Characterization of anthropogenic organic aerosols by TOF-ACSM with the new capture vaporizer

Abstract

Abstract. A new capture vaporizer (CV) has been developed and used recently in the Aerodyne aerosol mass spectrometer (AMS) and aerosol chemical speciation monitor (ACSM) instead of the standard vaporizer (SV) to reduce the particle bounce. It is important to characterize the CV performance in different environments. In this study, we characterized specific organic aerosols (OAs) from vehicle, cooking, biomass burning, and coal burning emissions by a time-of-flight ACSM (TOF-ACSM) with the CV. Their corresponding marker ions that have been defined in the previous SV-based analysis are still valid in the CV mass spectra. Spectra of OAs from cooking and vehicle exhaust show similarities in distinct alkyl fragments but different ratios of m∕z 55 and 57. Ions related to polycyclic aromatic hydrocarbons are present in the OA spectra obtained from burning lignite and bituminous coal but not in the spectra obtained from burning anthracite. Although the relative intensities of m∕z 60 and 73 are much lower in the CV spectra than in the SV spectra for biomass burning OA, they are still relatively greater compared with the spectra for other sources. Our data suggest an atmospheric background of f60 of below 0.03 % for CV. Moreover, we deployed the CV TOF-ACSM along with a SV AMS in urban Beijing during the winter of 2017 to characterize ambient OA with strong anthropogenic influences. The CV TOF-ACSM shows a collection efficiency (CE) of about unity. The CV and SV data show consistent mass concentrations of sulfate, nitrate, ammonium, and OA. Six OA factors are identified by the positive matrix factorization (PMF) analysis for both the CV and the SV data. The SV and CV PMF factors show good correlations in mass concentrations. The SV and CV factors related to coal combustion and cooking differ significantly in loadings, explained by the PMF uncertainty and the lack of understanding of the relative ionization efficiency and CE for primary OA. The CV factors related to secondary sources show greater loadings than the SV factors, which may be associated with the changes in signal-to-noise ratios of various ions in the PMF analysis. Our results support improved mass quantification and useful source identification by the CV for ambient particles in the polluted urban environment. The difference in factor loadings between SV and CV should be considered when interpreting or comparing the PMF results among studies.

Mass spectral characterization of primary emissions and implications in source apportionment of organic aerosol

“…It is interesting to note that the CCOA spectrum in Beijing (Sun et al, 2016a) resembles more that of flaming combustion of bituminous coal, while that observed at Changdao island in central eastern China (Hu et al, 2013) shows more similarity to that of smoldering combustion of bituminous coal. This is consistent with the fact that the bituminous coal accounted for ∼ 78 % of the total coal production according to the China Coal Industry Yearbook (Zhou et al, 2016), yet the CCOA emissions can be different in different areas due to different combustion conditions. We also noticed that the signals of m/z's > 150 contribute approximately ∼ 40 % of the total signal of CCOA measured by SV-AMS (Fig.…”

Highly Oxygenated Organic Molecules Produced by the Oxidation of Benzene and Toluene in a Wide Range of OH Exposure and NO<sub>x</sub> Conditions

“…The SOA mass concentrations are measured by an Aerodyne long-time-of-flight soot-particle aerosol mass spectrometer (LTOF-SP-AMS) (Zheng et al, 2020).…”

Spatial variability of air pollutants in a megacity characterized by mobile measurements: Chemical homogeneity under haze conditions

“…The common OA factors related to biomass burning (BBOA) or coal burning (CCOA) were not resolved in this data set and were perhaps mixed with OOAs (Liao et al, 2021). Their contributions to OA were however expected to be small because of the stringent emission control in NCP (Zheng et al, 2020;Duan et al, 2020). VOCs and OVOCs were detected by an Ionicon proton transfer reaction-quadrupole ion guide time-of-flight mass spectrometer (PTR-QiTOF).…”

“…Gas pollutants were detected by gas analyzers including NO2 (Teledyne, T500U), NO-NOx (Ecotech, EC9841A), SO2 (Ecotech, EC9850A), CO (Ecotech, EC9830A), and O3 (Ecotech, EC9810A). The chemical composition of NR-PM2.5 was measured by an Aerodyne time-of-flight aerosol chemical speciation monitor (TOF-ACSM) with PM2.5 lens and a capture vaporizer (Zheng et al, 2020). The uncertainty for the mass concentrations of NR-PM2.5 and its components is about 30% (Canagaratna et al, 2007).…”