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    Primary 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.
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    Characteristics of regional new particle formation in urban and regional background environments in the North China Plain
    (München : European Geopyhsical Union, 2013) Wang, Z.B.; Hu, M.; Sun, J.Y.; Wu, Z.J.; Yue, D.L.; Shen, X.J.; Zhang, Y.M.; Pei, X.Y.; Cheng, Y.F.; Wiedensohler, A.
    Long-term measurements of particle number size distributions were carried out both at an urban background site (Peking University, PKU) and a regional Global Atmospheric Watch station (Shangdianzi, SDZ) from March to November in 2008. In total, 52 new particle formation (NPF) events were observed simultaneously at both sites, indicating that this is a regional phenomenon in the North China Plain. On average, the mean condensation sink value before the nucleation events started was 0.025 s−1 in the urban environment, which was 1.6 times higher than that at regional site. However, higher particle formation and growth rates were observed at PKU (10.8 cm−3 s−1 and 5.2 nm h−1) compared with those at SDZ (4.9 cm−3 s−1 and 4.0 nm h−1). These results implied that precursors were much more abundant in the polluted urban environment. Different from the observations in cleaner environments, the background conditions of the observed particle homogeneous nucleation events in the North China Plain could be characterized as the co-existing of a stronger source of precursor gases and a higher condensational sink of pre-existing aerosol particles. Secondary aerosol formation following nucleation events results in an increase of particle mass concentration, particle light scattering coefficient, and cloud condensation nuclei (CCN) number concentration, with consequences on visibility, radiative effects, and air quality. Typical regional NPF events with significant particle nucleation rates and subsequent particle growth over a sufficiently long time period at both sites were chosen to investigate the influence of NPF on the number concentration of "potential" CCN. As a result, the NPF and the subsequent condensable growth increased the CCN number concentration in the North China Plain by factors in the range from 5.6 to 8.7. Moreover, the potential contribution of anthropogenic emissions to the CCN number concentration was more than 50%, to which more attention should be drawn in regional and global climate modeling, especially in the polluted urban areas.
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    Aerosol hygroscopicity parameter derived from the light scattering enhancement factor measurements in the North China Plain
    (Göttingen : Copernicus, 2014) Chen, J.; Zhao, C.S.; Ma, N.; Yan, P.
    The relative humidity (RH) dependence of aerosol light scattering is an essential parameter for accurate estimation of the direct radiative forcing induced by aerosol particles. Because of insufficient information on aerosol hygroscopicity in climate models, a more detailed parameterization of hygroscopic growth factors and resulting optical properties with respect to location, time, sources, aerosol chemistry and meteorology are urgently required. In this paper, a retrieval method to calculate the aerosol hygroscopicity parameter, κ, is proposed based on the in situ measured aerosol light scattering enhancement factor, namely f(RH), and particle number size distribution (PNSD) obtained from the HaChi (Haze in China) campaign. Measurements show that f(RH) increases sharply with increasing RH, and that the time variance of f(RH) is much greater at higher RH. A sensitivity analysis reveals that the f(RH) is more sensitive to the aerosol hygroscopicity than PNSD. f(RH) for polluted cases is distinctly higher than that for clean periods at a specific RH. The derived equivalent κ, combined with the PNSD measurements, is applied in the prediction of the cloud condensation nuclei (CCN) number concentration. The predicted CCN number concentration with the derived equivalent κ agrees well with the measured ones, especially at high supersaturations. The proposed calculation algorithm of κ with the f(RH) measurements is demonstrated to be reasonable and can be widely applied.
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    Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories
    (Katlenburg-Lindau : EGU, 2018) Schmale, Julia; Henning, Silvia; Decesari, Stefano; Henzing, Bas; Keskinen, Helmi; Sellegri, Karine; Ovadnevaite, Jurgita; Pöhlker, Mira L.; Brito, Joel; Bougiatioti, Aikaterini; Kristensson, Adam; Kalivitis, Nikos; Stavroulas, Iasonas; Carbone, Samara; Jefferson, Anne; Park, Minsu; Schlag, Patrick; Iwamoto, Yoko; Aalto, Pasi; Äijälä, Mikko; Bukowiecki, Nicolas; Ehn, Mikael; Frank, Göran; Fröhlich, Roman; Frumau, Arnoud; Herrmann, Erik; Herrmann, Hartmut; Holzinger, Rupert; Kos, Gerard; Kulmala, Markku; Mihalopoulos, Nikolaos; Nenes, Athanasios; O'Dowd, Colin; Petäjä, Tuukka; Picard, David; Pöhlker, Christopher; Pöschl, Ulrich; Poulain, Laurent; Prévôt, André Stephan Henry; Swietlicki, Erik; Andreae, Meinrat O.; Artaxo, Paulo; Wiedensohler, Alfred; Ogren, John; Matsuki, Atsushi; Yum, Seong Soo; Stratmann, Frank; Baltensperger, Urs; Gysel, Martin
    Aerosol-cloud interactions (ACI) constitute the single largest uncertainty in anthropogenic radiative forcing. To reduce the uncertainties and gain more confidence in the simulation of ACI, models need to be evaluated against observations, in particular against measurements of cloud condensation nuclei (CCN). Here we present a data set - ready to be used for model validation - of long-term observations of CCN number concentrations, particle number size distributions and chemical composition from 12 sites on 3 continents. Studied environments include coastal background, rural background, alpine sites, remote forests and an urban surrounding. Expectedly, CCN characteristics are highly variable across site categories. However, they also vary within them, most strongly in the coastal background group, where CCN number concentrations can vary by up to a factor of 30 within one season. In terms of particle activation behaviour, most continental stations exhibit very similar activation ratios (relative to particles 20nm) across the range of 0.1 to 1.0% supersaturation. At the coastal sites the transition from particles being CCN inactive to becoming CCN active occurs over a wider range of the supersaturation spectrum. Several stations show strong seasonal cycles of CCN number concentrations and particle number size distributions, e.g. at Barrow (Arctic haze in spring), at the alpine stations (stronger influence of polluted boundary layer air masses in summer), the rain forest (wet and dry season) or Finokalia (wildfire influence in autumn). The rural background and urban sites exhibit relatively little variability throughout the year, while short-term variability can be high especially at the urban site. The average hygroscopicity parameter, calculated from the chemical composition of submicron particles was highest at the coastal site of Mace Head (0.6) and lowest at the rain forest station ATTO (0.2-0.3). We performed closure studies based on -Köhler theory to predict CCN number concentrations. The ratio of predicted to measured CCN concentrations is between 0.87 and 1.4 for five different types of . The temporal variability is also well captured, with Pearson correlation coefficients exceeding 0.87. Information on CCN number concentrations at many locations is important to better characterise ACI and their radiative forcing. But long-term comprehensive aerosol particle characterisations are labour intensive and costly. Hence, we recommend operating migrating-CCNCs to conduct collocated CCN number concentration and particle number size distribution measurements at individual locations throughout one year at least to derive a seasonally resolved hygroscopicity parameter. This way, CCN number concentrations can only be calculated based on continued particle number size distribution information and greater spatial coverage of long-term measurements can be achieved.
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    Detection and attribution of aerosol-cloud interactions in large-domain large-eddy simulations with the ICOsahedral Non-hydrostatic model
    (Katlenburg-Lindau : EGU, 2020) Costa-Surós, Montserrat; Sourdeval, Odran; Acquistapace, Claudia; Baars, Holger; Carbajal Henken, Cintia; Genz, Christa; Hesemann, Jonas; Jimenez, Cristofer; König, Marcel; Kretzschmar, Jan; Madenach, Nils; Meyer, Catrin I.; Schrödner, Roland; Seifert, Patric; Senf, Fabian; Brueck, Matthias; Cioni, Guido; Engels, Jan Frederik; Fieg, Kerstin; Gorges, Ksenia; Heinze, Rieke; Kumar Siligam, Pavan; Burkhardt, Ulrike; Crewell, Susanne; Hoose, Corinna; Seifert, Axel; Tegen, Ina; Quaas, Johannes
    Clouds and aerosols contribute the largest uncertainty to current estimates and interpretations of the Earth's changing energy budget. Here we use a new-generation large-domain large-eddy model, ICON-LEM (ICOsahedral Non-hydrostatic Large Eddy Model), to simulate the response of clouds to realistic anthropogenic perturbations in aerosols serving as cloud condensation nuclei (CCN). The novelty compared to previous studies is that (i) the LEM is run in weather prediction mode and with fully interactive land surface over a large domain and (ii) a large range of data from various sources are used for the detection and attribution. The aerosol perturbation was chosen as peak-aerosol conditions over Europe in 1985, with more than fivefold more sulfate than in 2013. Observational data from various satellite and ground-based remote sensing instruments are used, aiming at the detection and attribution of this response. The simulation was run for a selected day (2 May 2013) in which a large variety of cloud regimes was present over the selected domain of central Europe. It is first demonstrated that the aerosol fields used in the model are consistent with corresponding satellite aerosol optical depth retrievals for both 1985 (perturbed) and 2013 (reference) conditions. In comparison to retrievals from groundbased lidar for 2013, CCN profiles for the reference conditions were consistent with the observations, while the ones for the 1985 conditions were not. Similarly, the detection and attribution process was successful for droplet number concentrations: the ones simulated for the 2013 conditions were consistent with satellite as well as new ground-based lidar retrievals, while the ones for the 1985 conditions were outside the observational range. For other cloud quantities, including cloud fraction, liquid water path, cloud base altitude and cloud lifetime, the aerosol response was small compared to their natural vari ability. Also, large uncertainties in satellite and ground-based observations make the detection and attribution difficult for these quantities. An exception to this is the fact that at a large liquid water path value (LWP > 200 g m-2), the control simulation matches the observations, while the perturbed one shows an LWP which is too large. The model simulations allowed for quantifying the radiative forcing due to aerosol-cloud interactions, as well as the adjustments to this forcing. The latter were small compared to the variability and showed overall a small positive radiative effect. The overall effective radiative forcing (ERF) due to aerosol-cloud interactions (ERFaci) in the simulation was dominated thus by the Twomey effect and yielded for this day, region and aerosol perturbation-2:6 W m-2. Using general circulation models to scale this to a global-mean present-day vs. pre-industrial ERFaci yields a global ERFaci of-0:8 W m-2 © 2020 Author(s).