Chemical and Physical Properties of the Atmosphere
Workpackage 4
Workpackage 4
Improving the understanding of aerosol source distribution, transport and physico-chemical transformation using advanced merging of remote sensing with atmospheric modeling.
Our objective is to reduce the uncertainties in aerosol modeling by improving the knowledge of aerosol sources, transport, physico-chemical transformations and removal processes. We propose to merge observational and modeling capabilities using inverse modeling methodologies developed in the frame of the CaPPA project, and using forward calculations and statistical data analysis :
to improve global and regional distribution of desert dust, carbonaceous and sulfate aerosols by inverse modeling (Henze et al., 2007, Dubovik et al., 2008, Chen et al., 2018, 2019). The approach has been shown to improve the emission sources and to correct removal processes. The data from polar and geostationary imagers, lidar satellite systems, ground-based networks of radiometers and lidars and in situ data (provided by WP3) are to be used. Known trends in aerosol impacts on climate and environment at the global and regional scales will be revised.
to benefit from the methodology developed in the frame of the CaPPA project (Boichu et al. 2015, 2016) in order to improve further the reconstruction of volcanic SO2 and ash emissions at high temporal resolution, using inverse modeling that will assimilate a broader panel of satellite and ground-based observations of the volcanic cloud (provided by WP3). Using these better-resolved emissions, we will explore the lifecycle of volcanic sulfur-rich aerosols and ash. To validate and improve current models of volcanic cloud dispersal and chemical evolution, we will exploit observations from space, ground-based and in situ data in collaboration with WP3 and WP2.
to investigate source apportionment of aerosols and their gaseous precursors through source-receptor modeling and statistical modeling coupled to local wind or back-trajectory analyses.
to investigate case studies of local atmospheric phenomena by modeling at multiple scales, including Large-Eddy Simulations and to test forecasting of the local atmospheric state using the MESO-NH model and ECMWF predictions.
Illustration: Schematic views of models and satellite combinations (relevant for aerosols).
Behera, A., Boichu, M. and Thieuleux, F. (2020) “Strength of TROPOMI observations on the retrieval of volcanic SO2 emissions at high temporal resolution from space“, Geophysical Research Abstracts of the European Geophysical Union.
Belis, C.A., Pernigotti, D., Pirovano, G., Favez, O., Jaffrezo, J.L., Kuenen, J., Denier van Der Gon, H., Reizer, M., Riffault, V., Alleman, L.Y., Almeida, M., Amato, F., Angyal, A., Argyropoulos, G., Bande, S., Beslic, I., Besombes, J.-L., Bove, M.C., Brotto, P., Calori, G., et al. (2020). Evaluation of receptor and chemical transport models for PM10 source apportionment. Atmospheric Environment: X 5, 100053. https://doi.org/10.1016/j.aeaoa.2019.100053
Boichu, M., Menut, L., Khvorostyanov, D., Clarisse, L., Turquety, S., Clerbaux, C., Coheur, P.F., 2013, Inverting for volcanic SO2 flux at high temporal resolution using spaceborne plume imagery and chemistry-transport modelling: the 2010 Eyjafjallajökull eruption case-study, Atmospheric Chemistry and Physics, doi:10.5194/acp-13-8569-2013
Boichu, M., Clarisse, L., Péré, J.-C., Herbin, H., Goloub, P., Thieuleux, F., Ducos, F., Clerbaux, C., Tanré, D. 2015, Temporal variations of flux and altitude of sulfur dioxide emissions during volcanic eruptions: implications for long-range dispersal of volcanic clouds, Atmospheric Chemistry and Physics, 15, 8381-8400, doi:10.5194/acp-15-8381-2015
Boichu, M., Chiapello, I., Brogniez, C., Péré, J.-C., Thieuleux, F., Torres, B., Blarel, L., Mortier, A., Podvin, T., Goloub, P., Söhne, N., Clarisse, L., Bauduin, S., Hendrick, F., Theys, N., Van Roozendael, M. & Tanré, D. (2016). Current challenges in modelling far-range air pollution induced by the 2014–2015 Bárðarbunga fissure eruption (Iceland). Atmos. Chem. Phys., 16(17), 10831-10845. 10.5194/acp-16-10831-2016
Boichu, M., Favez, O., Riffault, V., Petit, J.-E., Zhang, Y., Brogniez, C., Sciare, J., Chiapello, I., Clarisse, L., Zhang, S., Pujol-Söhne, N., Tison, E., Delbarre, H., and Goloub, P. (2019) “Large-scale particulate air pollution and chemical fingerprint of volcanic sulfate aerosols from the 2014–2015 Holuhraun flood lava eruption of Bárðarbunga volcano (Iceland)”, Atmos. Chem. Phys., 19, 14253–14287, https://doi.org/10.5194/acp-19-14253-2019
Chen, C., O. Dubovik, D. K. Henze, M. Chin, T. Lapyonok, G. L. Schuster , F. Ducos, D. Fuertes, P. Litvinov, L. Li, A. Lopatin, Q. Hu, and B. Torres, « Constraining global aerosol emissions using POLDER/PARASOLsatellite remote sensing observations », Atmos. Chem. Phys., 19, 14585-14606, 2019https://doi.org/10.5194/acp-19-14585-2019, 2019.
Chen, C., O. Dubovik, D. K. Henze, T. Lapyonak, M. Chin, F. Ducos, P. Litvinov, X. Huang, and L. Li, Retrieval of Desert Dust and Carbonaceous Aerosol Emissions over Africa from POLDER/PARASOL Products Generated by GRASP Algorithm, Atmos. Chem. Phys., https://doi.org/10.5194/acp-18-12551-2018, 18, 12551-12580, 2018.
Dubovik, O., T. Lapyonok, Y. J. Kaufman, M. Chin, P. Ginoux, R. A. Kahn and A. Sinyuk, Retrieving global aerosol sources from satellites using inverse modeling, Atmos. Chem. Phys., 8, 209-250, 2008.
Dubovik, O., Lapyonok, T., Litvinov, P., Herman, M., Fuertes, D., Ducos, F., Lopatin, A., Chaikovsky, A., Torres, B., Derimian, Y., Huang, X., Aspetsberger, M., and Federspiel C.: GRASP: a versatile algorithm fo characterizing the atmosphere, SPIE: Newsroom, Doi: 10.1117/2.1201408.005558, Published Online: 19 /09/2014. http://spie.org/x109993.xml.
Elguindi, N., C. Granier, T. Stavrakou, S. Darras, M. Bauwens, H. Cao, C. Chen, H.A.C. Denier van der Gon, O. Dubovik, T.M. Fu, D. Henze, Z. Jiang, J.J.P. Kuenen, J. Kurokawa, C. Liousse, K. Miyazaki1, J.-F. MuÃàller, Z. Qu, K. Sekou, F. Solmon and B. Zheng, « Intercomparison of magnitudesand trends in anthropogenic surfaceemissions from bottom‚Äêup inventories, top‚Äêdown estimates, and emission scenarios », Earth’s Future , 8 , e2020EF001520, https://doi.org/10.1029/2020EF001520, 2020.
Henze, D. K., Hakami, A. and Seinfeld, J. H.: Development of the adjoint of GEOS-Chem, Atmos. Chem. Phys., 7(9), 2413–2433, doi:10.5194/acp-7-2413-2007, 2007.
