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    Organic aerosol concentration and composition over Europe: Insights from comparison of regional model predictions with aerosol mass spectrometer factor analysis
    (München : European Geopyhsical Union, 2014) Fountoukis, C.; Megaritis, A.G.; Skyllakou, K.; Charalampidis, P.E.; Pilinis, C.; van der Gon, H.A.C. Denier; Crippa, M.; Canonaco, F.; Mohr, C.; Prévôt, A.S.H.; Allan, J.D.; Poulain, L.; Petäjä, T.; Tiitta, P.; Carbone, S.; Kiendler-Scharr, A.; Nemitz, E.; O'Dowd, C.; Swietlicki, E.; Pandis, S.N.
    A detailed three-dimensional regional chemical transport model (Particulate Matter Comprehensive Air Quality Model with Extensions, PMCAMx) was applied over Europe, focusing on the formation and chemical transformation of organic matter. Three periods representative of different seasons were simulated, corresponding to intensive field campaigns. An extensive set of AMS measurements was used to evaluate the model and, using factor-analysis results, gain more insight into the sources and transformations of organic aerosol (OA). Overall, the agreement between predictions and measurements for OA concentration is encouraging, with the model reproducing two-thirds of the data (daily average mass concentrations) within a factor of 2. Oxygenated OA (OOA) is predicted to contribute 93% to total OA during May, 87% during winter and 96% during autumn, with the rest consisting of fresh primary OA (POA). Predicted OOA concentrations compare well with the observed OOA values for all periods, with an average fractional error of 0.53 and a bias equal to −0.07 (mean error = 0.9 μg m−3, mean bias = −0.2 μg m−3). The model systematically underpredicts fresh POA at most sites during late spring and autumn (mean bias up to −0.8 μg m−3). Based on results from a source apportionment algorithm running in parallel with PMCAMx, most of the POA originates from biomass burning (fires and residential wood combustion), and therefore biomass burning OA is most likely underestimated in the emission inventory. The sensitivity of POA predictions to the corresponding emissions' volatility distribution is discussed. The model performs well at all sites when the Positive Matrix Factorization (PMF)-estimated low-volatility OOA is compared against the OA with saturation concentrations of the OA surrogate species C* ≤ 0.1 μg m−3 and semivolatile OOA against the OA with C* > 0.1 μg m−3.
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    Aerosol particle formation events and analysis of high growth rates observed above a subarctic wetland-forest mosaic
    (Milton Park : Taylor & Francis, 2017) Svenningsson, Birgitta; Arneth, Almut; Hayward, Sean; Holst, Thomas; Massling, Andreas; Swietlicki, Erik; Hirsikko, Anne; Junninen, Heikki; Riipinen, Ilona; Vana, Marko; Dal Maso, Miikka; Hussein, Tareq; Kulmala, Markku
    An analysis of particle formation (PF) events over a subarctic mire in northern Swedenwas performed, based on number– size distributions of atmospheric aerosol particles (10–500 nm in diameter) and ions (0.4–40 nm in Tammet diameter). We present classification statistics for PF events from measurements covering the period July 2005–September 2006, with a break over the winter period. The PF event frequency peaked during the summer months, in contrast to other Scandinavian sites where the frequency is highest during spring and autumn. Our analysis includes calculated growth rates and estimates of concentrations and production rates of condensing vapour, deduced from the growth rates and condensational sink calculations, using AIS and SMPS data. Particle formation events with high growth rates (up to 50 nm h-1) occurred repeatedly. In these cases, the newly formed nucleation mode particles were often only present for periods of a few hours. On several occasions, repeated particle formation events were observed within 1 d, with differences in onset time of a few hours. These high growth rates were only observed when the condensation sink was higher than 0.001 s-1.