Primary and secondary aerosols in Beijing in winter: Sources, variations and processes

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Abstract

Winter has the worst air pollution of the year in the megacity of Beijing. Despite extensive winter studies in recent years, our knowledge of the sources, formation mechanisms and evolution of aerosol particles is not complete. Here we have a comprehensive characterization of the sources, variations and processes of submicron aerosols that were measured by an Aerodyne high-resolution aerosol mass spectrometer from 17 December 2013 to 17 January 2014 along with offline filter analysis by gas chromatography/mass spectrometry. Our results suggest that submicron aerosols composition was generally similar across the winter of different years and was mainly composed of organics (60 %), sulfate (15 %) and nitrate (11 %). Positive matrix factorization of high- and unit-mass resolution spectra identified four primary organic aerosol (POA) factors from traffic, cooking, biomass burning (BBOA) and coal combustion (CCOA) emissions as well as two secondary OA (SOA) factors. POA dominated OA, on average accounting for 56 %, with CCOA being the largest contributor (20 %). Both CCOA and BBOA showed distinct polycyclic aromatic hydrocarbons (PAHs) spectral signatures, indicating that PAHs in winter were mainly from coal combustion (66 %) and biomass burning emissions (18 %). BBOA was highly correlated with levoglucosan, a tracer compound for biomass burning (r2 = 0.93), and made a considerable contribution to OA in winter (9 %). An aqueous-phase-processed SOA (aq-OOA) that was strongly correlated with particle liquid water content, sulfate and S-containing ions (e.g. CH2SO2+) was identified. On average aq-OOA contributed 12 % to the total OA and played a dominant role in increasing oxidation degrees of OA at high RH levels (> 50 %). Our results illustrate that aqueous-phase processing can enhance SOA production and oxidation states of OA as well in winter. Further episode analyses highlighted the significant impacts of meteorological parameters on aerosol composition, size distributions, oxidation states of OA and evolutionary processes of secondary aerosols.

Figures

  • Figure 1. Time series of (a) relative humidity (RH) and temperature (T ), (b) wind speed (WS) and wind direction (WD), (c) O3 and SO2, (d) CO and NOx , (e) mass concentrations of NR-PM1 species and (f) mass fractions of NR-PM1 species for the entire study period. In addition, five episodes with relatively high RH levels (E1–E5), five episodes with moderately high RH levels (M1–M5), and two clean periods (C1, C2) are marked for further discussion.
  • Figure 2. Average chemical composition of (a) organic aerosols and (b) NR-PM1 in the megacity of Beijing measured by aerosol mass spectrometers. Also shown in panel (a) is the oxygen-to-carbon (O / C) ratio of organic aerosol for each study. The O / C was calculated using the A-A method (Aiken et al., 2008). A more detailed description of the data is presented in Table S1.
  • Figure 3. (a) Variations of SO4/ NO3 ratios as a function of RH, (b) size-resolved SO4/ NO3 ratio during five episodes (E1–E5) with high RH levels (> 40 %) and five episodes (M1–M5) with low RH levels (< 40 %).
  • Figure 4. Average diurnal cycles of (a) NR-PM1 species and (b) NR-PM1 species/1CO, panels (c) and (d) show the average mass size distributions of NR-PM1 species. The pie chart in panel (d) shows the average chemical composition of NR-PM1 for the entire study period.
  • Figure 5. Time series of (a) H / C and (b) O / C ratios, (c) average diurnal cycles of O / C and H / C. Also shown are the average diurnal cycles of elemental ratios by excluding the contribution of cooking organics aerosol and (d) Van Krevelen diagram of H / C vs. O / C. The RH colour-coded triangle and circle points represent the data with the contributions of aq-OOA and COA being larger than 20 and 40 %, respectively.
  • Figure 6. Variations of (a) O / C and OA, (b) mass fractions of POA, SOA and aq-OOA as a function of RH. The data points are grouped in RH bins (5 % increment).
  • Figure 7. Left panel: high resolution mass spectra of six OA factors. Right panel: unit mass resolution spectra (m/z 120–350) of six OA factors.
  • Figure 8. Correlations between six OA factors and HRMS ions that are segregated into five categories (CxH+y , CxHyO+, CxHyO + 2 , CxHyN+p and CxHyOzS + q ).

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APA

Sun, Y., Du, W., Fu, P., Wang, Q., Li, J., Ge, X., … Wang, Z. (2016). Primary and secondary aerosols in Beijing in winter: Sources, variations and processes. Atmospheric Chemistry and Physics, 16(13), 8309–8329. https://doi.org/10.5194/acp-16-8309-2016

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