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Author: Birmili, W. × Author: Hamed, A. × DDC: 550 × Subject: numerical model ×

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    Explaining global surface aerosol number concentrations in terms of primary emissions and particle formation
    (München : European Geopyhsical Union, 2010) Spracklen, D.V.; Carslaw, K.S.; Merikanto, J.; Mann, G.W.; Reddington, C.L.; Pickering, S.; Ogren, J.A.; Andrews, E.; Baltensperger, U.; Weingartner, E.; Boy, M.; Kulmala, M.; Laakso, L.; Lihavainen, H.; Kivekäs, N.; Komppula, M.; Mihalopoulos, N.; Kouvarakis, G.; Jennings, S.G.; O'Dowd, C.; Birmili, W.; Wiedensohler, A.; Weller, R.; Gras, J.; Laj, P.; Sellegri, K.; Bonn, B.; Krejci, R.; Laaksonen, A.; Hamed, A.; Minikin, A.; Harrison, R.M.; Talbot, R.; Sun, J.
    We synthesised observations of total particle number (CN) concentration from 36 sites around the world. We found that annual mean CN concentrations are typically 300–2000 cm−3 in the marine boundary layer and free troposphere (FT) and 1000–10 000 cm−3 in the continental boundary layer (BL). Many sites exhibit pronounced seasonality with summer time concentrations a factor of 2–10 greater than wintertime concentrations. We used these CN observations to evaluate primary and secondary sources of particle number in a global aerosol microphysics model. We found that emissions of primary particles can reasonably reproduce the spatial pattern of observed CN concentration (R2=0.46) but fail to explain the observed seasonal cycle (R2=0.1). The modeled CN concentration in the FT was biased low (normalised mean bias, NMB=−88%) unless a secondary source of particles was included, for example from binary homogeneous nucleation of sulfuric acid and water (NMB=−25%). Simulated CN concentrations in the continental BL were also biased low (NMB=−74%) unless the number emission of anthropogenic primary particles was increased or a mechanism that results in particle formation in the BL was included. We ran a number of simulations where we included an empirical BL nucleation mechanism either using the activation-type mechanism (nucleation rate, J, proportional to gas-phase sulfuric acid concentration to the power one) or kinetic-type mechanism (J proportional to sulfuric acid to the power two) with a range of nucleation coefficients. We found that the seasonal CN cycle observed at continental BL sites was better simulated by BL particle formation (R2=0.3) than by increasing the number emission from primary anthropogenic sources (R2=0.18). The nucleation constants that resulted in best overall match between model and observed CN concentrations were consistent with values derived in previous studies from detailed case studies at individual sites. In our model, kinetic and activation-type nucleation parameterizations gave similar agreement with observed monthly mean CN concentrations.
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    Meteorological and trace gas factors affecting the number concentration of atmospheric Aitken (DP Combining double low line 50 nm) particles in the continental boundary layer: Parameterization using a multivariate mixed effects model
    (München : European Geopyhsical Union, 2011) Mikkonen, S.; Korhonen, H.; Romakkaniemi, S.; Smith, J.N.; Joutsensaari, J.; Lehtinen, K.E.J.; Hamed, A.; Breider, T.J.; Birmili, W.; Spindler, G.; Plass-Duelmer, C.; Facchini, M.C.; Laaksonen, A.
    Measurements of aerosol size distribution and different gas and meteorological parameters, made in three polluted sites in Central and Southern Europe: Po Valley, Italy, Melpitz and Hohenpeissenberg in Germany, were analysed for this study to examine which of the meteorological and trace gas variables affect the number concentration of Aitken (Dp= 50 nm) particles. The aim of our study was to predict the number concentration of 50 nm particles by a combination of in-situ meteorological and gas phase parameters. The statistical model needs to describe, amongst others, the factors affecting the growth of newly formed aerosol particles (below 10 nm) to 50 nm size, but also sources of direct particle emissions in that size range. As the analysis method we used multivariate nonlinear mixed effects model. Hourly averages of gas and meteorological parameters measured at the stations were used as predictor variables; the best predictive model was attained with a combination of relative humidity, new particle formation event probability, temperature, condensation sink and concentrations of SO2, NO2 and ozone. The seasonal variation was also taken into account in the mixed model structure. Model simulations with the Global Model of Aerosol Processes (GLOMAP) indicate that the parameterization can be used as a part of a larger atmospheric model to predict the concentration of climatically active particles. As an additional benefit, the introduced model framework is, in theory, applicable for any kind of measured aerosol parameter.