Articles | Volume 16, issue 10
https://doi.org/10.5194/acp-16-6041-2016
https://doi.org/10.5194/acp-16-6041-2016
Research article
 | 
18 May 2016
Research article |  | 18 May 2016

Evaluation of the performance of four chemical transport models in predicting the aerosol chemical composition in Europe in 2005

Marje Prank, Mikhail Sofiev, Svetlana Tsyro, Carlijn Hendriks, Valiyaveetil Semeena, Xavier Vazhappilly Francis, Tim Butler, Hugo Denier van der Gon, Rainer Friedrich, Johannes Hendricks, Xin Kong, Mark Lawrence, Mattia Righi, Zissis Samaras, Robert Sausen, Jaakko Kukkonen, and Ranjeet Sokhi

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Cited articles

Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation: 2. Multiple aerosol types, J. Geophys. Res. Atmos., 105, 6837–6844, 2000.
Akagi, S. K., Yokelson, R. J., Wiedinmyer, C., Alvarado, M. J., Reid, J. S., Karl, T., Crounse, J. D., and Wennberg, P. O.: Emission factors for open and domestic biomass burning for use in atmospheric models, Atmos. Chem. Phys., 11, 4039–4072, https://doi.org/10.5194/acp-11-4039-2011, 2011.
Alastuey, A., Minguillón, M. C., Pérez, N., Querol, X., Viana, M. and Leeuw, F. De: PM 10 measurement methods and correction factors?: 2009 status report, available at: http://acm.eionet.europa.eu/reports/ETCACM_TP_2011_21_PM10Equivalence (last access: 12 May 2016), 2012.
Andreae, M. O. and Merlet, P.: Emission of trace gases and aerosols from biomass burning, Global Biogeochem. Cy., 15, 955–966, 2001.
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Short summary
Aerosol composition in Europe was simulated by four chemistry transport models and compared to observations to identify the most prominent areas for model improvement. Notable differences were found between the models' predictions, attributable to different treatment or omission of aerosol sources and processes. All models underestimated the observed concentrations by 10–60 %, mostly due to under-predicting the carbonaceous and mineral particles and omitting the aerosol-bound water.
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