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      Modelling black carbon absorption of solar radiation: combining external and internal mixing assumptions

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          Abstract

          An accurate simulation of the absorption properties is key for assessing the radiative effects of aerosol on meteorology and climate. The representation of how chemical species are mixed inside the particles (the mixing state) is one of the major uncertainty factors in the assessment of these effects. Here we compare aerosol optical properties simulations over Europe and North America, coordinated in the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII), to 1 year of AERONET sunphotometer retrievals, in an attempt to identify a mixing state representation that better reproduces the observed single scattering albedo and its spectral variation. We use a single post-processing tool (FlexAOD) to derive aerosol optical properties from simulated aerosol speciation profiles, and focus on the absorption enhancement of black carbon when it is internally mixed with more scattering material, discarding from the analysis scenes dominated by dust.

          We found that the single scattering albedo at 440 nm ( ω 0,440) is on average overestimated (underestimated) by 3–5 % when external (core-shell internal) mixing of particles is assumed, a bias comparable in magnitude with the typical variability of the quantity. The (unphysical) homogeneous internal mixing assumption underestimates ω 0,440 by ~ 14 %. The combination of external and core-shell configurations (partial internal mixing), parameterized using a simplified function of air mass aging, reduces the ω 0,440 bias to −1/−3 %. The black carbon absorption enhancement ( E abs) in core-shell with respect to the externally mixed state is in the range 1.8–2.5, which is above the currently most accepted upper limit of ~ 1.5. The partial internal mixing reduces E abs to values more consistent with this limit. However, the spectral dependence of the absorption is not well reproduced, and the absorption Ångström exponent AAE 675 440 is overestimated by 70–120 %. Further testing against more comprehensive campaign data, including a full characterization of the aerosol profile in terms of chemical speciation, mixing state, and related optical properties, would help in putting a better constraint on these calculations.

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          Variability of Absorption and Optical Properties of Key Aerosol Types Observed in Worldwide Locations

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            Optical Properties of Aerosols and Clouds: The Software Package OPAC

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              An emerging ground-based aerosol climatology: Aerosol optical depth from AERONET

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                Author and article information

                Journal
                101214388
                38670
                Atmos Chem Phys
                Atmos Chem Phys
                Atmospheric chemistry and physics
                1680-7316
                1680-7324
                21 February 2019
                7 January 2019
                2019
                07 January 2020
                : 19
                : 1
                : 181-204
                Affiliations
                [1 ]Department of Physical and Chemical Sciences, University of L’Aquila, L’Aquila, Italy
                [2 ]Center of Excellence in Telesening of Environment and Model Prediction of Severe Events (CETEMPS), University of L’Aquila, L’Aquila (AQ), Italy
                [3 ]Eurasia Institute of Earth Sciences, Istanbul Technical University, 34469 Istanbul, Turkey
                [4 ]Department of Physics, University of Murcia, Murcia, 30003, Spain
                [5 ]Enviroware s.r.l., Concorezzo (MB), 20863, Italy
                [6 ]Helmholtz-Zentrum Geesthacht, Zentrum für Material- und Küstenforschung GmbH, Geesthacht, 21502, Germany
                [7 ]Atmospheric Modelling Secton (ATMO), Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000 Roskilde, Denmark
                [8 ]Atmospheric Modelling and Environmental Mapping Unit, INERIS, BP2, Verneuil-en-Halatte, 60550, France
                [9 ]Centre for Atmospheric and Instrumentation Research (CAIR), University of Hertfordshire College Lane, Hatfield, AL10 9AB, UK
                [10 ]NRC Research Associate at Computational Exposure Division, National Exposure Research Laboratory, U.S. Environmental Protection Agency (EPA), Research Triangle Park, NC 27711, USA
                [11 ]TNO, PO Box 80015, 3508 TA Utrecht, the Netherlands
                [12 ]Finnish Meteorological Institute, Atmospheric Composition Research Unit, Helsinki, 00560, Finland
                [13 ]Cornell University, Department of Earth and Atmospheric Sciences, Ithaca, 14853 NY, USA
                [14 ]Joint Research Centre (JRC), European Commission, Ispra (VA), 21027, Italy
                [15 ]CIEMAT, Madrid, 28040, Spain
                [16 ]Computational Exposure Division, National Exposure Research Laboratory, U.S. Environmental Protection Agency (EPA), Research Triangle Park, NC 27711, USA
                Author notes

                Author contributions. GC designed the study, performed data analysis and FlexAOD development and calculations, and wrote the paper. All authors performed and provided simulations with their chemistry-transport models and commented on drafts of the manuscripts.

                Correspondence: Gabriele Curci ( gabriele.curci@ 123456aquila.infn.it )
                Article
                EPAPA1519935
                10.5194/acp-19-181-2019
                6392454
                30828349
                44769421-5f2c-4dcb-a5ad-0ecb7e3f15b8

                This work is distributed under the Creative Commons Attribution 4.0 License.

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