Cloud condensation nuclei in polluted air and biomass burning smoke near the mega-city Guangzhou, China – Part 2: Size-resolved aerosol chemical composition, diurnal cycles, and externally mixed weakly CCN-active soot particles

Abstract. Size-resolved chemical composition, mixing state, and cloud condensation nucleus (CCN) activity of aerosol particles in polluted mega-city air and biomass burning smoke were measured during the PRIDE-PRD2006 campaign near Guangzhou, China, using an aerosol mass spectrometer (AMS), a volatility tandem differential mobility analyzer (VTDMA), and a continuous-flow CCN counter (DMT-CCNC).

The size-dependence and temporal variations of the effective average hygroscopicity parameter for CCN-active particles (κ_a) could be parameterized as a function of organic and inorganic mass fractions (f_org, f_inorg) determined by the AMS: κ_a,p=κ_org·f_org + κ_inorg·f_inorg. The characteristic κ values of organic and inorganic components were similar to those observed in other continental regions of the world: κ_org≈0.1 and κ_inorg≈0.6. The campaign average κ_a values increased with particle size from ~0.25 at ~50 nm to ~0.4 at ~200 nm, while f_org decreased with particle size. At ~50 nm, f_org was on average 60% and increased to almost 100% during a biomass burning event.

The VTDMA results and complementary aerosol optical data suggest that the large fractions of CCN-inactive particles observed at low supersaturations (up to 60% at S≤0.27%) were externally mixed weakly CCN-active soot particles with low volatility (diameter reduction <5% at 300 °C) and effective hygroscopicity parameters around κ_LV≈0.01. A proxy for the effective average hygroscopicity of the total ensemble of CCN-active particles including weakly CCN-active particles (κ_t) could be parameterized as a function of κ_a,p and the number fraction of low volatility particles determined by VTDMA (φ_LV): κ_t,p=κ_a,p−φ_LV·(κ_a,p−κ_LV).

Based on κ values derived from AMS and VTDMA data, the observed CCN number concentrations (N_CCN,S≈10²–10⁴ cm⁻³ at S = 0.068–0.47%) could be efficiently predicted from the measured particle number size distribution. The mean relative deviations between observed and predicted CCN concentrations were ~10% when using κ_t,p, and they increased to ~20% when using only κ_a,p. The mean relative deviations were not higher (~20%) when using an approximate continental average value of κ≈0.3, although the constant κ value cannot account for the observed temporal variations in particle composition and mixing state (diurnal cycles and biomass burning events).

Overall, the results confirm that on a global and climate modeling scale an average value of κ≈0.3 can be used for approximate predictions of CCN number concentrations in continental boundary layer air when aerosol size distribution data are available without information about chemical composition. Bulk or size-resolved data on aerosol chemical composition enable improved CCN predictions resolving regional and temporal variations, but the composition data need to be highly accurate and complemented by information about particle mixing state to achieve high precision (relative deviations <20%).