Analysis of secondary organic aerosol formation and aging using positive matrix factorization of high-resolution aerosol mass spectra: application to the dodecane low-NO<sub>x</sub> system

Abstract

Abstract. Positive matrix factorization (PMF) of highresolution laboratory chamber aerosol mass spectra is applied for the first time, the results of which are consistent with molecular level MOVI-HRToF-CIMS aerosolphase and CIMS gas-phase measurements. Secondary organic aerosol was generated by photooxidation of dodecane under low-NO x conditions in the Caltech environmental chamber. The PMF results exhibit three factors representing a combination of gas-particle partitioning, chemical conversion in the aerosol, and wall deposition. The slope of the measured high-resolution aerosol mass spectrometer (HRToF-AMS) composition data on a Van Krevelen diagram is consistent with that of other low-NO x alkane systems in the same O : C range. Elemental analysis of the PMF factor mass spectral profiles elucidates the combinations of functionality that contribute to the slope on the Van Krevelen diagram.

Peak-fitting and integration imprecision in the Aerodyne aerosol mass spectrometer: effects of mass accuracy on location-constrained fits

“…In particular, thermally generated ions such as K + (Drewnick et al, 2006;Corbin et al, 2015a) or other slowly evaporating species (Salcedo et al, 2010;Craven et al, 2012) may lead to additional uncertainties for this reason.…”

“…Craven et al (2012) discussed and addressed a number of HR-AMS uncertainties with regard to background signals and overlapping ions. Craven et al (2012) also developed a data-smoothing approach to evaluate data quality for PMF, rejecting noisy variables.…”

“…Craven et al (2012) discussed and addressed a number of HR-AMS uncertainties with regard to background signals and overlapping ions. Craven et al (2012) also developed a data-smoothing approach to evaluate data quality for PMF, rejecting noisy variables. Such an approach may remain useful for the very-slowly changing systems studied by Craven et al (2012), as it may account for imprecisions other than those caused by peak integration; however, it did not result in improved PMF uncertainty estimates but rather the selective rejection of low signal-to-noise variables.…”

“…Craven et al (2012) also developed a data-smoothing approach to evaluate data quality for PMF, rejecting noisy variables. Such an approach may remain useful for the very-slowly changing systems studied by Craven et al (2012), as it may account for imprecisions other than those caused by peak integration; however, it did not result in improved PMF uncertainty estimates but rather the selective rejection of low signal-to-noise variables. More generally, smoothing approaches cannot be applied to the rapidly changing signals observed during roadside studies, aircraft studies, or laboratory studies on rapidly changing sources, all of which may entail the measurement of the high PM loadings for which peak-integration uncertainties are most important.…”

Collection efficiency of <i>α</i>-pinene secondary organic aerosol particles explored via light-scattering single-particle aerosol mass spectrometry

“…It has enabled significant advances in our understanding of how organic aerosols form (Craven et al, 2012), age (Aiken et al, 2008), and mix (Robinson et al, 2013) by providing real-time measurements of size-resolved composition and mass for submicron, nonrefractory particulate matter (NR-PM 1 ). However, a lingering challenge with full quantification of NR-PM 1 in the AMS is the mass collection efficiency (CE m ; Canagaratna et al, 2007), which is the ratio of the measured AMS mass signal to the actual NR-PM 1 mass concentration.…”