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    EURODELTA III exercise: An evaluation of air quality models’ capacity to reproduce the carbonaceous aerosol
    (Amsterdam : Elsevier, 2019) Mircea, Mihaela; Bessagnet, Bertrand; D'Isidoro, Massimo; Pirovano, Guido; Aksoyoglu, Sebnem; Ciarelli, Giancarlo; Tsyro, Svetlana; Manders, Astrid; Bieser, Johannes; Stern, Rainer; Vivanco, Marta García; Cuvelier, Cornelius; Aas, Wenche; Prévôt, André S.H.; Aulinger, Armin; Briganti, Gino; Calori, Giuseppe; Cappelletti, Andrea; Colette, Augustin; Couvidat, Florian; Fagerli, Hilde; Finardi, Sandro; Kranenburg, Richard; Rouïl, Laurence; Silibello, Camillo; Spindler, Gerald; Poulain, Laurent; Herrmann, Hartmut; Jimenez, Jose L.; Day, Douglas A.; Tiitta, Petri; Carbone, Samara
    The carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-art in modelling carbonaceous aerosol over Europe by comparing simulations performed with seven chemical transport models (CTMs) currently in air quality assessments in Europe: CAMx, CHIMERE, CMAQ, EMEP/MSC-W, LOTOS-EUROS, MINNI and RCGC. The simulations were carried out in the framework of the EURODELTA III modelling exercise and were evaluated against field measurements from intensive campaigns of European Monitoring and Evaluation Programme (EMEP) and the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Model simulations were performed over the same domain, using as much as possible the same input data and covering four seasons: summer (1–30 June 2006), winter (8 January – 4 February 2007), autumn (17 September- 15 October 2008) and spring (25 February - 26 March 2009). The analyses of models’ performances in prediction of elemental carbon (EC) for the four seasons and organic aerosol components (OA) for the last two seasons show that all models generally underestimate the measured concentrations. The maximum underestimation of EC is about 60% and up to about 80% for total organic matter (TOM). The underestimation of TOM outside of highly polluted area is a consequence of an underestimation of secondary organic aerosol (SOA), in particular of its main contributor: biogenic secondary aerosol (BSOA). This result is independent on the SOA modelling approach used and season. The concentrations and daily cycles of total primary organic matter (TPOM) are generally better reproduced by the models since they used the same anthropogenic emissions. However, the combination of emissions and model formulation leads to overestimate TPOM concentrations in 2009 for most of the models. All models capture relatively well the SOA daily cycles at rural stations mainly due to the spatial resolution used in the simulations. For the investigated carbonaceous aerosol compounds, the differences between the concentrations simulated by different models are lower than the differences between the concentrations simulated with a model for different seasons. © 2019 The Authors
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    The EMEP Intensive Measurement Period campaign, 2008-2009: Characterizing carbonaceous aerosol at nine rural sites in Europe
    (Katlenburg-Lindau : EGU, 2019) Yttri, Karl Espen; Simpson, David; Bergström, Robert; Kiss, Gyula; Szidat, Sönke; Ceburnis, Darius; Eckhardt, Sabine; Hueglin, Christoph; Nøjgaard, Jacob Klenø; Perrino, Cinzia; Pisso, Ignazio; Prevot, Andre Stephan Henry; Putaud, Jean-Philippe; Spindler, Gerald; Vana, Milan; Zhang, Yan-Lin; Aas, Wenche
    Carbonaceous aerosol (total carbon, TCp) was source apportioned at nine European rural background sites, as part of the European Measurement and Evaluation Programme (EMEP) Intensive Measurement Periods in fall 2008 and winter/spring 2009. Five predefined fractions were apportioned based on ambient measurements: elemental and organic carbon, from combustion of biomass (ECbb and OCbb) and from fossil-fuel (ECff and OCff) sources, and remaining non-fossil organic carbon (OCrnf), dominated by natural sources.OCrnf made a larger contribution to TCp than anthropogenic sources (ECbb, OCbb, ECff, and OCff) at four out of nine sites in fall, reflecting the vegetative season, whereas anthropogenic sources dominated at all but one site in winter/spring. Biomass burning (OCbb + ECbb) was the major anthropogenic source at the central European sites in fall, whereas fossil-fuel (OCff + ECff) sources dominated at the southernmost and the two northernmost sites. Residential wood burning emissions explained 30 %-50 % of TCp at most sites in the first week of sampling in fall, showing that this source can be the dominant one, even outside the heating season. In winter/spring, biomass burning was the major anthropogenic source at all but two sites, reflecting increased residential wood burning emissions in the heating season. Fossil-fuel sources dominated EC at all sites in fall, whereas there was a shift towards biomass burning for the southernmost sites in winter/spring.Model calculations based on base-case emissions (mainly officially reported national emissions) strongly underpredicted observational derived levels of OCbb and ECbb outside Scandinavia. Emissions based on a consistent bottom-up inventory for residential wood burning (and including intermediate volatility compounds, IVOCs) improved model results compared to the base-case emissions, but modeled levels were still substantially underestimated compared to observational derived OCbb and ECbb levels at the southernmost sites.Our study shows that natural sources are a major contributor to carbonaceous aerosol in Europe, even in fall and in winter/spring, and that residential wood burning emissions are equally as large as or larger than that of fossil-fuel sources, depending on season and region. The poorly constrained residential wood burning emissions for large parts of Europe show the obvious need to improve emission inventories, with harmonization of emission factors between countries likely being the most important step to improve model calculations for biomass burning emissions, and European PM2.5 concentrations in general. © Author(s) 2019.