airshed, the PMFFull MS method enabled additional conclusions to be drawn in terms of aerosol sources and chemical processes. While performing PMFOrg MS can provide important distinctions between types of organic aerosol, it is shown that including inorganic species in the PMF analysis can permit further apportionment of organics for unit mass resolution AMS mass spectra.

Highlights

  • Atmospheric aerosol or particulate matter (PM) is known to have important implications for atmospheric visibility (Watson, 2002), climate change (IPCC, 2013), and human health (Pope and Dockery, 2006; Anderson et al, 2012; Brook et al, 2010)

  • Most have focused on the organic fraction of the AMS mass spectrum (e.g., Lanz et al, 2007; Ulbrich et al, 2009) in an effort to resolve uncertainty regarding the sources and processes contributing to secondary organic aerosol (SOA), an aerosol component with potential implications for climate (IPCC, 2013)

  • Many of these studies have focused on the application of factor analysis to the organic mass fraction in an attempt to deconvolve it into descriptive sub-components, namely a hydrocarbon-like organic aerosol (HOA) factor, and an oxygenated organic aerosol (OOA)

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Summary

Introduction

Atmospheric aerosol or particulate matter (PM) is known to have important implications for atmospheric visibility (Watson, 2002), climate change (IPCC, 2013), and human health (Pope and Dockery, 2006; Anderson et al, 2012; Brook et al, 2010). Receptor modeling using positive matrix factorization (PMF) has become a useful analytical technique for further understanding the origins of AMS-measured aerosol Among these studies, most have focused on the organic fraction of the AMS mass spectrum (e.g., Lanz et al, 2007; Ulbrich et al, 2009) in an effort to resolve uncertainty regarding the sources and processes contributing to secondary organic aerosol (SOA), an aerosol component with potential implications for climate (IPCC, 2013). Most have focused on the organic fraction of the AMS mass spectrum (e.g., Lanz et al, 2007; Ulbrich et al, 2009) in an effort to resolve uncertainty regarding the sources and processes contributing to secondary organic aerosol (SOA), an aerosol component with potential implications for climate (IPCC, 2013) Many of these studies have focused on the application of factor analysis to the organic mass fraction in an attempt to deconvolve it into descriptive sub-components, namely a hydrocarbon-like organic aerosol (HOA) factor, and an oxygenated organic aerosol (OOA)

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