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

Related authors

Multi-model ensemble simulations of olive pollen distribution in Europe in 2014: current status and outlook
Mikhail Sofiev, Olga Ritenberga, Roberto Albertini, Joaquim Arteta, Jordina Belmonte, Carmi Geller Bernstein, Maira Bonini, Sevcan Celenk, Athanasios Damialis, John Douros, Hendrik Elbern, Elmar Friese, Carmen Galan, Gilles Oliver, Ivana Hrga, Rostislav Kouznetsov, Kai Krajsek, Donat Magyar, Jonathan Parmentier, Matthieu Plu, Marje Prank, Lennart Robertson, Birthe Marie Steensen, Michel Thibaudon, Arjo Segers, Barbara Stepanovich, Alvaro M. Valdebenito, Julius Vira, and Despoina Vokou
Atmos. Chem. Phys., 17, 12341–12360, https://doi.org/10.5194/acp-17-12341-2017,https://doi.org/10.5194/acp-17-12341-2017, 2017
Short summary
Evaluation and error apportionment of an ensemble of atmospheric chemistry transport modeling systems: multivariable temporal and spatial breakdown
Efisio Solazzo, Roberto Bianconi, Christian Hogrefe, Gabriele Curci, Paolo Tuccella, Ummugulsum Alyuz, Alessandra Balzarini, Rocío Baró, Roberto Bellasio, Johannes Bieser, Jørgen Brandt, Jesper H. Christensen, Augistin Colette, Xavier Francis, Andrea Fraser, Marta Garcia Vivanco, Pedro Jiménez-Guerrero, Ulas Im, Astrid Manders, Uarporn Nopmongcol, Nutthida Kitwiroon, Guido Pirovano, Luca Pozzoli, Marje Prank, Ranjeet S. Sokhi, Alper Unal, Greg Yarwood, and Stefano Galmarini
Atmos. Chem. Phys., 17, 3001–3054, https://doi.org/10.5194/acp-17-3001-2017,https://doi.org/10.5194/acp-17-3001-2017, 2017
Short summary
Construction of the SILAM Eulerian atmospheric dispersion model based on the advection algorithm of Michael Galperin
M. Sofiev, J. Vira, R. Kouznetsov, M. Prank, J. Soares, and E. Genikhovich
Geosci. Model Dev., 8, 3497–3522, https://doi.org/10.5194/gmd-8-3497-2015,https://doi.org/10.5194/gmd-8-3497-2015, 2015
Short summary
MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe
M. Sofiev, U. Berger, M. Prank, J. Vira, J. Arteta, J. Belmonte, K.-C. Bergmann, F. Chéroux, H. Elbern, E. Friese, C. Galan, R. Gehrig, D. Khvorostyanov, R. Kranenburg, U. Kumar, V. Marécal, F. Meleux, L. Menut, A.-M. Pessi, L. Robertson, O. Ritenberga, V. Rodinkova, A. Saarto, A. Segers, E. Severova, I. Sauliene, P. Siljamo, B. M. Steensen, E. Teinemaa, M. Thibaudon, and V.-H. Peuch
Atmos. Chem. Phys., 15, 8115–8130, https://doi.org/10.5194/acp-15-8115-2015,https://doi.org/10.5194/acp-15-8115-2015, 2015
Short summary

Related subject area

Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Comparing the simulated influence of biomass burning plumes on low-level clouds over the southeastern Atlantic under varying smoke conditions
Alejandro Baró Pérez, Michael S. Diamond, Frida A.-M. Bender, Abhay Devasthale, Matthias Schwarz, Julien Savre, Juha Tonttila, Harri Kokkola, Hyunho Lee, David Painemal, and Annica M. L. Ekman
Atmos. Chem. Phys., 24, 4591–4610, https://doi.org/10.5194/acp-24-4591-2024,https://doi.org/10.5194/acp-24-4591-2024, 2024
Short summary
Improved simulations of biomass burning aerosol optical properties and lifetimes in the NASA GEOS Model during the ORACLES-I campaign
Sampa Das, Peter R. Colarco, Huisheng Bian, and Santiago Gassó
Atmos. Chem. Phys., 24, 4421–4449, https://doi.org/10.5194/acp-24-4421-2024,https://doi.org/10.5194/acp-24-4421-2024, 2024
Short summary
Sharp increase in Saharan dust intrusions over the western Euro-Mediterranean in February–March 2020–2022 and associated atmospheric circulation
Emilio Cuevas-Agulló, David Barriopedro, Rosa Delia García, Silvia Alonso-Pérez, Juan Jesús González-Alemán, Ernest Werner, David Suárez, Juan José Bustos, Gerardo García-Castrillo, Omaira García, África Barreto, and Sara Basart
Atmos. Chem. Phys., 24, 4083–4104, https://doi.org/10.5194/acp-24-4083-2024,https://doi.org/10.5194/acp-24-4083-2024, 2024
Short summary
Temporal and spatial variations in dust activity in Australia based on remote sensing and reanalysis datasets
Yahui Che, Bofu Yu, and Katherine Bracco
Atmos. Chem. Phys., 24, 4105–4128, https://doi.org/10.5194/acp-24-4105-2024,https://doi.org/10.5194/acp-24-4105-2024, 2024
Short summary
Sensitivity of global direct aerosol shortwave radiative forcing to uncertainties in aerosol optical properties
Jonathan Elsey, Nicolas Bellouin, and Claire Ryder
Atmos. Chem. Phys., 24, 4065–4081, https://doi.org/10.5194/acp-24-4065-2024,https://doi.org/10.5194/acp-24-4065-2024, 2024
Short summary

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.
Download
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.
Altmetrics
Final-revised paper
Preprint