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Now showing 1 - 7 of 7
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    Organic aerosol components derived from 25 AMS data sets across Europe using a consistent ME-2 based source apportionment approach
    (München : European Geopyhsical Union, 2014) Crippa, M.; Canonaco, F.; Lanz, V.A.; Äijälä, M.; Allan, J.D.; Carbone, S.; Capes, G.; Ceburnis, D.; Dall'Osto, M.; Day, D.A.; DeCarlo, P.F.; Ehn, M.; Eriksson, A.; Freney, E.; Hildebrandt Ruiz, L.; Hillamo, R.; Jimenez, J.L.; Junninen, H.; Kiendler-Scharr, A.; Kortelainen, A.-M.; Kulmala, M.; Laaksonen, A.; Mensah, A.A.; Mohr, C.; Nemitz, E.; O'Dowd, C.; Ovadnevaite, J.; Pandis, S.N.; Petäjä, T.; Poulain, L.; Saarikoski, S.; Sellegri, K.; Swietlicki, E.; Tiitta, P.; Worsnop, D.R.; Baltensperger, U.; Prévôt, A.S.H.
    Organic aerosols (OA) represent one of the major constituents of submicron particulate matter (PM1) and comprise a huge variety of compounds emitted by different sources. Three intensive measurement field campaigns to investigate the aerosol chemical composition all over Europe were carried out within the framework of the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI) and the intensive campaigns of European Monitoring and Evaluation Programme (EMEP) during 2008 (May–June and September–October) and 2009 (February–March). In this paper we focus on the identification of the main organic aerosol sources and we define a standardized methodology to perform source apportionment using positive matrix factorization (PMF) with the multilinear engine (ME-2) on Aerodyne aerosol mass spectrometer (AMS) data. Our source apportionment procedure is tested and applied on 25 data sets accounting for two urban, several rural and remote and two high altitude sites; therefore it is likely suitable for the treatment of AMS-related ambient data sets. For most of the sites, four organic components are retrieved, improving significantly previous source apportionment results where only a separation in primary and secondary OA sources was possible. Generally, our solutions include two primary OA sources, i.e. hydrocarbon-like OA (HOA) and biomass burning OA (BBOA) and two secondary OA components, i.e. semi-volatile oxygenated OA (SV-OOA) and low-volatility oxygenated OA (LV-OOA). For specific sites cooking-related (COA) and marine-related sources (MSA) are also separated. Finally, our work provides a large overview of organic aerosol sources in Europe and an interesting set of highly time resolved data for modeling purposes.
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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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    Simulating ultrafine particle formation in Europe using a regional CTM: Contribution of primary emissions versus secondary formation to aerosol number concentrations
    (München : European Geopyhsical Union, 2012) Fountoukis, C.; Riipinen, I.; Denier van der Gon, H.A.C.; Charalampidis, P.E.; Pilinis, C.; Wiedensohler, A.; O'Dowd, C.; Putaud, J.P.; Moerman, M.; Pandis, S.N.
    A three-dimensional regional chemical transport model (CTM) with detailed aerosol microphysics, PMCAMx-UF, was applied to the European domain to simulate the contribution of direct emissions and secondary formation to total particle number concentrations during May 2008. PMCAMx-UF uses the Dynamic Model for Aerosol Nucleation and the Two-Moment Aerosol Sectional (TOMAS) algorithm to track both aerosol number and mass concentration using a sectional approach. The model predicts nucleation events that occur over scales of hundreds up to thousands of kilometers especially over the Balkans and Southeast Europe. The model predictions were compared against measurements from 7 sites across Europe. The model reproduces more than 70% of the hourly concentrations of particles larger than 10 nm (N10) within a factor of 2. About half of these particles are predicted to originate from nucleation in the lower troposphere. Regional nucleation is predicted to increase the total particle number concentration by approximately a factor of 3. For particles larger than 100 nm the effect varies from an increase of 20% in the eastern Mediterranean to a decrease of 20% in southern Spain and Portugal resulting in a small average increase of around 1% over the whole domain. Nucleation has a significant effect in the predicted N50 levels (up to a factor of 2 increase) mainly in areas where there are condensable vapors to grow the particles to larger sizes. A semi-empirical ternary sulfuric acid-ammonia-water parameterization performs better than the activation or the kinetic parameterizations in reproducing the observations. Reducing emissions of ammonia and sulfur dioxide affects certain parts of the number size distribution.
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    Evaluation of a three-dimensional chemical transport model (PMCAMx) in the European domain during the EUCAARI May 2008 campaign
    (München : European Geopyhsical Union, 2011) Fountoukis, C.; Racherla, P.N.; Denier van der Gon, H.A.C.; Polymeneas, P.; Charalampidis, P.E.; Pilinis, C.; Wiedensohler, A.; Dall'Osto, M.; O'Dowd, C.; Pandis, S.N.
    Sea salt aerosol can significantly affect the air quality. Sea salt can cause enhanced concentrations of particulate matter and change particle chemical composition, in particular in coastal areas, and therefore should be accounted for in air quality modelling. We have used an EMEP Unified model to calculate sea salt concentrations and depositions over Europe, focusing on studying the effects of uncertainties in sea salt production and lifetime on calculation results. Model calculations of sea salt have been compared with EMEP observations of sodium concentrations in air and precipitation for a four year period, from 2004 to 2007, including size (fine/coarse) resolved EMEP intensive measurements in 2006 and 2007. In the presented calculations, sodium air concentrations are between 8% and 46% overestimated, whereas concentrations in precipitation are systematically underestimated by 65–70% for years 2004–2007. A series of model tests have been performed to investigate the reasons for this underestimation, but further studies are needed. The model is found to reproduce the spatial distribution of Na+ in air and precipitation over Europe fairly well, and to capture most of sea salt episodes. The paper presents the main findings from a series of tests in which we compare several different sea spray source functions and also look at the effects of meteorological input and the efficiency of removal processes on calculated sea salt concentrations. Finally, sea salt calculations with the EMEP model have been compared with results from the SILAM model and observations for 2007. While the models produce quite close results for Na+ at the majority of 26 measurement sites, discrepancies in terms of bias and temporal correlation are also found. Those differences are believed to occur due to differences in the representation of source function and size distribution of sea salt aerosol, different meteorology used for model runs and the different models' resolution. This study contributes to getting a better insight on uncertainties associated with sea salt calculations and thus facilitates further improvement of aerosol modelling on both regional and global scales.
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    General overview: European Integrated project on Aerosol Cloud Climate and Air Quality interactions (EUCAARI) – integrating aerosol research from nano to global scales
    (München : European Geopyhsical Union, 2011) Kulmala, M.; Asmi, A.; Lappalainen, H.K.; Carslaw, K.S.; Pöschl, U.; Baltensperger, U.; Hov, Ø.; Brenquier, J.-L.; Pandis, S.N.; Facchini, M.C.; Hansson, H.-C.; Wiedensohler, A.; O'Dowd, C.D.; Boers, R.; Boucher, O.; de Leeuw, G.; Denier van der Gon, H.A.C.; Feichter, J.; Krejci, R.; Laj, P.; Lihavainen, H.; Lohmann, U.; McFiggans, G.; Mentel, T.; Pilinis, C.; Riipinen, I.; Schulz, M.; Stohl, A.; Swietlicki, E.; Vignati, E.; Alves, C.; Amann, M.; Ammann, M.; Arabas, S.; Artaxo, P.; Baars, H.; Beddows, D.C.S.; Bergström, R.; Beukes, J.P.; Bilde, M.; Burkhart, J.F.; Canonaco, F.; Clegg, S.L.; Coe, H.; Crumeyrolle, S.; D'Anna, B.; Decesari, S.; Gilardoni, S.; Fischer, M.; Fjaeraa, A.M.; Fountoukis, C.; George, C.; Gomes, L.; Halloran, P.; Hamburger, T.; Harrison, R.M.; Herrmann, H.; Hoffmann, T.; Hoose, C.; Hu, M.; Hyvärinen, A.; Hõrrak, U.; Iinuma, Y.; Iversen, T.; Josipovic, M.; Kanakidou, M.; Kiendler-Scharr, A.; Kirkevåg, A.; Kiss, G.; Klimont, Z.; Kolmonen, P.; Komppula, M.; Kristjánsson, J.-E.; Laakso, L.; Laaksonen, A.; Labonnote, L.; Lanz, V.A.; Lehtinen, K.E.J.; Rizzo, L.V.; Makkonen, R.; Manninen, H.E.; McMeeking, G.; Merikanto, J.; Minikin, A.; Mirme, S.; Morgan, W.T.; Nemitz, E.; O'Donnell, D.; Panwar, T.S.; Pawlowska, H.; Petzold, A.; Pienaar, J.J.; Pio, C.; Plass-Duelmer, C.; Prévôt, A.S.H.; Pryor, S.; Reddington, C.L.; Roberts, G.; Rosenfeld, D.; Schwarz, J.; Seland, Ø.; Sellegri, K.; Shen, X.J.; Shiraiwa, M.; Siebert, H.; Sierau, B.; Simpson, D.; Sun, J.Y.; Topping, D.; Tunved, P.; Vaattovaara, P.; Vakkari, V.; Veefkind, J.P.; Visschedijk, A.; Vuollekoski, H.; Vuolo, R.; Wehner, B.; Wildt, J.; Woodward, S.; Worsnop, D.R.; van Zadelhoff, G.-J.; Zardini, A.A.; Zhang, K.; van Zyl, P.G.; Kerminen, V.-M.
    In this paper we describe and summarize the main achievements of the European Aerosol Cloud Climate and Air Quality Interactions project (EUCAARI). EUCAARI started on 1 January 2007 and ended on 31 December 2010 leaving a rich legacy including: (a) a comprehensive database with a year of observations of the physical, chemical and optical properties of aerosol particles over Europe, (b) comprehensive aerosol measurements in four developing countries, (c) a database of airborne measurements of aerosols and clouds over Europe during May 2008, (d) comprehensive modeling tools to study aerosol processes fron nano to global scale and their effects on climate and air quality. In addition a new Pan-European aerosol emissions inventory was developed and evaluated, a new cluster spectrometer was built and tested in the field and several new aerosol parameterizations and computations modules for chemical transport and global climate models were developed and evaluated. These achievements and related studies have substantially improved our understanding and reduced the uncertainties of aerosol radiative forcing and air quality-climate interactions. The EUCAARI results can be utilized in European and global environmental policy to assess the aerosol impacts and the corresponding abatement strategies.
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    Introduction: European Integrated Project on Aerosol Cloud Climate and Air Quality interactions (EUCAARI) – integrating aerosol research from nano to global scales
    (München : European Geopyhsical Union, 2009) Kulmala, M.; Asmi, A.; Lappalainen, H.K.; Carslaw, K.S.; Pöschl, U.; Baltensperger, U.; Hov, Ø.; Brenquier, J.-L.; Pandis, S.N.; Facchini, M.C.; Hansson, H.-C.; Wiedensohler, A.; O'Dowd, C.D.
    The European Aerosol Cloud Climate and Air Quality Interactions project EUCAARI is an EU Research Framework 6 integrated project focusing on understanding the interactions of climate and air pollution. EUCAARI works in an integrative and multidisciplinary way from nano- to global scale. EUCAARI brings together several leading European research groups, state-of-the-art infrastructure and some key scientists from third countries to investigate the role of aerosol on climate and air quality. Altogether 48 partners from 25 countries are participating in EUCAARI. During the first 16 months EUCAARI has built operational systems, e.g. established pan-European measurement network for Lagrangian studies and four stations in developing countries. Also an improved understanding of nanoscale processes (like nucleation) has been implemented in global models. Here we present the research methods, organisation, operations and first results of EUCAARI.
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    In situ formation and spatial variability of particle number concentration in a European megacity
    (München : European Geopyhsical Union, 2015) Pikridas, M.; Sciare, J.; Freutel, F.; Crumeyrolle, S.; von der Weiden-Reinmüller, S.-L.; Borbon, A.; Schwarzenboeck, A.; Merkel, M.; Crippa, M.; Kostenidou, E.; Psichoudaki, M.; Hildebrandt, L.; Engelhart, G.J.; Petäjä, T.; Prévôt, A.S.H.; Drewnick, F.; Baltensperger, U.; Wiedensohler, A.; Kulmala, M.; Beekmann, M.; Pandis, S.N.
    Ambient particle number size distributions were measured in Paris, France, during summer (1–31 July 2009) and winter (15 January to 15 February 2010) at three fixed ground sites and using two mobile laboratories and one airplane. The campaigns were part of the Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation (MEGAPOLI) project. New particle formation (NPF) was observed only during summer on approximately 50 % of the campaign days, assisted by the low condensation sink (about 10.7 ± 5.9 × 10−3 s−1). NPF events inside the Paris plume were also observed at 600 m altitude onboard an aircraft simultaneously with regional events identified on the ground. Increased particle number concentrations were measured aloft also outside of the Paris plume at the same altitude, and were attributed to NPF. The Paris plume was identified, based on increased particle number and black carbon concentration, up to 200 km away from the Paris center during summer. The number concentration of particles with diameters exceeding 2.5 nm measured on the surface at the Paris center was on average 6.9 ± 8.7 × 104 and 12.1 ± 8.6 × 104 cm−3 during summer and winter, respectively, and was found to decrease exponentially with distance from Paris. However, further than 30 km from the city center, the particle number concentration at the surface was similar during both campaigns. During summer, one suburban site in the NE was not significantly affected by Paris emissions due to higher background number concentrations, while the particle number concentration at the second suburban site in the SW increased by a factor of 3 when it was downwind of Paris.