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- ItemPrimary versus secondary contributions to particle number concentrations in the European boundary layer(München : European Geopyhsical Union, 2011) Reddington, C.L.; Carslaw, K.S.; Spracklen, D.V.; Frontoso, M.G.; Collins, L.; Merikanto, J.; Minikin, A.; Hamburger, T.; Coe, H.; Kulmala, M.; Aalto, P.; Flentje, H.; Plass-Dülmer, C.; Birmili, W.; Wiedensohler, A.; Wehner, B.; Tuch, T.; Sonntag, A.; O'Dowd, C.D.; Jennings, S.G.; Dupuy, R.; Baltensperger, U.; Weingartner, E.; Hansson, H.-C.; Tunved, P.; Laj, P.; Sellegri, K.; Boulon, J.; Putaud, J.-P.; Gruening, C.; Swietlicki, E.; Roldin, P.; Henzing, J.S.; Moerman, M.; Mihalopoulos, N.; Kouvarakis, G.; Ždímal, V.; Zíková, N.; Marinoni, A.; Bonasoni, P.; Duchi, R.It is important to understand the relative contribution of primary and secondary particles to regional and global aerosol so that models can attribute aerosol radiative forcing to different sources. In large-scale models, there is considerable uncertainty associated with treatments of particle formation (nucleation) in the boundary layer (BL) and in the size distribution of emitted primary particles, leading to uncertainties in predicted cloud condensation nuclei (CCN) concentrations. Here we quantify how primary particle emissions and secondary particle formation influence size-resolved particle number concentrations in the BL using a global aerosol microphysics model and aircraft and ground site observations made during the May 2008 campaign of the European Integrated Project on Aerosol Cloud Climate Air Quality Interactions (EUCAARI). We tested four different parameterisations for BL nucleation and two assumptions for the emission size distribution of anthropogenic and wildfire carbonaceous particles. When we emit carbonaceous particles at small sizes (as recommended by the Aerosol Intercomparison project, AEROCOM), the spatial distributions of campaign-mean number concentrations of particles with diameter >50 nm (N50) and >100 nm (N100) were well captured by the model (R2≥0.8) and the normalised mean bias (NMB) was also small (−18% for N50 and −1% for N100). Emission of carbonaceous particles at larger sizes, which we consider to be more realistic for low spatial resolution global models, results in equally good correlation but larger bias (R2≥0.8, NMB = −52% and −29%), which could be partly but not entirely compensated by BL nucleation. Within the uncertainty of the observations and accounting for the uncertainty in the size of emitted primary particles, BL nucleation makes a statistically significant contribution to CCN-sized particles at less than a quarter of the ground sites. Our results show that a major source of uncertainty in CCN-sized particles in polluted European air is the emitted size of primary carbonaceous particles. New information is required not just from direct observations, but also to determine the "effective emission size" and composition of primary particles appropriate for different resolution models.
- ItemCloud 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(München : European Geopyhsical Union, 2011) Rose, D.; Gunthe, S.S.; Su, H.; Garland, R.M.; Yang, H.; Berghof, M.; Cheng, Y.F.; Wehner, B.; Achtert, P.; Nowak, A.; Wiedensohler, A.; Takegawa, N.; Kondo, Y.; Hu, M.; Zhang, Y.; Andreae, M.O.; Pöschl, U.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%).