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Now showing 1 - 6 of 6
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    Primary 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.
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    Diurnal variations of ambient particulate wood burning emissions and their contribution to the concentration of Polycyclic Aromatic Hydrocarbons (PAHs) in Seiffen, Germany
    (München : European Geopyhsical Union, 2011) Poulain, L.; Iinuma, Y.; Müller, K.; Birmili, W.; Weinhold, K.; Brüggemann, E.; Gnauk, T.; Hausmann, A.; Löschau, G.; Wiedensohler, A.; Herrmann, H.
    Residential wood burning is becoming an increasingly important cause of air quality problems since it has become a popular source of alternative energy to fossil fuel. In order to characterize the contribution of residential wood burning to local particle pollution, a field campaign was organized at the village of Seiffen (Saxony, Germany). During this campaign, an Aerosol Mass Spectrometer (AMS) was deployed in parallel to a PM1 high volume filter sampler. The AMS mass spectra were analyzed using Positive Matrix Factorization (PMF) to obtain detailed information about the organic aerosol (OA). Biomass-burning organic aerosol (BBOA), Hydrocarbon-like organic aerosol (HOA), and Oxygenated Organic Aerosol (OOA) were identified and represented 20%, 17% and 62% of total OA, respectively. Additionally, Polycyclic Aromatic Hydrocarbons (PAH) were measured by the AMS with an average concentration of 10 ng m−3 and short term events of extremely high PAH concentration (up to 500 ng m−3) compared to the mean PAH value were observed during the whole measurement period. A comparison with the results from PM1 filter samples showed that the BBOA factor and the AMS PAH are good indicators of the total concentration of the different monosaccharide anhydrides and PAH measured on the filter samples. Based on its low correlation with CO and the low car traffic, the HOA factor was considered to be related to residential heating using liquid fuel. An influence of the time of the week (week vs. weekend) on the diurnal profiles of the different OA components was observed. The weekdays were characterized by two maxima; a first one early in the morning and a stronger one in the evening. During the weekend days, the different OA components principally reached only one maximum in the afternoon. Finally, the PAH emitted directly from residential wood combustion was estimated to represent 1.5% of the total mass of the BBOA factor and around 62% of the total PAH concentration measured at Seiffen. This result highlights the important contribution of residential wood combustion to air quality and PAH emissions at the sampling place, which might have a significant impact on human health. Moreover, it also emphasizes the need for a better time resolution of the chemical characterization of toxic particulate compounds in order to provide more information on variations of the different sources through the days as well as to better estimate the real human exposure.
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    ACTRIS ACSM intercomparison - Part 2: Intercomparison of ME-2 organic source apportionment results from 15 individual, co-located aerosol mass spectrometers
    (München : European Geopyhsical Union, 2015) Fröhlich, R.; Crenn, V.; Setyan, A.; Belis, C.A.; Canonaco, F.; Favez, O.; Riffault, V.; Slowik, J.G.; Aas, W.; Aijälä, M.; Alastuey, A.; Artiñano, B.; Bonnaire, N.; Bozzetti, C.; Bressi, M.; Carbone, C.; Coz, E.; Croteau, P.L.; Cubison, M.J.; Esser-Gietl, J.K.; Green, D.C.; Gros, V.; Heikkinen, L.; Herrmann, H.; Jayne, J.T.; Lunder, C.R.; Minguillón, M.C.; Močnik, G.; O'Dowd, C.D.; Ovadnevaite, J.; Petralia, E.; Poulain, L.; Priestman, M.; Ripoll, A.; Sarda-Estève, R.; Wiedensohler, A.; Baltensperger, U.; Sciare, J.; Prévôt, A.S.H.
    Chemically resolved atmospheric aerosol data sets from the largest intercomparison of the Aerodyne aerosol chemical speciation monitors (ACSMs) performed to date were collected at the French atmospheric supersite SIRTA. In total 13 quadrupole ACSMs (Q-ACSM) from the European ACTRIS ACSM network, one time-of-flight ACSM (ToF-ACSM), and one high-resolution ToF aerosol mass spectrometer (AMS) were operated in parallel for about 3 weeks in November and December~2013. Part 1 of this study reports on the accuracy and precision of the instruments for all the measured species. In this work we report on the intercomparison of organic components and the results from factor analysis source apportionment by positive matrix factorisation (PMF) utilising the multilinear engine 2 (ME-2). Except for the organic contribution of mass-to-charge ratio m/z 44 to the total organics (f44), which varied by factors between 0.6 and 1.3 compared to the mean, the peaks in the organic mass spectra were similar among instruments. The m/z 44 differences in the spectra resulted in a variable f44 in the source profiles extracted by ME-2, but had only a minor influence on the extracted mass contributions of the sources. The presented source apportionment yielded four factors for all 15 instruments: hydrocarbon-like organic aerosol (HOA), cooking-related organic aerosol (COA), biomass burning-related organic aerosol (BBOA) and secondary oxygenated organic aerosol (OOA). ME-2 boundary conditions (profile constraints) were optimised individually by means of correlation to external data in order to achieve equivalent / comparable solutions for all ACSM instruments and the results are discussed together with the investigation of the influence of alternative anchors (reference profiles). A comparison of the ME-2 source apportionment output of all 15 instruments resulted in relative standard deviations (SD) from the mean between 13.7 and 22.7 % of the source's average mass contribution depending on the factors (HOA: 14.3 ± 2.2 %, COA: 15.0 ± 3.4 %, OOA: 41.5 ± 5.7 %, BBOA: 29.3 ± 5.0 %). Factors which tend to be subject to minor factor mixing (in this case COA) have higher relative uncertainties than factors which are recognised more readily like the OOA. Averaged over all factors and instruments the relative first SD from the mean of a source extracted with ME-2 was 17.2 %.
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    Quantitative determination of carbonaceous particle mixing state in Paris using single-particle mass spectrometer and aerosol mass spectrometer measurements
    (München : European Geopyhsical Union, 2013) Healy, R.M.; Sciare, J.; Poulain, L.; Crippa, M.; Wiedensohler, A.; Prévôt, A.S.H.; Baltensperger, U.; Sarda-Estève, R.; McGuire, M.L.; Jeong, C.-H.; McGillicuddy, E.; O'Connor, I.P.; Sodeau, J.R.; Evans, G.J.; Wenger, J.C.
    Single-particle mixing state information can be a powerful tool for assessing the relative impact of local and regional sources of ambient particulate matter in urban environments. However, quantitative mixing state data are challenging to obtain using single-particle mass spectrometers. In this study, the quantitative chemical composition of carbonaceous single particles has been determined using an aerosol time-of-flight mass spectrometer (ATOFMS) as part of the MEGAPOLI 2010 winter campaign in Paris, France. Relative peak areas of marker ions for elemental carbon (EC), organic aerosol (OA), ammonium, nitrate, sulfate and potassium were compared with concurrent measurements from an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS), a thermal–optical OCEC analyser and a particle into liquid sampler coupled with ion chromatography (PILS-IC). ATOFMS-derived estimated mass concentrations reproduced the variability of these species well (R2 = 0.67–0.78), and 10 discrete mixing states for carbonaceous particles were identified and quantified. The chemical mixing state of HR-ToF-AMS organic aerosol factors, resolved using positive matrix factorisation, was also investigated through comparison with the ATOFMS dataset. The results indicate that hydrocarbon-like OA (HOA) detected in Paris is associated with two EC-rich mixing states which differ in their relative sulfate content, while fresh biomass burning OA (BBOA) is associated with two mixing states which differ significantly in their OA / EC ratios. Aged biomass burning OA (OOA2-BBOA) was found to be significantly internally mixed with nitrate, while secondary, oxidised OA (OOA) was associated with five particle mixing states, each exhibiting different relative secondary inorganic ion content. Externally mixed secondary organic aerosol was not observed. These findings demonstrate the range of primary and secondary organic aerosol mixing states in Paris. Examination of the temporal behaviour and chemical composition of the ATOFMS classes also enabled estimation of the relative contribution of transported emissions of each chemical species and total particle mass in the size range investigated. Only 22% of the total ATOFMS-derived particle mass was apportioned to fresh, local emissions, with 78% apportioned to regional/continental-scale emissions.
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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.