Abstract
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 (κa) could be parameterized as a function of organic and inorganic mass fractions (forg, finorg) determined by the AMS: κa,p=κorg·forg + κinorg·finorg. The characteristic κ values of organic and inorganic components were similar to those observed in other continental regions of the world: κorg≈0.1 and κinorg≈0.6. The campaign average κa values increased with particle size from ~0.25 at ~50 nm to ~0.4 at ~200 nm, while forg decreased with particle size. At ~50 nm, forg 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 κLV≈0.01. A proxy for the effective average hygroscopicity of the total ensemble of CCN-active particles including weakly CCN-active particles (κt) could be parameterized as a function of κa,p and the number fraction of low volatility particles determined by VTDMA (φLV): κt,p=κa,p−φLV·(κa,p−κLV). Based on κ values derived from AMS and VTDMA data, the observed CCN number concentrations (NCCN,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 κt,p, and they increased to ~20% when using only κa,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%).
Highlights
In this study, which is a companion to Rose et al (2010a), we used data from aerosol mass spectrometry (AMS), volatility tandem differential mobility analyzer (VTDMA), and optical measurements to investigate and characterize the relationship between cloud condensation nuclei (CCN) activity, hygroscopicity, chemical composition, and mixing state of aerosol particles in mega-city air and biomass burning smoke
Two different hygroscopicity parameters were derived from the CCN measurements
The parameter κa characterizes the average hygroscopicity of the internally mixed CCNactive particles whereas the parameter κt is an approximate measure for the effective average hygroscopicity of the total ensemble of aerosol particles including internally mixed CCN-active as well as externally mixed weakly CCNactive particles. Both of these parameters were consistent with AMS and VTDMA measurement data
Summary
Atmospheric aerosol particles serving as cloud condensation nuclei (CCN) play an important role in the formation of clouds and precipitation, and influence atmospheric chemistry and physics, the hydrological cycle and climate (Pruppacher and Klett, 1997; Seinfeld and Pandis, 2006; Lohmann and Feichter, 2005; IPCC, 2007; Heintzenberg and Charlson, 2009).Substantial progress has been made in recent years in understanding the source processes that produce cloud-active aerosols, the properties that enable aerosols to act as CCN, the effects of aerosols on cloud physics and precipitation, and the consequences for the climate system (Andreae and Rosenfeld, 2008; Stevens and Feingold, 2009; Poschl et al, 2009, and references therein). The actual influence and relative importance of aerosol size distribution, chemical composition, and mixing state on the variability and predictability of CCN concentrations remained a subject of continued discussion (e.g., Broekhuizen et al, 2006; Dusek et al, 2006; Hudson, 2007; Cubison et al, 2008; Kuwata et al, 2008; Wang et al, 2008; Bougiatioti et al, 2009; Gunthe et al, 2009; Ervens et al, 2010; Juranyi et al, 2010; Rose et al, 2010a; Wex et al, 2010). Size-resolved measurements, long-term data sets, and uncertainty analyses of CCN modeling techniques are needed to resolve these issues
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