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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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    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 %.