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- ItemOrganic 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.
- ItemPrimary and secondary organic aerosol origin by combined gas-particle phase source apportionment(München : European Geopyhsical Union, 2013) Crippa, M.; Canonaco, F.; Slowik, J.G.; El Haddad, I.; DeCarlo, P.F.; Mohr, C.; Heringa, M.F.; Chirico, R.; Marchand, N.; Temime-Roussel, B.; Abidi, E.; Poulain, L.; Wiedensohler, A.; Baltensperger, U.; Prévôt, A.S.H.Secondary organic aerosol (SOA), a prominent fraction of particulate organic mass (OA), remains poorly constrained. Its formation involves several unknown precursors, formation and evolution pathways and multiple natural and anthropogenic sources. Here a combined gas-particle phase source apportionment is applied to wintertime and summertime data collected in the megacity of Paris in order to investigate SOA origin during both seasons. This was possible by combining the information provided by an aerosol mass spectrometer (AMS) and a proton transfer reaction mass spectrometer (PTR-MS). A better constrained apportionment of primary OA (POA) sources is also achieved using this methodology, making use of gas-phase tracers. These tracers made possible the discrimination between biogenic and continental/anthropogenic sources of SOA. We found that continental SOA was dominant during both seasons (24–50% of total OA), while contributions from photochemistry-driven SOA (9% of total OA) and marine emissions (13% of total OA) were also observed during summertime. A semi-volatile nighttime component was also identified (up to 18% of total OA during wintertime). This approach was successfully applied here and implemented in a new source apportionment toolkit.
- ItemOrganic 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.
- ItemWintertime aerosol chemical composition and source apportionment of the organic fraction in the metropolitan area of Paris(München : European Geopyhsical Union, 2013) Crippa, M.; DeCarlo, P.F.; Slowik, J.G.; Mohr, C.; Heringa, M.F.; Chirico, R.; Poulain, L.; Freutel, F.; Sciare, J.; Cozic, J.; Di Marco, C.F.; Elsasser, M.; Nicolas, B.; Marchand, N.; Abidi, E.; Wiedensohler, A.; Drewnick, F.; Schneider, J.; Borrmann, S.; Nemitz, E.; Zimmermann, R.; Jaffrezo, J.-L.; Prévôt, A.S.H.; Baltensperger, U.The effect of a post-industrial megacity on local and regional air quality was assessed via a month-long field measurement campaign in the Paris metropolitan area during winter 2010. Here we present source apportionment results from three aerosol mass spectrometers and two aethalometers deployed at three measurement stations within the Paris region. Submicron aerosol composition is dominated by the organic fraction (30–36%) and nitrate (28–29%), with lower contributions from sulfate (14–16%), ammonium (12–14%) and black carbon (7–13%). Organic source apportionment was performed using positive matrix factorization, resulting in a set of organic factors corresponding both to primary emission sources and secondary production. The dominant primary sources are traffic (11–15% of organic mass), biomass burning (13–15%) and cooking (up to 35% during meal hours). Secondary organic aerosol contributes more than 50% to the total organic mass and includes a highly oxidized factor from indeterminate and/or diverse sources and a less oxidized factor related to wood burning emissions. Black carbon was apportioned to traffic and wood burning sources using a model based on wavelength-dependent light absorption of these two combustion sources. The time series of organic and black carbon factors from related sources were strongly correlated. The similarities in aerosol composition, total mass and temporal variation between the three sites suggest that particulate pollution in Paris is dominated by regional factors, and that the emissions from Paris itself have a relatively low impact on its surroundings.